text:
84949844107&doi=10.1109%2fJSTARS.2015.2496951&partnerID=40&md5=eed77ad94d484631feb6dae0593e0274},
  abstract = {Urbanization increases the impacts of cities on the natural environment, in part by altering local environmental conditions. The Web-Enabled Landsat Data (WELD) archive (2003-2012) provides an opportunity to analyze the impacts of urbanization and urban heat islands (UHIs) on vegetation dynamics in and around cities. Here, we modeled the WELD normalized difference vegetation index (NDVI) product as a convex quadratic function of thermal time and derived land surface phenology (LSP) metrics to investigate the influence of UHIs on LSP along an urban-rural gradient and to characterize the response of vegetation to urbanization for two cities in the U.S. Northern Great Plains. Results show that for perennial vegetation, proximity to city center is positively associated with increased duration of growing season in thermal time. We found a linear relationship between the modeled rate of vegetation green-up and the peak height of NDVI for developed and forest pixels and after croplands were converted to developed land covers. © 2015 IEEE.},
  affiliation = {South Dakota State University, Brookings, SD 57007, United States},
  art_number = {7335573},
  author_keywords = {Environmental monitoring; geospatial analysis; remote sensing; urban areas; vegetation mapping},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\krehbiel_et_al_2016_web-enabled_landsat_data_time_series_for_monitoring_urban_heat_island_impacts.pdf}
}

@article{Krehbiel2017,
  title = {Impacts of Thermal Time on Land Surface Phenology in Urban Areas},
  author = {Krehbiel, C. and Zhang, X. and Henebry, G.M.},
  date = {2017},
  journaltitle = {Remote Sensing},
  volume = {9},
  number = {5},
  doi = {10.3390/rs9050499},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019963876&doi=10.3390%2frs9050499&partnerID=40&md5=72d634ac54c24156d3cef7381662f896},
  abstract = {Urban areas alter local atmospheric conditions by modifying surface albedo and consequently the surface radiation and energy balances, releasing waste heat from anthropogenic uses, and increasing atmospheric aerosols, all of which combine to increase temperatures in cities, especially overnight, compared with surrounding rural areas, resulting in a phenomenon called the "urban heat island" effect. Recent rapid urbanization of the planet has generated calls for remote sensing research related to the impacts of urban areas and urbanization on the natural environment. Spatially extensive, high spatial resolution data products are needed to capture phenological patterns in regions with heterogeneous land cover and external drivers such as cities, which are comprised of a mixture of land cover/land uses and experience microclimatic influences. Here we use the 30 m normalized difference vegetation index (NDVI) product from the Web-Enabled Landsat Data (WELD) project to analyze the impacts of urban areas and their surface heat islands on the seasonal development of the vegetated land surface along an urban-rural gradient for 19 cities located in the Upper Midwest of the United States. We fit NDVI observations from 2003-2012 as a quadratic function of thermal time as accumulated growing degree-days (AGDD) calculated from the Moderate-resolution Imaging Spectroradiometer (MODIS) 1 km land surface temperature product to model decadal land surface phenology metrics at 30 m spatial resolution. In general, duration of growing season (measured in AGDD) in green core areas is equivalent to duration of growing season in urban extent areas, but significantly longer than duration of growing season in areas outside of the urban extent. We found an exponential relationship in the difference of duration of growing season between urban and surrounding rural areas as a function of distance from urban core areas for perennial vegetation, with an average magnitude of 669 AGDD (base 0 C) and the influence of urban areas extending greater than 11 km from urban core areas. At the regional scale, relative change in duration of growing season does not appear to be significantly related to total area of urban extent, population, or latitude. The distance and magnitude that urban areas exert influence on vegetation in and near cities is relatively uniform. © 2017 by the authors.},
  affiliation = {Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD 57007, United States; Department of Geography, South Dakota State University, Brookings, SD 57007, United States; Department of Natural Resource Management, South Dakota State University, Brookings, SD 57007, United States},
  art_number = {107},
  author_keywords = {Growing degree-days; Land surface phenology; Land surface temperature; MODIS; NDVI; Surface urban heat island; Web-Enabled Landsat Data},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\krehbiel_et_al_2017_impacts_of_thermal_time_on_land_surface_phenology_in_urban_areas.pdf}
}

@inproceedings{krtalic2019,
  title = {Monitoring of Short Temporal Changes in Intra-Urban Vegetation Areas},
  author = {Krtalic, A. and Petrovic, D.},
  date = {2019},
  series = {International {{Multidisciplinary Scientific GeoConference Surveying Geology}} and {{Mining Ecology Management}}, {{SGEM}}},
  volume = {19},
  number = {2.2},
  pages = {577--584},
  publisher = {{International Multidisciplinary Scientific Geoconference}},
  issn = {13142704},
  doi = {10.5593/sgem2019/2.2/S10.071},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073354684&doi=10.5593%2fsgem2019%2f2.2%2fS10.071&partnerID=40&md5=496edfe45cc5cfc6710825ee2cedbaae},
  abbrev_source_title = {Int. Multidisciplinary Sci. Geoconf. Surveying Geology Mining Ecology Manage., SGEM},
  abstract = {Monitoring short temporal changes in intra-urban vegetation areas will become very important as the proportion of urban areas continue to increase. Intra-urban variations in vegetation abundance influence environmental conditions by selective reflection and absorption of solar radiation and by sequestration of pollutants. This research investigates the hypothesis that it should be possible to use easily accessible multispectral Landsat 8 images to track intra-urban vegetation, and obtaining sufficient quality information about short temporal changes, in the town of Zagreb (Croatia). In situ measurements have not been performed. The article presents only the results of remote sensing methods based on multi-temporal Landsat 8 satellite imagery. These results are the following vegetation indices: Normalized Difference Vegetation Index (NDVI), Green-Red Vegetation Index (GRVI) and Ratio Vegetation Index (RVI), calculated on the basis of the channels of the mentioned satellite system. The conditions of vegetation have been observed in three seasons: spring (April), summer (August) and autumn (October) in 2016 and 2017. In the focus area there is mostly deciduous vegetation (forest), which is why the conditions of vegetation have not been observed in winter months. The values of vegetation indices were used to extract information on changes in vegetation and this analysis are represented in this article. Further studies should include foresters in order to make a more meaningful interpretation of the results. © SGEM2019. All Rights Reserved.},
  affiliation = {University of Zagreb, Faculty of Geodesy, Croatia},
  author_keywords = {Analysis; Intra-urban vegetation; Landsat 8 images; Remote sensing; Vegetation indices},
  document_type = {Conference Paper},
  funding_details = {Hrvatska Zaklada za ZnanostHrvatska Zaklada za Znanost, HRZZ},
  funding_text_1 = {The research leading to these results is part of research within project GEospatial Monitoring of green INfrastructure by means of terrestrial, airborne and satellite Imagery (GEMNI) funded by Croatian Science Foundation.},
  isbn = {978-619-7408-76-8 978-619-7408-77-5 978-619-7408-78-2 978-619-7408-79-9 978-619-7408-80-5 978-619-7408-81-2 978-619-7408-82-9 978-619-7408-83-6 978-619-7408-84-3 978-619-7408-85-0 978-619-7408-86-7 978-619-7408-87-4 978-619-7408-88-1 978-619-7408-89-8},
  langid = {english},
  source = {Scopus},
  keywords = {Absorption of solar radiation,Analysis,Environmental conditions,Forestry,LANDSAT,Normalized difference vegetation index,Ratio vegetation indices,Remote sensing,Satellite imagery,Urban vegetation,Vegetation,Vegetation index}
}

@article{labib2021,
  title = {Modelling and Mapping Eye-Level Greenness Visibility Exposure Using Multi-Source Data at High Spatial Resolutions},
  author = {Labib, S.M. and Huck, J.J. and Lindley, S.},
  date = {2021},
  journaltitle = {Science of the Total Environment},
  volume = {755},
  publisher = {{Elsevier B.V.}},
  issn = {00489697},
  doi = {10.1016/j.scitotenv.2020.143050},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094825068&doi=10.1016%2fj.scitotenv.2020.143050&partnerID=40&md5=9cfee407107bf8e6a7783832ba65c83b},
  abstract = {The visibility of natural greenness is associated with several health benefits along multiple pathways, including stress recovery and attention restoration mechanisms. However, existing methodologies are inadequate for capturing eye-level greenness visibility exposure at high spatial resolutions for observers located on the ground. As a response, we developed an innovative methodological approach to model and map eye-level greenness visibility exposure for 5 m interval locations within a large study area. We used multi-source spatial data and applied viewshed analysis in conjunction with a distance decay model to compute a novel Viewshed Greenness Visibility Index (VGVI) at more than 86 million observer locations. We compared our eye-level visibility exposure map with traditional top-down greenness exposure metrics such as Normalised Differential Vegetation Index (NDVI) and a Street view based Green View Index (SGVI). Furthermore, we compared greenness visibility at street-only locations with total neighbourhood greenness visibility. We found strong to moderate correlations (r = 0.65–0.42, p {$<$} 0.05) between greenness visibility and mean NDVI, with a decreasing trend in correlation strength at increasing buffer distances from observer locations. Our findings suggest that top-down and eye-level measurements of greenness are two distinct metrics for assessing greenness exposure. Additionally, VGVI showed a strong correlation (r = 0.481, p {$<$} 0.01) with SGVI. Although the new VGVI has good agreement with existing street view based measures, we found that street-only greenness visibility values are not wholly representative of total neighbourhood visibility due to the under-representation of visible greenness in locations such as backyards and community parks. Our new methodology overcomes such underestimations, is easily transferable, and offers a computationally efficient approach to assessing eye-level greenness exposure. © 2020 The Authors},
  langid = {english},
  keywords = {Attention restorations,Computationally efficient,Correlation strength,Distance decay model,GIS,greenspace,High spatial resolution,Location,mapping,Methodological approach,modeling,Multi-source spatial data,NDVI,neighborhood,spatial data,spatial resolution,Strong correlation,urban area,Visibility}
}

@article{Lahoti2020,
  title = {Vegetation Structure, Species Composition, and Carbon Sink Potential of Urban Green Spaces in {{Nagpur City}}, {{India}}},
  author = {Lahoti, S. and Lahoti, A. and Joshi, R.K. and Saito, O.},
  date = {2020},
  journaltitle = {Land},
  volume = {9},
  number = {4},
  doi = {10.3390/land9040107},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083790055&doi=10.3390%2fland9040107&partnerID=40&md5=fa12b1d84cd2f0ca94af8f69885e70a2},
  abstract = {Nagpur is rapidly urbanizing, and in the process witnessing decline in its green status which is one of the identities of the city. The study aims to understand the current species diversity, composition and structure in different classes of greens prevalent in the city. As urban green spaces (UGS) are also reservoirs of carbon stock, the study estimates their biomass. Through rigorous field work, data were collected from 246 sample plots across various UGS classes as pre-stratification. Then the biomass was estimated using non-destructive method with species-specific equation. The diversity of tree species recorded in UGS varies, with high diversity recorded in avenue plantation and institutional compounds. The overall variation in species composition among UGS classes was 36.8\%. While in managed greens the species composition was similar, in institutional greens and forest it was different. Particularly, in forest the evenness was high with low diversity and low species richness. The structural distribution indicate lack of old trees in the city, with high number of tree species between diameter classes of 10-40 cm. Biomass was recorded high in road-side plantations (335 t ha-1) and playgrounds (324 t ha-1), and trees with bigger girth size where the main contributors. The dominant species indicates that high growth rate, tolerance to drought and pollution are the key attributes considered for species selection by local authorities. Though the city holds green image, vegetation along the avenues and institutions are stressed, exposed, and threatened by felling activities for grey infrastructure expansions. In such scenario, protection and preservation of older trees is crucial to maintain the carbon stock of the city. In addition, local authorities need to focus on effective afforestation programs through public participation to achieve high survival rate and reduce the maintenance cost. For species selection in addition to phenology and growth rate, tree biomass and life span needs to be considered to significantly enhance the urban environment and increase the benefits derived from UGS. © 2020 by the authors.},
  affiliation = {United Nations University Institute for the Advanced Study of Sustainability (UNU-IAS), Tokyo, 150-8925, Japan; Independent Researcher, Tokyo, 136-0073, Japan; Jawaharlal Nehru University, New Delhi, 110067, India; Institute for Global Environmental Strategies (IGES), Kanagawa, 240-0115, Japan},
  art_number = {107},
  author_keywords = {Biomass; Carbon stock; Species diversity; Urban green space; Vegetation structure},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\lahoti_et_al_2020_vegetation_structure,_species_composition,_and_carbon_sink_potential_of_urban.pdf}
}

