text:
@article{alba1998,
  title = {The Effect of Air Temperature on the Starting Dates of the {{Ulmus}}, {{Platanus}} and {{Olea}} Pollen Seasons in the {{SE Iberian Peninsula}}},
  author = {Alba, F. and Díaz De La Guardia, C.},
  date = {1998},
  journaltitle = {Aerobiologia},
  volume = {14},
  number = {2-3},
  pages = {191--194},
  doi = {10.1007/BF02694205},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0031772134&doi=10.1007%2fBF02694205&partnerID=40&md5=d526786cff0ac690b174cbe1386335c0},
  abstract = {A study is made of the effect of air temperature on the start of the pollen seasons of three tree species-Ulmus, Platanus and Olea-in the southeastern Iberian Peninsula. These initial results are based on an aerobiological analysis performed over a 4-year period in the city of Granada, Spain. Sampling was carried out with a Burkard spore trap. The main aim of the present study was to use regression analysis to identify the preseasonal date when these species start to accumulate heat in their floral buds, enabling models to be created that indicate the onset of the pollen season for these taxa. For Ulmus there was no significant correlation between the onset of pollination and the mean temperature during the preceding period, whereas Platanus presented a significant correlation with mean temperature during the month of January, and Olea with mean temperature during the second fortnight in February and the month of March. For Ulmus, the start of the pollen season ranged between 30 January and 8 February; for Platanus, between 13 and 17 March; and for Olea, between 20 April and 13 May. The accumulated temperature needed to induce the onset of flowering ranged between 121 and 256°C for Ulmus, with values of 428-607°C and 656-881°C for Platanus and Olea, respectively.},
  affiliation = {Departamento de Biología Vegetal, Facultad de Ciencias, Universidad de Granada, E-18071 Granada, Spain},
  author_keywords = {Air temperature; Phenology; Pollen season; SE Iberian Peninsula},
  document_type = {Conference Paper},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\alba_diaz_de_la_guardia_1998_the_effect_of_air_temperature_on_the_starting_dates_of_the_ulmus,_platanus_and.pdf}
}

@article{anjomshoaa2018,
  title = {City {{Scanner}}: {{Building}} and {{Scheduling}} a {{Mobile Sensing Platform}} for {{Smart City Services}}},
  shorttitle = {City {{Scanner}}},
  author = {Anjomshoaa, Amin and Duarte, Fabio and Rennings, Daniel and Matarazzo, Thomas J. and {deSouza}, Priyanka and Ratti, Carlo},
  date = {2018-12},
  journaltitle = {IEEE Internet of Things Journal},
  shortjournal = {IEEE Internet Things J.},
  volume = {5},
  number = {6},
  pages = {4567--4579},
  issn = {2327-4662, 2372-2541},
  doi = {10.1109/JIOT.2018.2839058},
  url = {https://ieeexplore.ieee.org/document/8361419/},
  urldate = {2021-01-26},
  abstract = {A large number of vehicles routinely navigate through city streets; with on-board sensors, they can be transformed into a dynamic network that monitors the urban environment comprehensively and efficiently. In this paper, driveby approaches are discussed as a form of mobile sensing, that offer a number of advantages over more traditional sensing approaches. It is shown that the physical properties of the urban environment that can be captured using drive-by sensing include Ambient Fluid, Electromagnetic, Urban Envelope, Photonic, and Acoustic properties, which comprise the FEELS classification. In addition, the spatiotemporal variations of these phenomena are discussed as well as their implications on discrete-time sampling. The mobility patterns of sensor-hosting vehicles play a major role in drive-by sensing. Vehicles with scheduled trajectories, e.g., buses, and those with less predictable mobility patterns, e.g., taxis, are investigated for sensing efficacy in terms of spatial and temporal coverage. City Scanner is a drive-by approach with a modular sensing architecture, which enables cost-effective mass data acquisition on a multitude of city features. The City Scanner framework follows a centralized IoT regime to generate a near real-time visualization of sensed data. The sensing platform was mounted on top of garbage trucks and collected drive-by data for eight months in Cambridge, MA, USA. Acquired data were streamed to the cloud for processing and subsequent analyses. Based on a real-world application, we discuss and show the potential of using drive-by approaches to collect environmental data in urban areas using a variety of non-dedicated land vehicles to optimize data collection in terms of spatiotemporal coverage.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\anjomshoaa_et_al_2018_city_scanner.pdf}
}

@inproceedings{anjomshoaa2018a,
  title = {Challenges of {{Drive-By IoT Sensing}} for {{Smart Cities}}: {{City Scanner Case Study}}},
  shorttitle = {Challenges of {{Drive-By IoT Sensing}} for {{Smart Cities}}},
  booktitle = {Proceedings of the 2018 {{ACM International Joint Conference}} and 2018 {{International Symposium}} on {{Pervasive}} and {{Ubiquitous Computing}} and {{Wearable Computers}}},
  author = {Anjomshoaa, Amin and Mora, Simone and Schmitt, Philip and Ratti, Carlo},
  date = {2018-10-08},
  pages = {1112--1120},
  publisher = {{ACM}},
  location = {{Singapore Singapore}},
  doi = {10.1145/3267305.3274167},
  url = {https://dl.acm.org/doi/10.1145/3267305.3274167},
  urldate = {2021-06-09},
  abstract = {Fixed sensor stations are the primary means to collect environmental data in cities. Yet, their high cost of deployment and maintenance often result in an accurate but geographicallysparse monitoring. We advocate for a drive-by approach to urban sensing in which vehicles are used as sensors to scan the city with a high spatiotemporal resolution. We present City Scanner, a highly-customizable, self-sufficient platform that allows for cost-efficient drive-by sensing. City Scanner modules can be deployed on existing vehicles (e.g. busses and taxis) without interfering with their operations. We describe our first prototype that includes sensing modules for air quality, temperature, humidity, and thermal imaging. We discuss the challenges we encountered during an 8-months deployment of the platform on trash trucks in order to derive implications for the design of future drive-by sensing systems.},
  eventtitle = {{{UbiComp}} '18: {{The}} 2018 {{ACM International Joint Conference}} on {{Pervasive}} and {{Ubiquitous Computing}}},
  isbn = {978-1-4503-5966-5},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\Y68MLD6I\\Anjomshoaa et al. - 2018 - Challenges of Drive-By IoT Sensing for Smart Citie.pdf}
}

