text:
Research},
  volume = {191},
  pages = {110031},
  issn = {0013-9351},
  doi = {10.1016/j.envres.2020.110031},
  url = {https://www.sciencedirect.com/science/article/pii/S0013935120309282},
  urldate = {2021-06-15},
  abstract = {There is high demand for online, real-time and high-quality pollen data. To the moment pollen monitoring has been done manually by highly specialized experts. Here we evaluate the electronic Pollen Information Network (ePIN) comprising 8 automatic BAA500 pollen monitors in Bavaria, Germany. Automatic BAA500 and manual Hirst-type pollen traps were run simultaneously at the same locations for one pollen season. Classifications by BAA500 were checked by experts in pollen identification, which is traditionally considered to be the “gold standard” for pollen monitoring. BAA500 had a multiclass accuracy of over 90\%. Correct identification of any individual pollen taxa was always {$>$}85\%, except for Populus (73\%) and Alnus (64\%). The BAA500 was more precise than the manual method, with less discrepancies between determinations by pairs of automatic pollen monitors than between pairs of humans. The BAA500 was online for 97\% of the time. There was a significant correlation of 0.84 between airborne pollen concentrations from the BAA500 and Hirst-type pollen traps. Due to the lack of calibration samples it is unknown which instrument gives the true concentration. The automatic BAA500 network delivered pollen data rapidly (3~h delay with real-time), reliably and online. We consider the ability to retrospectively check the accuracy of the reported classification essential for any automatic system.},
  langid = {english},
  keywords = {Aerobiology,Allergy,BAA500,ePIN,Hirst,Quality control},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\TFC6MI4B\\S0013935120309282.html}
}

@article{Paolini2016211,
  title = {Vegetation Productivity Trends in Response to Urban Dynamics},
  author = {Paolini, L. and Aráoz, E. and Gioia, A. and Powell, P.A.},
  date = {2016},
  journaltitle = {Urban Forestry and Urban Greening},
  volume = {17},
  pages = {211--216},
  doi = {10.1016/j.ufug.2016.04.005},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969513569&doi=10.1016%2fj.ufug.2016.04.005&partnerID=40&md5=dfb5fa65214a1ea0e45f864ec1bad058},
  abstract = {Urbanization is a global phenomenon with still unknown consequences for vegetation dynamics of urban ecosystems, especially in subtropical areas of developing countries. In this paper we analyze the vegetation productivity trend associated to urban densification and urban expansion during the last decade, in twelve cities of northern Argentina. We used time series analysis of MODIS-NDVI images to reconstruct the phenological patterns to retrieve a productivity trend under three spatial classes of urban dynamics: (1) urban, (2) expansion and (3) periphery. Our results show that trends in vegetation productivity are more associated to the environmental characteristics (basal productivity and climate) than to the land cover class. The average trend in productivity in urban areas ranged between -2.54\% year-1 (Metán) and -0.22\% year-1 (Concepción). In contrast, the range was much tighter between classes; it was -1.37\% year-1 in urban areas and -1.21\% in the periphery. In this sense we found significant differences between cities, but no significant differences were observed between classes. Urban growth and urban expansion patterns found in our study suggest the system dynamics is dominated by sprawl patterns rather than by a homogeneous densification. Related to this phenomenon, our results dismissed the idea of urban expansion as the main factor affecting vegetation phenology and supported the hypothesis of regional warming as an explanation for the decrease in vegetation productivity, probably due to the decrease of water balance in arid regions. © 2016 Elsevier GmbH.},
  affiliation = {Instituto de Ecología Regional, Universidad Nacional de Tucumán, CC 34, Tucumán, 4107, Argentina; Centro de Investigación de Ecosistemas Urbanos, Universidad del Norte Santo Tomás de Aquino, Av. Perón 2085, Tucumán, 4107, Argentina},
  author_keywords = {MODIS; Time series analysis; Urban expansion; Vegetation productivity},
  document_type = {Article},
  source = {Scopus}
}

@article{park2021,
  title = {Scale Gaps in Landscape Phenology: Challenges and Opportunities},
  shorttitle = {Scale Gaps in Landscape Phenology},
  author = {Park, Daniel S. and Newman, Erica A. and Breckheimer, Ian K.},
  date = {2021-05},
  journaltitle = {Trends in Ecology \& Evolution},
  shortjournal = {Trends in Ecology \& Evolution},
  pages = {S0169534721001087},
  issn = {01695347},
  doi = {10.1016/j.tree.2021.04.008},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0169534721001087},
  urldate = {2021-06-07},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\MKW2KLUH\\Park et al. - 2021 - Scale gaps in landscape phenology challenges and .pdf}
}

@article{petach2014,
  title = {Monitoring Vegetation Phenology Using an Infrared-Enabled Security Camera},
  author = {Petach, Anika R. and Toomey, Michael and Aubrecht, Donald M. and Richardson, Andrew D.},
  date = {2014-09-15},
  journaltitle = {Agricultural and Forest Meteorology},
  shortjournal = {Agricultural and Forest Meteorology},
  volume = {195--196},
  pages = {143--151},
  issn = {0168-1923},
  doi = {10.1016/j.agrformet.2014.05.008},
  url = {http://www.sciencedirect.com/science/article/pii/S0168192314001257},
  urldate = {2021-01-06},
  abstract = {Sensor-based monitoring of vegetation phenology is being widely used to quantify phenological responses to climate variability and change. Digital repeat photography, in particular, can characterize the seasonality of canopy greenness. However, these data cannot be directly compared to satellite vegetation indices (e.g. NDVI, the normalized difference vegetation index) that require information about vegetation properties at near-infrared (NIR) wavelengths. Here, we develop a new method, using an inexpensive, NIR-enabled camera originally designed for security monitoring, to calculate a “camera NDVI” from sequential visible and visible+NIR photographs. We use a lab experiment for proof-of-concept, and then test the method using a year of data from an ongoing field campaign in a mixed temperate forest. Our analysis shows that the seasonal cycle of camera NDVI is almost identical to that of NDVI measured using narrow-band radiometric instruments, or as observed from space by the MODIS platform. This camera NDVI thus provides different information about the state of the canopy than can be obtained using only visible-wavelength imagery. In addition to phenological monitoring, our method should be useful for a variety of applications, including continuous monitoring of plant stress and quantifying vegetation responses to manipulative treatments in large field experiments.},
  langid = {english},
  keywords = {Digital repeat photography,Green chromatic coordinate (),Near-surface remote sensing,Normalized difference vegetation index (NDVI),Phenology,Stress monitoring},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\petach_et_al_2014_monitoring_vegetation_phenology_using_an_infrared-enabled_security_camera.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\6XRUT7MV\\S0168192314001257.html}
}

@article{peters2010a,
  title = {Influence of Seasonality and Vegetation Type on Suburban Microclimates},
  author = {Peters, E.B. and McFadden, J.P.},
  date = {2010},
  journaltitle = {Urban Ecosystems},
  volume = {13},
  number = {4},
  pages = {443--460},
  doi = {10.1007/s11252-010-0128-5},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77957818892&doi=10.1007%2fs11252-010-0128-5&partnerID=40&md5=ccd7ae413f4f7fc53f177c16013d7b4c},
  abstract = {Urbanization is responsible for some of the fastest rates of land-use change around the world, with important consequences for local, regional, and global climate. Vegetation, which represents a significant proportion of many urban and suburban landscapes, can modify climate by altering local exchanges of heat, water vapor, and CO2. To determine how distinct urban forest communities vary in their microclimate effects over time, we measured stand-level leaf area index, soil temperature, infrared surface temperature, and soil water content over a complete growing season at 29 sites representing the five most common vegetation types in a suburban neighborhood of Minneapolis-Saint Paul, Minnesota. We found that seasonal patterns of soil and surface temperatures were controlled more by differences in stand-level leaf area index and tree cover than by plant functional type. Across the growing season, sites with high leaf area index had soil temperatures that were 7°C lower and surface temperatures that were 6°C lower than sites with low leaf area index. Site differences in mid-season soil temperature and turfgrass ground cover were best explained by leaf area index, whereas differences in mid-season surface temperature were best explained by percent tree cover. The significant cooling effects of urban tree canopies on soil temperature imply that seasonal changes in leaf area index may also modulate CO2 efflux from urban soils, a highly temperature-dependent process, and that this should be considered in calculations of total CO2 efflux for urban carbon budgets. Field-based estimates of percent tree cover were found to better predict mid-season leaf area index than satellite-derived estimates and consequently offer an approach to scale up urban biophysical properties. © 2010 The Author(s).},
  affiliation = {Department of Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, MN, United States; Department of Geography, University of California, Santa Barbara, CA, United States},
  author_keywords = {Leaf area index; Phenology; Plant functional type; Soil temperature; Surface temperature; Urban ecology},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\peters_mcfadden_2010_influence_of_seasonality_and_vegetation_type_on_suburban_microclimates.pdf}
}

@article{phelan2015,
  title = {Urban {{Heat Island}}: {{Mechanisms}}, {{Implications}}, and {{Possible Remedies}}},
  shorttitle = {Urban {{Heat Island}}},
  author = {Phelan, Patrick E. and Kaloush, Kamil and Miner, Mark and Golden, Jay and Phelan, Bernadette and Silva, Humberto and Taylor, Robert A.},
  date = {2015},
  journaltitle = {Annual Review of Environment and Resources},
  volume = {40},
  number = {1},
  pages = {285--307},
  doi = {10.1146/annurev-environ-102014-021155},
  url = {https://doi.org/10.1146/annurev-environ-102014-021155},
  urldate = {2020-04-08},
  abstract = {Urban heat island (UHI) manifests as the temperature rise in built-up urban areas relative to the surrounding rural countryside, largely because of the relatively greater proportion of incident solar energy that is absorbed and stored by man-made materials. The direct impact of UHI can be significant on both daytime and night-time temperatures, and the indirect impacts include increased air conditioning loads, deteriorated air and water quality, reduced pavement lifetimes, and exacerbated heat waves. Modifying the thermal properties and emissivity of roofs and paved surfaces and increasing the vegetated area within the city are potential mitigation strategies. A quantitative comparison of their efficacies and costs suggests that so-called cool roofs are likely the most cost-effective UHI mitigation strategy. However, additional research is needed on how to modify surface emissivities and dynamically control surface and material properties, as well as on the health and socioeconomic impacts of UHI.},
  annotation = {\_eprint: https://doi.org/10.1146/annurev-environ-102014-021155},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\TTLYBA8X\\Phelan et al_2015_Urban Heat Island.pdf}
}

@article{pielou1966,
  title = {The Measurement of Diversity in Different Types of Biological Collections},
  author = {Pielou, E. C.},
  date = {1966-12-01},
  journaltitle = {Journal of Theoretical Biology},
  shortjournal = {Journal of Theoretical Biology},
  volume = {13},
  pages = {131--144},
  issn = {0022-5193},
  doi = {10.1016/0022-5193(66)90013-0},
  url = {https://www.sciencedirect.com/science/article/pii/0022519366900130},
  urldate = {2021-04-22},
  abstract = {Information content may be used as a measure of the diversity of a many-species biological collection. The diversity of small collections, all of whose members can be identified and counted, is defined by Brillouin's measure of information. With larger collections it becomes necessary to estimate diversity; what is estimated is Shannon's measure of information which is a function of the population proportions of the several species. Different methods of estimation are appropriate for different types of collections. If the collection can be randomly sampled and the total number of species is known, Basharin's formula may be used. With a random sample from a population containing an unknown number of species, Good's method is sometimes applicable. With a patchy population of sessile organisms, such as a plant community, random samples are unobtainable since the contents of a randomly placed quadrat are not a random sample of the parent population. To estimate the diversity of such a community a method is proposed whereby the sample size is progressively increased by addition of new quadrats; as this is done the diversity of the pooled sample increases and then levels off. The mean increment in total diversity that results from enlarging the sample still more then provides an estimate of the diversity per individual in the whole population.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\RGHES5PA\\0022519366900130.html}
}

@article{prakash2020,
  title = {Open {{Earth Observations}} for {{Sustainable Urban Development}}},
  author = {Prakash, Mihir and Ramage, Steven and Kavvada, Argyro and Goodman, Seth},
  date = {2020-05-21},
  journaltitle = {Remote Sensing},
  shortjournal = {Remote Sensing},
  volume = {12},
  number = {10},
  pages = {1646},
  issn = {2072-4292},
  doi = {10.3390/rs12101646},
  url = {https://www.mdpi.com/2072-4292/12/10/1646},
  urldate = {2021-01-12},
  abstract = {Our cities are the frontier where the battle to achieve the global sustainable development agenda over the next decade would be won or lost. This requires an evidence-based approach to local decision-making and resource allocation, which can only be possible if current gaps in urban data are bridged. Earth observation (EO) offers opportunities to provide timely, spatially disaggregated information that supports this need. Spatially disaggregated information, which is also demanded by cities for forward planning and land management, has not received much attention largely due to three reasons: (i) the cost of generating this data through traditional methods remains high; (ii) the technical capacity in geospatial sciences in many countries is low due to a shortage of skilled professionals who can find and/or process available data; and (iii) the inertia against disturbing routine workflows and adopting new practices that are not imposed through legal requirements at the country level. In support of overcoming the first two challenges, this paper discusses the importance of EO data in the urban context, how it is already being used by some city leaders for decision making, and what other applications it offers in the realm of urban sustainability monitoring. It also illustrates how the EO community, via the Group on Earth Observations (GEO) and its members, is working to make this data more easily accessible and lower barriers of use by policymakers and urban practitioners that are interested in implementing and tracking sustainable development in their jurisdictions. The paper concludes by shining a light on the challenges that remain to be overcome for better adoption of EO data for urban decision making through better communication between the two groups, to enable a more effective alignment of the produced data with the users’ needs.},
  langid = {english}
}