@article{Lai20197025,
  title = {The Phenological Responses of Plants to the Heat Island Effect in the Main Urban Area of {{Chongqing}}},
  author = {Lai, X. and Li, M. and Liu, C. and Zhong, Y. and Lin, L. and Wang, H.},
  date = {2019},
  journaltitle = {Shengtai Xuebao/ Acta Ecologica Sinica},
  volume = {39},
  number = {19},
  pages = {7025--7034},
  doi = {10.5846/stxb201809252082},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075360690&doi=10.5846%2fstxb201809252082&partnerID=40&md5=cafab87676ddc760874a3c4a4a652314},
  abstract = {: In this study ' we aimed to reveal the impact of the urban heat island effect on plant phenology in a mountain city' To this end' ground observations of the phenology of 80 woody plants were conducted from January 2016 to January 2017 in the main urban area of Chongqing' and Landsat 8 thermal infrared data as well as concurrent temperature data were used for classification of heat island intensity. The result showed that' compared with a cool island' the urban heat island has led to an advance in the transition zone and heat island zone for spring phenology (5.1 and 8.1 days for the timing of leaf expansion' 4.0 and 20.8 days for the timing of blossoming' and 4.8 and 11.6 days for the timing of flower fall' respectively) ' and a delay for autumn phenology (8.5 and 18.9 days for the timing of leaf fall ' respectively) . Furthermore ' the growth season has been extended. Differences existed among functional types in response to urban heat island effect; the sensitivity of shrubs' evergreens and exotic plants to urban warming were found to be higher than that of trees' and deciduous and native species. Our research' to some extent' fills the gap in the research on phenology in the southwest area of China and might provide an early warning for predicting the phenological responses of urban plants to future urban microclimate changes in mountain cities and even to global warming trends. © 2019 Science Press. All rights reserved.},
  affiliation = {College of Horticulture and Landscape Architecture' Southwest University, Chongqing, 400715, China; Chongqing Engineering Research Center for Floriculture, Chongqing, 400715, China; Key Laboratory of Horticulture Science for Southern Mountainous Regions, Chongqing, 4007l5, China},
  author_keywords = {Functional type; Mountain city; Plant phenology; Response; Urban heat island},
  document_type = {Article},
  source = {Scopus}
}

@article{lara2020,
  title = {Impact of {{Plane Tree Abundance}} on {{Temporal}} and {{Spatial Variations}} in {{Pollen Concentration}}},
  author = {Lara, Beatriz and Rojo, Jesús and Fernández-González, Federico and González-García-Saavedra, Antonio and Serrano-Bravo, Mariano D. and Pérez-Badia, Rosa},
  date = {2020-07-28},
  journaltitle = {Forests},
  shortjournal = {Forests},
  volume = {11},
  number = {8},
  pages = {817},
  issn = {1999-4907},
  doi = {10.3390/f11080817},
  url = {https://www.mdpi.com/1999-4907/11/8/817},
  urldate = {2021-06-07},
  abstract = {Many ornamental species growing in cities have considerable allergenic potential and pose a risk to allergy sufferers. Such species include members of the genus Platanus, or London plane tree, which is increasingly prevalent in a number of southern European cities. Analysis of airborne pollen concentrations enables biological air quality to be assessed, and also provides information on the local distribution of vegetation. The aim of this study was to analyze trends in annual Platanus pollen concentrations in central Spain and to determine the extent to which they are linked to the presence of this species in urban green spaces. The results point to a correlation between the growing number of plane trees and an increase both in the annual pollen index and in the number of days on which allergy sufferers are at risk. Analysis suggests that variations in the diversity and abundance of allergenic ornamental species in urban green spaces may account for the trends observed in the dynamics and behavior of airborne pollen from these species. The results obtained in studies of this kind should be reflected in urban green-space management plans, in order to decrease the allergenic load and thus both reduce exposure to allergenic pollen and improve air quality in these spaces.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\EGSKXWD9\\Lara et al. - 2020 - Impact of Plane Tree Abundance on Temporal and Spa.pdf}
}

@article{larkin2019,
  title = {Evaluating Street View Exposure Measures of Visible Green Space for Health Research},
  author = {Larkin, Andrew and Hystad, Perry},
  date = {2019-07},
  journaltitle = {Journal of Exposure Science \& Environmental Epidemiology},
  volume = {29},
  number = {4},
  pages = {447--456},
  publisher = {{Nature Publishing Group}},
  issn = {1559-064X},
  doi = {10.1038/s41370-018-0017-1},
  url = {https://www.nature.com/articles/s41370-018-0017-1},
  urldate = {2021-01-26},
  abstract = {Urban green space, or natural environments, are associated with multiple physical and mental health outcomes. Several proposed pathways of action for these benefits (e.g., stress reduction and attention restoration) require visual perception of green space; however, existing green space exposure measures commonly used in epidemiological studies do not capture street-scale exposures. We downloaded 254 Google Street View (GSV) panorama images from Portland, Oregon and calculated percent of green in each image, called Green View Index (GVI). For these locations we also calculated satellite-based normalized difference vegetation index (NDVI), \% tree cover, \% green space, \% street tree buffering, distance to parks, and several neighborhood socio-economic variables. Correlations between the GVI and other green space measures were low (−0.02 to 0.50), suggesting GSV-based measures captured unique information about green space exposures. We further developed a GVI:NDVI ratio, which was associated with the amount of vertical green space in an image. The GVI and GVI:NDVI ratio were weakly related to neighborhood socioeconomic status and are therefore less susceptible to confounding in health studies compared to other green space measures. GSV measures captured unique characteristics of the green space environment and offer a new approach to examine green space and health associations in epidemiological research.},
  issue = {4},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\larkin_hystad_2019_evaluating_street_view_exposure_measures_of_visible_green_space_for_health.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\3J34EVCE\\s41370-018-0017-1.html}
}

@article{li2015,
  title = {Assessing Street-Level Urban Greenery Using {{Google Street View}} and a Modified Green View Index},
  author = {Li, Xiaojiang and Zhang, Chuanrong and Li, Weidong and Ricard, Robert and Meng, Qingyan and Zhang, Weixing},
  date = {2015},
  journaltitle = {Urban Forestry \& Urban Greening},
  shortjournal = {Urban Forestry \& Urban Greening},
  volume = {14},
  number = {3},
  pages = {675--685},
  issn = {16188667},
  doi = {10.1016/j.ufug.2015.06.006},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S1618866715000874},
  urldate = {2021-01-26},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\li_et_al_2015_assessing_street-level_urban_greenery_using_google_street_view_and_a_modified.pdf}
}

@article{Li20172818,
  title = {Response of Vegetation Phenology to Urbanization in the Conterminous {{United States}}},
  author = {Li, X. and Zhou, Y. and Asrar, G.R. and Mao, J. and Li, X. and Li, W.},
  date = {2017},
  journaltitle = {Global Change Biology},
  volume = {23},
  number = {7},
  pages = {2818--2830},
  doi = {10.1111/gcb.13562},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007223374&doi=10.1111%2fgcb.13562&partnerID=40&md5=8cef9668a514a4cc4e38570aef5701ab},
  abstract = {The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends later (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th   75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology. © 2016 John Wiley \& Sons Ltd},
  affiliation = {Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, United States; Pacific Northwest National Laboratory, Joint Global Change Research Institute, College Park, MD 20740, United States; Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, United States; Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, 100084, China},
  author_keywords = {phenology response; urban expansion; urban size; urbanization; vegetation type},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\li_et_al_2017_response_of_vegetation_phenology_to_urbanization_in_the_conterminous_united.pdf}
}

@article{Li201743,
  title = {Urban Vegetation Phenology Analysis Using High Spatio-Temporal {{NDVI}} Time Series},
  author = {Li, F. and Song, G. and Liujun, Z. and Yanan, Z. and Di, L.},
  date = {2017},
  journaltitle = {Urban Forestry and Urban Greening},
  volume = {25},
  pages = {43--57},
  doi = {10.1016/j.ufug.2017.05.001},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019087067&doi=10.1016%2fj.ufug.2017.05.001&partnerID=40&md5=e8b77f6a98687d92675db7ce022c5bd9},
  abstract = {Most of current products can partially reach the requirement of high spatial and temporal resolution needed in urban applications. Fortunately, the new generation of satellite in a form of constellation, e.g. Europe's Sentinel-2, China's HJ-1A/B and GF-1/6, is expected to provide more frequent observations (¡1 week) with a higher spatial resolution (¡30 m). Consequently, a proper method should be selected to construct high spatio-temporal time-series NDVI and to derive phenological features for urban applications. In this study, a high spatio-temporal NDVI product for urban scale vegetation time series is conducted based on HJ-1A/B data. Three related issues, i.e. the optimal filter, time series decomposition, phenological features derivation are addressed. In addition, the effect of spatial and temporal resolution on the phenological features extraction is also discussed according to the comparison between the derived NDVI product and that extracted from MODIS. The results show that the Savitzky-Golay (S-G) filter is the best filter for the reconstruction of HJ NDVI time series. There is some difference for phenology derivation using “season” and “season + trend” depending on the absence/presence of breakpoints in the curve. The spatial details of phenological features can be built by the high-spatial time-series NDVI, showing a great potential in urban applications. Compared with the MODIS NDVI time series, HJ NDVI time series can get more detail information than overall phenological features because of its high spatio-temporal resolution. © 2017 Elsevier GmbH},
  affiliation = {Department of Geographic Information Science, Hohai University, Nanjing, 211000, China; Department of Civil Engineering, Monash University3800, Australia},
  author_keywords = {High spatio-temporal NDVI time series; Phenological features; S-G filter; Spatial distribution patterns of phenology; Urban vegetation},
  document_type = {Article},
  source = {Scopus}
}

@article{Li2017721,
  title = {Characterizing Spatiotemporal Dynamics in Phenology of Urban Ecosystems Based on {{Landsat}} Data},
  author = {Li, X. and Zhou, Y. and Asrar, G.R. and Meng, L.},
  date = {2017},
  journaltitle = {Science of the Total Environment},
  volume = {605--606},
  pages = {721--734},
  doi = {10.1016/j.scitotenv.2017.06.245},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021436247&doi=10.1016%2fj.scitotenv.2017.06.245&partnerID=40&md5=5109f28b833b2a2874e172e6af17ee67},
  abstract = {Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observations (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9–14 days) start-of-season (SOS) and a later (13–20 days) end-of-season (EOS), resulting in an extended (5–30 days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (− 0.30 day per year), and increasing EOS and GSL (0.50 and 0.90 day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation types, and different urban-rural settings. The Landsat derived phenology information for urban domains provides more details when compared to the coarse-resolution datasets such as MODIS, thus improves our understanding of human-natural systems interactions (or feedbacks) in urban domains. Such information is very valuable for urban planning in light of rapid urbanization and expansion of major metropolitans at the national and global levels. © 2016 Elsevier B.V.},
  affiliation = {Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, United States; Joint Global Change Research Institute of Pacific Northwest National Laboratory, College Park, MD 20740, United States},
  author_keywords = {Double sigmoid; Landsat; Urban systems; Urbanization; Vegetation phenology},
  document_type = {Article},
  source = {Scopus}
}

@article{Lim20201,
  title = {Monitoring for Changes in Spring Phenology at Both Temporal and Spatial Scales Based on Modis Lst Data in South Korea},
  author = {Lim, C.H. and Jung, S.H. and Kim, A.R. and Kim, N.S. and Lee, C.S.},
  date = {2020},
  journaltitle = {Remote Sensing},
  volume = {12},
  number = {20},
  pages = {1--25},
  doi = {10.3390/rs12203282},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092774876&doi=10.3390%2frs12203282&partnerID=40&md5=14142fb68c0df662debfcd830fda2cee},
  abstract = {This study aims to monitor spatiotemporal changes of spring phenology using the green-up start dates based on the accumulated growing degree days (AGDD) and the enhanced vegetation index (EVI), which were deducted from moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST) data. The green-up start dates were extracted from the MODIS-derived AGDD and EVI for 30 Mongolian oak (Quercus mongolica Fisch.) stands throughout South Korea. The relationship between green-up day of year needed to reach the AGDD threshold (DoYAGDD) and air temperature was closely maintained in data in both MODIS image interpretation and from 93 meteorological stations. Leaf green-up dates of Mongolian oak based on the AGDD threshold obtained from the records measured at five meteorological stations during the last century showed the same trend as the result of cherry observed visibly. Extrapolating the results, the spring onset of Mongolian oak and cherry has become earlier (14.5 ± 4.3 and 10.7 ± 3.6 days, respectively) with the rise of air temperature over the last century. The temperature in urban areas was consistently higher than that in the forest and the rural areas and the result was reflected on the vegetation phenology. Our study expanded the scale of the study on spring vegetation phenology spatiotemporally by combining satellite images with meteorological data. We expect our findings could be used to predict long-term changes in ecosystems due to climate change. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
  affiliation = {Division of Ecological Survey Research, National Institute of Ecology, 1210 Geumgang-no, Maseo-myeon, Seocheon, 33657, South Korea; Gwangneung Forest Conservation Center, Korea National Arboretum, 415 Gwangneungsumogwon-ro, Soheul-eup, Pocheon, 11186, South Korea; Graduate School of Seoul Women’s University, Seoul Women’s University, 621 Hwarang-no, Nowon-gu, Seoul, 01797, South Korea; Division of Chemistry and Bio-Environmental Sciences, Seoul Women’s University, 621 Hwarang-no, Nowon-gu, Seoul, 01797, South Korea},
  art_number = {3282},
  author_keywords = {AGDD; Climate change; EVI; MODIS LST; Mongolian oak; Phenology},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\lim_et_al_2020_monitoring_for_changes_in_spring_phenology_at_both_temporal_and_spatial_scales.pdf}
}