@article{anjomshoaa2021,
  title = {Quantifying the {{Spatio-Temporal Potential}} of {{Drive-by Sensing}} in {{Smart Cities}}},
  author = {Anjomshoaa, Amin and Santi, Paolo and Duarte, Fabio and Ratti, Carlo},
  date = {2021-04-03},
  journaltitle = {Journal of Urban Technology},
  shortjournal = {Journal of Urban Technology},
  volume = {28},
  number = {1-2},
  pages = {199--216},
  issn = {1063-0732, 1466-1853},
  doi = {10.1080/10630732.2020.1791679},
  url = {https://www.tandfonline.com/doi/full/10.1080/10630732.2020.1791679},
  urldate = {2021-06-09},
  abstract = {Recently, portable sensors, with high accuracy and embedded communication technologies, have become available and affordable. By deploying such sensors on various urban vehicles that routinely navigate through city streets, vehicles can form a dynamic network for comprehensively and efficiently monitoring the urban environment. This drive-by sensing approach benefits also from the lower costs of sensor deployment and maintenance compared to stationary sensor networks. However, the data sampling frequency and spatial granularity of measurements are constrained by factors such as topology of the underlying street network and mobility pattern of sensor-equipped vehicles. In this paper we investigate the effect of street network topology on the quality of data captured through drive-by sensing. To this end, we first study the temporal aspects of drive-by sensing and present a quantitative method for comparing various street networks. Then, we consider the spatial aspects of drive-by sensing by defining a sensing-potential indicator for urban areas based on the geometrical properties of the street networks. This indicator is then combined with vehicle mobility patterns derived to measure the sensing potential of routes and cycles. In this context, we define the novel concept of Sensogram for describing the spatial sensing potential of network cycles using dedicated vehicles.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\DRAG45WT\\Anjomshoaa et al. - 2021 - Quantifying the Spatio-Temporal Potential of Drive.pdf}
}

@article{anniballe2014,
  title = {Spatial and Temporal Trends of the Surface and Air Heat Island over {{Milan}} Using {{MODIS}} Data},
  author = {Anniballe, R. and Bonafoni, S. and Pichierri, M.},
  date = {2014},
  journaltitle = {Remote Sensing of Environment},
  volume = {150},
  pages = {163--171},
  publisher = {{Elsevier Inc.}},
  issn = {00344257},
  doi = {10.1016/j.rse.2014.05.005},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901485889&doi=10.1016%2fj.rse.2014.05.005&partnerID=40&md5=3ccb15451b85d3d8cf701c05e3450771},
  abbrev_source_title = {Remote Sens. Environ.},
  abstract = {In this work the analysis of the surface and air heat island in Milan, Italy, by means of satellite maps is proposed. The urban heat island (UHI) maps were produced using data provided by the Moderate-resolution Imaging Spectroradiometer (MODIS) on board of both Terra and Aqua satellites. Two types of UHI were analyzed simultaneously: the canopy layer heat island (CLHI) and the surface urban heat island (SUHI). The aim of this work is the realization of the SUHI and CLHI maps to monitor the spatial and temporal evolution of surface and air heating; also, to highlight and quantify the different features (e.g. magnitude, spatial extent, orientation and UHI center location) a Gaussian surface was used to fit the spatially distributed heat island patterns.The analysis during summer months points out that the SUHI effect is a noticeable phenomenon throughout the whole diurnal cycle: it has a stronger intensity in the daytime with peaks around 9-10. K while in the nighttime, in the absence of solar forcing, it decreases by a factor of 2. In contrast, the canopy layer heat island during the daytime is absent: the CLHI emerges after sunset with an average intensity around 3-4. K, showing features similar to the nighttime SUHI.In addition, comparisons between UHI intensity and normalized difference vegetation index (NDVI) were performed, confirming that green areas can contribute to the mitigation of this phenomenon. © 2014 Elsevier Inc.},
  affiliation = {Department of Electronic and Information Engineering, University of Perugia, via G. Duranti 93, 06125 Perugia, Italy; Institute of Environmental Engineering, ETH Zurich, Stefano-Franscini-Platz 3, 8093 Zurich, Switzerland},
  author_keywords = {Gaussian fit; Satellite-based sensor; Surface and air temperature; Urban heat island},
  coden = {RSEEA},
  correspondence_address1 = {Bonafoni, S.; Department of Electronic and Information Engineering, University of Perugia, via G. Duranti 93, 06125 Perugia, Italy; email: stefania.bonafoni@unipg.it},
  document_type = {Article},
  langid = {english},
  source = {Scopus},
  keywords = {Air temperature,Atmospheric temperature,climate variation,Gaussian fits,Gaussian method,heat island,Image reconstruction,Italy,Lombardy,Milan,Milano [Lombardy],Moderate resolution imaging spectroradiometer,MODIS,Normalized difference vegetation index,Radiometers,satellite imagery,Satellite-based sensors,Satellites,seasonal variation,Spatial and temporal trends,spatiotemporal analysis,Surface urban heat islands,Thermal pollution,Urban heat island}
}