@article{pretzsch2017,
  title = {Climate Change Accelerates Growth of Urban Trees in Metropolises Worldwide},
  author = {Pretzsch, Hans and Biber, Peter and Uhl, Enno and Dahlhausen, Jens and Schütze, Gerhard and Perkins, Diana and Rötzer, Thomas and Caldentey, Juan and Koike, Takayoshi and van Con, Tran and Chavanne, Aurélia and du Toit, Ben and Foster, Keith and Lefer, Barry},
  date = {2017-11-13},
  journaltitle = {Scientific Reports},
  volume = {7},
  number = {1},
  pages = {1--10},
  issn = {2045-2322},
  doi = {10.1038/s41598-017-14831-w},
  url = {https://www.nature.com/articles/s41598-017-14831-w},
  urldate = {2019-12-06},
  abstract = {Despite the importance of urban trees, their growth reaction to climate change and to the urban heat island effect has not yet been investigated with an international scope. While we are well informed about forest growth under recent conditions, it is unclear if this knowledge can be simply transferred to urban environments. Based on tree ring analyses in ten metropolises worldwide, we show that, in general, urban trees have undergone accelerated growth since the 1960s. In addition, urban trees tend to grow more quickly than their counterparts in the rural surroundings. However, our analysis shows that climate change seems to enhance the growth of rural trees more than that of urban trees. The benefits of growing in an urban environment seem to outweigh known negative effects, however, accelerated growth may also mean more rapid ageing and shortened lifetime. Thus, city planners should adapt to the changed dynamics in order to secure the ecosystem services provided by urban trees.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\SWP6A2CG\\Pretzsch et al_2017_Climate change accelerates growth of urban trees in metropolises worldwide.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\XYAABIN7\\s41598-017-14831-w.html}
}

@article{qiu2017,
  title = {Impacts of Urbanization on Vegetation Phenology over the Past Three Decades in {{Shanghai}}, {{China}}},
  author = {Qiu, T. and Song, C. and Li, J.},
  date = {2017},
  journaltitle = {Remote Sensing},
  volume = {9},
  number = {9},
  doi = {10.3390/rs9090970},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029764985&doi=10.3390%2frs9090970&partnerID=40&md5=b80ff7c2e487ed8d2f96782b752853dd},
  abstract = {Vegetation phenology manifests the rhythm of annual plant life activities. It has been extensively studied in natural ecosystems. However, major knowledge gaps still exist in understanding the impacts of urbanization on vegetation phenology. This study addresses two questions to fill the knowledge gaps: (1) How does vegetation phenology vary spatially and temporally along a rural-to-urban transect in Shanghai, China, over the past three decades? (2) How do landscape composition and configuration affect those variations of vegetation phenology? To answer these questions, 30 m × 30 m mean vegetation phenology metrics, including the start of growing season (SOS), end of growing season (EOS), and length of growing season (LOS), were derived for urban vegetation using dense stacks of enhanced vegetation index (EVI) time series from images collected by Landsat 5-8 satellites from 1984 to 2015. Landscape pattern metrics were calculated using high spatial resolution aerial photos. We then used Pearson correlation analysis to quantify the associations between phenology patterns and landscape metrics. We found that vegetation in urban centers experienced advances of SOS for 5-10 days and delays of EOS for 5-11 days compared with those located in the surrounding rural areas. Additionally, we observed strong positive correlations between landscape composition (percentage of landscape area) of developed land and LOS of urban vegetation. We also found that the landscape configuration of local land cover types, especially patch density and edge density, was significantly correlated with the spatial patterns of vegetation phenology. These results demonstrate that vegetation phenology in the urban area is significantly different from its rural surroundings. These findings have implications for urban environmental management, ranging from biodiversity protection to public health risk reduction. © 2017 by the authors.},
  affiliation = {Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; School of Ecological and Environmental Sciences, East China Normal University, Shanghai, 200241, China; Shanghai Key Laboratory of Urbanization and Eco-Restoration, Shanghai, 200241, China},
  art_number = {970},
  author_keywords = {EVI; Landscape metrics; Rural-to-urban gradient; Urban landscape; Urban phenology},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\qiu_et_al_2017_impacts_of_urbanization_on_vegetation_phenology_over_the_past_three_decades_in.pdf}
}

@article{Qiu2020,
  title = {Urbanization and Climate Change Jointly Shift Land Surface Phenology in the Northern Mid-Latitude Large Cities},
  author = {Qiu, T. and Song, C. and Zhang, Y. and Liu, H. and Vose, J.M.},
  date = {2020},
  journaltitle = {Remote Sensing of Environment},
  volume = {236},
  doi = {10.1016/j.rse.2019.111477},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074877644&doi=10.1016%2fj.rse.2019.111477&partnerID=40&md5=5fe3af9b4eb6aa6b48acca8634ad22d4},
  abstract = {Land surface phenology (LSP) has been widely used as the “footprint” of urbanization and global climate change. Shifts of LSP have cascading effects on food production, carbon sequestration, water consumption, biodiversity, and public health. Previous studies mainly focused on investigating the effects of urbanization on the spatial patterns of LSP by comparing phenological metrics, e.g. start of season (SOS) and end of season (EOS), between urban center and the surrounding rural regions. However, it remains unclear how urbanization-induced land cover conversions and climate change jointly influence the temporal variations of SOS and EOS within the urban ecosystem. To fill this knowledge gap, we utilized daily two-band enhanced vegetation index, daily meteorological record, and annual land cover dataset to investigate the respective impacts of urbanization and climate change on temporal shifts of LSP between the post- and the pre-urbanization periods over 196 large cities in the northern mid-latitudes. We found 51\% of the cities experienced an advanced SOS with an average of −6.39 ± 5.82 days after urbanization has occurred, while the remaining 49\% of the cities had a delayed SOS with an average of 7.56 ± 5.63 days. We also found a later EOS at 53\% of the cities and an earlier EOS at 47\% of the cities with an average of 8.43 ± 7.59 and −5.57 ± 4.99 days between the post- and pre-urbanization periods, respectively. Multiple linear regression analysis indicates that climate variables (i.e. temperature, precipitation, and insolation) play dominant roles in regulating the temporal shifts of LSP. Furthermore, the earlier SOS and later EOS were significantly correlated with the amplitude of urbanization (i.e. increase of impervious surface area) in cities after controlling for effects of climate factors. These patterns were generally consistent across eight climate zones. Our findings provide critical information in modeling natural and anthropogenic effects on urban ecosystem, with important benefits for urban sustainability and biodiversity conservation. © 2019 Elsevier Inc.},
  affiliation = {Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States; Center for Integrated Forest Science, USDA Forest Service, Southern Research Station, Research Triangle ParkNC 27709, United States; Department of Forestry and Environmental Resources, College of Natural Resources, North Carolina State University, Raleigh, NC 27695, United States},
  art_number = {111477},
  author_keywords = {Climate change; Land surface phenology; Two-band enhanced vegetation index; Urbanization},
  document_type = {Article},
  source = {Scopus}
}

@article{quigley2004,
  title = {Street Trees and Rural Conspecifics: {{Will}} Long-Lived Trees Reach Full Size in Urban Conditions?},
  shorttitle = {Street Trees and Rural Conspecifics},
  author = {Quigley, Martin F.},
  date = {2004-03-01},
  journaltitle = {Urban Ecosystems},
  shortjournal = {Urban Ecosystems},
  volume = {7},
  number = {1},
  pages = {29--39},
  issn = {1573-1642},
  doi = {10.1023/B:UECO.0000020170.58404.e9},
  url = {https://doi.org/10.1023/B:UECO.0000020170.58404.e9},
  urldate = {2020-03-06},
  abstract = {Urban conditions are known to affect tree growth, but not all trees respond similarly to presumed stress. I test a hypothesis that successional status of hardwood tree species, rather than taxon, will differentially affect tree size relative to age, in forest versus street plantings. In central Ohio, USA, samples (N = 230) representing 15 native tree species were matched for size between rural woodlot and city street-side conditions. Their girth was measured and their age determined by a count of annual growth rings. Age and size data were analyzed by a general linear model. Most urban trees had smaller trunk diameters than rural conspecifics of the same age. However, trees of early and mid-successional ecologies, despite smaller girth, showed no reduction in growth rate over time. Late successional species appeared to be affected by proximity to impervious areas, showing reduced growth rates, and by inference,reduced ultimate size.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\3WNUQPT8\\Quigley_2004_Street trees and rural conspecifics.pdf}
}

@article{rahman2020,
  title = {Traits of Trees for Cooling Urban Heat Islands: {{A}} Meta-Analysis},
  shorttitle = {Traits of Trees for Cooling Urban Heat Islands},
  author = {Rahman, Mohammad A. and Stratopoulos, Laura M.F. and Moser-Reischl, Astrid and Zölch, Teresa and Häberle, Karl-Heinz and Rötzer, Thomas and Pretzsch, Hans and Pauleit, Stephan},
  date = {2020-03},
  journaltitle = {Building and Environment},
  shortjournal = {Building and Environment},
  volume = {170},
  pages = {106606},
  issn = {03601323},
  doi = {10.1016/j.buildenv.2019.106606},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0360132319308182},
  urldate = {2020-10-14},
  langid = {english}
}

@article{randrup2001,
  title = {A Review of Tree Root Conflicts with Sidewalks, Curbs, and Roads},
  author = {Randrup, T.B. and McPherson, E.G. and Costello, L.R.},
  date = {2001-09-01},
  journaltitle = {Urban Ecosystems},
  shortjournal = {Urban Ecosystems},
  volume = {5},
  number = {3},
  pages = {209--225},
  issn = {1573-1642},
  doi = {10.1023/A:1024046004731},
  url = {https://doi.org/10.1023/A:1024046004731},
  urldate = {2020-03-06},
  abstract = {Literature relevant to tree root and urban infrastructure conflicts is reviewed. Although tree roots can conflict with many infrastructure elements, sidewalk and curb conflicts are the focus of this review. Construction protocols, urban soils, root growth, and causal factors (soil conditions, limited planting space, tree size, variation in root architecture, management practices, and construction materials) are discussed. Because costs related to sidewalk and curb damage are substantial, a review of research addressing repair, mitigation, prevention, and litigation costs is included. Finally, future research needs are discussed.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\ZU3CA5WN\\Randrup et al_2001_A review of tree root conflicts with sidewalks, curbs, and roads.pdf}
}

@article{rani2018,
  title = {Multi-Temporal {{NDVI}} and Surface Temperature Analysis for {{Urban Heat Island}} Inbuilt Surrounding of Sub-Humid Region: {{A}} Case Study of Two Geographical Regions},
  author = {Rani, M. and Kumar, P. and Pandey, P.C. and Srivastava, P.K. and Chaudhary, B.S. and Tomar, V. and Mandal, V.P.},
  date = {2018},
  journaltitle = {Remote Sensing Applications: Society and Environment},
  volume = {10},
  pages = {163--172},
  publisher = {{Elsevier B.V.}},
  issn = {23529385},
  doi = {10.1016/j.rsase.2018.03.007},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045454843&doi=10.1016%2fj.rsase.2018.03.007&partnerID=40&md5=29d99f2c562448f266a1ab65ec2333c2},
  abbrev_source_title = {Remote Sens. Appl. Soc. Environ.},
  abstract = {Rapid growing urban population has resulted in the occupancy of large proportionate of the city and its outskirts, thereby contributing factors to change in the environmental conditions. This has resulted in widespread land acquisition for built up and industrial development, covering the centre of the city while moving at the outskirts of the city as well. Land Use /Land Cover (LULC) changes causes alterations in the land use categories, mostly the concrete forests which has increased the urban temperature as compared to the rural regions due to rapidly growing urbanized environment. Urban Heat Island (UHI) is one of the human-induced environmental phenomenon affecting the urban inhabitant in many ways, such as altering and disturbing the land cover its use which changes thermal energy flow causing elevated surface and air temperature. Temporal satellite datasets (LANDSAT ETM+ image of 1989, 2000 and 2006) can be used to monitor surface temperature while vegetation indices can be used to assess the coverage of the vegetation and non-vegetation area in the region. Temporal NDVI is employed in the study area to analyse the impact of land surface temperature against NDVI in the region. Therefore, temporal remotely sensed data can be used to map LULC and its dynamic changes and other environmental phenomena such as surface temperature over a period of time. Temporal UHI has been estimated using geospatial technology to incorporate it for environmental impact assessment on the surrounding environment. The present research focuses on temporal NDVI and Surface temperature, the methodology used altogether for the assessment of resolution dynamic UHI change on environmental condition for Haridwar district, Uttrakhand India and Kanpur district, Uttar Pradesh in India. Both case study has different environmental conditions, geographical locations and demography. Hilly and forested region with almost no industrial activities for Haridwar while several industrial activities and densely populated region Kanpur located in an Indo-Gangetic plain. The research outcome demonstrates the correlation between temporal NDVI and Surface temperature exemplified with case study conducted over two different regions, geographically as well as economically. There is a need to consider the environmental dimension while making progress to urbanization. © 2018 Elsevier B.V.},
  affiliation = {G.B. Pant National Institute of Himalayan Environment \& Sustainable Development, India; Remote Sensing and GIS, Department of Geography, Kumaun University, S.S.J. Campus, Almora, Uttarakhand, India; Institute of environment and Sustainable Development, Banaras Hindu University, Varanasi, India; Department of Geophysics, Kurukshetra University, Kurukshetra, Haryana, India; Haryana Institute of Public Administration, Gurgaon, India; Department of Geography, Faculty of Natural Sciences, Jamia Millia IslamiaNew Delhi, India},
  author_keywords = {Dynamic changes; Temporal NDVI; Temporal surface temperature; UHI},
  correspondence_address1 = {Pandey, P.C.; Institute of environment and Sustainable Development, Banaras Hindu UniversityIndia; email: prem26bit@gmail.com},
  document_type = {Article},
  langid = {english},
  source = {Scopus}
}