@article{lin2021,
  title = {Socioeconomic and Spatial Inequalities of Street Tree Abundance, Species Diversity, and Size Structure in {{New York City}}},
  author = {Lin, J. and Wang, Q. and Li, X.},
  date = {2021},
  journaltitle = {Landscape and Urban Planning},
  volume = {206},
  publisher = {{Elsevier B.V.}},
  issn = {01692046},
  doi = {10.1016/j.landurbplan.2020.103992},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096685699&doi=10.1016%2fj.landurbplan.2020.103992&partnerID=40&md5=9b84dcff7786f45281c06e5ab5589e9b},
  abstract = {Street trees are often unequally distributed in urban areas, and their physical and structural attributes, such as extent of canopy cover, species composition, and size distribution, are also spatially heterogeneous. Some studies report that inequalities are more prevalent in streetscapes than in private landscapes. Considering the existing inequality issues and public nature of street trees, street tree inequality studies warrant greater attention. However, most existing studies in this field focus heavily on the unequal distribution of tree canopy cover, while disregarding other tree attributes. In this study, seven street tree measures covering tree abundance, species diversity, and size structure were derived from high-resolution satellite images, Google Street View, and street tree census. We then applied the geographically weighted regression to these seven tree measures in New York City, United States, compared street tree inequalities among different socioeconomic groups, and identified inequality hotspots. Our results show that street tree inequalities are greatest with respect to tree abundance and species diversity. Furthermore, race-based and education-based inequalities are most notable, and age-, income-, and household characteristic-based inequalities were also detected based on tree abundance or species diversity. Socially vulnerable areas that suffer the most severe inequalities are clustered in Brooklyn and Queens. Disaggregated street tree inequalities, with explicit recognition of the differentiated distribution of limited tree resources among different social groups and across geographical areas, are critical for effective decision-making to alleviate environmental inequities. © 2020 Elsevier B.V.},
  langid = {english},
  keywords = {abundance,Brooklyn,decision making,equity,landscape change,New York [New York (STT)],New York [United States],Queens County,satellite imagery,size structure,socioeconomic impact,spatial analysis,species diversity,United States}
}

@article{liu2010,
  title = {Monitoring vegetation-cover changes based on NDVI dimidiate pixel model},
  author = {Liu, L. and Yao, B.},
  date = {2010},
  journaltitle = {Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering},
  volume = {26},
  pages = {230--234},
  issn = {10026819},
  doi = {10.3969/j.issn.1002-6819.2010.z1.042},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650442699&doi=10.3969%2fj.issn.1002-6819.2010.z1.042&partnerID=40&md5=1bc67874d8a00737cb02194b01a4747c},
  abbrev_source_title = {Nongye Gongcheng Xuebao},
  abstract = {The accuracy and scope of vegetation fraction by NDVI dimidiate pixel model was studied in this paper. Selecting the appropriate NDVIsoil and NDVIveg for urban areas, vegetation fraction values were calculated respectively based on TM of Hefei City, Anhui Province in 2002 and 2007 by NDVI dimidiate pixel model, changes in vegetation fraction were obtained by image - minus method. For Hefei City, during the study period, vegetation coverage in general decreased. The most obvious was the decline in Binhu New Area and Baohe Industrial Park, decreased values were 16.7\% and 21.4\%, respectively. The sharp reduction of vegetation cover caused by urban expansion is a remarkable ecological problem. Compared with the results of aerophotograph surveying, the value of vegetation fraction obtained by this method is higher in low vegetation-covered area, and which is lower in high vegetation-covered forest area, but the vegetation fraction change calculated by image -minus method can eliminate some system error and achieve higher precision in all areas, so image -minus method based on NDVI dimidiate pixel model can serve as an important means of monitoring vegetation cover.},
  affiliation = {School of Science, Anhui Agricultural University, Hefei 230036, China; Geophysical and Geochemical Exploration Institute of Anhui Province, Hefei 230022, China},
  author_keywords = {Hefei City; Monitoring; NDVI; Remote sensing; Vegetation},
  coden = {NGOXE},
  correspondence_address1 = {Liu, L.; School of Science, Anhui Agricultural University, Hefei 230036, China},
  document_type = {Article},
  issue = {SUPPL. 1},
  langid = {chinese},
  source = {Scopus},
  keywords = {Anhui province,Ecological problem,Ecology,Forest area,Hefei City,Industrial parks,NDVI,Pixels,Remote sensing,System errors,Urban areas,Urban expansion,Vegetation,Vegetation cover,Vegetation coverage,Vegetation fractions}
}

@article{livesley2016,
  title = {The Urban Forest and Ecosystem Services: Impact on Urban Water, Heat, and Pollution Cycles at the Tree, Street, and City Scale},
  shorttitle = {The Urban Forest and Ecosystem Services},
  author = {Livesley, S. J. and McPherson, E. G. and Calfapietra, C.},
  date = {2016},
  journaltitle = {Journal of Environmental Quality. 45: 119-124},
  volume = {45},
  pages = {119--124},
  doi = {10.2134/jeq2015.11.0567},
  url = {https://www.fs.usda.gov/treesearch/pubs/50499},
  urldate = {2021-09-10},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\livesley_et_al_2016_the_urban_forest_and_ecosystem_services.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\9ZH8P33S\\50499.html}
}

@article{Lu2006120,
  title = {Advance of Tree-Flowering Dates in Response to Urban Climate Change},
  author = {Lu, P. and Yu, Q. and Liu, J. and Lee, X.},
  date = {2006},
  journaltitle = {Agricultural and Forest Meteorology},
  volume = {138},
  number = {1-4},
  pages = {120--131},
  doi = {10.1016/j.agrformet.2006.04.002},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33744797831&doi=10.1016%2fj.agrformet.2006.04.002&partnerID=40&md5=1847767cda02a544e7330ac72c6496c3},
  abstract = {An increase in temperature due to greenhouse effects is manifest in the changes in diurnal, annual and inter-annual patterns, which may alter phenological events in plants. Flowering dates of four tree species, Prunus davidina, Prunus armeniaca, Robinia pseudoacacia and Syringa oblata, were significantly advanced in response to temperature increase over the years 1950-2004 in Beijing, China, due to the impact of urban climate warming. Because both climate warming and the urban heat island effect in winter and early-spring were more rapid than in late-spring and early summer, the dates in early flowering species advanced more quickly than in late flowering species. The early flowering species, P. davidina, advanced by 2.9 days/decade, while the other species advanced by 1.5-2.0 days/decade during 1950-2004. Therefore, the intervals between flowering dates of different species were expanded. P. davidina, flowering in early-spring, was much more sensitive to minimum and average temperatures (2.88-2.96 days/°C), but less sensitive to maximum temperature (2.46 days/°C). R. pseudoacacia, flowering late in the warmer season, was more sensitive to average and maximum temperatures (2.45-2.89 days/°C), but less sensitive to minimum temperature (1.91 days/°C). Statistical analysis showed that, in Beijing, plant flowering is most sensitive to average temperature over 30 days before average blossom date. On the basis of the temperature response curve, the goodness of fitting demonstrates that spring flowering dates can be predicted from the period when temperature is over 0 °C. © 2006 Elsevier B.V. All rights reserved.},
  affiliation = {College of Resources and Environment, Beijing Forestry University, Beijing, 100083, China; Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, No. 11, Datun Road, Beijing, 100101, China; Institute of Agrometeorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China; School of Forestry and Environmental Studies, Yale University, New Haven, CT 06511, United States},
  author_keywords = {Beijing; Climate warming; Flowering date; Temperature; Tree phenology; Urban heat island},
  document_type = {Article},
  source = {Scopus}
}

@article{luketich2019,
  title = {Ecohydrology of Urban Trees under Passive and Active Irrigation in a Semiarid City},
  author = {Luketich, A.M. and Papuga, S.A. and Crimmins, M.A.},
  date = {2019},
  journaltitle = {PLoS ONE},
  volume = {14},
  number = {11},
  publisher = {{Public Library of Science}},
  issn = {19326203},
  doi = {10.1371/journal.pone.0224804},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074719794&doi=10.1371%2fjournal.pone.0224804&partnerID=40&md5=f508f544e72d96e06893b1becb44fd9a},
  abbrev_source_title = {PLoS ONE},
  abstract = {The infiltration of stormwater runoff for use by urban trees is a major co-benefit of green infrastructure for desert cities with limited water resources. However, the effects of this passive irrigation versus regular, controlled moisture inputs, or active irrigation, is largely unquantified. We monitored the ecohydrology of urban mesquite trees (Prosopis spp.) under these contrasting irrigation regimes in semiarid Tucson, AZ. Measurements included soil moisture, sap velocity, canopy greenness, and leaf-area index. We expected both irrigation types to provide additional deep (¿20 cm) soil moisture compared to natural conditions, and that trees would depend on this deep moisture for transpiration and phenological activity. Results show that active irrigation supported higher soil moisture throughout the study than passive irrigation. Passive irrigation only provided additional deep moisture when green infrastructure features received impervious runoff from a city street. Sap velocity and greenness were similar under both irrigation types, outside of isolated periods of time. These differences occurred during the extremely wet summer 2017 when passively irrigated trees exhibited a greenness peak, and the dry conditions of spring when actively irrigated trees had higher sap flow and relative greenness. Finally, it was not determined that deep soil moisture had a stronger relationship with mesquite productivity than shallow moisture, but both relationships were stronger in the spring, before summer rains. This study aims to contribute empirical observations of green infrastructure performance for urban watershed management. © 2019 Luketich et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.},
  affiliation = {Department of Biology, University of New Mexico, Albuquerque, NM, United States; School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, United States; Department of Geology, Wayne State University, Detroit, MI, United States; Department of Environmental Science, University of Arizona, Tucson, AZ, United States},
  art_number = {e0224804},
  chemicals_cas = {Soil},
  coden = {POLNC},
  correspondence_address1 = {Luketich, A.M.; Department of Biology, University of New MexicoUnited States; email: luketich.anthony@gmail.com},
  document_type = {Article},
  funding_details = {University of ArizonaUniversity of Arizona, UA},
  funding_text_1 = {SP received funding from NSF CNH award 1518376. https://www.nsf.gov/ awardsearch/showAward?AWD\textsubscript{I}D=1518376. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We would like to thank Phil Guertin and Tom Meixner for their guidance throughout this research. Additionally, we thank Yoga Korgaonkar, Neha Gupta, Jack Anderson, Emily Bell, and Liliana Gomez for field and computational assistance. Finally, we thank the staff at Watershed Management Group and University of Arizona Residence Life for providing assistance and the necessary space to conduct this research.},
  langid = {english},
  pubmed_id = {31703086},
  source = {Scopus},
  keywords = {Agricultural Irrigation,algorithm,Algorithms,article,canopy,chemistry,Cities,city,city planning,City Planning,drought,ecosystem,Ecosystem,irrigation (agriculture),leaf area,Models,productivity,runoff,sap flow,season,Seasons,soil,Soil,soil moisture,spring,summer,sweating,Theoretical,theoretical model,tree,Trees,Urban Renewal,watershed management}
}

@thesis{lumnitz2019,
  type = {MSc Thesis},
  title = {Mapping {{Urban Trees}} with {{Deep Learning}} and {{Street-Level Imagery}}},
  author = {Lumnitz, Stefanie},
  date = {2019},
  institution = {{University of British Columbia}},
  location = {{Vancouver, Canada}},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\KDZIIDL6\\Lumnitz - MAPPING URBAN TREES WITH DEEP LEARNING AND STREET-.pdf}
}