@article{atasoy2018,
  title = {Monitoring the Urban Green Spaces and Landscape Fragmentation Using Remote Sensing: A Case Study in {{Osmaniye}}, {{Turkey}}},
  author = {Atasoy, M.},
  date = {2018},
  journaltitle = {Environmental Monitoring and Assessment},
  volume = {190},
  number = {12},
  publisher = {{Springer International Publishing}},
  issn = {01676369},
  doi = {10.1007/s10661-018-7109-1},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056322303&doi=10.1007%2fs10661-018-7109-1&partnerID=40&md5=6f62b65bb002d165964241d0f836ee55},
  abbrev_source_title = {Environ. Monit. Assess.},
  abstract = {Urban green spaces play a significant role in management of physical activity, psychological well-being, and public health of urban residents. With the expansion of urban areas in Turkey during the past decades, urban green spaces have been fragmented and dispersed causing impairment and environmental degradation. The purpose of this study is to model urban green space distribution by focusing on the landscape fragmentation in city of Osmaniye using remote sensing and geographic information system technology. Normalized difference vegetation index (NDVI) and urban landscape ratio (ULR) were used to assess the proximity and spatial arrangement of urban green spaces within the neighbor landscapes to quantify the urban land use effect. The geospatial analysis results showed that increase in total built-up area and population has significantly decreased the urban green space cover because of high levels of landscape fragmentation in urban city center. Also, due to high levels of landscape fragmentation, approximately 45\% of the Osmaniye city is estimated to become urbanized by 2030. This study demonstrated the benefits of directional vegetation index application with geospatial analyses in characterizing the environmental quality for planning and management of urban green spaces. This approach could be used for determining the future urban land development scenarios correlating with regional planning procedures. © 2018, Springer Nature Switzerland AG.},
  affiliation = {Faculty of Architecture, Design, and Fine Arts, Osmaniye Korkut Ata University, Osmaniye, 80000, Turkey},
  art_number = {713},
  author_keywords = {Environmental monitoring; Landscape fragmentation; Remote sensing; Urban green space},
  coden = {EMASD},
  correspondence_address1 = {Atasoy, M.; Faculty of Architecture, Design, and Fine Arts, Osmaniye Korkut Ata UniversityTurkey; email: muratatasoy@osmaniye.edu.tr},
  document_type = {Article},
  langid = {english},
  pubmed_id = {30415308},
  source = {Scopus},
  keywords = {article,Cities,city,city planning,environmental monitoring,Environmental Monitoring,geographic information system,Geographic Information Systems,human,Humans,landscape,procedures,quantitative analysis,remote sensing,Remote Sensing Technology,trends,Turkey,turkey (bird),Turkey (republic),urban area,urban population,Urban Population,Urban Renewal,urbanization,Urbanization,vegetation}
}

@article{au2018,
  title = {An Integrated Approach to Tree Stress Monitoring},
  author = {Au, K N},
  date = {2018},
  journaltitle = {Arborist News, International Society of Arboriculture},
  volume = {27},
  number = {4},
  pages = {28--31},
  issn = {1542-2399},
  url = {http://geocarto.com.hk/readings/aug2018_issue/#page/1},
  urldate = {2020-01-12},
  entrysubtype = {magazine},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\k._n._au_2018_an_integrated_approach_to_tree_stress_monitoring.pdf}
}

@article{baeker2019,
  title = {Perspektiven für ein bundesweites Pollenmonitoring in Deutschland},
  author = {Baeker, Regine and Bergmann, Karl-Christian and Buters, Jeroen and Dümmel, Thomas and Endler, Christina and Fuchs, Thomas and Gilge, Stefan and Gloyna, Kai and Heesen, Ruth and Herr, Caroline and Hicke, Martin and Höflich, Conny and Klimek, Ludger and Kutzora, Susanne and Langner, Marcel and Mücke, Hans-Guido and Petzold, Gudrun and Pleschka, Silvia and Röseler, Stefani and Schwalfenberg, Anja and Simon, Sven and Straff, Wolfgang and Weber, Alisa and Werchan, Barbora and Werchan, Matthias and {Fachübergreifender Arbeitskreis „Bundesweites Pollenmonitoring“}},
  date = {2019-05-01},
  journaltitle = {Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz},
  shortjournal = {Bundesgesundheitsbl},
  volume = {62},
  number = {5},
  pages = {652--661},
  issn = {1437-1588},
  doi = {10.1007/s00103-019-02940-y},
  url = {https://doi.org/10.1007/s00103-019-02940-y},
  urldate = {2021-06-21},
  abstract = {Allergene Pollen sind natürliche, biologische luftgetragene Partikel und der Hauptauslöser allergischer Atemwegserkrankungen. Die Messung allergener Pollen ist Voraussetzung für die gesundheitliche Vorsorge und zeigt Veränderungen im Pollenspektrum an, wie sie z.\,B. im Rahmen des Klimawandels zu erwarten sind.},
  langid = {german},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\baeker_et_al_2019_perspektiven_fur_ein_bundesweites_pollenmonitoring_in_deutschland.pdf}
}

@inproceedings{bannari2007,
  title = {Spatial Distribution Mapping of Vegetation Cover in Urban Environment Using {{TDVI}} for Quality of Life Monitoring},
  author = {Bannari, A. and Ozbakir, A. and Langlois, A.},
  date = {2007},
  series = {International {{Geoscience}} and {{Remote Sensing Symposium}} ({{IGARSS}})},
  pages = {679--682},
  location = {{Barcelona}},
  doi = {10.1109/IGARSS.2007.4422887},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-82355170059&doi=10.1109%2fIGARSS.2007.4422887&partnerID=40&md5=c52afb4070e0500a1d1c0c246f4ca80f},
  abbrev_source_title = {Dig Int Geosci Remote Sens Symp (IGARSS)},
  abstract = {In previous work, we have demonstrated that the semi-empirical model Transformed Difference Vegetation Index (TDVI) is less sensitive to soil optical properties variation, and more suitable for estimating the fraction of vegetation cover in forest and agricultural environment. This paper reports on a comparative study between TDVT, Normalized Difference Vegetation Index (NDVI), and the Soil Adjusted Vegetation Index (SAVI) for estimating fraction vegetation cover in urban environment using an image acquired with the Linear Imaging Self Scanner-III (LISS-III) onboard of the Indian Remote Sensing Satellite-1D (IRS-1D). The data were acquired on august 13, 1998 over the Montreal Island, period of the year when the vegetation is in the maximum phonological stage. A combined correction of the atmospheric effects (scattering and absorption) and the radiometric drift of the sensor were applied to transform the raw data to the surface reflectance. The validation of the obtained results according to the ground truth shows that the TDVI is a very good tool for vegetation cover monitoring in urban environment. It does not saturate like NDVI or SAVI, it shows a good linearity as a function of vegetation cover rate. © 2007 IEEE.},
  affiliation = {Department of Geography, University of Ottawa, 60 University str., Ottawa, ON K1N 6N5, Canada; Department of City and Regional Planning, Yildiz Technical University, Barbaros Bulvari, 34349 Yildiz-Istanbul, Turkey},
  art_number = {4422887},
  author_keywords = {LISS-IRS-ID imagery; NDVI; Quality of life; Quality of place; SAVI; TDVI; Urban environment; Vegetation indices},
  coden = {IGRSE},
  correspondence_address1 = {Bannari, A.; Department of Geography, University of Ottawa, 60 University str., Ottawa, ON K1N 6N5, Canada; email: abannari@uottawa.ca},
  document_type = {Conference Paper},
  isbn = {1-4244-1212-9 978-1-4244-1212-9},
  langid = {english},
  source = {Scopus},
  keywords = {Image acquisition,Image analysis,LISS-IRS-ID imagery,Mapping,Radiometry,Urban environment,Vegetation,Vegetation indices}
}