@article{ren2018,
  title = {Urbanization Impacts on Vegetation Phenology in {{China}}},
  author = {Ren, Q. and He, C. and Huang, Q. and Zhou, Y.},
  date = {2018},
  journaltitle = {Remote Sensing},
  volume = {10},
  number = {12},
  doi = {10.3390/rs10121905},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058873478&doi=10.3390%2frs10121905&partnerID=40&md5=aca20e4c7d5ca0c90fe626fce1fe25b2},
  abstract = {Urbanization can affect the ecological processes, local climate and human health in urban areas by changing the vegetation phenology. In the past 20 years, China has experienced rapid urbanization. Thus, it is imperative to understand the impact of urbanization on vegetation phenology in China. In this study, we quantitatively analyzed the impact of urbanization on vegetation phenology at the national and climate zone scales using remotely sensed data. We found that the start of the growing season (SOS) was advanced by approximately 2.4 days (P \< 0.01), and the end of the growing season (EOS) was delayed by approximately 0.7 days (P \< 0.01) in the urban areas compared to the rural areas. As a result, the growing season length (GSL) was extended by approximately 3.1 days (P \< 0.01). The difference in the SOS and GSL between the urban and rural areas increased from 2001 to 2014, with an annual rate of 0.2 days (R 2 = 0.39, P \< 0.05) and 0.2 days (R 2 = 0.31, P \< 0.05), respectively. We also found that the impact of urbanization on vegetation phenology varied among different vegetation types at the national and climate zone levels (P \< 0.05). The SOS was negatively correlated with land surface temperature (LST), with a correlation coefficient of -0.24 (P \< 0.01), and EOS and GSL were positively correlated with LST, with correlation coefficients of 0.56 and 0.44 (P \< 0.01), respectively. The improved understanding of the impact of urbanization on vegetation phenology from this study will be of great help for policy-makers in terms of developing relevant strategies to mitigate the negative environmental effects of urbanization in China. © 2018 by the authors.},
  affiliation = {Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Beijing Normal University, Beijing, 100875, China; School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China; Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, United States},
  art_number = {1905},
  author_keywords = {Land surface temperature; Sustainability; Urbanization; Vegetation phenology; Vegetation types},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\ren_et_al_2018_urbanization_impacts_on_vegetation_phenology_in_china.pdf}
}

@article{ren2019,
  title = {Changes in Spatio-Temporal Patterns of Urban Forest and Its above-Ground Carbon Storage: {{Implication}} for Urban {{CO2}} Emissions Mitigation under {{China}}'s Rapid Urban Expansion and Greening},
  author = {Ren, Z. and Zheng, H. and He, X. and Zhang, D. and Shen, G. and Zhai, C.},
  date = {2019},
  journaltitle = {Environment International},
  volume = {129},
  pages = {438--450},
  publisher = {{Elsevier Ltd}},
  issn = {01604120},
  doi = {10.1016/j.envint.2019.05.010},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066279755&doi=10.1016%2fj.envint.2019.05.010&partnerID=40&md5=04bc06ee93920ca7c54b7be7b63b3f8e},
  abbrev_source_title = {Environ. Int.},
  abstract = {Background: Understanding spatio-temporal dynamics of UF and its above-ground carbon storage (CS) is important for mitigating urban CO2 emissions under China's rapid urban expansion and greening. Methods: In our study, vegetation index (VI) data obtained from TM image and CS derived from field-based surveys were amalgamated to develop a regression model to predict spatio-temporal patterns of CS. VI correction model was established by normalizing previous imagery (1984, 1995, and 2005) to 2014 image data. Results: NDVI is better than other VIs for predicting urban forest CS. Both UF area and its CS increased gradually from 1984 to 2014, especially in outer rings of the city. CS showed a definite decreasing trend from outer rings to downtown. Due to urban greening policies, landscape patches of UF or CS recently became larger and more aggregated. The CS by UF class distribution was skewed toward low values in all the years, but the skew gradually decreased over time. It was estimated that the average annual increase of CS by UF could offset 3.9\% of the average annual increase in urban carbon emissions. Conclusions: Our study proposes that spatio-temporal changes in UF patterns dramatically affected the amount of CS and carbon capture. The increase in UF coverage and quality would mitigate more urban carbon emissions, especially in outer rings. © 2019 The Authors},
  affiliation = {Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, Changchun, Jilin Province 130102, China; Horticultural College, Changchun University, 6543 Weixing Road, Changchun, Jilin Province 130022, China},
  author_keywords = {Carbon storage; Urban forest (UF); Urban greening; Urbanization},
  chemicals_cas = {carbon, 7440-44-0; carbon dioxide, 124-38-9, 58561-67-4; Carbon; Carbon Dioxide},
  coden = {ENVID},
  correspondence_address1 = {Zheng, H.; Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, China; email: zhenghaifeng@iga.ac.cn},
  document_type = {Article},
  funding_details = {Y6H2091001, 41601094},
  funding_text_1 = {This research was supported by Foundation for Excellent Young Scholars of Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences ( DLSYQ13004 ), the National Natural Science Foundation of China ( 41701210 ), Science Development Project of Jilin Province, China ( 20180418138FG ), and “ Strategic Planning Project from Institute of Northeast Geography and Agroecology (IGA), Chinese Academy of Sciences ” ( Y6H2091001 ), the National Natural Science Foundation of China (Grant No. 41601094 ). The authors express gratitude to the editors and the anonymous reviewers who gave us their insightful comments and suggestions.},
  langid = {english},
  pubmed_id = {31154146},
  source = {Scopus},
  keywords = {Above-ground carbons,Article,carbon,Carbon,carbon dioxide,Carbon dioxide,Carbon Dioxide,carbon emission,carbon footprint,carbon sequestration,carbon storage,Carbon storage,chemistry,China,Cities,city,city planning,Digital storage,emission control,environmental monitoring,environmental planning,environmental temperature,forest,forest management,Forestry,Forests,geographic distribution,global positioning system,landscape,metabolism,policy,priority journal,regression analysis,Regression analysis,Spatio-temporal changes,Spatio-temporal dynamics,spatiotemporal analysis,Spatiotemporal patterns,urban area,urban forestry,Urban forests,Urban greening,urbanization,Urbanization,vegetation,vegetation index}
}

@article{rojo2015,
  title = {Spatiotemporal Analysis of Olive Flowering Using Geostatistical Techniques},
  author = {Rojo, Jesús and Pérez-Badia, Rosa},
  date = {2015-02-01},
  journaltitle = {Science of The Total Environment},
  shortjournal = {Science of The Total Environment},
  volume = {505},
  pages = {860--869},
  issn = {0048-9697},
  doi = {10.1016/j.scitotenv.2014.10.022},
  url = {https://www.sciencedirect.com/science/article/pii/S0048969714014600},
  urldate = {2021-06-07},
  abstract = {Analysis of flowering patterns in the olive (Olea europaea L.) are of considerable agricultural and ecological interest, and also provide valuable information for allergy-sufferers, enabling identification of the major sources of airborne pollen at any given moment by interpreting the aerobiological data recorded in pollen traps. The present spatiotemporal analysis of olive flowering in central Spain combined geostatistical techniques with the application of a Geographic Information Systems, and compared results for flowering intensity with airborne pollen records. The results were used to obtain continuous phenological maps which determined the pattern of the succession of the olive flowering. The results show also that, although the highest airborne olive-pollen counts were recorded during the greatest flowering intensity of the groves closest to the pollen trap, the counts recorded at the start of the pollen season were not linked to local olive groves, which had not yet begin to flower. To detect the remote sources of olive pollen several episodes of pollen recorded before the local flowering season were analysed using a HYSPLIT trajectory model and the findings showed that western, southern and southwestern winds transported pollen grains into the study area from earlier-flowering groves located outside the territory.},
  langid = {english},
  keywords = {Cokriging,Elevation,Flowering phenology,HYSPLIT model,Pollen season},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\rojo_perez-badia_2015_spatiotemporal_analysis_of_olive_flowering_using_geostatistical_techniques.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\M5TCKQIB\\S0048969714014600.html}
}

@article{roman2014,
  title = {How Many Trees Are Enough? {{Tree}} Death and the Urban Canopy},
  shorttitle = {How Many Trees Are Enough?},
  author = {Roman, Lara A.},
  date = {2014},
  journaltitle = {Scenario Journal. Scenario 04. 8 p.},
  pages = {1--8},
  url = {https://www.fs.usda.gov/treesearch/pubs/45905},
  urldate = {2021-09-10},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\roman_2014_how_many_trees_are_enough.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\BCG93RDL\\45905.html}
}

@article{roman2020,
  title = {Beyond 'Trees Are Good': {{Disservices}}, Management Costs, and Tradeoffs in Urban Forestry},
  shorttitle = {Beyond 'Trees Are Good'},
  author = {Roman, Lara A. and Conway, Tenley M. and Eisenman, Theodore S. and Koeser, Andrew K. and Barona, Camilo Ordóñez and Locke, Dexter H. and Jenerette, G. Darrel and Östberg, Johan and Vogt, Jess},
  date = {2020},
  journaltitle = {Ambio},
  volume = {21},
  pages = {183},
  doi = {10.1007/s13280-020-01396-8},
  url = {https://www.fs.usda.gov/treesearch/pubs/61426},
  urldate = {2021-09-10},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\roman_et_al_2020_beyond_'trees_are_good'.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\JVZ898AE\\61426.html}
}

@article{rotzer2019,
  title = {Process Based Simulation of Tree Growth and Ecosystem Services of Urban Trees under Present and Future Climate Conditions},
  author = {Rötzer, T. and Rahman, M. A. and Moser-Reischl, A. and Pauleit, S. and Pretzsch, H.},
  date = {2019-08-01},
  journaltitle = {Science of The Total Environment},
  shortjournal = {Science of The Total Environment},
  volume = {676},
  pages = {651--664},
  issn = {0048-9697},
  doi = {10.1016/j.scitotenv.2019.04.235},
  url = {http://www.sciencedirect.com/science/article/pii/S0048969719317644},
  urldate = {2019-10-04},
  abstract = {Global processes of urban growth lead to severe environmental impacts such as temperature increase with an intensification of the urban heat island effect, and hydrological changes with far reaching consequences for plant growth and human health and well-being. Urban trees can help to mitigate the negative effects of climate change by providing ecosystem services such as carbon storage, shading, cooling by transpiration or reduction of rainwater runoff. The extent of each ecosystem service is closely linked with the tree species as well as with a tree's age, size, structure and vitality. To evaluate the ecosystem services of urban trees, the process-based growth model CityTree was developed which is able to estimate not only tree growth but also the species-specific ecosystem services including carbon storage, transpiration and runoff, shading, and cooling by transpiration. The model was parametrized for the species small-leaved lime (Tilia cordata), robinia (Robinia pseudoacacia), plane (Platanus×acerifolia) and horse chestnut (Aesculus hippocastanum). The model validation for tree growth (stem diameter increment, coefficient of correlation=0.76) as well as for the water balance (transpiration, coefficient of correlation=0.92) seems plausible and realistic. Tree growth and ecosystem services were simulated and analyzed for Central European cities both under current climate conditions and for the future climate scenarios. The simulations revealed that urban trees can significantly improve the urban climate and mitigate climate change effects. The quantity of the improvements depends on tree species and tree size as well as on the specific site conditions. Such simulation scenarios can be a proper basis for planning options to mitigate urban climate changes in individual cities.},
  keywords = {Carbon storage,Climate change,Cooling,Growth model,Shading,Water balance},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\84MQPKQF\\Rötzer et al. - 2019 - Process based simulation of tree growth and ecosys.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\NNVS2QD8\\S0048969719317644.html}
}