@article{manoli2019a,
  title = {Magnitude of Urban Heat Islands Largely Explained by Climate and Population},
  author = {Manoli, Gabriele and Fatichi, Simone and Schläpfer, Markus and Yu, Kailiang and Crowther, Thomas W. and Meili, Naika and Burlando, Paolo and Katul, Gabriel G. and Bou-Zeid, Elie},
  date = {2019-09},
  journaltitle = {Nature},
  shortjournal = {Nature},
  volume = {573},
  number = {7772},
  pages = {55--60},
  publisher = {{Nature Publishing Group}},
  issn = {1476-4687},
  doi = {10.1038/s41586-019-1512-9},
  url = {https://www.nature.com/articles/s41586-019-1512-9},
  urldate = {2020-04-20},
  abstract = {The effect of cities on urban climate (often warmer but sometimes cooler than their surroundings) is largely explained by local hydroclimate and patterns of city development.},
  issue = {7772},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\6FMYA5Q9\\Manoli et al_2019_Magnitude of urban heat islands largely explained by climate and population.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\RBLYHHNL\\Manoli et al. - 2019 - Magnitude of urban heat islands largely explained .pdf;C\:\\Users\\ahurl\\Zotero\\storage\\462W7CR6\\s41586-019-1512-9.html}
}

@article{matasov2020,
  title = {{{IoT Monitoring}} of {{Urban Tree Ecosystem Services}}: {{Possibilities}} and {{Challenges}}},
  shorttitle = {{{IoT Monitoring}} of {{Urban Tree Ecosystem Services}}},
  author = {Matasov, Victor and Belelli Marchesini, Luca and Yaroslavtsev, Alexey and Sala, Giovanna and Fareeva, Olga and Seregin, Ivan and Castaldi, Simona and Vasenev, Viacheslav and Valentini, Riccardo},
  date = {2020-07},
  journaltitle = {Forests},
  volume = {11},
  number = {7},
  pages = {775},
  publisher = {{Multidisciplinary Digital Publishing Institute}},
  doi = {10.3390/f11070775},
  url = {https://www.mdpi.com/1999-4907/11/7/775},
  urldate = {2021-03-29},
  abstract = {Urban green infrastructure plays an increasingly significant role in sustainable urban development planning as it provides important regulating and cultural ecosystem services. Monitoring of such dynamic and complex systems requires technological solutions which provide easy data collection, processing, and utilization at affordable costs. To meet these challenges a pilot study was conducted using a network of wireless, low cost, and multiparameter monitoring devices, which operate using Internet of Things (IoT) technology, to provide real-time monitoring of regulatory ecosystem services in the form of meaningful indicators for both human health and environmental policies. The pilot study was set in a green area situated in the center of Moscow, which is exposed to the heat island effect as well as high levels of anthropogenic pressure. Sixteen IoT devices were installed on individual trees to monitor their ecophysiological parameters from 1 July to 31 November 2019 with a time resolution of 1.5 h. These parameters were used as input variables to quantify indicators of ecosystem services related to climate, air quality, and water regulation. Our results showed that the average tree in the study area during the investigated period reduced extreme heat by 2 \°C via shading, cooled the surrounding area by transferring 2167 \± 181 KWh of incoming solar energy into latent heat, transpired 137 \± 49 mm of water, sequestered 8.61 \± 1.25 kg of atmospheric carbon, and removed 5.3 \± 0.8 kg of particulate matter (PM10). The values of the monitored processes varied spatially and temporally when considering different tree species (up to five to ten times), local environmental conditions, and seasonal weather. Thus, it is important to use real-time monitoring data to deepen understandings of the processes of urban forests. There is a new opportunity of applying IoT technology not only to measure trees functionality through fluxes of water and carbon, but also to establish a smart urban green infrastructure operational system for management.},
  issue = {7},
  langid = {english},
  keywords = {ecological engineering,ecosystem services indicators,real-time monitoring,smart cities,sustainability,TreeTalker,urban forests},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\matasov_et_al_2020_iot_monitoring_of_urban_tree_ecosystem_services.pdf}
}

@article{mathan2020,
  title = {Monitoring Spatio-Temporal Dynamics of Urban and Peri-Urban Land Transitions Using Ensemble of Remote Sensing Spectral Indices—a Case Study of {{Chennai Metropolitan Area}}, {{India}}},
  author = {Mathan, M. and Krishnaveni, M.},
  date = {2020},
  journaltitle = {Environmental Monitoring and Assessment},
  volume = {192},
  number = {1},
  publisher = {{Springer}},
  issn = {01676369},
  doi = {10.1007/s10661-019-7986-y},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076297803&doi=10.1007%2fs10661-019-7986-y&partnerID=40&md5=272a1b97a17d245472a3d595790a938f},
  abbrev_source_title = {Environ. Monit. Assess.},
  abstract = {Land-use/land-cover change is the most vulnerable factor in any developing urban environment. Increased infrastructure and population density tend to alter the land features which in turn will have an impact on climate change and will increase the impervious layer. Study of trends in land-use/land-cover change is required for analyzing the possible ways of managing the natural system. In this study, the spatial and temporal changes of the urban and peri-urban landscape of the Chennai Metropolitan Area (CMA), Tamil Nadu, India, were analyzed using satellite images. Imageries from Landsat 5 (TM) and Landsat 8 (OLI/TIRS) sensors were taken for the years 1988, 1997, 2006, and 2017. Ensembles of remote sensing spectral indices (NDVI, MNDWI, NDBI, and NDBaI) were calculated for the land-use/land-cover classification. The confusion matrix was used for assessing the accuracy for the year 2017. The overall accuracy of the LULC classification obtained was 91.76\% with the kappa coefficient of 0.84. The results show that during the period of February 1988 to February 2017, the agriculture/fallow land, barren/semi-barren, vegetation, and water bodies/wetlands have decreased by 53.62\%, 1.45\%, 58.99\%, and 30.59\%, respectively. This decrease has contributed to an increase of 173.83\% in built-up area. About 26,881 ha of agriculture/fallow land, 10,482 ha of vegetation land, and 2454 ha of water bodies/wetlands were converted to built-up and other land-use over the period. This essentially meant that CMA has changed from predominantly an agricultural area (42.21\%) in 1988 to built-up area (48.72\%) in 2017. © 2019, Springer Nature Switzerland AG.},
  affiliation = {Centre for Water Resources, Anna University, Chennai, India},
  art_number = {15},
  author_keywords = {CMA; GIS; Land-use/land-cover; Remote sensing; Spectral indices; Urban sprawl},
  coden = {EMASD},
  correspondence_address1 = {Mathan, M.; Centre for Water Resources, Anna UniversityIndia; email: 1512719121@annauniv.edu.in},
  document_type = {Article},
  langid = {english},
  pubmed_id = {31811511},
  source = {Scopus},
  keywords = {accuracy,Agricultural areas,agriculture,Agriculture,Article,Chennai,climate change,Climate change,environmental monitoring,Geographic information systems,GIS,India,land classification,land cover,land use,Land use,land use change,Land use/land cover change,metropolitan area,monitoring,periurban area,Population densities,population density,Population statistics,remote sensing,Remote sensing,satellite imagery,Spatial and temporal changes,spatial variation,Spatio-temporal dynamics,Spectral indices,suburban area,Tamil Nadu,temporal variation,trend study,urban area,Urban environments,urban sprawl,Urban sprawl,vegetation,Vegetation,wetland}
}

@article{mayamanzano2017,
  title = {Distribution of Ornamental Urban Trees and Their Influence on Airborne Pollen in the {{SW}} of {{Iberian Peninsula}}},
  author = {Maya Manzano, José María and Tormo Molina, Rafael and Fernández Rodríguez, Santiago and Silva Palacios, Inmaculada and Gonzalo Garijo, Ángela},
  date = {2017-01-01},
  journaltitle = {Landscape and Urban Planning},
  shortjournal = {Landscape and Urban Planning},
  volume = {157},
  pages = {434--446},
  issn = {0169-2046},
  doi = {10.1016/j.landurbplan.2016.08.011},
  url = {https://www.sciencedirect.com/science/article/pii/S0169204616301645},
  urldate = {2021-06-07},
  abstract = {Ornamental trees in urban environment are a relevant cause of illness due to allergenic pollen airborne dispersed. The work presented here analyses the importance of ornamental tree distribution and investigates airborne pollen records using volumetric spore traps. Three localities in the southwest of Spain were studied: Don Benito (DB), Plasencia (PL), and Zafra (ZA), in the Extremadura region. Volumetric Hirst type spore traps recorded pollen levels continuously for three years. Ornamental street trees in the study area were identified, counted and mapped. Airborne pollen records were found to be related to the number of trees, the proximity of the trees to traps, the different pollination systems and wind direction. A total of 17635 trees, from all localities were counted, belonging to 67 species, 58\% anemophilous, 22\% entomophilous, and 20\% both pollination systems. Five species represented more than 50\% of the total number of ornamental trees: Platanus hispanica, Olea europaea, Ulmus minor, Acer negundo and Melia azedarach. The average total pollen concentration in gm−3 was 102 (DB), 93 (PL), and 99 (ZA)… Omitting the data for Quercus pollen, a statistically significant correlation between the number of trees at 0.5km around the spore traps and the types of pollen recorded was found. Some measures to decrease the amount of potential allergenic airborne pollen in urban environments were identified, such as reducing trees with anemophilic pollination systems, eliminating male trees and employing suitable pruning practices. In any case, the closer the source of ornamental pollen, the greater the allergenic risks.},
  langid = {english},
  keywords = {Airborne pollen,Allergy,Ornamental trees,Urban green infrastructure},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\GVGML3X5\\S0169204616301645.html}
}

@online{maykes1,
  title = {A {{Raspberry Pi Multispectral Camera}}},
  author = {{MaykeS1}},
  url = {https://www.instructables.com/A-Raspberry-Pi-Multispectral-Camera/},
  urldate = {2021-07-01},
  abstract = {A Raspberry Pi Multispectral Camera: A multispectral camera can be a handy tool to detect stress in plants, or recognise different species in lieu of the differences in the reflectance signatures of plants in general. If combined with a drone, the camera can provide the data for quick …},
  langid = {english},
  organization = {{Instructables}},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\5MJH5H97\\A-Raspberry-Pi-Multispectral-Camera.html}
}

@article{mcculloh2019,
  title = {A Dynamic yet Vulnerable Pipeline: {{Integration}} and Coordination of Hydraulic Traits across Whole Plants},
  shorttitle = {A Dynamic yet Vulnerable Pipeline},
  author = {McCulloh, Katherine A. and Domec, Jean-Christophe and Johnson, Daniel M. and Smith, Duncan D. and Meinzer, Frederick C.},
  date = {2019},
  journaltitle = {Plant, Cell \& Environment},
  volume = {42},
  number = {10},
  pages = {2789--2807},
  issn = {1365-3040},
  doi = {10.1111/pce.13607},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/pce.13607},
  urldate = {2020-08-08},
  abstract = {The vast majority of measurements in the field of plant hydraulics have been on small-diameter branches from woody species. These measurements have provided considerable insight into plant functioning, but our understanding of plant physiology and ecology would benefit from a broader view, because branch hydraulic properties are influenced by many factors. Here, we discuss the influence that other components of the hydraulic network have on branch vulnerability to embolism propagation. We also modelled the impact of changes in the ratio of root-to-leaf areas and soil texture on vulnerability to hydraulic failure along the soil-to-leaf continuum and showed that hydraulic function is better maintained through changes in root vulnerability and root-to-leaf area ratio than in branch vulnerability. Differences among species in the stringency with which they regulate leaf water potential and in reliance on stored water to buffer changes in water potential also affect the need to construct embolism resistant branches. Many approaches, such as measurements on fine roots, small individuals, combining sap flow and psychrometry techniques, and modelling efforts, could vastly improve our understanding of whole-plant hydraulic functioning. A better understanding of how traits are coordinated across the whole plant will improve predictions for plant function under future climate conditions.},
  langid = {english},
  keywords = {capacitance,iso/anisohydry,P50,plant hydraulics,soil nutrients,vulnerability to embolism},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/pce.13607},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\DLB5WM8L\\McCulloh et al_2019_A dynamic yet vulnerable pipeline.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\SX2PDRGQ\\pce.html}
}