@report{basler2020,
  title = {{{PhenoCar}}: {{Assessment}} of Phenology of Thousands of Trees along an Environmental Gradient Using Car Mounted Cameras and Deep-Learning Based Image Segmentation},
  shorttitle = {{{PhenoCar}}},
  author = {Basler, David and Richardson, Andrew D.},
  date = {2020-03-09},
  number = {EGU2020-18521},
  institution = {{Copernicus Meetings}},
  doi = {10.5194/egusphere-egu2020-18521},
  url = {https://meetingorganizer.copernicus.org/EGU2020/EGU2020-18521.html},
  urldate = {2020-12-21},
  eventtitle = {{{EGU2020}}},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\basler_richardson_2020_phenocar.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\CMZAKEN6\\EGU2020-18521_presentation.pptx;C\:\\Users\\ahurl\\Zotero\\storage\\XQ9H67CC\\EGU2020-18521.html}
}

@article{Bennie2016611,
  title = {Ecological Effects of Artificial Light at Night on Wild Plants},
  author = {Bennie, J. and Davies, T.W. and Cruse, D. and Gaston, K.J.},
  date = {2016},
  journaltitle = {Journal of Ecology},
  volume = {104},
  number = {3},
  pages = {611--620},
  doi = {10.1111/1365-2745.12551},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959440570&doi=10.1111%2f1365-2745.12551&partnerID=40&md5=1e7e81ec63dc8d7a5d6ea527a26da1b8},
  abstract = {Plants use light as a source of both energy and information. Plant physiological responses to light, and interactions between plants and animals (such as herbivory and pollination), have evolved under a more or less stable regime of 24-h cycles of light and darkness, and, outside of the tropics, seasonal variation in day length. The rapid spread of outdoor electric lighting across the globe over the past century has caused an unprecedented disruption to these natural light cycles. Artificial light is widespread in the environment, varying in intensity by several orders of magnitude from faint skyglow reflected from distant cities to direct illumination of urban and suburban vegetation. In many cases, artificial light in the night-time environment is sufficiently bright to induce a physiological response in plants, affecting their phenology, growth form and resource allocation. The physiology, behaviour and ecology of herbivores and pollinators are also likely to be impacted by artificial light. Thus, understanding the ecological consequences of artificial light at night is critical to determine the full impact of human activity on ecosystems. Synthesis. Understanding the impacts of artificial night-time light on wild plants and natural vegetation requires linking the knowledge gained from over a century of experimental research on the impacts of light on plants in the laboratory and glasshouse with knowledge of the intensity, spatial distribution, spectral composition and timing of light in the night-time environment. To understand fully the extent of these impacts requires conceptual models that can (i) characterize the highly heterogeneous nature of the night-time light environment at a scale relevant to plant physiology; and (ii) scale physiological responses to predict impacts at the level of the whole plant, population, community and ecosystem. Understanding the impacts of artificial night-time light on wild plants and natural vegetation requires linking the knowledge gained from over a century of experimental research on the impacts of light on plants in the laboratory and glasshouse with knowledge of the intensity, spatial distribution, spectral composition and timing of light in the night-time environment. To understand fully the extent of these impacts requires conceptual models that can (i) characterize the highly heterogeneous nature of the night-time light environment at a scale relevant to plant physiology; and (ii) scale physiological responses to predict impacts at the level of the whole plant, population, community and ecosystem. © 2016 British Ecological Society.},
  affiliation = {Environment and Sustainability Institute, University of Exeter, Penryn Campus, Penryn, TR10 9FE, United Kingdom},
  author_keywords = {Circadian; Ecophysiology; Light cycles; Light pollution; Photoperiodism; Photopollution; Physiology; Sky glow; Urban ecology},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\bennie_et_al_2016_ecological_effects_of_artificial_light_at_night_on_wild_plants.pdf}
}

@article{beutner2021,
  title = {Sensitization Rates to Common Inhaled Allergens in {{Germany}} – Increase and Change Patterns over the Last 20 Years},
  author = {Beutner, Caroline and Werchan, Barbora and Forkel, Susann and Gupta, Sidhi and Fuchs, Thomas and Schön, Michael P. and Geier, Johannes and Buhl, Timo},
  date = {2021},
  journaltitle = {JDDG: Journal der Deutschen Dermatologischen Gesellschaft},
  volume = {19},
  number = {1},
  pages = {37--44},
  issn = {1610-0387},
  doi = {10.1111/ddg.14312},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/ddg.14312},
  urldate = {2021-06-21},
  abstract = {Background: Sensitization rates to aeroallergens are rising worldwide. The prevalence is increasing, especially in Western countries. We aimed to investigate (1) sensitization rates and (2) cross-sensitization patterns in skin prick tests (SPTs) for the most relevant inhaled allergens in central Germany over 20 years, adjusted for regional pollen counts. Patients and Methods: This monocentric study evaluated SPTs for tree pollen, grass pollen and house dust mites (HDMs) in 4,315 patients (including children) with suspected airway allergies, from 1998–2017. Results: Sensitization rates to almost all aeroallergens have increased significantly over time, without relevant changes in regional pollen counts. Current sensitization rates in all our symptomatic patients were highest for grass (55.3 \%) and rye pollen (59.6 \%), with most pronounced increases in HDM sensitization over time (from 37.8 \% to the current figure of 50.1 \%). However, a low but consistent proportion of tree-sensitized patients (3.6–7.8 \%) showed isolated positive SPTs to alder and/or hazel pollen without sensitization to birch pollen. Conclusions We demonstrate a significant rise in the total number of sensitized patients as well as increases in cross-sensitization between closely related allergens. Individuals with unusual mono-sensitization profiles to common inhaled allergens should be studied in more detail, since these patients are currently excluded from clinical trials for allergen immunotherapy.},
  langid = {english},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/ddg.14312},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\beutner_et_al_2021_sensitization_rates_to_common_inhaled_allergens_in_germany_–_increase_and.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\WC9HJMXQ\\ddg.html}
}