@article{roy2012,
  title = {A Systematic Quantitative Review of Urban Tree Benefits, Costs, and Assessment Methods across Cities in Different Climatic Zones},
  author = {Roy, Sudipto and Byrne, Jason and Pickering, Catherine},
  date = {2012-01-01},
  journaltitle = {Urban Forestry \& Urban Greening},
  shortjournal = {Urban Forestry \& Urban Greening},
  volume = {11},
  number = {4},
  pages = {351--363},
  issn = {1618-8667},
  doi = {10.1016/j.ufug.2012.06.006},
  url = {http://www.sciencedirect.com/science/article/pii/S1618866712000829},
  urldate = {2019-12-03},
  abstract = {Urban trees can potentially mitigate environmental degradation accompanying rapid urbanisation via a range of tree benefits and services. But uncertainty exists about the extent of tree benefits and services because urban trees also impose costs (e.g. asthma) and may create hazards (e.g. windthrow). Few researchers have systematically assessed how urban tree benefits and costs vary across different cities, geographic scales and climates. This paper provides a quantitative review of 115 original urban tree studies, examining: (i) research locations, (ii) research methods, and (iii) assessment techniques for tree services and disservices. Researchers published findings in 33 journals from diverse disciplines including: forestry, land use planning, ecology, and economics. Research has been geographically concentrated (64\% of studies were conducted in North America). Nearly all studies (91.3\%) used quantitative research, and most studies (60\%) employed natural science methods. Demonstrated tree benefits include: economic, social, health, visual and aesthetic benefits; identified ecosystem services include: carbon sequestration, air quality improvement, storm water attenuation, and energy conservation. Disservices include: maintenance costs, light attenuation, infrastructure damage and health problems, among others. Additional research is required to better inform public policy, including comparative assessment of tree services and disservices, and assessment of urban residents and land managers’ understanding of tree benefits and costs.},
  langid = {english},
  keywords = {Cities,Ecosystem disservices,Ecosystem services,Land use policy,Trees},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\roy_et_al_2012_a_systematic_quantitative_review_of_urban_tree_benefits,_costs,_and_assessment.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\TEYEI7AT\\S1618866712000829.html}
}

@article{ruan2019,
  title = {Enhanced Vegetation Growth in the Urban Environment across 32 Cities in the Northern Hemisphere},
  author = {Ruan, Y. and Zhang, X. and Xin, Q. and Ao, Z. and Sun, Y.},
  date = {2019},
  journaltitle = {Journal of Geophysical Research: Biogeosciences},
  volume = {124},
  number = {12},
  pages = {3831--3846},
  doi = {10.1029/2019JG005262},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076767703&doi=10.1029%2f2019JG005262&partnerID=40&md5=98bdbe0f96a0af358e085db6c8c97da6},
  abstract = {How the urban environment influences vegetation phenology is important to understand the living environment and the climate-vegetation interaction. This study investigates changes in vegetation phenology in the urban environment using remote sensing data for 32 major cities in the Northern Hemisphere. Vegetation phenological information for both urban and rural areas of each individual city was derived from the remote sensing data. We found that the urban environment generally enhanced vegetation growth but at varied degrees for different regions in the Northern Hemisphere. Vegetation phenology metrics, including the start of season (SOS), the end of season (EOS), and the growing season length (GSL), have large differences between urban and rural environment. Vegetation SOS in urban areas occurred earlier than in rural areas for 22 in 32 cities, and the relationships between advanced urban SOS and the distance away from urban centers are significant for 9 cities. Vegetation EOS in urban areas occurred later than in rural areas for 19 in 32 cities, and the relationships between delayed urban EOS and the distance away from urban centers are significant for 10 cities. The response of SOS to the urban environment is found dependent upon the latitude of urban centers and urban spring daytime and nighttime temperatures. Analysis on ground observational records of vegetation phenology in the region of North America supports the findings derived from remote sensing data. These findings could help to understand the impacts of the urban environment on vegetation growth. ©2019. American Geophysical Union. All Rights Reserved.},
  affiliation = {School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China; School of Geographical Science, Guangzhou University, Guangzhou, China; The College of Environment and Planning of Henan University, Henan University, Kaifeng, China; State Key Laboratory of Desert and Oasis Ecology, Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, China},
  author_keywords = {climate change; spring onset; urbanization; vegetation phenology},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\ruan_et_al_2019_enhanced_vegetation_growth_in_the_urban_environment_across_32_cities_in_the.pdf}
}

@article{rumora2020,
  title = {Spatial Video Remote Sensing for Urban Vegetation Mapping Using Vegetation Indices},
  author = {Rumora, L. and Majić, I. and Miler, M. and Medak, D.},
  date = {2020},
  journaltitle = {Urban Ecosystems},
  publisher = {{Springer}},
  issn = {10838155},
  doi = {10.1007/s11252-020-01002-5},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086038610&doi=10.1007%2fs11252-020-01002-5&partnerID=40&md5=808ac0b03bdbc0aa3f84d83166172aac},
  abbrev_source_title = {Urban Ecosyst.},
  abstract = {Urban vegetation is important because of the fast-growing urbanization. If we want cities to have sustainable growth and well-kept ecology, we need to develop a smart and efficient urban vegetation monitoring system. This paper examines the possibility of using a modified GoPro camera mounted on a car. The lens of a GoPro camera was replaced with the NDVI-7 lens to obtain blue, green and near-infrared band. The performance of four vegetation indices was tested: Blue normalized difference vegetation index (BNDVI), Green normalized difference vegetation index (GNDVI), Green-blue normalized difference vegetation index (GBNDVI), Blue-wide dynamic range vegetation index (BWDRVI). Based on those indices, binary classification was performed to classify objects in the scene as either vegetation or non-vegetation. Finally, the accuracy of each index was assessed on three different study sites. Results show that GBNDVI performs best for the given task with average classification accuracy of 95.10\% for all study sites. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.},
  affiliation = {Department of Geoinformatics, Faculty of Geodesy, University of Zagreb, Kačićeva 26, Zagreb, 10000, Croatia; Department of Infrastructure Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia},
  author_keywords = {GBNDVI; GoPro; Spatial video; Urban vegetation; Vegetation monitoring},
  correspondence_address1 = {Rumora, L.; Department of Geoinformatics, Faculty of Geodesy, University of Zagreb, Kačićeva 26, Croatia; email: lurumora@geof.hr},
  document_type = {Article},
  funding_details = {Hrvatska Zaklada za ZnanostHrvatska Zaklada za Znanost, HRZZ, IP-2016-06-5621},
  funding_text_1 = {This research was supported by the Croatian Science Foundation under the projects IP-2016-06-5621 ‘Geospatial Monitoring of Green Infrastructure by Means of Terrestrial, Airborne and Satellite Imagery (GEMINI)’.},
  langid = {english},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\rumora_et_al_2020_spatial_video_remote_sensing_for_urban_vegetation_mapping_using_vegetation.pdf}
}

@article{ryu2010,
  title = {Testing the Performance of a Novel Spectral Reflectance Sensor, Built with Light Emitting Diodes ({{LEDs}}), to Monitor Ecosystem Metabolism, Structure and Function},
  author = {Ryu, Youngryel and Baldocchi, Dennis D. and Verfaillie, Joseph and Ma, Siyan and Falk, Matthias and Ruiz-Mercado, Ilse and Hehn, Ted and Sonnentag, Oliver},
  date = {2010-12-15},
  journaltitle = {Agricultural and Forest Meteorology},
  shortjournal = {Agricultural and Forest Meteorology},
  volume = {150},
  number = {12},
  pages = {1597--1606},
  issn = {0168-1923},
  doi = {10.1016/j.agrformet.2010.08.009},
  url = {http://www.sciencedirect.com/science/article/pii/S0168192310002236},
  urldate = {2021-01-06},
  abstract = {We developed and tested the use of light emitting diodes (LEDs) to monitor vegetation reflectance in narrow spectral bands as a tool suitable for quantifying and monitoring ecosystem structure, function and metabolism. LEDs are appealing because they are inexpensive, small and reliable light sources that, when used in reverse mode, can measure spectrally selective radiation. We selected LEDs in red and near-infrared wavebands as they are used to calculate the normalized difference vegetation index (NDVI). The lab experiments revealed that the LEDs showed linear relation with a hyper-spectral spectroradiometer (R2{$>$}0.94 and 0.99 for red and NIR, respectively) and marginal sensitivity to temperature. To test the efficacy of this novel sensor, we measured spectral reflectance with LEDs over an annual grassland in California over 3.5 years. The LED-sensor captured daily to interannual variation of the spectral reflectance at the two bands with reliable and stable performance. The spectral reflectance in the two bands and NDVI proved to be useful to identify the leaf-on and leaf-off dates (mean bias errors of 5.3 and 4.2 days, respectively) and to estimate canopy photosynthesis (R2=0.91). We suggest that this novel instrument can monitor other structural and functional (e.g. leaf area index, leaf nitrogen) variables by employing LEDs that have other specific wavelengths bands. Considering that off-the-shelf LEDs cover a wide range of wavebands from the ultraviolet to near-infrared regions, we believe that the research community could explore a range of similar instruments across a range of bands for a variety of ecological applications.},
  langid = {english},
  keywords = {Canopy photosynthesis,Leaf area index,Light emitting diode,NDVI,Phenology,Spectral reflectance},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\ryu_et_al_2010_testing_the_performance_of_a_novel_spectral_reflectance_sensor,_built_with.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\JWD8RR4B\\S0168192310002236.html}
}

@article{ryu2014,
  title = {Monitoring Multi-Layer Canopy Spring Phenology of Temperate Deciduous and Evergreen Forests Using Low-Cost Spectral Sensors},
  author = {Ryu, Youngryel and Lee, Galam and Jeon, Soohyun and Song, Youngkeun and Kimm, Hyungsuk},
  date = {2014-06-01},
  journaltitle = {Remote Sensing of Environment},
  shortjournal = {Remote Sensing of Environment},
  volume = {149},
  pages = {227--238},
  issn = {0034-4257},
  doi = {10.1016/j.rse.2014.04.015},
  url = {http://www.sciencedirect.com/science/article/pii/S0034425714001588},
  urldate = {2021-01-06},
  abstract = {Emerging near-surface remote sensing techniques have advanced our ability to monitor forest canopy phenology. Thus far, however, little effort has been made to monitor the phenologies of the various canopies of multi-layer forests separately, despite their importance in regulating forest biogeochemical cycles. Here we report phenological changes in multi-layer canopies of deciduous broadleaf and evergreen needleleaf forests in the Republic of Korea during the spring of 2013. We installed light-emitting diode (LED) sensors at four different canopy heights at two sites to measure the normalized difference vegetation index (NDVI) using red and near-infrared (NIR) spectral reflectance and to estimate leaf area index (LAI) using the blue band gap fraction. LED-sensors identified leaf-out dates of over- and understory canopies at both sites; leaves unfolded 8–11days earlier in the understory canopy than the overstory canopy. At the deciduous forest site, LED-NDVI failed to capture the leaf-out date in the overstory canopy, because all four LED-sensors started to see green-up from the understory canopy while the overstory canopy was leafless. LED-LAI identified different leaf-out dates for the over- and understory canopy, because the gap fraction was measured explicitly for each canopy layer. In the evergreen forest site, LED-NDVI signals between the top of the tower and beneath the overstory canopy were decoupled because of the dense evergreen overstory canopy. Both LED-NDVI and LED-LAI identified new needle expansion in the overstory canopy and understory canopy development. MODIS NDVI agreed well with LED-NDVI data (R2=0.96, RMSE=0.04) at the deciduous forest site, and we discovered that understory canopy development determined the onset of greenness based on MODIS NDVI data. LED-LAI data agreed well with independent estimates from the other instruments, indicating that LED-sensors could be used to monitor multi-layer canopy LAI. Continuous, in-situ observation of multi-layer canopy phenology will aid in the interpretation of satellite remote sensing phenology products and improve land surface models that adopt a multi-layer canopy model.},
  langid = {english},
  keywords = {Leaf area index,LED,MODIS,Multi-layer canopy,NDVI,Phenology,Spectral reflectance},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\ryu_et_al_2014_monitoring_multi-layer_canopy_spring_phenology_of_temperate_deciduous_and.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\BD3XRWWS\\S0034425714001588.html}
}

@article{sauliene2019,
  title = {Automatic Pollen Recognition with the {{Rapid-E}} Particle Counter: The First-Level Procedure, Experience and next Steps},
  shorttitle = {Automatic Pollen Recognition with the {{Rapid-E}} Particle Counter},
  author = {Šaulienė, Ingrida and Šukienė, Laura and Daunys, Gintautas and Valiulis, Gediminas and Vaitkevičius, Lukas and Matavulj, Predrag and Brdar, Sanja and Panic, Marko and Sikoparija, Branko and Clot, Bernard and Crouzy, Benoît and Sofiev, Mikhail},
  date = {2019-06-28},
  journaltitle = {Atmospheric Measurement Techniques},
  volume = {12},
  number = {6},
  pages = {3435--3452},
  publisher = {{Copernicus GmbH}},
  issn = {1867-1381},
  doi = {10.5194/amt-12-3435-2019},
  url = {https://amt.copernicus.org/articles/12/3435/2019/},
  urldate = {2021-06-15},
  abstract = {{$<$}p{$><$}strong class="journal-contentHeaderColor"{$>$}Abstract.{$<$}/strong{$>$} Pollen-induced allergies are among the most prevalent non-contagious diseases, with about a quarter of the European population being sensitive to various atmospheric bioaerosols. In most European countries, pollen information is based on a weekly-cycle Hirst-type pollen trap method. This method is labour-intensive and requires narrow specialized abilities and substantial time, so that the pollen data are always delayed and subject to sampling- and counting-related uncertainties. Emerging new approaches to automatic pollen monitoring can, in principle, allow for real-time availability of the data with no human involvement.{$<$}/p{$>$} {$<$}p{$>$}The goal of the current paper is to evaluate the capabilities of the new Plair Rapid-E pollen monitor and to construct a first-level pollen recognition algorithm. The evaluation was performed for three devices located in Lithuania, Serbia and Switzerland, with independent calibration data and classification algorithms. The Rapid-E output data include multi-angle scattering images and the fluorescence spectra recorded at several times for each particle reaching the device. Both modalities of the Rapid-E output were treated with artificial neural networks (ANNs) and the results were combined to obtain the pollen type. For the first classification experiment, the monitor was challenged with a large variety of pollen types and the quality of many-to-many classification was evaluated. It was shown that in this case, both scattering- and fluorescence-based recognition algorithms fall short of acceptable quality. The combinations of these algorithms performed better, exceeding 80\ \% accuracy for 5 out of 11 species. Fluorescence spectra showed similarities among different species, ending up with three well-resolved groups: (\emph{Alnus}, \emph{Corylus}, \emph{Betula} and \emph{Quercus}), (\emph{Salix} and \emph{Populus}) and (\emph{Festuca}, \emph{Artemisia} and \emph{Juniperus}). Within these groups, pollen is practically indistinguishable for the first-level recognition procedure. Construction of multistep algorithms with sequential discrimination of pollen inside each group seems to be one of the possible ways forward. In order to connect the classification experiment to existing technology, a short comparison with the Hirst measurements is presented and the issue of false positive pollen detections by Rapid-E is discussed.{$<$}/p{$>$}},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\sauliene_et_al_2019_automatic_pollen_recognition_with_the_rapid-e_particle_counter.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\CKUXJ5E9\\2019.html}
}