@article{mcdonoughmackenzie2019,
  title = {Trails-as-Transects: Phenology Monitoring across Heterogeneous Microclimates in {{Acadia National Park}}, {{Maine}}},
  author = {McDonough MacKenzie, C. and Primack, R.B. and Miller-Rushing, A.J.},
  date = {2019},
  journaltitle = {Ecosphere},
  volume = {10},
  number = {3},
  publisher = {{Wiley-Blackwell}},
  issn = {21508925},
  doi = {10.1002/ecs2.2626},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074962601&doi=10.1002%2fecs2.2626&partnerID=40&md5=388771535c1fa3ebb44c13b5ecc7434b},
  abbrev_source_title = {Ecosphere},
  abstract = {Climate-driven shifts in phenology, which are being observed worldwide, affect ecosystem services, trophic interactions, and community composition, presenting challenges to managers in protected areas. Resource management benefits from local, species-specific phenology information. However, phenology monitoring programs in heterogeneous landscapes typically require serendipitous historical records or many years of contemporary data before trends in phenological responses to changes in climate can be analyzed. Here, we used a trails-as-transects approach to rapidly accumulate monitoring data across environmental gradients on three mountains in Acadia National Park, Maine, USA, and compared our results to phenological changes observed in Concord, Massachusetts, USA. In four years of intensive monitoring of transects on three mountains, we found large variability in spring temperatures across the mountains, but consistent patterns of advancing flower and leaf phenology in warmer microclimates. Reduced sampling intensity would have yielded similar results, but a shorter duration would not have revealed these patterns. The plants in Acadia responded to warming spring temperatures by shifting leaf and flower phenology in the same direction (earlier), but at a reduced rate (as measured in d/°C), in comparison with plants in southern New England (e.g., Concord, Massachusetts, USA). Our approach takes advantage of topographical complexity and associated microclimate gradients to substitute for long time series, allowing for rapid assessment of phenological response to climate. Other climate gradients (e.g., urban-to-rural, latitudinal, or coastal-to-inland) could work similarly. This intensive monitoring over a short time period quickly builds a robust dataset and can inform management decisions regarding future monitoring strategies, including sampling designs for citizen science-based phenology monitoring programs. © 2019 The Authors.},
  affiliation = {Climate Change Institute, University of Maine, Orono, ME 04469, United States; Department of Biology, Boston University, Boston, MA 02215, United States; Acadia National Park, U.S. National Park Service, Bar Harbor, ME 04609, United States},
  art_number = {e02626},
  author_keywords = {citizen science; climate change; conservation; flowering; leaf out; Maine; National Park; phenology},
  correspondence_address1 = {McDonough MacKenzie, C.; Climate Change Institute, University of MaineUnited States; email: caitlin.mcdonough@maine.edu},
  document_type = {Article},
  funding_details = {U.S. Department of the InteriorU.S. Department of the Interior, DOI},
  funding_text_1 = {CMM, AM-R, and RBP planned the project; fieldwork and analysis by CMM; first draft written by CMM; revisions by CMM, AM-R, and RBP. We appreciate the work of our dedicated field assistants Paul Excoffier, Natasha Krell, and Ella Samuel. Many others volunteered their time to hike transects with us, including Mike MacKenzie, Linden Mara Hope MacKenzie, Lisa McDonough, Neil McDonough, Wingman, Robyn King, Taylor Brady, Sam Truesdell, Karen James, Cassie Irwin, Yan Liu, Amanda Gallinat, Lucy Zipf, Christine Lamanna, Lisa Heider, Larissa Lee, Fiana Shapiro, and Linda Eddings. The Resource Management team at Acadia National Park provided incredible support: We especially thank Emma Albee for her guidance in permits. Nishi Rajakaruna, Glen Mittelhauser, and Tim Garrity provided ecological, botanical, and historical expertise on Mount Desert Island. We thank Bonnie McGill for sharing her artwork in Fig. Finally, we thank the editor and three anonymous reviewers for their comments which greatly improved this manuscript. CMM was supported by funding from NSF (DEB-1501266), New England Botanical Club, Waterman Fund, the George Melendez Wright Fellowship, and Schoodic Institute. The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the U.S. Department of Interior or U.S. Government.},
  langid = {english},
  source = {Scopus}
}

@article{mcpherson2012,
  title = {Urban {{Tree Growth Modeling}}},
  author = {McPherson, E Gregory and Peper, Paula J},
  date = {2012},
  journaltitle = {Journal of Arboriculture \& Urban Forestry},
  volume = {38},
  number = {5},
  pages = {175--183},
  abstract = {Selecting, locating, and managing trees to provide ecosystem services are becoming increasingly important facets of municipal and consulting forestry. The science of urban tree growth modeling is fundamental to quantifying these services. This paper describes three long-term tree growth studies conducted to evaluate tree performance because repeated measurements of the same trees produce critical data for growth model calibration and validation. Several empirical and process-based approaches to modeling tree growth are reviewed. Modeling is more advanced in the fields of forestry and pomology than in urban forestry. The USDA Forest Service’s reference city research has developed over 1,800 growth equations from measurements on more than 17,000 trees in 16 cities. The database is a valuable source of information that reflects regional differences in species composition, climate, soils, site conditions, and management practices. Several examples illustrate how differences in local climate and management practices can influence growth of a single species and the resulting value of services. Further advances in urban tree growth modeling are needed to inform the design, management, and modeling of high performing landscapes.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\Y7Z4RHWE\\McPherson and Peper - 2012 - Urban Tree Growth Modeling.pdf}
}

@article{meineke2018,
  title = {Water Availability Drives Urban Tree Growth Responses to Herbivory and Warming},
  author = {Meineke, Emily K. and Frank, Steven D.},
  date = {2018},
  journaltitle = {Journal of Applied Ecology},
  volume = {55},
  number = {4},
  pages = {1701--1713},
  issn = {1365-2664},
  doi = {10.1111/1365-2664.13130},
  url = {https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/1365-2664.13130},
  urldate = {2020-12-04},
  abstract = {Urban forests provide important ecosystem services to city residents, including pollution removal and carbon storage. Climate change and urbanization pose multiple threats to these services. However, how these threats combine to affect urban trees, and thus how to mitigate their effects, remains largely untested because multi-factorial experiments on mature trees are impractical. We used a unique urban warming experiment paired with a laboratory chamber experiment to determine how three of the most potentially damaging factors associated with global change for urban and rural trees—warming, drought, and insect herbivory—affect growth of Quercus phellos (willow oak), the most commonly planted large shade tree in the southeastern US, which is known for its resilience to these potential stressors. In a previous study, we found that the urban heat island effect was associated with reduced growth of Q. phellos and higher abundance of Parthenolecanium scale insects, key pests of oaks in cities. Here, we tested the hypothesis that tree water stress is the mechanism for these effects of warming. We found evidence that water stress is a major, interactive factor reducing urban tree growth, but found no evidence that water stress is associated with Parthenolecanium survival or abundance. Warming and Parthenolecanium only reduced growth in Q. phellos saplings that were simultaneously water stressed. Synthesis and applications. Across many temperate cities worldwide, urban trees grow less than rural trees. Our results point to water stress as the most likely driver for this pattern. Importantly, we found that water stress both reduces tree growth on its own and exacerbates effects of warming and insect pests on tree growth. Therefore, management strategies targeted at increasing tree hydration in cities may reduce effects of these three key stressors that are expected to intensify with further urbanization and climate change.},
  langid = {english},
  keywords = {climate change,herbivory,trees,urban heat island effect,warming,water relations},
  annotation = {\_eprint: https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2664.13130},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\meineke_frank_2018_water_availability_drives_urban_tree_growth_responses_to_herbivory_and_warming.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\UC35CT68\\1365-2664.html}
}

@article{melaas2016,
  title = {Interactions between Urban Vegetation and Surface Urban Heat Islands: A Case Study in the {{Boston}} Metropolitan Region},
  shorttitle = {Interactions between Urban Vegetation and Surface Urban Heat Islands},
  author = {Melaas, Eli K. and Wang, Jonathan A. and Miller, David L. and Friedl, Mark A.},
  date = {2016-05},
  journaltitle = {Environmental Research Letters},
  shortjournal = {Environ. Res. Lett.},
  volume = {11},
  number = {5},
  pages = {054020},
  publisher = {{IOP Publishing}},
  issn = {1748-9326},
  doi = {10.1088/1748-9326/11/5/054020},
  url = {https://doi.org/10.1088%2F1748-9326%2F11%2F5%2F054020},
  urldate = {2020-04-06},
  abstract = {Many studies have used thermal data from remote sensing to characterize how land use and surface properties modify the climate of cities. However, relatively few studies have examined the impact of elevated temperature on ecophysiological processes in urban areas. In this paper, we use time series of Landsat data to characterize and quantify how geographic variation in Boston’s surface urban heat island (SUHI) affects the growing season of vegetation in and around the city, and explore how the quality and character of vegetation patches in Boston affect local heat island intensity. Results from this analysis show strong coupling between Boston’s SUHI and vegetation phenology at the scale of both individual landscape units and for the region as a whole, with significant detectable signatures in both surface temperature and growing season length extending 15 km from Boston’s urban core. On average, land surface temperatures were about 7 °C warmer and the growing season was 18–22 days longer in Boston relative to adjacent rural areas. Within Boston’s urban core, patterns of temperature and timing of phenology in areas with higher vegetation amounts (e.g., parks) were similar to those in adjacent rural areas, suggesting that vegetation patches provide an important ecosystem service that offsets the urban heat island at local scales. Local relationships between phenology and temperature were affected by the intensity of urban land use surrounding vegetation patches and possibly by the presence of exotic tree species that are common in urban areas. Results from this analysis show how species composition, land cover configuration, and vegetation patch sizes jointly influence the nature and magnitude of coupling between vegetation phenology and SUHIs, and demonstrate that urban vegetation provides a significant ecosystem service in cities by decreasing the local intensity of SUHIs.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\VL2R5Z88\\Melaas et al_2016_Interactions between urban vegetation and surface urban heat islands.pdf}
}

@article{Melaas2016,
  title = {Interactions between Urban Vegetation and Surface Urban Heat Islands: {{A}} Case Study in the {{Boston}} Metropolitan Region},
  author = {Melaas, E.K. and Wang, J.A. and Miller, D.L. and Friedl, M.A.},
  date = {2016},
  journaltitle = {Environmental Research Letters},
  volume = {11},
  number = {5},
  doi = {10.1088/1748-9326/11/5/054020},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013111359&doi=10.1088%2f1748-9326%2f11%2f5%2f054020&partnerID=40&md5=728a75404c1abda93749e15e23954a8a},
  abstract = {Many studies have used thermal data from remote sensing to characterize how land use and surface properties modify the climate of cities. However, relatively few studies have examined the impact of elevated temperature on ecophysiological processes in urban areas. In this paper, we use time series of Landsat data to characterize and quantify how geographic variation in Boston's surface urban heat island (SUHI) affects the growing season of vegetation in and around the city, and explore how the quality and character of vegetation patches in Boston affect local heat island intensity. Results from this analysis show strong coupling between Boston's SUHI and vegetation phenology at the scale of both individual landscape units and for the region as a whole, with significant detectable signatures in both surface temperature and growing season length extending 15 km from Boston's urban core. On average, land surface temperatures were about 7°C warmer and the growing season was 18-22 days longer in Boston relative to adjacent rural areas. Within Boston's urban core, patterns of temperature and timing of phenology in areas with higher vegetation amounts(e.g., parks) were similar to those in adjacent rural areas, suggesting that vegetation patches provide an important ecosystem service that offsets the urban heat island at local scales. Local relationships between phenology and temperature were affected by the intensity of urban land use surrounding vegetation patches and possibly by the presence of exotic tree species that are common in urban areas. Results from this analysis show how species composition, land cover configuration, and vegetation patch sizes jointly influence the nature and magnitude of coupling between vegetation phenology and SUHIs, and demonstrate that urban vegetation provides a significant ecosystem service in cities by decreasing the local intensity of SUHIs. © 2016 IOP Publishing Ltd.},
  affiliation = {Department of Earth and Environment, Boston University, 675 Commonwealth Avenue, Boston, MA 02215, United States},
  art_number = {054020},
  author_keywords = {Landsat; Phenology; Urban heat island},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\melaas_et_al_2016_interactions_between_urban_vegetation_and_surface_urban_heat_islands.pdf}
}