@article{bilgili2014,
  title = {A Simplified Method for the Determination and Monitoring of Green Areas in Urban Parks Using Multispectral Vegetation Indices},
  author = {Bilgili, B.C. and Satir, O. and Muftuoglu, V. and Ozyavuz, M.},
  date = {2014},
  journaltitle = {Journal of Environmental Protection and Ecology},
  volume = {15},
  number = {3},
  pages = {1059--1065},
  publisher = {{Scibulcom Ltd.}},
  issn = {13115065},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84914103013&partnerID=40&md5=25d2e9212fa3b72d57d4f74fc214b0d9},
  abbrev_source_title = {J. Environ. Prot. Ecol.},
  abstract = {In this article, a simple method to be used in determining and monitoring existing urban green areas was examined from an ecological point of view. To this end, Altinpark, which is located in the city of Ankara in Turkey, was studied as a pilot area. Normalised difference vegetation index (NDVI), soil adjusted vegetation index (SAVI) and tasselled cap green vegetation index (GVI) values of Altinpark were used as ecological indicators. Vegetation cover size and temporal growing rates in the park area in Ankara were determined by employing Remote Sensing Technology. The results were assessed using Kappa statistics. Green area detection accuracies from NDVI, SAVI and GVI were 71, 73 and 56\%, respectively. Additionally, the 1989 and 2006 green areas of Altinpark were compared with each other to see the temporal growth of green cover in the park area. Green cover change was detected to be 43.9 ha.},
  affiliation = {Department of Landscape Architecture, University of Cankiri Karatekin, Cankiri, Turkey; Department of Landscape Architecture, University of Yuzuncu Yil, Van, 65 080, Turkey; Department of Landscape Architecture, University of Ankara, Ankara, 06 110, Turkey; Department of Landscape Architecture, University of Namik Kemal, Tekirdag, 59 030, Turkey},
  author_keywords = {Monitoring; Remote sensing; Urban green cover; Vegetation indices},
  correspondence_address1 = {Bilgili, B.C.; Department of Landscape Architecture, University of Cankiri KaratekinTurkey},
  document_type = {Article},
  langid = {english},
  source = {Scopus}
}

@article{bosch2020,
  title = {{{DetecTree}}: {{Tree}} Detection from Aerial Imagery in {{Python}}},
  shorttitle = {{{DetecTree}}},
  author = {Bosch, Martí},
  date = {2020-06-25},
  journaltitle = {Journal of Open Source Software},
  volume = {5},
  number = {50},
  pages = {2172},
  issn = {2475-9066},
  doi = {10.21105/joss.02172},
  url = {https://joss.theoj.org/papers/10.21105/joss.02172},
  urldate = {2021-02-06},
  abstract = {Bosch, M., (2020). DetecTree: Tree detection from aerial imagery in Python. Journal of Open Source Software, 5(50), 2172, https://doi.org/10.21105/joss.02172},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\bosch_2020_detectree.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\73QMN2FC\\joss.html}
}

@article{branson2018,
  title = {From {{Google Maps}} to a Fine-Grained Catalog of Street Trees},
  author = {Branson, Steve and Wegner, Jan Dirk and Hall, David and Lang, Nico and Schindler, Konrad and Perona, Pietro},
  date = {2018-01},
  journaltitle = {ISPRS Journal of Photogrammetry and Remote Sensing},
  shortjournal = {ISPRS Journal of Photogrammetry and Remote Sensing},
  volume = {135},
  pages = {13--30},
  issn = {09242716},
  doi = {10.1016/j.isprsjprs.2017.11.008},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0924271617303453},
  urldate = {2021-01-11},
  abstract = {Up-to-date catalogs of the urban tree population are of importance for municipalities to monitor and improve quality of life in cities. Despite much research on automation of tree mapping, mainly relying on dedicated airborne LiDAR or hyperspectral campaigns, tree detection and species recognition is still mostly done manually in practice. We present a fully automated tree detection and species recognition pipeline that can process thousands of trees within a few hours using publicly available aerial and street view images of Google MapsTM. These data provide rich information from different viewpoints and at different scales from global tree shapes to bark textures. Our work-flow is built around a supervised classification that automatically learns the most discriminative features from thousands of trees and corresponding, publicly available tree inventory data. In addition, we introduce a change tracker that recognizes changes of individual trees at city-scale, which is essential to keep an urban tree inventory up-todate. The system takes street-level images of the same tree location at two different times and classifies the type of change (e.g., tree has been removed). Drawing on recent advances in computer vision and machine learning, we apply convolutional neural networks (CNN) for all classification tasks. We propose the following pipeline: download all available panoramas and overhead images of an area of interest, detect trees per image and combine multi-view detections in a probabilistic framework, adding prior knowledge; recognize fine-grained species of detected trees. In a later, separate module, track trees over time, detect significant changes and classify the type of change. We believe this is the first work to exploit publicly available image data for city-scale street tree detection, species recognition and change tracking, exhaustively over several square kilometers, respectively many thousands of trees. Experiments in the city of Pasadena, California, USA show that we can detect {$>$}70\% of the street trees, assign correct species to {$>$}80\% for 40 different species, and correctly detect and classify changes in {$>$}90\% of the cases.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\branson_et_al_2018_from_google_maps_to_a_fine-grained_catalog_of_street_trees.pdf}
}