@inproceedings{Savastru2020,
  title = {Assessing Climate Impacts on Urban Forest Changes Using Time Series Satellite Data},
  author = {Savastru, D.M. and Zoran, M.A. and Savastru, R.S.},
  date = {2020},
  series = {Proceedings of {{SPIE}} - {{The International Society}} for {{Optical Engineering}}},
  volume = {11524},
  doi = {10.1117/12.2570453},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091198316&doi=10.1117%2f12.2570453&partnerID=40&md5=f7ae0a3e5d4bf020638bd52d7e8163e1},
  abstract = {Understanding how urban forest land cover responds to climate change requires knowledge of land-surface interaction processes, which control the degree to which interannual variability and mean trends in climatic variables affect the surface energy budget and by this forest vegetation. Urban forest represents unique areas for the detection of climatic change and the assessment of climate-related impacts. Effects of climate extremes and anthropogenic changes on urban/periurban forest systems in Romania can have both short-term and long-term implications for standing biomass, tree health and species composition. This paper used time series of normalized difference of vegetation index (NDVI) and enhanced vegetation index (EVI) as well as leaf area index (LAI) as a measurement indicators of forest dynamics at metropolitan scale in order to assess impacts of climate changes on forest ecosystem phenology in metropolitan area of Bucharest. Use of satellite remote sensing to monitor the forest changes due to climatic stressors is an excellent example of the value of multispectral, multiresolution and multitemporal observations. Fusion technique was applied to time series satellite imagery data (Landsat TM/ETM/OLI, Sentinel 2 and MODIS Terra/Aqua satellite data) for urban/periurban forest ecosystem of Bucharest metropolitan area in Romania over 2000-2019 period. Also, this paper addresses a number of issues related to changes in land surface temperature (LST), and analyses correlations between NDVI/EVI time series and climatic variables under different scenarios for summer heat waves, windstorms and heavy precipitation. © 2020 SPIE.},
  affiliation = {National Institute of R \&d for Optoelectronics, MG5 Bucharest, Magurele, 077125, Romania},
  art_number = {115241V},
  author_keywords = {Biophysical parameters; Bucharest metropolitan area; Romania; Satellite imagery; Urban/periurban forest},
  document_type = {Conference Paper},
  source = {Scopus}
}

@article{seiferling2017,
  title = {Green Streets − {{Quantifying}} and Mapping Urban Trees with Street-Level Imagery and Computer Vision},
  author = {Seiferling, Ian and Naik, Nikhil and Ratti, Carlo and Proulx, Raphäel},
  date = {2017-09-01},
  journaltitle = {Landscape and Urban Planning},
  shortjournal = {Landscape and Urban Planning},
  volume = {165},
  pages = {93--101},
  issn = {0169-2046},
  doi = {10.1016/j.landurbplan.2017.05.010},
  url = {http://www.sciencedirect.com/science/article/pii/S0169204617301147},
  urldate = {2021-01-26},
  abstract = {Traditional tools to map the distribution of urban green space have been hindered by either high cost and labour inputs or poor spatial resolution given the complex spatial structure of urban landscapes. What’s more, those tools do not observe the urban landscape from a perspective in which citizens experience a city. We test a novel application of computer vision to quantify urban tree cover at the street-level. We do so by utilizing the open-source image data of city streetscapes that is now abundant (Google Street View). We show that a multi-step computer vision algorithm segments and quantifies the percent of tree cover in streetscape images to a high degree of precision. By then modelling the relationship between neighbouring images along city street segments, we are able to extend this image representation and estimate the amount of perceived tree cover in city streetscapes to a relatively high level of accuracy for an entire city. Though not a replacement for high resolution remote sensing (e.g., aerial LiDAR) or intensive field surveys, the method provides a new multi-feature metric of urban tree cover that quantifies tree presence and distribution from the same viewpoint in which citizens experience and see the urban landscape.},
  langid = {english},
  keywords = {Computer vision,Greenspace,Streetscapes,Tree cover,Urban trees},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\AUSLXT2Y\\S0169204617301147.html}
}

@article{sekertekin2021,
  title = {Simulation of Future Land Surface Temperature Distribution and Evaluating Surface Urban Heat Island Based on Impervious Surface Area},
  author = {Sekertekin, A. and Zadbagher, E.},
  date = {2021},
  journaltitle = {Ecological Indicators},
  volume = {122},
  publisher = {{Elsevier B.V.}},
  issn = {1470160X},
  doi = {10.1016/j.ecolind.2020.107230},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098458052&doi=10.1016%2fj.ecolind.2020.107230&partnerID=40&md5=e78d4daa845e84f6311fd709e0eaaabc},
  abstract = {This study aims to simulate the future form of Land Surface Temperature (LST) distribution and Surface Urban Heat Island (SUHI) evaluation based on the impervious surface area. For this purpose, Landsat-5 and Landsat-8 satellite data acquired in 2006, 2011 and 2016, respectively, were utilized, and Zonguldak, a province of Turkey, was selected as a test site. In the study, LST image for 2021 was projected using spectral indices, namely Normalized Difference Built-up Index (NDBI) and Normalized Difference Vegetation Index (NDVI). Actually, the correlation analysis between four spectral indices (NDVI, SAVI, MNDWI and NDBI) and LST was conducted. However, NDBI and NDVI were determined as highly correlated indices with LST having correlation coefficient 0.89 and −0.90, respectively, thus MNDWI and SAVI were not considered for the further steps. A Multiple Linear Regression (MLR) analysis was carried out between these two indices (NDBI and NDVI) and LST to extract a mathematical model for LST retrieval. In order to obtain the future form of LST image (2021), these indices were simulated for 2021 using Markov Chain method and then regression model was applied. Before generating LST image for 2021, LST for 2016 image was simulated and compared with the existing 2016 LST image using Kappa index of agreement technique to evaluate the performance. The Kappa value was obtained as 0.73 which is reasonable for future simulation. SUHI evaluation was conducted based on the observed (2016) and simulated (2021) impervious area and normalized LST images. The obtained results showed that the distribution of SUHI effect was highly related to impervious area and if the urbanization rate in the study area continues as it is, this expansion will cause to a dramatic increase in SUHI distribution unless any proper urban planning model is considered by decision makers. © 2020 The Author(s)},
  langid = {english},
  keywords = {Atmospheric temperature,Correlation analysis,Correlation coefficient,data acquisition,Decision making,Impervious surface area,Kappa index of agreements,land surface,Land surface temperature,Landforms,Landsat,Linear regression,Markov chains,Meleagris gallopavo,Multiple linear regressions,NDVI,Normalized difference vegetation index,Normalized differences,satellite data,satellite imagery,simulation,spatial distribution,spectral analysis,surface area,Surface measurement,Surface properties,surface temperature,Surface urban heat islands,Turkey,urban climate,urbanization,Zonguldak}
}

@article{seyednasrollah2019,
  title = {Tracking Vegetation Phenology across Diverse Biomes Using {{Version}} 2.0 of the {{PhenoCam Dataset}}},
  author = {Seyednasrollah, Bijan and Young, Adam M. and Hufkens, Koen and Milliman, Tom and Friedl, Mark A. and Frolking, Steve and Richardson, Andrew D.},
  date = {2019-10-22},
  journaltitle = {Scientific Data},
  volume = {6},
  number = {1},
  pages = {222},
  publisher = {{Nature Publishing Group}},
  issn = {2052-4463},
  doi = {10.1038/s41597-019-0229-9},
  url = {https://www.nature.com/articles/s41597-019-0229-9},
  urldate = {2021-01-26},
  abstract = {Monitoring vegetation phenology is critical for quantifying climate change impacts on ecosystems. We present an extensive dataset of 1783 site-years of phenological data derived from PhenoCam network imagery from 393 digital cameras, situated from tropics to tundra across a wide range of plant functional types, biomes, and climates. Most cameras are located in North America. Every half hour, cameras upload images to the PhenoCam server. Images are displayed in near-real time and provisional data products, including timeseries of the Green Chromatic Coordinate (Gcc), are made publicly available through the project web page (https://phenocam.sr.unh.edu/webcam/gallery/). Processing is conducted separately for each plant functional type in the camera field of view. The PhenoCam Dataset v2.0, described here, has been fully processed and curated, including outlier detection and expert inspection, to ensure high quality data. This dataset can be used to validate satellite data products, to evaluate predictions of land surface models, to interpret the seasonality of ecosystem-scale CO2 and H2O flux data, and to study climate change impacts on the terrestrial biosphere.},
  issue = {1},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\seyednasrollah_et_al_2019_tracking_vegetation_phenology_across_diverse_biomes_using_version_2.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\HCUSPRTS\\s41597-019-0229-9.html}
}

@article{sharma2013,
  title = {Change Assessment of Urban Green Spaces of {{Dehradun}} City Using Image Derived Parameters},
  author = {Sharma, K. and Jalan, S.},
  date = {2013},
  journaltitle = {Transactions of the Institute of Indian Geographers},
  volume = {35},
  number = {1},
  pages = {63--74},
  issn = {09709851},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892730522&partnerID=40&md5=ed7741d4ee30be3f871ff613cc652287},
  abbrev_source_title = {Trans. Inst. Indian Geogr.},
  abstract = {Mapping and monitoring of urban green spaces is a prerequisite for effective management and protection of urban living environment. Fast growth of settlements and consequent ecological problems in urban zones necessitates application of advanced technologies like Remote Sensing to obtain detailed, upto date and accurate information about land use/land cover (LU/LC) status for management and planning of urban growth. This paper attempts to investigate the LU/LC changes in Dehradun city and associated changes in urban green cover over the period from 2004 to 2009.IRS P6 (LISS-IV) datasets of year 2004 and 2009 have been used. LU/LC of both years has been delineated using Maximum Likelihood Supervised classification technique. Classified maps were crossed to generate an urban green cover change map. Normalized Difference Vegetation Index (NDVI) has been employed for detection of change areas and quantification of the amount of decline or increase in urban greenery. Results reveal that over the period of five years a significant decline has occurred in the extent of urban green spaces in Dehradun city with concomitant fragmentation resulting in considerable degradation of urban environment especially in southern parts of the city.},
  affiliation = {University of Rajasthan, Udaipur, Rajasthan, India; Department of Geography, University College of Social Sciences and Humanities, Mohan Lal Sukhadia University, Udaipur, Rajasthan, India},
  author_keywords = {Change detection; IRS-P6 LISS-IV; Land cover; Remote sensing; Urban green space},
  correspondence_address1 = {University of Rajasthan, Udaipur, Rajasthan, India},
  document_type = {Article},
  langid = {english},
  source = {Scopus},
  keywords = {Dehradun,greenspace,image analysis,India,land management,mapping,maximum likelihood analysis,parameterization,remote sensing,urban area,urban growth,Uttarakhand}
}