@article{meng2019,
  title = {Spatio-Temporal Variation Indicators for Landscape Structure Dynamics Monitoring Using Dense Normalized Difference Vegetation Index Time Series},
  author = {Meng, Y. and Liu, X. and Wu, L. and Liu, M. and Zhang, B. and Zhao, S.},
  date = {2019},
  journaltitle = {Ecological Indicators},
  volume = {107},
  publisher = {{Elsevier B.V.}},
  issn = {1470160X},
  doi = {10.1016/j.ecolind.2019.105607},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070200367&doi=10.1016%2fj.ecolind.2019.105607&partnerID=40&md5=dfa2fd0ddb591dd8e705e0672fdbc6be},
  abbrev_source_title = {Ecol. Indic.},
  abstract = {Terrestrial ecosystems are constantly changing at various spatial and temporal scales due to natural and/or anthropogenic factors. It is therefore of great interest to develop effective indicators based on spatio-temporal variations to detect, map, and monitor ecosystem changes on the continental and global scales. In this study, spatio-temporal variation indicators were established to characterize landscape structure changes based on temporal analysis combined with spatial information obtained using dense Landsat time series in Changting County, Fujian, Province, China. All available Landsat images from 1987 to 2017 were collected. The fractal dimension (FD) of the spatial neighbor normalized difference vegetation index (NDVI) derived from the Landsat images was calculated. Four change patterns (stable, increasing, decreasing, and wave) were explored using the ordinary least-squares method between abrupt change points performed by a Mann–Kendall test on the FD time series to characterize the spatio-temporal dynamics. The results showed that 49.98\% of the landscape structure in the study area decreased over the 31-year study period. The forest and water were dominated by decreasing patterns (67.00\% and 56.27\%); the urban land and cropland were dominated by wave patterns (50.07\% and 50.95\%); bare land regions were dominated by wave patterns and increasing patterns (50.52\% and 31.38\%). Wide and discontinuous landscape structures with high heterogeneity were replaced by landscape patches. The regional landscape structure heterogeneity increased in the bare land regions and other homogeneous landscape structures, while the decreases may be coupled with internal landscape structure changes. It was concluded that the spatial and temporal variations of the change patterns and change processes determined based on the FD of the NDVI in the spatial neighbor region are systematic indicators and can be used to detect landscape structure changes successfully and provide insights into dynamic trends. © 2019},
  affiliation = {School of Information Engineering, China University of Geosciences, Beijing, 100083, China; School of Geology and Geomatics, Tianjin Chengjian University, Tianjin, 300384, China},
  art_number = {105607},
  author_keywords = {Change patterns; Dense Landsat time series; Landscape structure; Spatio-temporal variation indicators},
  correspondence_address1 = {Liu, X.; School of Information Engineering, China University of GeosciencesChina; email: liuxn@cugb.edu.cn},
  document_type = {Article},
  funding_details = {National Natural Science Foundation of ChinaNational Natural Science Foundation of China, NSFC, 41871223},
  funding_text_1 = {This research was funded by the National Natural Science Foundation of China under Grant 41871223 , China, the Fundamental Research Funds for the Central Universities under Grant 2652017116 , China.},
  langid = {english},
  source = {Scopus},
  keywords = {anthropogenic effect,Change patterns,Changting,China,Ecosystems,environmental monitoring,Finite difference method,Fractal dimension,Fujian,land use change,Landsat,Landsat time series,landscape change,landscape structure,Landscape structures,Least squares approximations,NDVI,Normalized difference vegetation index,Normalized difference vegetation index time series,Ordinary least squares methods,Spatial and temporal variation,spatial variation,Spatio-temporal variation,temporal variation,Time series,time series analysis,Time series analysis,Vegetation}
}

@article{meng2020,
  title = {Urban Warming Advances Spring Phenology but Reduces the Response of Phenology to Temperature in the Conterminous {{United States}}},
  author = {Meng, Lin and Mao, Jiafu and Zhou, Yuyu and Richardson, Andrew D. and Lee, Xuhui and Thornton, Peter E. and Ricciuto, Daniel M. and Li, Xuecao and Dai, Yongjiu and Shi, Xiaoying and Jia, Gensuo},
  date = {2020-02-05},
  journaltitle = {Proceedings of the National Academy of Sciences},
  shortjournal = {PNAS},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1911117117},
  url = {https://www.pnas.org/content/early/2020/02/04/1911117117},
  urldate = {2020-02-11},
  abstract = {Urbanization has caused environmental changes, such as urban heat islands (UHIs), that affect terrestrial ecosystems. However, how and to what extent urbanization affects plant phenology remains relatively unexplored. Here, we investigated the changes in the satellite-derived start of season (SOS) and the covariation between SOS and temperature (RT) in 85 large cities across the conterminous United States for the period 2001–2014. We found that 1) the SOS came significantly earlier (6.1 ± 6.3 d) in 74 cities and RT was significantly weaker (0.03 ± 0.07) in 43 cities when compared with their surrounding rural areas (P {$<$} 0.05); 2) the decreased magnitude in RT mainly occurred in cities in relatively cold regions with an annual mean temperature {$<$}17.3 °C (e.g., Minnesota, Michigan, and Pennsylvania); and 3) the magnitude of urban−rural difference in both SOS and RT was primarily correlated with the intensity of UHI. Simulations of two phenology models further suggested that more and faster heat accumulation contributed to the earlier SOS, while a decrease in required chilling led to a decline in RT magnitude in urban areas. These findings provide observational evidence of a reduced covariation between temperature and SOS in major US cities, implying the response of spring phenology to warming conditions in nonurban environments may decline in the warming future.},
  langid = {english},
  keywords = {phenology,temperature response,urban heat island,urbanization},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\QGS2VUV5\\Meng et al_2020_SI.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\UIPT8WH3\\Meng et al_2020_Urban warming advances spring phenology but reduces the response of phenology.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\CII32GCT\\1911117117.html}
}

@inproceedings{mora2019,
  title = {Towards {{Large-scale Drive-by Sensing}} with {{Multi-purpose City Scanner Nodes}}},
  booktitle = {2019 {{IEEE}} 5th {{World Forum}} on {{Internet}} of {{Things}} ({{WF-IoT}})},
  author = {Mora, Simone and Anjomshoaa, Amin and Benson, Tom and Duarte, Fabio and Ratti, Carlo},
  date = {2019-04},
  pages = {743--748},
  publisher = {{IEEE}},
  location = {{Limerick, Ireland}},
  doi = {10.1109/WF-IoT.2019.8767186},
  url = {https://ieeexplore.ieee.org/document/8767186/},
  urldate = {2021-06-09},
  abstract = {Drive-by sensing has the potential to provide hyperlocal data to study a number of urban phenomena and deliver actionable insights for public good. Yet drive-by deployments are often characterized by small fleets, huge costs and lack of flexibility to adapt to a city’s multiple sensing needs. The City Scanner project aims to accelerate the development of driveby sensing by turning everyday vehicles into sensing nodes. In this paper we present Greta II, a solar-powered sensing platform that allows for low-cost continuous data collection and streaming of multiple phenomena. Thanks to a modular design it can be customized with off-the-shelf sensors and re-used across different deployments. Greta II can be easily built and deployed without disrupting a vehicle’s normal operation. The platform has been validated during test deployments in two large American cities to collect air quality data. Drawing on our experience building and deploying Greta II we discuss challenges to be solved for enabling large-scale drive-by sensing.},
  eventtitle = {2019 {{IEEE}} 5th {{World Forum}} on {{Internet}} of {{Things}} ({{WF-IoT}}'19)},
  isbn = {978-1-5386-4980-0},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\W8BGS567\\Mora et al. - 2019 - Towards Large-scale Drive-by Sensing with Multi-pu.pdf}
}

@article{moser-reischl2019a,
  title = {Growth Patterns and Effects of Urban Micro-Climate on Two Physiologically Contrasting Urban Tree Species},
  author = {Moser-Reischl, Astrid and Rahman, Mohammad A. and Pauleit, Stephan and Pretzsch, Hans and Rötzer, Thomas},
  date = {2019-03-01},
  journaltitle = {Landscape and Urban Planning},
  shortjournal = {Landscape and Urban Planning},
  volume = {183},
  pages = {88--99},
  issn = {0169-2046},
  doi = {10.1016/j.landurbplan.2018.11.004},
  url = {http://www.sciencedirect.com/science/article/pii/S0169204618313367},
  urldate = {2019-12-06},
  abstract = {Urban tree plantings for climate-adapted and resilient cities need to consider growth, vitality and ecosystem services of the planted tree species particularly during drought. However, information on growth and ecosystem services of urban trees under changed climate conditions are rare for most species. This study investigated the intra-annual growth patterns of two common but physiologically contrasting urban tree species: small-leaved lime (Tilia cordata) and black locust (Robinia pseudoacacia). Although meteorological variables at the study site in the outer city center of Munich, Germany for the year 2016 were similar to the long-term average climate (1961–1990) different growth patterns were found. This was mainly influenced by species characteristics (water use efficiency, wood anatomy) leading to different transpiration rates and reaction patterns to drought stress. Moreover, species’ drought reactions compared to past years were analyzed in detail with a retrospective dendrochronological approach. Distinct species patterns were identified, highlighting the greater drought tolerance and recovery of R. pseudoacacia compared to T. cordata. These results show that under a drier and warmer climate T. cordata can provide more canopy air cooling for short periods of time due to high transpiration, albeit this is at the expense of great water demands and following growth declines under water shortage. Contrary, R. pseudoacacia proved to be a more suitable and adapted species at sites with less water availability due to better water use efficiency, even at the cost of low canopy transpiration though higher soil moisture and latent heat exchange from the soil.},
  langid = {english},
  keywords = {Drought,Transpiration,Urban tree growth,Water use efficiency},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\EV6RE5JG\\Moser-Reischl et al_2019_Growth patterns and effects of urban micro-climate on two physiologically.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\UXWSXVZE\\S0169204618313367.html}
}

@article{mudede2020,
  title = {Monitoring the Urban Environment Quality in the City of {{Johannesburg}} Using Remote Sensing Data},
  author = {Mudede, M.F. and Newete, S.W. and Abutaleb, K. and Nkongolo, N.},
  date = {2020},
  journaltitle = {Journal of African Earth Sciences},
  volume = {171},
  publisher = {{Elsevier Ltd}},
  issn = {1464343X},
  doi = {10.1016/j.jafrearsci.2020.103969},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088977541&doi=10.1016%2fj.jafrearsci.2020.103969&partnerID=40&md5=297dc68b3b56d1a323433941e2223612},
  abbrev_source_title = {J. Afr. Earth Sci.},
  abstract = {Quantification and analysis of urban greenness is important in evaluating the role of urban trees in carbon sequestration and regulating land surface temperature of an urban environment. Landsat 8 satellite data was used to evaluate the effects of urban heat island based on land surface temperature (LST) in the affluent suburb of Rosebank in the north and the previously marginalized township of Soweto south of Johannesburg. It was found that the LST of Soweto was 2.58 °C hotter than Rosebank, suggesting that high-density areas with less street trees and parks are hotter than low-density suburbs. The Pearson's correlation coefficient computed between the LST and the Normalized Difference Built-up Index (NDBI) or the Normalized Difference Vegetation Index (NDVI) for the two areas, Rosebank and Soweto showed a positive correlation of 0.92 and 0.98) and a negative correlation of −0.91 and −0.99 respectively. The correlation between the NDVI and NDBI also showed negative values of −0.90 and −0.85, respectively. Based on the global bench mark for safe solar UVI, the residents of Soweto are likely to be at risk of skin and eye damage due to prolonged exposure to ultraviolet radiation than the residents of Rosebank. Thus, this study has effectively computed and evaluated the land surface temperatures of the two study areas from Landsat 8 satellite data, an information which can help potential vegetation cover programs to improve existing disparity in urban greenness in the city of Johannesburg. © 2020 Elsevier Ltd},
  affiliation = {School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Private Bag X3, Johannesburg, 2050, South Africa; Agricultural Research Council – Soil, Climate and Water (ARC-SCW), Geo-Information Science Division, Arcadia, Private Bag X79, Pretoria, 0001, South Africa; School of Geography, Archaeological and Environmental Studies, University of the Witwatersrand, Johannesburg, 2050, South Africa; National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt},
  art_number = {103969},
  author_keywords = {Land surface temperature; Rosebank; Soweto; Urban heat island; Urban thermal field variance and solar ultraviolet index},
  correspondence_address1 = {Mudede, M.F.; School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Private Bag X3, South Africa; email: mfmudede@gmail.com},
  document_type = {Article},
  funding_details = {University of the Witwatersrand, JohannesburgUniversity of the Witwatersrand, Johannesburg, WITS, 2858},
  funding_text_1 = {I would like to extend my special gratitude to Wits School of Governance (WSG) at the University of the Witwatersrand for all the financial support of my research field expenses through the ‘Life in City” project (Project No.: 2858 ) lead by Dr S. Newete; the South African National Space Agency (SANSA) team for SPOT 6 satellite images of Rosebank and Soweto areas in the City of Johannesburg; United States Geological Survey (USGS) for free access to Landsat 8 satellite images. I would also like to thank the Zimbabwean Government and National Scholarships Department for making this academic journey a success by granting me a scholarship to further my studies at the University of the Witwatersrand.},
  langid = {english},
  source = {Scopus},
  keywords = {correlation,environmental quality,Gauteng,greenspace,Johannesburg,Landsat,monitoring,NDVI,remote sensing,satellite data,South Africa}
}