@report{brune2016,
  title = {Urban Trees under Climate Change. {{Potential}} Impacts of Dry Spells and Heat Waves in Three {{German}} Regions in the 2050s},
  author = {Brune, M},
  date = {2016},
  number = {Report 24},
  institution = {{Climate Service Center Germany}},
  location = {{Hamburg}},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\436N2SAS\\Brune - Publication date May 2016.pdf}
}

@article{bryk2019,
  title = {Monitoring Heterogeneous Urban and Rural Area Using {{Normalised Difference Infrared Index}}–a Case Study from {{SE Poland}}},
  author = {Bryk, M. and Kołodziej, B.},
  date = {2019},
  journaltitle = {European Journal of Remote Sensing},
  volume = {52},
  number = {1},
  pages = {308--321},
  publisher = {{Taylor and Francis Ltd.}},
  issn = {11298596},
  doi = {10.1080/22797254.2019.1604080},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064560352&doi=10.1080%2f22797254.2019.1604080&partnerID=40&md5=c98293d6d721a28d0a0d41bb2ca8f6ae},
  abbrev_source_title = {European J. Remote Sens.},
  abstract = {The results of a study of NDII applicability for monitoring of a heterogeneous rural and urban area during a growing season (April–November) were shown. We evaluated the spatial and quantitative distributions, and temporal trends of NDII derived from Landsat 8 imagery, NDII = (NIR–SWIR)/(NIR+SWIR) or NDII = (Band5–Band6)/(Band5+Band6), over a typical medium-sized European city with its surroundings. The temporal changes of NDII were also correlated with sunshine duration, temperature, and precipitation. Vegetation was the component of land cover that was changing to the highest degree during the growing season. The most dynamic temporal alterations of NDII were recorded within the arable land. In forest areas and grassland NDII was relatively stable through the summer. The NDII values were stable also in the built-up area in view of practically constant state of human-made covers in the studied period. NDII can support the monitoring of land cover/land use in the urban and rural areas, provided that the images of fully developed plant cover are used. It was stated that NDII correlated with weather conditions. The relationships between NDII and precipitation, temperature, and sunshine duration could facilitate risk assessment and planning of agronomic practices with regard to the weather. © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor \& Francis Group.},
  affiliation = {Institute of Soil Science, Environment Engineering and Management, University of Life Sciences in Lublin, Lublin, Poland},
  author_keywords = {arable land; forest; grassland; Landsat satellite imagery; NDII; weather conditions},
  correspondence_address1 = {Kołodziej, B.; Institute of Soil Science, Environment Engineering and Management, University of Life Sciences in Lublin, Leszczyńskiego 7, Poland; email: beata.kolodziej@up.lublin.pl},
  document_type = {Article},
  langid = {english},
  source = {Scopus},
  keywords = {agricultural land,Arable land,climate conditions,environmental monitoring,forest,Forestry,grassland,growing season,Infrared devices,Infrared radiation,Land use,Landsat,Landsat satellite,Meteorology,NDII,NDVI,Poland [Central Europe],Risk assessment,rural area,Rural areas,satellite imagery,Satellite imagery,summer,urban area,Urban planning,vegetation index}
}

@article{Bühler20063,
  title = {Growth and Phenology of Established {{Tilia}} Cordata Street Trees in Response to Different Irrigation Regimes},
  author = {Bühler, O. and Nielsen, C.N. and Kristoffersen, P.},
  date = {2006},
  journaltitle = {Arboriculture and Urban Forestry},
  volume = {32},
  number = {1},
  pages = {3--9},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33745047110&partnerID=40&md5=e25c8ac09c54b034bb45ec23a712a955},
  abstract = {The effect of different irrigation regimes on growth and phenology of 100 established Tilia cordata street trees was investigated during the growth period of 2004. Relative stem increment increased significantly when irrigating with 280, 320, or 640 L (74, 84.5, and 169 gal) of water throughout the growth period. The length of the growth period was affected by irrigation regimes in regard to termination of growth, as the trees receiving 640 L (169 gal) had a growth period significantly longer than the control trees. These results indicate that growth and growth period of street trees are augmented by an increase in the amount of water available to them. In addition, block effects concerning the start of the growth period were observed, as trees situated on the northern side of the street initiated stem growth 7 days earlier than the trees on the southern side. © 2006 International Society of Arboriculture.},
  affiliation = {Division of Parks and Urban Landscapes, Danish Centre for Forest and Landscape Planning-KVL, Royal Veterinary and Agricultural University, Rolighedsvej 23, DK-1958 Frederiksberg C, Denmark},
  author_keywords = {Irrigation; Phenology; Stem growth; Street trees; Tilia cordata; Tree management; Urban climate; Water balance},
  document_type = {Article},
  source = {Scopus}
}

@article{bussotti2014,
  title = {Ecophysiology of Urban Trees in a Perspective of Climate Change.},
  author = {Bussotti, F. and Pollastrini, M. and Killi, D. and Ferrini, F. and Fini, A.},
  date = {2014},
  journaltitle = {Agrochimica},
  volume = {58},
  number = {3},
  pages = {247--268},
  publisher = {{Università degli Studi di Pisa}},
  issn = {0002-1857},
  url = {https://www.cabdirect.org/cabdirect/abstract/20153144491},
  urldate = {2020-04-06},
  abstract = {The current ecological condition of cities in respect to the surrounding countryside (higher temperatures and CO2 levels, drought, photochemical pressure and particulate matter pollutants), may anticipate the effects of climate change at a broader scale. However, the condition of urban trees can be exacerbated by some specific factors within cities, such as mismanagement and the direct impact of...},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\ecophysiology_of_urban_trees_in_a_perspective_of_climate_change.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\BH63X5L7\\20153144491.html;C\:\\Users\\ahurl\\Zotero\\storage\\ZTVU7DP9\\www.cabdirect.org.html}
}

@article{buters2020,
  title = {Automatisches {{Pollenmonitoring}} in {{Deutschland}}},
  author = {Buters, Jeroen and Oteros, Jose and Gebauer, Robert and Heigl, Katharina},
  date = {2020},
  journaltitle = {Allergo Journal},
  shortjournal = {Allergo J},
  volume = {29},
  number = {3},
  eprint = {32362726},
  eprinttype = {pmid},
  pages = {14--16},
  issn = {0941-8849},
  doi = {10.1007/s15007-020-2527-0},
  url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189004/},
  urldate = {2021-06-15},
  pmcid = {PMC7189004},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\buters_et_al_2020_automatisches_pollenmonitoring_in_deutschland.pdf}
}