@article{shiflett2017,
  title = {Variation in the Urban Vegetation, Surface Temperature, Air Temperature Nexus},
  author = {Shiflett, S.A. and Liang, L.L. and Crum, S.M. and Feyisa, G.L. and Wang, J. and Jenerette, G.D.},
  date = {2017},
  journaltitle = {Science of the Total Environment},
  volume = {579},
  pages = {495--505},
  publisher = {{Elsevier B.V.}},
  issn = {00489697},
  doi = {10.1016/j.scitotenv.2016.11.069},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007109734&doi=10.1016%2fj.scitotenv.2016.11.069&partnerID=40&md5=7db8935282cc69a3cb6452c5e0bdb417},
  abbrev_source_title = {Sci. Total Environ.},
  abstract = {Our study examines the urban vegetation – air temperature (Ta) – land surface temperature (LST) nexus at micro- and regional-scales to better understand urban climate dynamics and the uncertainty in using satellite-based LST for characterizing Ta. While vegetated cooling has been repeatedly linked to reductions in urban LST, the effects of vegetation on Ta, the quantity often used to characterize urban heat islands and global warming, and on the interactions between LST and Ta are less well characterized. To address this need we quantified summer temporal and spatial variation in Ta through a network of 300 air temperature sensors in three sub-regions of greater Los Angeles, CA, which spans a coastal to desert climate gradient. Additional sensors were placed within the inland sub-region at two heights (0.1 m and 2 m) within three groundcover types: bare soil, irrigated grass, and underneath citrus canopy. For the entire study region, we acquired new imagery data, which allowed calculation of the normalized difference vegetation index (NDVI) and LST. At the microscale, daytime Ta measured along a vertical gradient, ranged from 6 to 3 °C cooler at 0.1 and 2 m, underneath tall canopy compared to bare ground respectively. At the regional scale NDVI and LST were negatively correlated (p \< 0.001). Relationships between diel variation in Ta and daytime LST at the regional scale were progressively weaker moving away from the coast and were generally limited to evening and nighttime hours. Relationships between NDVI and Ta were stronger during nighttime hours, yet effectiveness of mid-day vegetated cooling increased substantially at the most arid region. The effectiveness of vegetated Ta cooling increased during heat waves throughout the region. Our findings suggest an important but complex role of vegetation on LST and Ta and that vegetation may provide a negative feedback to urban climate warming. © 2016 Elsevier B.V.},
  affiliation = {Department of Botany and Plant Sciences, University of California, Riverside, California, United States; Department of Natural Resource Management, Jimma University, Ethiopia; Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa, United States; Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, Iowa, United States; School of Science, University of Waikato, Hamilton, New Zealand},
  author_keywords = {Air temperature; HyspIRI; Land surface temperature; Microclimate; Urban warming; Vegetation cooling},
  coden = {STEVA},
  correspondence_address1 = {Jenerette, G.D.; Department of Botany and Plant Sciences, University of California, University of WaikatoNew Zealand; email: darrel.jenerette@ucr.edu},
  document_type = {Article},
  funding_details = {National Aeronautics and Space AdministrationNational Aeronautics and Space Administration, NASA, NNX12AQ02G, NNX15AF36G},
  funding_text_1 = {We thank Lindy Allsman, Lauren Velasco, and Carina De La Cueva for providing field assistance. Funding was provided by National Aeronautics and Space Administration (NASA) through grants NNX12AQ02G, NNX15AF36G.},
  langid = {english},
  pubmed_id = {27894802},
  source = {Scopus},
  keywords = {air temperature,Air temperature,arid region,Article,Atmospheric temperature,California,canopy,Citrus,climate,Climate,climate change,Complex networks,environment,Environment,environmental factor,environmental monitoring,Environmental Monitoring,environmental planning,environmental sustainability,environmental temperature,Feedback,Global warming,greenhouse effect,heat island,HyspIRI,land surface,land surface temperature,Land surface temperature,Los Angeles,Los Angeles [California],microclimate,Microclimate,NDVI,priority journal,remote sensing,satellite imagery,Satellite Imagery,season,Seasons,spatial variation,Surface measurement,Surface properties,surface temperature,temperature,Temperature,temperature measurement,United States,urban area,urban climate,Urban warming,urbanization,Urbanization,Vegetation,vegetation cover,vegetation dynamics}
}

@inproceedings{Simoniello2004644,
  title = {Landscape-Scale Characterization of Vegetation Phenology by Using {{AVHRR-NDVI}} and {{Landsat-TM}} Data},
  author = {Simoniello, T. and Carone, M.T. and Lanfredi, M. and Macchiato, M. and Cuomo, V.},
  date = {2004},
  series = {Proceedings of {{SPIE}} - {{The International Society}} for {{Optical Engineering}}},
  volume = {5232},
  pages = {644--651},
  doi = {10.1117/12.511335},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-1942452320&doi=10.1117%2f12.511335&partnerID=40&md5=01aac148db3960fb49600485d1ae9565},
  abstract = {The strict link between intra-annual vegetation dynamics (phenology) and Earth's climate makes phenological information fundamental to improve understanding and models of inter-annual variability in terrestrial carbon exchange and climate-biosphere interactions. In order to monitor phenology in a landscape characterized by heterogeneous features rapidly changing over the territory, we performed multitemporal classifications of NDVI-AVHRR data and interfaced them with Landsat-TM data and orography. The sample area is the Vulture basin (Southern Italy), where cultivated and densely vegetated areas coexist with urban and recently built industrial areas. These land cover patterns rapidly change over the territory at very small spatial scales; it is a complex zone very interesting for studying the use of remote sensing techniques in the integrated monitoring context. Clusters having homogeneous NDVI time behaviors were identified. In spite of its spatial resolution, AVHRR NDVI effectively picks up the characteristic phenology for different covers and altitudes. Moreover, some pixels having particular microclimate were clustered and their characterization was only possible by using orography and TM classification information. The comparison of two intra-annual classifications (1996 and 1998) showed that the proposed approach can be very useful for studying change in pattern of vegetation dynamics.},
  affiliation = {IMAA-CNR, C/da S. Loja - zona Industriale, 85050 Tito Scab (PZ), Italy; DIFA, Università Basilicata, Potenza, Italy; INFM, Unità di. Napoli, Italy; DSF, Università Federico II, Monte Sant'Angelo, Napoli, Italy},
  author_keywords = {AVHRR; Multitemporal classification; NDVI; Phenology; TM},
  document_type = {Conference Paper},
  source = {Scopus}
}

@article{sjoman2018,
  title = {Improving Confidence in Tree Species Selection for Challenging Urban Sites: A Role for Leaf Turgor Loss},
  shorttitle = {Improving Confidence in Tree Species Selection for Challenging Urban Sites},
  author = {Sjöman, H. and Hirons, A. D. and Bassuk, N. L.},
  date = {2018-12},
  journaltitle = {Urban Ecosystems},
  volume = {21},
  number = {6},
  pages = {1171--1188},
  issn = {1083-8155, 1573-1642},
  doi = {10.1007/s11252-018-0791-5},
  url = {http://link.springer.com/10.1007/s11252-018-0791-5},
  urldate = {2020-01-16},
  abstract = {High species diversity is argued to be the most important requisite for a resilient urban forest. In spite of this, there are many cities in the northern hemisphere that have very limited species diversity within their tree population. Consequently, there is an immense risk to urban canopy cover, if these over-used species succumb to serious pests or pathogens. Recognition of this should motivate the use of less commonly used species. Analysis of plant traits, such as the leaf water potential at turgor loss (ΨP0), can provide useful insights into a species’ capacity to grow in warm and dry urban environments. Therefore, the aim of this study was to evaluate ΨP0 of 45 tree species, the majority of which are rare in urban environments. To help evaluate the potential for using ΨP0 data to support future decision-making, a survey of professionals engaged with establishing trees in urban environments was also used to assess the relationship between the measured ΨP0 and the perceived drought tolerance of selected species. This study demonstrates that ΨP0 gives strong evidence for a species’ capacity to tolerate dry growing conditions and is a trait that varies substantially across species. Furthermore, ΨP0 was shown to closely relate to the experience of professionals involved in establishing trees in urban environments, thus providing evidence of its practical significance. Use of plant traits, such as ΨP0, should, therefore, give those specifying trees confidence to recommend non-traditional species for challenging urban environments.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\GSBK7YVQ\\Sjöman et al. - 2018 - Improving confidence in tree species selection for.pdf}
}

@article{skjoth2013,
  title = {Identifying Urban Sources as Cause of Elevated Grass Pollen Concentrations Using {{GIS}} and Remote Sensing},
  author = {Skjøth, C. A. and Ørby, P. V. and Becker, T. and Geels, C. and Schlünssen, V. and Sigsgaard, T. and Bønløkke, J. H. and Sommer, J. and Søgaard, P. and Hertel, O.},
  date = {2013-01-29},
  journaltitle = {Biogeosciences},
  shortjournal = {Biogeosciences},
  volume = {10},
  number = {1},
  pages = {541--554},
  issn = {1726-4189},
  doi = {10.5194/bg-10-541-2013},
  url = {https://bg.copernicus.org/articles/10/541/2013/},
  urldate = {2021-06-07},
  abstract = {Abstract. We examine here the hypothesis that during flowering, the grass pollen concentrations at a specific site reflect the distribution of grass pollen sources within a few kilometres of this site. We perform this analysis on data from a measurement campaign in the city of Aarhus (Denmark) using three pollen traps and by comparing these observations with a novel inventory of grass pollen sources. The source inventory is based on a new methodology developed for urban-scale grass pollen sources. The new methodology is believed to be generally applicable for the European area, as it relies on commonly available remote sensing data combined with management information for local grass areas. The inventory has identified a number of grass pollen source areas present within the city domain. The comparison of the measured pollen concentrations with the inventory shows that the atmospheric concentrations of grass pollen in the urban zone reflect the source areas identified in the inventory, and that the pollen sources that are found to affect the pollen levels are located near or within the city domain. The results also show that during days with peak levels of pollen concentrations there is no correlation between the three urban traps and an operational trap located just 60 km away. This finding suggests that during intense flowering, the grass pollen concentration mirrors the local source distribution and is thus a local-scale phenomenon. Model simulations aimed at assessing population exposure to pollen levels are therefore recommended to take into account both local sources and local atmospheric transport, and not to rely only on describing regional to long-range transport of pollen. The derived pollen source inventory can be entered into local-scale atmospheric transport models in combination with other components that simulate pollen release in order to calculate urban-scale variations in the grass pollen load. The gridded inventory with a resolution of 14 m is therefore made available as supplementary material to this paper, and the verifying grass pollen observations are additionally available in tabular form.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\DRUVAQSZ\\Skjøth et al. - 2013 - Identifying urban sources as cause of elevated gra.pdf}
}

@article{smerdu2020,
  title = {Automatic Detection of Japanese Knotweed in Urban Areas from Aerial and Satellite Data},
  author = {Smerdu, A. and Kanjir, U. and Kokalj, Ž.},
  date = {2020},
  journaltitle = {Management of Biological Invasions},
  volume = {11},
  number = {4},
  pages = {661--676},
  publisher = {{Regional Euro-Asian Biological Invasions Centre}},
  issn = {19898649},
  doi = {10.3391/mbi.2020.11.4.03},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097490772&doi=10.3391%2fmbi.2020.11.4.03&partnerID=40&md5=646b59276cb83a129eca9f7bdd13b152},
  abbrev_source_title = {Manag. Biol. Invasions},
  abstract = {Presence of invasive alien plant species in urban areas has become an issue throughout the globe. City administrations are making efforts to avoid invasions, to eradicate and/or control invasive species, or alternatively, try to process them into useful products. To monitor the spread of species over a region, it is important to map invasive species. In the scope of the APPLAUSE project, we have developed a One-Class support vector machine (SVM) approach to detect invasive species from individual aerial and multiple Sentinel-2 satellite images over the City of Ljubljana (Slovenia). In this paper, we focus specifically on the detection of Japanese knotweed, because it produces large stands and is therefore the most detectable invasive species in the studied area. The proposed SVM approach uses red-green-blue (RGB) band composites and infrared (IR) bands as input data for aerial images, while for satellite images additionally normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) are used. In the study, we used ground truth data collected by experts both as training and as validation data. On aerial images, we first perform segmentation, which is followed by two One-Class SVM classifications. On these classification outputs, we use K-means algorithm on the IR band, which groups the samples and removes the ones that were falsely recognized as Japanese knotweed. Merging the results together and masking out small samples and areas where Japanese knotweed is not present, we get the final result. On satellite data the approach is similar; the only difference is the usage of multiple input images from different acquisition dates for SVM classification. For detection of Japanese knotweed from the aerial images the accuracy was 83\%, and 90\% for stands larger than 100 m2 on satellite data. The results demonstrate that the applied methodology with the qualitative ground truth data can be used operationally for automatic detection of Japanese knotweed on the municipality level. © Smerdu et al.},
  affiliation = {Centre of Excellence for Space Sciences and Technologies (Space-SI), Aškerčeva cesta 12, Ljubljana, 1000, Slovenia; Research Centre of the Slovenian Academy of Sciences and Arts (ZRC SAZU), Novi trg 2, Ljubljana, 1000, Slovenia},
  author_keywords = {Invasive species; Orthophoto; Phenology; Sentinel-2; SVM},
  correspondence_address1 = {Kanjir, U.; Research Centre of the Slovenian Academy of Sciences and Arts (ZRC SAZU), Centre of Excellence for Space Sciences and Technologies (Space-SI), Novi trg 2, Slovenia; email: ukanjir@zrc-sazu.si},
  document_type = {Article},
  funding_details = {Urban Innovative ActionsUrban Innovative Actions, UIA},
  funding_text_1 = {This research was partly funded under the scope of APPLAUSE project, which is co-financed by the European Regional Development Fund through the Urban Innovative Actions (UIA) initiative and by the Slovenian Research Agency core funding (No. P2-0406), as well as a research project (No. J6-9395). The information and standpoints exclusively reflect the authors’ views. The UIA initiative shall not be liable for them nor for their use.},
  langid = {english},
  source = {Scopus}
}