@article{myeong2006,
  title = {A Temporal Analysis of Urban Forest Carbon Storage Using Remote Sensing},
  author = {Myeong, S. and Nowak, D.J. and Duggin, M.J.},
  date = {2006},
  journaltitle = {Remote Sensing of Environment},
  volume = {101},
  number = {2},
  pages = {277--282},
  issn = {00344257},
  doi = {10.1016/j.rse.2005.12.001},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33644759109&doi=10.1016%2fj.rse.2005.12.001&partnerID=40&md5=d55a2c246e62a53f0786ceff7ad59194},
  abbrev_source_title = {Remote Sens. Environ.},
  abstract = {Quantifying the carbon storage, distribution, and change of urban trees is vital to understanding the role of vegetation in the urban environment. At present, this is mostly achieved through ground study. This paper presents a method based on the satellite image time series, which can save time and money and greatly speed the process of urban forest carbon storage mapping, and possibly of regional forest mapping. Satellite imagery collected in different decades was used to develop a regression equation to predict the urban forest carbon storage from the Normalized Difference Vegetation Index (NDVI) computed from a time sequence (1985-1999) of Landsat image data. This regression was developed from the 1999 field-based model estimates of carbon storage in Syracuse, NY. The total carbon storage estimates based on the NDVI data agree closely with the field-based model estimates. Changes in total carbon storage by trees in Syracuse were estimated using the image data from 1985, 1992, and 1999. Radiometric correction was accomplished by normalizing the imagery to the 1999 image data. After the radiometric image correction, the carbon storage by urban trees in Syracuse was estimated to be 146,800 tons, 149,430 tons, and 148,660 tons of carbon for 1985, 1992, and 1999, respectively. The results demonstrate the rapid and cost-effective capability of remote sensing-based quantitative change detection in monitoring the carbon storage change and the impact of urban forest management over wide areas. © 2005 Elsevier Inc. All rights reserved.},
  affiliation = {SUNY College of Environmental Science and Forestry, Syracuse, NY, United States; USDA Forest Service, United States},
  author_keywords = {Carbon storage; NDVI; Urban environment; Urban forest},
  coden = {RSEEA},
  correspondence_address1 = {Myeong, S.; SUNY College of Environmental Science and Forestry, Syracuse, NY, United States; email: smyeong@syr.edu},
  document_type = {Article},
  langid = {english},
  source = {Scopus},
  keywords = {carbon sequestration,Carbon storage,Image analysis,Mathematical models,NDVI,New York [United States],North America,remote sensing,Remote sensing,Satellites,Statistical methods,Syracuse,temporal analysis,United States,urban ecosystem,Urban environment,Urban forest,Vegetation}
}

@inproceedings{najafi2019,
  title = {Vegetation Dynamics Trend Using Satellite Time Series Imagery},
  author = {Najafi, Z. and Fatehi, P. and Darvishsefat, A.A.},
  date = {2019},
  series = {International {{Archives}} of the {{Photogrammetry}}, {{Remote Sensing}} and {{Spatial Information Sciences}} - {{ISPRS Archives}}},
  volume = {42},
  number = {4/W18},
  pages = {783--788},
  doi = {10.5194/isprs-archives-XLII-4-W18-783-2019},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083226262&doi=10.5194%2fisprs-archives-XLII-4-W18-783-2019&partnerID=40&md5=4265fce5e8ae82b5da10f56aeb864096},
  abstract = {In this study, the trend of vegetation dynamics in Kermanshah city assessed using NDVI MOD13Q1 product over the time period of 2000-2017. Based on time series imagery the pick of vegetation phenology stage (maximum NDVI) identified, then the trend of vegetation dynamic was investigated using the Ordinary Least Square regression and the Theil-Sen approaches. To generate a pixel-wise trend map, a pixel-based vegetation dynamics was also implemented. A non-parametric Mann-Kendall statistics approach was used to examine a statistically significant trend analysis. The mean maximum NDVI observed for the first half or second half of April. Trend analysis using regression and Theil-Sen methods indicated a no-trend in vegetation fractions. The pixel-based trend assessment using regression showed that a 50\% of the study area faced a positive trend and reaming part faced a negative trend. The Theil-Sen method revealed the no-trend for a large majority of area. The Mann-Kendall test indicated that only 20 percent of the area shows a statistically significant trend. © 2019 Z. Najafi et al.},
  affiliation = {Department of Forestry and Forest Economic, Faculty of Natural Resources, University of Tehran, Karaj, Iran},
  author_keywords = {Mann-Kendall; NDVI; Regression; Theil-Sen; Time Series; Vegetation dynamic},
  document_type = {Conference Paper},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\najafi_et_al_2019_vegetation_dynamics_trend_using_satellite_time_series_imagery.pdf}
}

@article{neumann2016a,
  title = {Mapping Multiple Plant Species Abundance Patterns - {{A}} Multiobjective Optimization Procedure for Combining Reflectance Spectroscopy and Species Ordination},
  author = {Neumann, Carsten and Itzerott, Sibylle and Weiss, Gabriele and Kleinschmit, Birgit and Schmidtlein, Sebastian},
  date = {2016},
  journaltitle = {Ecological Informatics},
  volume = {36},
  pages = {61--76},
  issn = {1574-9541},
  doi = {10.1016/j.ecoinf.2016.10.002},
  url = {https://www.sciencedirect.com/science/article/pii/S1574954116301054},
  abstract = {Nature conservation and ecological restoration crucially depends on the knowledge about spatial patterns of plant species that control habitat conversion and disturbance regimes. Especially, species abundances are capable of indicating early development tendencies for setting habitat management strategies. This study demonstrates the transfer of field spectroscopy to hyperspectral imagery to map multiple plant species abundances in an open dryland area using two imaging spectrometers in two different phenological phases. We show that species abundances can partially be described by multiple gradients forming different coordinates in a contour map. For this purpose, species abundances were projected into an ordination space using non-metric multidimensional scaling and subsequent spatial interpolation. It was demonstrated that different gradients can be modeled in a Partial Least Squares regression framework resulting in distinct spectral features for certain gradient directions. We combine both objectives in a multiobjective NSGA-II procedure to maximize the quantitative determination of species abundance in ordination and spectral predictability in related field spectra, simultaneously. NSGA-II was finally used to select optimal spectral models for n=35 single species that were transferred to hyperspectral imagery for mapping purpose. We can show that abundance predictabilities can be evaluated on the basis of individual model performances that hold different spectral features for each species in a designated phenological phase. Finally, we present spatially explicit multi-species maps for the best n=18 and abundance maps for n=8 models that could be linked to patterns of species richness, coexistence, succession stages and habitat type conditions.},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\neumann_et_al_2016_mapping_multiple_plant_species_abundance_patterns_-_a_multiobjective.pdf}
}

@article{nichol2005,
  title = {Urban Vegetation Monitoring in {{Hong Kong}} Using High Resolution Multispectral Images},
  author = {Nichol, J. and Lee, C.M.},
  date = {2005},
  journaltitle = {International Journal of Remote Sensing},
  volume = {26},
  number = {5},
  pages = {903--918},
  publisher = {{Taylor and Francis Ltd.}},
  issn = {01431161},
  doi = {10.1080/01431160412331291198},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-13644253878&doi=10.1080%2f01431160412331291198&partnerID=40&md5=75e0de8042e12c493a24730f7f518873},
  abbrev_source_title = {Int. J. Remote Sens.},
  abstract = {Very high resolution (VHR) satellite remote sensing systems are now capable of providing imagery with similar spatial detail to aerial photography, but with superior spectral information. This research investigates the hypothesis that it should be possible to use multispectral IKONOS images to quantify urban vegetation, obtaining similar accuracy to that achieved from false colour aerial photographs. Two parameters, vegetation cover and vegetation density are used to represent biomass in the study area (Kowloon, Hong Kong), for which data is collected for 41 field quadrats. Regression equations relating the field measurements of vegetation density to image wavebands obtained similar high correlations for both image types and lower but significant correlations for vegetation cover. Vegetation density is a quantifiable measure of vegetation in multiple layers above ground, representing the total amount of biomass and is thus well able to indicate the diverse structural types of vegetation found in urban areas. Furthermore it can be accurately measured using the IKONOS green/red ratio (Chlorophyll Index). The superiority of the latter to the more commonly used Normalized Difference Vegetation Index (NDVI), is attributed to the sub-optimal timing of the imagery during the dry season, and its greater sensitivity to multiple layering within the vegetation canopy. A time and cost comparison between the two image types suggests that the use of IKONOS images is much more cost effective than aerial photographs for urban vegetation monitoring. © 2005 Taylor \& Francis Ltd.},
  affiliation = {Dept. of Land Surv./Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong},
  coden = {IJSED},
  correspondence_address1 = {Nichol, J.; Dept. of Land Surv./Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong; email: lsjanet@polyu.edu.hk},
  document_type = {Article},
  funding_details = {B-Q611},
  funding_text_1 = {The authors would like to acknowledge funding from the Hong Kong Government CERG grant B-Q611, and the help of an anonymous reviewer.},
  langid = {english},
  source = {Scopus},
  keywords = {Aerial photography,Biomass,Chlorophyll,Cost effectiveness,IKONOS,image analysis,Image sensors,Multispectral images,NDVI,Normalized difference vegetation index (NDVI),Regression analysis,remote sensing,Remote sensing,resolution,satellite imagery,Satellite remote sensing systems,Satellites,urban area,Urban vegetation monitoring,Vegetation,vegetation cover}
}

@article{norton2015,
  title = {Planning for Cooler Cities: {{A}} Framework to Prioritise Green Infrastructure to Mitigate High Temperatures in Urban Landscapes},
  shorttitle = {Planning for Cooler Cities},
  author = {Norton, Briony A. and Coutts, Andrew M. and Livesley, Stephen J. and Harris, Richard J. and Hunter, Annie M. and Williams, Nicholas S. G.},
  date = {2015-02-01},
  journaltitle = {Landscape and Urban Planning},
  shortjournal = {Landscape and Urban Planning},
  volume = {134},
  pages = {127--138},
  issn = {0169-2046},
  doi = {10.1016/j.landurbplan.2014.10.018},
  url = {http://www.sciencedirect.com/science/article/pii/S0169204614002503},
  urldate = {2020-03-06},
  abstract = {Warming associated with urban development will be exacerbated in future years by temperature increases due to climate change. The strategic implementation of urban green infrastructure (UGI) e.g. street trees, parks, green roofs and facades can help achieve temperature reductions in urban areas while delivering diverse additional benefits such as pollution reduction and biodiversity habitat. Although the greatest thermal benefits of UGI are achieved in climates with hot, dry summers, there is comparatively little information available for land managers to determine an appropriate strategy for UGI implementation under these climatic conditions. We present a framework for prioritisation and selection of UGI for cooling. The framework is supported by a review of the scientific literature examining the relationships between urban geometry, UGI and temperature mitigation which we used to develop guidelines for UGI implementation that maximises urban surface temperature cooling. We focus particularly on quantifying the cooling benefits of four types of UGI: green open spaces (primarily public parks), shade trees, green roofs, and vertical greening systems (green walls and facades) and demonstrate how the framework can be applied using a case study from Melbourne, Australia.},
  keywords = {Climate change adaptation,Green roof,Heat wave,Public health,Urban greening,Urban planning},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\SSI4Z9TX\\S0169204614002503.html}
}

@article{nouri2013,
  title = {High Spatial Resolution {{WorldView-2}} Imagery for Mapping {{NDVI}} and Its Relationship to Temporal Urban Landscape Evapotranspiration Factors},
  author = {Nouri, H. and Beecham, S. and Anderson, S. and Nagler, P.},
  date = {2013},
  journaltitle = {Remote Sensing},
  volume = {6},
  number = {1},
  pages = {580--602},
  issn = {20724292},
  doi = {10.3390/rs6010580},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893426265&doi=10.3390%2frs6010580&partnerID=40&md5=f413a43d2bb8c9a0e77dabba6460e7da},
  abbrev_source_title = {Remote Sens.},
  abstract = {Evapotranspiration estimation has benefitted from recent advances in remote sensing and GIS techniques particularly in agricultural applications rather than urban environments. This paper explores the relationship between urban vegetation evapotranspiration (ET) and vegetation indices derived from newly-developed high spatial resolution WorldView-2 imagery. The study site was Veale Gardens in Adelaide, Australia. Image processing was applied on five images captured from February 2012 to February 2013 using ERDAS Imagine. From 64 possible two band combinations of WorldView-2, the most reliable one (with the maximum median differences) was selected. Normalized Difference Vegetation Index (NDVI) values were derived for each category of landscape cover, namely trees, shrubs, turf grasses, impervious pavements, and water bodies. Urban landscape evapotranspiration rates for Veale Gardens were estimated through field monitoring using observational-based landscape coefficients. The relationships between remotely sensed NDVIs for the entire Veale Gardens and for individual NDVIs of different vegetation covers were compared with field measured urban landscape evapotranspiration rates. The water stress conditions experienced in January 2013 decreased the correlation between ET and NDVI with the highest relationship of ET-Landscape NDVI (Landscape Normalized Difference Vegetation Index) for shrubs (r2=0.66) and trees (r2=0.63). However, when the January data was excluded, there was a significant correlation between ET and NDVI. The highest correlation for ET-Landscape NDVI was found for the entire Veale Gardens regardless of vegetation type (r2=0.95, p \> 0.05) and the lowest one was for turf (r2=0.88, p \> 0.05). In support of the feasibility of ET estimation by WV2 over a longer period, an algorithm recently developed that estimates evapotranspiration rates based on the Enhanced Vegetation Index (EVI) from MODIS was employed. The results revealed a significant positive relationship between ETMODIS and ETWV2 (r2=0.9857, p \> 0.05). This indicates that the relationship between NDVI using high resolution WorldView-2 imagery and ground-based validation approaches could provide an effective predictive tool for determining ET rates from unstressed mixed urban landscape plantings. © 2014 by the authors.},
  affiliation = {SA Water Centre for Water Management and Reuse, University of South Australia, Adelaide, SA 5095, Australia; School of Natural and Built Environments, University of South Australia, Adelaide, SA 5095, Australia; Barbara Hardy Institute, University of South Australia, Adelaide, SA 5095, Australia; Sonoran Desert Research Station, Southwest Biological Science Center, US Geological Survey and University of Arizona, Tucson, AZ 85719, United States},
  author_keywords = {Evapotranspiration; Landscape coefficient; MODIS; NDVI; Urban vegetation; Water Use Classifications of Landscape Species (WUCOLS); WorldView-2},
  correspondence_address1 = {Nouri, H.; SA Water Centre for Water Management and Reuse, University of South Australia, Adelaide, SA 5095, Australia; email: Hamideh.Nouri@mymail.unisa.edu.au},
  document_type = {Article},
  langid = {english},
  source = {Scopus},
  keywords = {Classification,Estimation,Evaporation,Evapotranspiration,Forestry,Forests,Image Analysis,Image processing,Image resolution,Landscape coefficient,Landscape species,MODIS,NDVI,Plants,Plants (botany),Radiometers,Radiometry,Remote sensing,Remote Sensing,Satellite imagery,Satellites,Transpiration,Urban vegetation,Vegetation,Water supply,Water Supply,Worldview-2}
}