@article{buyantuyev2012,
  title = {A Space-for-Time ({{SFT}}) Substitution Approach to Studying Historical Phenological Changes in Urban Environment},
  author = {Buyantuyev, A. and Xu, P. and Wu, J. and Piao, S. and Wang, D.},
  date = {2012},
  journaltitle = {PLoS ONE},
  volume = {7},
  number = {12},
  issn = {19326203},
  doi = {10.1371/journal.pone.0051260},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870925298&doi=10.1371%2fjournal.pone.0051260&partnerID=40&md5=6c0939178c005ea8e7720535200e8dba},
  abbrev_source_title = {PLoS ONE},
  abstract = {Plant phenological records are crucial for predicting plant responses to global warming. However, many historical records are either short or replete with data gaps, which pose limitations and may lead to erroneous conclusions about the direction and magnitude of change. In addition to uninterrupted monitoring, missing observations may be substituted via modeling, experimentation, or gradient analysis. Here we have developed a space-for-time (SFT) substitution method that uses spatial phenology and temperature data to fill gaps in historical records. To do this, we combined historical data for several tree species from a single location with spatial data for the same species and used linear regression and Analysis of Covariance (ANCOVA) to build complementary spring phenology models and assess improvements achieved by the approach. SFT substitution allowed increasing the sample size and developing more robust phenology models for some of the species studied. Testing models with reduced historical data size revealed thresholds at which SFT improved historical trend estimation. We conclude that under certain circumstances both the robustness of models and accuracy of phenological trends can be enhanced although some limitations and assumptions still need to be resolved. There is considerable potential for exploring SFT analyses in phenology studies, especially those conducted in urban environments and those dealing with non-linearities in phenology modeling. © 2012 Buyantuyev et al.},
  affiliation = {Sino-US Center for Conservation, Energy, and Sustainability Science, Inner Mongolia University, Hohhot, China; School of Life Sciences, Inner Mongolia University, Hohhot, China; School of Life Sciences and Global Institute of Sustainability, Arizona State University, Tempe, AZ, United States},
  art_number = {e51260},
  correspondence_address1 = {Buyantuyev, A.; Sino-US Center for Conservation, Energy, and Sustainability Science, Inner Mongolia University, Hohhot, China; email: abuyantu@gmail.com},
  document_type = {Article},
  langid = {english},
  pubmed_id = {23236460},
  source = {Scopus},
  keywords = {20th Century,analysis of covariance,Analysis of Variance,article,Biological,China,Cities,Climate Change,controlled study,Demography,environmental change,environmental temperature,History,Linear Models,linear regression analysis,Models,nonhuman,phenology,sample size,Seasons,space for time substitution,Species Specificity,statistical analysis,statistical model,Temperature,tree,Trees,urban area}
}

@article{Buyantuyev2012149,
  title = {Urbanization Diversifies Land Surface Phenology in Arid Environments: {{Interactions}} among Vegetation, Climatic Variation, and Land Use Pattern in the {{Phoenix}} Metropolitan Region, {{USA}}},
  author = {Buyantuyev, A. and Wu, J.},
  date = {2012},
  journaltitle = {Landscape and Urban Planning},
  volume = {105},
  number = {1-2},
  pages = {149--159},
  doi = {10.1016/j.landurbplan.2011.12.013},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857442785&doi=10.1016%2fj.landurbplan.2011.12.013&partnerID=40&md5=32c302652658ebea8ab97e1b518d4d42},
  abstract = {Urbanization transforms vegetation pattern and ecosystem processes which are controlled primarily by climate in desert regions. The objective of this study was to investigate how urbanization affects vegetation phenology and its coupling with climate in the Phoenix metropolitan region, USA. Our analysis of Normalized Difference Vegetation Index (NDVI) time-series reveals a complex pattern of land surface phenology in response to urbanization. Croplands and urbanized areas show growth multimodality, which is usually found in riparian areas of the region but absent in the native desert. Agriculture is characterized by the shortest growth length and fastest greening and senescing rates. Conversely, urban vegetation stays photosynthetically active for longer periods. Desert NDVI is regulated by 3-5 month accumulated precipitation, but riparian vegetation is uncorrelated with rainfall. NDVI spatial patterns are best predicted by climatic variables near the peak of annual growth. Spring and summer NDVI is in better agreement with precipitation accumulated over longer time periods, while early autumn growth is strongly correlated with immediate and one-month rainfall. Temperature correlates negatively with desert but positively with riparian NDVI. Managed vegetation growth is decoupled from precipitation and completely unsynchronized with natural desert vegetation. Overall, urbanization has resulted in a greater phenological diversity that is not in sync with climatic variability. Our findings provide new insights into the interactions among vegetation growth, climate variability, and urbanization in dry lands. © 2011 Elsevier B.V.},
  affiliation = {School of Life Sciences and Global Institute of Sustainability, Arizona State University, P.O. Box 874501, Tempe, AZ 85287-4501, United States; Sino-US Center for Conservation, Energy, and Sustainability Science (SUCCESS), Inner Mongolia University, Hohhot 010021, China},
  author_keywords = {Land surface phenology; MODIS NDVI; Remote sensing; Sonoran desert; Urban-rural gradient; Vegetation phenology},
  document_type = {Article},
  source = {Scopus}
}