@article{smith2020,
  title = {A Comparison of Ground-Based Methods for Obtaining Large-Scale, High-Resolution Data on the Spring Leaf Phenology of Temperate Tree Species},
  author = {Smith, Alison M. and Ramsay, Paul M.},
  date = {2020-03-01},
  journaltitle = {International Journal of Biometeorology},
  shortjournal = {Int J Biometeorol},
  volume = {64},
  number = {3},
  pages = {521--531},
  issn = {1432-1254},
  doi = {10.1007/s00484-019-01839-2},
  url = {https://doi.org/10.1007/s00484-019-01839-2},
  urldate = {2021-06-07},
  abstract = {Phenological variation in spring leafing between and within species can determine plant responses to warmer winter and spring temperatures in the short term. Methods are needed for monitoring canopy development that can be replicated on a large-scale, while retaining fine-scale resolution at the level of individual trees. Citizen science has the potential to provide this, but a range of approaches exist in terms of the phenophase recorded (e.g. budburst or leaf expansion), how the phenophase is characterised (first events or intensity monitoring) and the portion of tree crown assessed and observation frequency. A comparison of spring budburst and leaf expansion of four tree species (Fraxinus excelsior, Fagus sylvatica, Quercus robur and Acer pseudoplatanus) was monitored in one woodland using (1) counts of expanded leaves on three crown sections, (2) percentage estimates of expanded leaves across the whole crown and (3) a greenness index from photography. Logistic growth models were applied to make comparisons. First-event dates were found to be misleading due to high variation in leaf development rates within and between species. Percentage estimates and counts produced similar estimates of leaf expansion timing and rate. The greenness index produced similar estimates of timing, but not rate, and was compromised by practicalities of photographing individual crowns in closed-canopy woodland. Citizen scientists could collect data across the period of spring leafing, with visual counts and/or estimates made every 3–4~days, subject to tests of reliability in pilot citizen science studies.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\smith_ramsay_2020_a_comparison_of_ground-based_methods_for_obtaining_large-scale,_high-resolution.pdf}
}

@article{sonti2019,
  title = {White Oak and Red Maple Tree Ring Analysis Reveals Enhanced Productivity in Urban Forest Patches},
  author = {Sonti, Nancy F. and Hallett, Richard A. and Griffin, Kevin L. and Sullivan, Joe H.},
  date = {2019-12},
  journaltitle = {Forest Ecology and Management},
  volume = {453},
  pages = {117626},
  issn = {03781127},
  doi = {10.1016/j.foreco.2019.117626},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0378112719306309},
  urldate = {2020-02-25},
  abstract = {Many aspects of the urban environment have the potential to affect tree growth and physiology in forest patches, including higher temperatures, elevated CO2 concentrations, and modified soil biogeochemistry from increased nutrient and heavy metal inputs. However, these changes in tree growth are likely to vary by species and across urban areas, reflecting the local environmental conditions associated with the idiosyncratic trajectory of development in a city. Here, we examine growth rates of two dominant native tree species (white oak (Quercus alba L.) and red maple (Acer rubrum L.)) across urban and reference forest sites of three major cities in the eastern United States (New York, NY (NYC); Philadelphia, PA; and Baltimore, MD). We also characterized soil physical and chemical properties around each tree and monitored air temperature over three growing seasons at each site. Throughout the growing season, the urban sites had consistently warmer daytime and nighttime temperatures than reference sites. Urban forest patch soils also had elevated calcium, magnesium, and heavy metal concentrations compared to reference forest soils. Urban vs. reference tree growth rates varied by species, by city, and over time. Despite differences in the two native species’ ecophysiology, both grew more rapidly in the urban environment than at nearby reference sites, particularly in recent decades. Over the entire 145-year tree ring record analyzed, white oak basal area increment was significantly higher in urban trees compared to reference trees. Changes in the relative production of white oak earlywood and latewood between site types in each city and over time may relate to precipitation patterns. Perhaps due to their ability to persist in a wide variety of environmental conditions, mature trees of both species appear to be acclimating to urban forest patch conditions of the eastern U.S. and in some cases are experiencing enhanced growth rates compared to trees in nearby reference forests. An understanding of past and present growth rates of trees in urban forest patches can provide insight into future ecosystem functioning of these urban green spaces as well as that of more rural ecosystems experiencing environmental change factors similar to those associated with urbanization.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\T8LBDABB\\Sonti et al. - 2019 - White oak and red maple tree ring analysis reveals.pdf}
}

@article{stratopoulos2019a,
  title = {Effects of {{Drought}} on the {{Phenology}}, {{Growth}}, and {{Morphological Development}} of {{Three Urban Tree Species}} and {{Cultivars}}},
  author = {Stratopoulos, Laura and {Zhang} and Häberle, Karl-Heinz and Pauleit, Stephan and {Duthweiler} and {Pretzsch} and Rötzer, Thomas},
  date = {2019-09-18},
  journaltitle = {Sustainability},
  shortjournal = {Sustainability},
  volume = {11},
  pages = {5117},
  doi = {10.3390/su11185117},
  abstract = {: Under changing climatic conditions, drought may become a critical constraint for trees in urban areas, particularly at roadsides and highly paved squares. As healthy urban trees have proven to be an important mitigation and adaptation tool for climate change as well as a significant provider of ecosystem services, there is a need for planting species and cultivars capable of coping with the limited water supply. However, data on species’ and cultivars’ response to drought, particularly their water supplying root systems remains rare. To consider the whole plant responses to drought situations, we studied the growth and phenology of three frequently planted tree species and cultivars with a diameter of 5–6 cm during a one-year rainfall exclusion experiment conducted in a nursery field as well as the dry biomass of the compartments branch, stem, and root after excavation. Our results revealed that species’ and cultivars’ performance were linked to their within-plant carbon partitioning. A high tolerance to drought was noted for Acer campestre, with a particularly high ratio of root:shoot ratio, which made it presumably less susceptible to droughts. Tilia cordata ‘Greenspire’ was highly affected by the reduced water availability visible through prematurely leaf senescence, while Carpinus betulus ‘Fastigiata’ suffered from losing a considerable part of its root biomass, which resulted in the lowest root:shoot ratio of all species and cultivars. This study demonstrated the need for investigating the reaction patterns of species and cultivars by considering both the above-and the below-ground plant parts. We recommend that, for future tree plantings at harsh and challenging urban sites, an important selection criterion should be species’ and cultivars’ capability to develop and retain strong and dense root systems even under limited water supply, as that is believed to be an important trait for drought tolerance.},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\6GJEFVXC\\Stratopoulos et al_2019_Effects of Drought on the Phenology, Growth, and Morphological Development of.pdf}
}

@article{Su2020,
  title = {Phenology Acts as a Primary Control of Urban Vegetation Cooling and Warming: {{A}} Synthetic Analysis of Global Site Observations},
  author = {Su, Y. and Liu, L. and Liao, J. and Wu, J. and Ciais, P. and Liao, J. and He, X. and Liu, X. and Chen, X. and Yuan, W. and Zhou, G. and Lafortezza, R.},
  date = {2020},
  journaltitle = {Agricultural and Forest Meteorology},
  volume = {280},
  doi = {10.1016/j.agrformet.2019.107765},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072640606&doi=10.1016%2fj.agrformet.2019.107765&partnerID=40&md5=cb5cda8d54f7475124835517a0a23a73},
  abstract = {Urban vegetation can influence local air temperatures through its biophysical effects on surface energy balance. These effects produce gradients (ΔTa) between air temperature of vegetation spaces (Tveg) and air temperature of open spaces (Topen) (ΔTa=Tveg−Topen), hereafter referred to as vegetation cooling (negative values of ΔTa) and warming (positive values of ΔTa), respectively. But vegetation cooling or warming highly depends on background climate of urban areas as well as on vegetation states. Field observations are usually restricted to one or few cities, setting limitations to a general understanding. In this study, a synthetic analysis of 3634 point-scale in-situ observations from 77 global sites in 35 cites was conducted using the bootstrap sampling and hierarchical partitioning methods. Results show that vegetation cooling is generally stronger during the daytime periods, in warm seasons, at low latitude zones, for forest lands and at leaf growth stage, while vegetation warming usually occurs in the opposite contexts. Urban vegetation begins to exert considerable cooling effects when the daily mean background air temperature (BAT) is \>10.0 °C, but on average has a slight warming effect when BAT is \<10.0 °C. Besides, vegetation cooling increases sharply when evapotranspiration is \>61.7 mm/month or when area of urban vegetation is \>35.2 ha. Plant growth stages (i.e., canopy leaf growth, senescence and dormancy stages) (37.6 ± 0.11\%), a vegetation phenology proxy, acts as the primary biotic factor, while seasonality (23.0 ± 0.11\%) and latitude (11.4 ± 0.07\%) that control the background climate are two most important abiotic contributors. Our findings suggest approximate thresholds for distinguishing vegetation cooling/warming effects and provide helpful information for future urban greenspace planning aimed at mitigating local climate warming. © 2019 Elsevier B.V.},
  affiliation = {Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou, 510070, China; Laboratoire des Sciences du Climat et de l'Environnement, UMR 1572 CEA-CNRS UVSQ, Gif sur, Yvette 91191, France; Department of Geography and City Planning, University of Toronto, Toronto, Ontario M5S 3G3, Canada; College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, 510642, China; Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, 510275, China; Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai), Zhuhai, China; Institute of Ecology, Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science \& Technology, Nanjing, 210044, China; Department of Geography, The University of Hong Kong, Centennial Campus, Pokfulam Road, Hong Kong; Department of Agricultural and Environmental Sciences, University of Bari “A. Moro”, Via Amendola 165/A, Bari, 70126, Italy},
  art_number = {107765},
  author_keywords = {Background climate; Canopy shading; Cooling and warming effect; Evapotranspiration; Plant phenology; Urban vegetation},
  document_type = {Article},
  source = {Scopus}
}

@report{szbi2015,
  title = {Straßenbaum-Zustandsbericht "Berliner Innenstadt 2015"},
  author = {{SZBI}},
  date = {2015},
  series = {Ergebnisse der Straßenbaum-Zustandserhebung aus CIR-Luftbildern},
  pages = {17},
  institution = {{Senatsverwaltung für Stadtentwicklung}},
  location = {{Berlin}},
  langid = {german},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\PNFKHH3T\\2015 - Straßenbaum-Zustandsbericht Berliner Innenstadt 2.pdf}
}

@article{taylor2020,
  title = {Automated Data‐intensive Forecasting of Plant Phenology throughout the {{United States}}},
  author = {Taylor, Shawn D. and White, Ethan P.},
  date = {2020-01},
  journaltitle = {Ecological Applications},
  shortjournal = {Ecol Appl},
  volume = {30},
  number = {1},
  issn = {1051-0761, 1939-5582},
  doi = {10.1002/eap.2025},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/eap.2025},
  urldate = {2021-06-07},
  abstract = {Phenology, the timing of cyclical and seasonal natural phenomena such as flowering and leaf out, is an integral part of ecological systems with impacts on human activities like environmental management, tourism, and agriculture. As a result, there are numerous potential applications for actionable predictions of when phenological events will occur. However, despite the availability of phenological data with large spatial, temporal, and taxonomic extents, and numerous phenology models, there have been no automated species-level forecasts of plant phenology. This is due in part to the challenges of building a system that integrates large volumes of climate observations and forecasts, uses that data to fit models and make predictions for large numbers of species, and consistently disseminates the results of these forecasts in interpretable ways. Here, we describe a new near-term phenology-forecasting system that makes predictions for the timing of budburst, flowers, ripe fruit, and fall colors for 78 species across the United States up to 6 months in advance and is updated every four days. We use the lessons learned in developing this system to provide guidance developing large-scale near-term ecological forecast systems more generally, to help advance the use of automated forecasting in ecology.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\2ZVHW8SZ\\Taylor and White - 2020 - Automated data‐intensive forecasting of plant phen.pdf}
}

@article{Tian2020,
  title = {Investigating the Urban-Induced Microclimate Effects on Winter Wheat Spring Phenology Using {{Sentinel-2}} Time Series},
  author = {Tian, J. and Zhu, X. and Shen, Z. and Wu, J. and Xu, S. and Liang, Z. and Wang, J.},
  date = {2020},
  journaltitle = {Agricultural and Forest Meteorology},
  volume = {294},
  doi = {10.1016/j.agrformet.2020.108153},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089949003&doi=10.1016%2fj.agrformet.2020.108153&partnerID=40&md5=7f571f04540d6d9fd2176a0c31843ef4},
  abstract = {Temperature is one of the most important factors controlling the phenology of winter wheat. Rapid urbanization in China dramatically modifies the microclimate, especially temperature, surrounding cities. However, it is unclear whether such urban-induced changes in microclimate can influence the phenology of winter wheat and whether the influence is consistent across cities of different sizes. Here, we investigated the urban-induced microclimate effects on winter wheat spring phenology (i.e., the regreen-up date, RGUD) in three cities spanning a range of sizes in northern China. These three cities include Shijiazhuang (350.98 km2), Baoding (118.95 km2), and Linqing (55.12 km2), and the key data for this study are Sentinel-2 images. Based on the Sentinel-2 images, we first calculated a vegetation index (normalized difference phenology index, NDPI), and then extracted winter wheat RGUD. Finally, we analyzed the distribution of the RGUD along an urban-rural gradient using buffers surrounding the urban areas. Our study has three main results: (1) The RGUD shows a significant increasing trend along the urban-rural gradients in both Shijiazhuang and Baoding, suggesting that urban-induced increases in temperature indeed advance the spring phenology of winter wheat. (2) The maximum influence size of the urban-induced temperature effects on the RGUD is positively correlated with city size, i.e., 27 km for Shijiazhuang, 14 km for Baoding and 7 km for Linqing. (3) The change rate of the RGUD with distance along the urban-rural gradient is significantly higher in the large city (Shijiazhuang: 0.26 day/km) than it is in the middle- and small-scale cities (Baoding: 0.21 day/km and Linqing: 0.11 day/km), which suggests that larger cities spread heat at a faster rate than that of smaller cities. This study suggests that the planting and management of winter wheat surrounding cities should consider the influence of city size to optimize yields. © 2020 Elsevier B.V.},
  affiliation = {Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic UniversityHong Kong, Hong Kong; Research Institute for Sustainable Urban Development, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China; School of Biological Sciences, Faculty of Science, The University of Hong KongHong Kong, Hong Kong},
  art_number = {108153},
  author_keywords = {NDPI; Sentinel-2 time series; Spring phenology; Urban heat island; Winter wheat},
  document_type = {Article},
  source = {Scopus}
}