@article{okeeffe2019,
  title = {Quantifying the Sensing Power of Vehicle Fleets},
  author = {O’Keeffe, Kevin P. and Anjomshoaa, Amin and Strogatz, Steven H. and Santi, Paolo and Ratti, Carlo},
  date = {2019-06-25},
  journaltitle = {Proceedings of the National Academy of Sciences},
  shortjournal = {Proc Natl Acad Sci USA},
  volume = {116},
  number = {26},
  pages = {12752--12757},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1821667116},
  url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1821667116},
  urldate = {2021-01-26},
  abstract = {Sensors can measure air quality, traffic congestion, and other aspects of urban environments. The fine-grained diagnostic information they provide could help urban managers to monitor a city’s health. Recently, a “drive-by” paradigm has been proposed in which sensors are deployed on third-party vehicles, enabling wide coverage at low cost. Research on drive-by sensing has mostly focused on sensor engineering, but a key question remains unexplored: How many vehicles would be required to adequately scan a city? Here, we address this question by analyzing the sensing power of a taxi fleet. Taxis, being numerous in cities, are natural hosts for the sensors. Using a ball-in-bin model in tandem with a simple model of taxi movements, we analytically determine the fraction of a city’s street network sensed by a fleet of taxis during a day. Our results agree with taxi data obtained from nine major cities and reveal that a remarkably small number of taxis can scan a large number of streets. This finding appears to be universal, indicating its applicability to cities beyond those analyzed here. Moreover, because taxis’ motion combines randomness and regularity (passengers’ destinations being random, but the routes to them being deterministic), the spreading properties of taxi fleets are unusual; in stark contrast to random walks, the stationary densities of our taxi model obey Zipf’s law, consistent with empirical taxi data. Our results have direct utility for town councilors, smart-city designers, and other urban decision makers.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\ZBBP5NCG\\O’Keeffe et al. - 2019 - Quantifying the sensing power of vehicle fleets.pdf}
}

@article{oliva2001,
  title = {[{{No}} Title Found]},
  author = {Oliva, Aude and Torralba, Antonio},
  date = {2001},
  journaltitle = {International Journal of Computer Vision},
  volume = {42},
  number = {3},
  pages = {145--175},
  issn = {09205691},
  doi = {10.1023/A:1011139631724},
  url = {http://link.springer.com/10.1023/A:1011139631724},
  urldate = {2021-02-06}
}

@article{orzechowska-szajda2020,
  title = {The Influence of Urban Conditions on the Phenology of Aesculus Hippocastanum l. {{Using}} the Example of Wroclaw (Poland)},
  author = {Orzechowska‐szajda, I.D. and Sobolewski, R.K. and Lewandowska, J. and Kowalska, P. and Kalbarczyk, R.},
  date = {2020},
  journaltitle = {Forests},
  volume = {11},
  number = {12},
  pages = {1--19},
  doi = {10.3390/f11121261},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096785362&doi=10.3390%2ff11121261&partnerID=40&md5=0f5350fa74603bb68a39fc2f6bc28e5d},
  abstract = {The differences in plant phenology between rural and urban areas are the subject of research conducted all over the world. There are few studies aimed at assessing the impact of the urban heat island on plant vegetation only in urban areas. The aim of this study is to assess the impact of the distance from the city center and the form of land cover on the phenological development of trees using the example of the horse chestnut (Aesculus hippocastanum L.). The research area covered the entire city of Wrocław. In order to best capture the impact of the distance from the city center on the rate of changes of individual phenophases, 3 areas were designated—at a distance of 1 km, 2 km and 5 km. The study assessed the average duration of individual phenological phases along with the variability characteristics for leafing, flowering and fruiting in relation to the designated zones and classified forms of land cover based on mean value (x̅) and standard deviation (± SD) in individual weeks of the year. For the leafing and flowering phases, the frequency of the occurrence of phases in individual weeks of the year was analyzed in relation to the designated zones and classified land use methods. The results obtained on the basis of phenological observations carried out in 2017 in Wrocław confirmed the extension of the period of vegetation in the city center in relation to its peripheries. Trees growing in road lanes entered the vegetation period later and defoliated faster, which confirms the negative impact of street conditions on the development of trees in urban space. Thus, the growing season in road lanes is shorter and due to the 1‐year observation period, it is justified to conduct further observations. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
  affiliation = {Institute of Landscape Architecture, Wrocław University of Environmental and Life Sciences, Grunwaldzaka55, Wrocław, 50‐375, Poland},
  art_number = {1261},
  author_keywords = {City climate; Horse chestnut; Phenological observations; Urban heat island},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\orzechowska‐szajda_et_al_2020_the_influence_of_urban_conditions_on_the_phenology_of_aesculus_hippocastanum_l.pdf}
}

@article{ossola2020,
  title = {The {{Global Urban Tree Inventory}}: {{A}} Database of the Diverse Tree Flora That Inhabits the World’s Cities},
  shorttitle = {The {{Global Urban Tree Inventory}}},
  author = {Ossola, Alessandro and Hoeppner, Malin J. and Burley, Hugh M. and Gallagher, Rachael V. and Beaumont, Linda J. and Leishman, Michelle R.},
  date = {2020},
  journaltitle = {Global Ecology and Biogeography},
  volume = {29},
  number = {11},
  pages = {1907--1914},
  issn = {1466-8238},
  doi = {10.1111/geb.13169},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/geb.13169},
  urldate = {2021-07-14},
  abstract = {Motivation The Global Urban Tree Inventory (GUTI) is a compilation of datasets on tree species found in cities and towns throughout the world. GUTI data can be used to address a diverse range of theoretical and applied investigations related to species’ biogeography and distribution, ecological and physiological tolerance to climatic, biophysical and environmental parameters, as well as plant conservation and invasion. Main types of variables contained GUTI contains current taxonomic data for 4,734 tree species planted in urban areas, their conservation status [International Union for Conservation of Nature’s (IUCN’s) Red List of Threatened Species] and invasion potential (Global Register of Introduced and Invasive Species). Spatial location and grain Four hundred and seventy-three urban areas in seventy-three countries across five continents. The urban areas spanned 21 of 29 Koppen–Geiger climatic zones, and all 19 Food and Agriculture Organization of the United Nations global ecofloristic zones. Time period and grain GUTI is based on the most recent collections of urban tree inventories and species lists compiled by local authorities or reported in the scientific literature. Most data have been collected or updated since 2010. Major taxa and level of measurement Four thousand seven hundred and thirty-four tree species (c. 8\% of the global known arboreal flora). One-tenth of these tree species face conservation risk in the wild, whereas 327 species are known to have invasion potential. Software format .xls file.},
  langid = {english},
  keywords = {biodiversity,conservation,horticulture,species richness,urban forests,urbanization},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/geb.13169},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\ossola_et_al_2020_the_global_urban_tree_inventory.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\3ZCJ42J2\\geb.html}
}

@article{ostberg2013,
  title = {Grading of {{Parameters}} for {{Urban Tree Inventories}} by {{City Officials}}, {{Arborists}}, and {{Academics Using}} the {{Delphi Method}}},
  author = {Östberg, Johan and Delshammar, Tim and Wiström, Björn and Nielsen, Anders Busse},
  date = {2013-03-01},
  journaltitle = {Environmental Management},
  shortjournal = {Environmental Management},
  volume = {51},
  number = {3},
  pages = {694--708},
  issn = {1432-1009},
  doi = {10.1007/s00267-012-9973-8},
  url = {https://doi.org/10.1007/s00267-012-9973-8},
  urldate = {2021-02-08},
  abstract = {Tree inventories are expensive to conduct and update, so every inventory carried out must be maximized. However, increasing the number of constituent parameters increases the cost of performing and updating the inventory, illustrating the need for careful parameter selection. This article reports the results of a systematic expert rating of tree inventories aiming to quantify the relative importance of each parameter. Using the Delphi method, panels comprising city officials, arborists, and academics rated a total of 148 parameters. The total mean score, the top ranking parameters, which can serve as a guide for decision-making at practical level and for standardization of tree inventories, were: Scientific name of the tree species and genera, Vitality, Coordinates, Hazard class, and Identification number. The study also examined whether the different responsibilities and usage of urban tree databases among organizations and people engaged in urban tree inventories affected their prioritization. The results revealed noticeable dissimilarities in the ranking of parameters between the panels, underlining the need for collaboration between the research community and those commissioning, administrating, and conducting inventories. Only by applying such a transdisciplinary approach to parameter selection can urban tree inventories be strengthened and made more relevant.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\ostberg_et_al_2013_grading_of_parameters_for_urban_tree_inventories_by_city_officials,_arborists,.pdf}
}

@article{oteros2019,
  title = {Spatial Interpolation of Current Airborne Pollen Concentrations Where No Monitoring Exists},
  author = {Oteros, Jose and Bergmann, Karl-Christian and Menzel, Annette and Damialis, Athanasios and Traidl-Hoffmann, Claudia and Schmidt-Weber, Carsten B. and Buters, Jeroen},
  date = {2019-02-15},
  journaltitle = {Atmospheric Environment},
  shortjournal = {Atmospheric Environment},
  volume = {199},
  pages = {435--442},
  issn = {1352-2310},
  doi = {10.1016/j.atmosenv.2018.11.045},
  url = {https://www.sciencedirect.com/science/article/pii/S1352231018308239},
  urldate = {2021-06-15},
  abstract = {Background Pollen is naturally emitted and is relevant for health, crop sciences and monitoring climate change, among others. Despite their relevance, pollen is often insufficiently monitored resulting in a lack of data. Thus, spatial modelling of pollen concentrations for unmonitored areas is necessary. The aim of this study was to develop an automatic system for calculating daily pollen concentrations at sites without regular pollen monitoring. Method We used data from 14 pollen taxa collected during 2015\,at 26 stations distributed across Bavaria, Germany. The proposed system was based on the Kriging interpolation method to spatially model pollen concentrations for unmonitored areas, in combination with regression of environmental parameters. The method also took into account weather effects on daily pollen concentrations. Results An automatic system was developed for calculating current pollen concentrations at any location of the county. The results were displayed as daily pollen concentrations per m3 in maps of 1\,km2 resolution. The models are trained automatically for every day by using the pollen and weather inputs. Automatic inputs will increase the usability of the model. In 50\% of the cases, Gaussian Kriging was selected as the optimal model. An R2 of 0.5 is reached in external validation without considering the effect of the weather. An R2 of 0.7 is reached after considering the effect of daily weather parameters. Conclusions A fully automatic pollen network (ePIN) was built in Bavaria during 2018 that delivers data on-line without delay. The proposed method allows for a comparably small number of automatic devices per study area, but still providing information on pollen on any location in the study area.},
  langid = {english},
  keywords = {Aerobiology,Automatic forecasting system,Geostatistics,Pollen,Prediction model},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\oteros_et_al_2019_spatial_interpolation_of_current_airborne_pollen_concentrations_where_no.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\GC32EIF5\\S1352231018308239.html}
}

@article{oteros2020,
  title = {An Operational Robotic Pollen Monitoring Network Based on Automatic Image Recognition},
  author = {Oteros, Jose and Weber, Alisa and Kutzora, Suzanne and Rojo, Jesús and Heinze, Stefanie and Herr, Caroline and Gebauer, Robert and Schmidt-Weber, Carsten B. and Buters, Jeroen T. M.},
  date = {2020-12-01},
  journaltitle = {Environmental Research},
  shortjournal = {Environmental