@article{tigges2013,
  title = {Urban Vegetation Classification: {{Benefits}} of Multitemporal {{RapidEye}} Satellite Data},
  author = {Tigges, J. and Lakes, T. and Hostert, P.},
  date = {2013},
  journaltitle = {Remote Sensing of Environment},
  volume = {136},
  pages = {66--75},
  issn = {00344257},
  doi = {10.1016/j.rse.2013.05.001},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878372022&doi=10.1016%2fj.rse.2013.05.001&partnerID=40&md5=355c941a0c23fb8e441dc7a2191ef8b4},
  abbrev_source_title = {Remote Sens. Environ.},
  abstract = {Global climate change and sustained urban growth have increased the necessity of assessing the role that urban vegetation plays in urban dwellers' lives, as well as in urban ecosystem services. Urban environmental studies, however, still lack methods to characterize urban vegetation with adequate detail and across large areas. To remedy this gap, we apply a Support-Vector-Machine approach to classify eight frequent tree genera in the capital city of Berlin, Germany. We investigate different spectral and temporal band combinations of five RapidEye images acquired during the 2009 phenological season, and use ancillary surface and terrain models for orthorectification and improved tree masking. Results show that intra-annual time-series of RapidEye data can be used for high-precision tree genera classification in an urban environment. Differences within RapidEye time-series correlate well with empirical phenological studies of different tree genera, and RapidEye's red-edge band supports class separability. Further assessment is needed on the individual tree level and mixed stands regarding the quality of mapping urban individual trees, as our sampling approach mainly focused on larger stands with only a single tree genus. Urban applications will benefit from multitemporal RapidEye data, which offers area-wide monitoring and allows in-depth vegetation analysis to augment existing assessments. Such information is indispensable for assessing differences in urban ecosystem services related to carbon storage, cooling or air filtering, all of which differ between tree species. Therefore, the importance of in-depth analyses of urban vegetation cannot be underestimated in today's context of climate change. © 2013 Elsevier Inc.},
  affiliation = {Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany},
  author_keywords = {Automatic feature selection; RapidEye; Red-edge; Support Vector Machine; Tree species classification; Urban ecology; Urban ecosystem services; Urban remote sensing; Vegetation phenology},
  coden = {RSEEA},
  correspondence_address1 = {Tigges, J.; Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany; email: jan.tigges@geo.hu-berlin.de},
  document_type = {Article},
  funding_details = {Deutsche ForschungsgemeinschaftDeutsche Forschungsgemeinschaft, DFG, 32108303, 32108304},
  funding_text_1 = {This study was supported by the German Research Foundation (DFG) as part of the Research Training Group 780 3 and 4 on “Perspectives on Urban Ecology” (project numbers: 32108303 and 32108304 ). The authors would like to thank Berlin Partner GmbH and virtualcitySYSTEMS GmbH for providing pre-processed LiDAR data of Berlin. The authors are grateful to Tom Bewernick (Institute of Ecology, Technical University of Berlin) for the field survey assistance, and for sharing his great expertise on urban vegetation in Berlin. We thank the two anonymous reviewers for their very useful input.},
  langid = {english},
  source = {Scopus},
  keywords = {Automatic feature selection,Berlin,carbon sequestration,Classification,climate change,Climate change,cooling,Ecology,ecosystem service,Ecosystems,environmental quality,Forestry,Germany,Information filtering,phenology,Plants,Rapideye,Red-edge,satellite data,Species Identification,Support vector machines,time series,Tree species,Trees,Trees (mathematics),urban area,Urban ecology,urban ecosystem,Urban ecosystem,urban growth,Urban remote sensing,Vegetation,vegetation classification,Vegetation phenology}
}

@article{Tigges201366,
  title = {Urban Vegetation Classification: {{Benefits}} of Multitemporal {{RapidEye}} Satellite Data},
  author = {Tigges, J. and Lakes, T. and Hostert, P.},
  date = {2013},
  journaltitle = {Remote Sensing of Environment},
  volume = {136},
  pages = {66--75},
  doi = {10.1016/j.rse.2013.05.001},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878372022&doi=10.1016%2fj.rse.2013.05.001&partnerID=40&md5=355c941a0c23fb8e441dc7a2191ef8b4},
  abstract = {Global climate change and sustained urban growth have increased the necessity of assessing the role that urban vegetation plays in urban dwellers' lives, as well as in urban ecosystem services. Urban environmental studies, however, still lack methods to characterize urban vegetation with adequate detail and across large areas. To remedy this gap, we apply a Support-Vector-Machine approach to classify eight frequent tree genera in the capital city of Berlin, Germany. We investigate different spectral and temporal band combinations of five RapidEye images acquired during the 2009 phenological season, and use ancillary surface and terrain models for orthorectification and improved tree masking. Results show that intra-annual time-series of RapidEye data can be used for high-precision tree genera classification in an urban environment. Differences within RapidEye time-series correlate well with empirical phenological studies of different tree genera, and RapidEye's red-edge band supports class separability. Further assessment is needed on the individual tree level and mixed stands regarding the quality of mapping urban individual trees, as our sampling approach mainly focused on larger stands with only a single tree genus. Urban applications will benefit from multitemporal RapidEye data, which offers area-wide monitoring and allows in-depth vegetation analysis to augment existing assessments. Such information is indispensable for assessing differences in urban ecosystem services related to carbon storage, cooling or air filtering, all of which differ between tree species. Therefore, the importance of in-depth analyses of urban vegetation cannot be underestimated in today's context of climate change. © 2013 Elsevier Inc.},
  affiliation = {Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany},
  author_keywords = {Automatic feature selection; RapidEye; Red-edge; Support Vector Machine; Tree species classification; Urban ecology; Urban ecosystem services; Urban remote sensing; Vegetation phenology},
  document_type = {Article},
  source = {Scopus}
}

@article{timilsina2020,
  title = {Mapping Urban Tree Cover Changes Using Object-Based Convolution Neural Network ({{OB-CNN}})},
  author = {Timilsina, S. and Aryal, J. and Kirkpatrick, J.B.},
  date = {2020},
  journaltitle = {Remote Sensing},
  volume = {12},
  number = {18},
  publisher = {{MDPI AG}},
  issn = {20724292},
  doi = {10.3390/RS12183017},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092112272&doi=10.3390%2fRS12183017&partnerID=40&md5=4f1365f720006efbe141ff8f61c2250e},
  abbrev_source_title = {Remote Sens.},
  abstract = {Urban trees provide social, economic, environmental and ecosystem services benefits that improve the liveability of cities and contribute to individual and community wellbeing. There is thus a need for effective mapping, monitoring and maintenance of urban trees. Remote sensing technologies can effectively map and monitor urban tree coverage and changes over time as an efficient and low-cost alternative to field-based measurements, which are time consuming and costly. Automatic extraction of urban land cover features with high accuracy is a challenging task, and it demands object based artificial intelligence workflows for efficiency and thematic accuracy. The aim of this research is to effectively map urban tree cover changes and model the relationship of such changes with socioeconomic variables. The object-based convolutional neural network (CNN) method is illustrated by mapping urban tree cover changes between 2005 and 2015/16 using satellite, Google Earth imageries and Light Detection and Ranging (LiDAR) datasets. The training sample for CNN model was generated by Object Based Image Analysis (OBIA) using thresholds in a Canopy Height Model (CHM) and the Normalised Difference Vegetation Index (NDVI). The tree heatmap produced from the CNN model was further refined using OBIA. Tree cover loss, gain and persistence was extracted, and multiple regression analysis was applied to model the relationship with socioeconomic variables. The overall accuracy and kappa coefficient of tree cover extraction was 96\% and 0.77 for 2005 images and 98\% and 0.93 for 2015/16 images, indicating that the object-based CNN technique can be effectively implemented for urban tree coverage mapping and monitoring. There was a decline in tree coverage in all suburbs. Mean parcel size and median household income were significantly related to tree cover loss (R2 = 58.5\%). Tree cover gain and persistence had positive relationship with tertiary education, parcel size and ownership change (gain: R2 = 67.8\% and persistence: R2 = 75.3\%). The research findings demonstrated that remote sensing data with intelligent processing can contribute to the development of policy input for management of tree coverage in cities. © 2020 by the authors.},
  affiliation = {School of Technology, Environments and Design, Discipline of Geography and Spatial Sciences, University of Tasmania, Hobart, TAS 7001, Australia; Melbourne School of Engineering, University of Melbourne, Parkville, VIC 3010, Australia},
  art_number = {3017},
  author_keywords = {Convolution neural networks (CNNs); Deep learning; GEOBIA; Object-based CNN; Socioeconomic predictor variables; Urban tree mapping},
  correspondence_address1 = {Aryal, J.; Melbourne School of Engineering, University of MelbourneAustralia; email: Jagannath.aryal@unimelb.edu.au},
  document_type = {Article},
  funding_details = {University of TasmaniaUniversity of Tasmania, UTAS},
  funding_text_1 = {This research received no external funding. The authors wish to thank the Kingborough Council, Tasmania for providing the aerial imagery of the study area. We are grateful to the University of Tasmania for providing research facilities. We also thank Google Earth and Land Information System Tasmania (LIST) for providing imagery and LiDAR point cloud and cadastral parcel datasets.},
  langid = {english},
  source = {Scopus},
  keywords = {Convolution,Convolution neural network,Convolutional neural networks,Data handling,Ecosystems,Extraction,Field-based measurements,Forestry,Heating,Intelligent processing,Light detection and ranging,Lithium compounds,Mapping,Multiple regression analysis,Normalised difference vegetation index,Object based image analysis (OBIA),Optical radar,Regression analysis,Remote sensing,Remote sensing technology,Research and development management,Trees (mathematics)}
}

@article{ustin2021,
  title = {Current and Near-Term Advances in {{Earth}} Observation for Ecological Applications},
  author = {Ustin, S.L. and Middleton, E.M.},
  date = {2021},
  journaltitle = {Ecological Processes},
  volume = {10},
  number = {1},
  publisher = {{Springer Science and Business Media Deutschland GmbH}},
  issn = {21921709},
  doi = {10.1186/s13717-020-00255-4},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098552549&doi=10.1186%2fs13717-020-00255-4&partnerID=40&md5=4cbbb2cb0ec254d2937167d78e1b9724},
  abstract = {There is an unprecedented array of new satellite technologies with capabilities for advancing our understanding of ecological processes and the changing composition of the Earth’s biosphere at scales from local plots to the whole planet. We identified 48 instruments and 13 platforms with multiple instruments that are of broad interest to the environmental sciences that either collected data in the 2000s, were recently launched, or are planned for launch in this decade. We have restricted our review to instruments that primarily observe terrestrial landscapes or coastal margins and are available under free and open data policies. We focused on imagers that passively measure wavelengths in the reflected solar and emitted thermal spectrum. The suite of instruments we describe measure land surface characteristics, including land cover, but provide a more detailed monitoring of ecosystems, plant communities, and even some species then possible from historic sensors. The newer instruments have potential to greatly improve our understanding of ecosystem functional relationships among plant traits like leaf mass area (LMA), total nitrogen content, and leaf area index (LAI). They provide new information on physiological processes related to photosynthesis, transpiration and respiration, and stress detection, including capabilities to measure key plant and soil biophysical properties. These include canopy and soil temperature and emissivity, chlorophyll fluorescence, and biogeochemical contents like photosynthetic pigments (e.g., chlorophylls, carotenoids, and phycobiliproteins from cyanobacteria), water, cellulose, lignin, and nitrogen in foliar proteins. These data will enable us to quantify and characterize various soil properties such as iron content, several types of soil clays, organic matter, and other components. Most of these satellites are in low Earth orbit (LEO), but we include a few in geostationary orbit (GEO) because of their potential to measure plant physiological traits over diurnal periods, improving estimates of water and carbon budgets. We also include a few spaceborne active LiDAR and radar imagers designed for quantifying surface topography, changes in surface structure, and 3-dimensional canopy properties such as height, area, vertical profiles, and gap structure. We provide a description of each instrument and tables to summarize their characteristics. Lastly, we suggest instrument synergies that are likely to yield improved results when data are combined. © 2021, The Author(s).},
  langid = {english},
  keywords = {Biogeochemistry,Biophysical properties,Budget control,Chlorophyll,Chlorophyll fluorescence,Composition of the Earth,Cost Control,Cyanobacteria,Earth (planet),Ecosystems,Functional relationship,Geostationary satellites,Land surface characteristics,Nitrogen,Open Data,Optical radar,Orbits,Photosynthetic pigments,Physiology,

license: MIT

license_type: permissive

branch_name: refs/heads/master

extension: bib