@article{bzdega2021,
  title = {Geostatistical Models with the Use of Hyperspectral Data and Seasonal Variation – {{A}} New Approach for Evaluating the Risk Posed by Invasive Plants},
  author = {Bzdęga, K. and Zarychta, A. and Urbisz, A. and Szporak-Wasilewska, S. and Ludynia, M. and Fojcik, B. and Tokarska-Guzik, B.},
  date = {2021},
  journaltitle = {Ecological Indicators},
  volume = {121},
  publisher = {{Elsevier B.V.}},
  issn = {1470160X},
  doi = {10.1016/j.ecolind.2020.107204},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097586350&doi=10.1016%2fj.ecolind.2020.107204&partnerID=40&md5=d94836fea21a30c97a86f9a1e40534b8},
  abstract = {The general trend of ongoing plant invasion and the increasing number of species that may become invasive in the future, force seeking solutions that can improve the efficiency and economy of their management. Thus, we applied a novel approach combining the use of geostatistical interpolators such as ordinary kriging (OK) and co-kriging (CK) with environmental and hyperspectral data to evaluate the potential threat associated with the distribution of invasive plant species and to predict their probabilities of occurrence above the selected threshold of 10\%. The specific spatial patterns of the probability of occurrence of Heracleum sosnowskyi and Fallopia spp. were modelled in two study areas in southern Poland. The significant achievement of this study was the application of geostatistical tools producing results characterized by a degree of precision quantified by cross-validation errors, and prediction errors after field verification. OK and CK returned root mean squared error (RMSE) values in a range from 0.21 to 0.51 and 0.21 to 0.47, respectively. For OK and CK, the prediction errors resulting from field verification in the following year were between 0.03–0.39, and 0.03–0.29, respectively. Additionally, the study provided the first prediction maps (2D) and Digital Prediction Models (DPMs) (3D) visualizations of the probability of occurrence of both invasive plants. Although the proposed approach is illustrated with real case studies related to Heracleum sosnowskyi and Fallopia spp., it could be extended to other species. This demonstrates the potential of an effective alternative strategy for evaluating the risk posed by invasive plants, that will be able to provide fast, low cost and effective prediction and monitoring of their spread. For institutions dealing with invasive plants, this may be beneficial and help to reduce the negative consequences of their improper management. © 2020 University of Silesia},
  langid = {english},
  keywords = {Cross validation errors,Degree of precision,Efficiency and economies,Errors,Fallopia,Field verifications,Forecasting,Geostatistical models,Geostatistical tools,geostatistics,Heracleum,Interpolation,invasive species,kriging,Mean square error,numerical model,Poland [Central Europe],Predictive analytics,Probability distributions,Probability of occurrence,risk assessment,Root mean squared errors,seasonal variation,spectral analysis,Three dimensional computer graphics}
}

@article{cai2014,
  title = {Research advances in plant phenological responses to urban heat island},
  author = {Cai, H.-Y. and Yang, X.-H. and Zhang, S.-W.},
  date = {2014},
  journaltitle = {Chinese Journal of Ecology},
  volume = {33},
  number = {1},
  pages = {221--228},
  publisher = {{editorial Board of Chinese Journal of Ecology}},
  issn = {10004890},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84939129696&partnerID=40&md5=23733b9079f117c71b3e52ad4d528e6f},
  abbrev_source_title = {Chinese J. Ecol.},
  abstract = {Local microclimate changes caused by urban heat island (UHI) have increasingly impacted the patterns, processes and functions of ecosystems. Plant phenology is a sensitive and easily observed biological indicator to detect these impacts, and its responses to UHI have become hotspots in the fields of urban ecology and global climate change. This paper reviewed related researches in recent years. It points out that there are three major ways to obtain urban phenology, that is, field observation, phenology modeling and remote sensing monitoring. Through cooperating with the public and employing photos and multi-resolution images, we can enrich the phenology data. Due to the impacts of UHI, spring phenology in urban area has been earlier than the surrounding rural area; however, the impact mechanism is still controversial. At temporal scale, spring phenology has advanced and autumn phenology has delayed induced by urban warming. Urban warming is caused by UHI and climate warming, and how to quantitatively discern their contributions is difficult. In addition, biological factors (e. g. plant functional types and exotic plants) and geographical location have affected the plant phenological responses to UHI. Thus, this paper proposes that future researches need to eliminate the interference factors, and enhance the researches in response mechanisms. © 2014, Editorial Board of Chinese Journal of Ecology. All rights reserved.},
  affiliation = {State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China},
  author_keywords = {Phenological models; Plant phenology; Remote sensing; Urban heat island effect},
  coden = {SZAZE},
  correspondence_address1 = {Cai, H.-Y.; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesChina; email: yangxh@igsnrr.ac.cn},
  document_type = {Article},
  funding_details = {National Natural Science Foundation of ChinaNational Natural Science Foundation of China, NSFC, 41301155},
  langid = {chinese},
  source = {Scopus},
  keywords = {climate change,climate modeling,global warming,heat island,image resolution,microclimate,phenology,plant,remote sensing,urban area}
}

@article{cao,
  title = {Automated {{Pollen Detection}} with an {{Affordable Technology}}†},
  author = {Cao, Matthias Meyer Nam},
  pages = {12},
  abstract = {Airborne pollen cause seasonal allergies and the number of people affected increases yearly due to global warming and urbanization. Governmental pollen sensing stations are sampling traps which require manual pollen identification and counting by trained personnel in the lab. In the past years, a number of researchers and startups started working towards automated pollen measurements by exploring a wide range of techniques. Many solutions reported in the literature are expensive or work for a limited number of pollen species. In this paper, we present the design of a prototype of an automated and affordable pollen detection device built from off-the-shelf components. The design consists of three subsystems operating in the field and communicating the data to the backend server: (1) a particle trap with automatic filtering, (2) a particle concentration subsystem, and (3) a digital transmitted light microscope with layer-wise focus. The prototype shows effective particle gathering, filtering and concentration in a tiny-sized area. As a result, we reduce particle loss and improve image quality taken by the optical system when searching and focusing on pollen grains. The test results show that our device achieves high efficiency with up to 150 l/min air flow rates, evaluates over 90 \% of captured pollen grains, and achieves 1 h measurement delay on average (2 h at maximum). The prototype collects raw time-stamped microscopic images of pollen with 5-60 depth layers per sample depending on the number of objects contained in one sample. All images are transmitted to the backend server where we run a pollen detection algorithm to extract individual pollen grains from every image. We achieve 0.90 average precision and F1-score of 0.88 when detecting pollen in the images of individual layers taken in the field. Our prototype successfully operated in the wild for 115 days between April and August 2019, and shows high stability under a wide range of varying weather conditions, little maintenance need and low device-to-device variation.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\9EA3L687\\Cao - Automated Pollen Detection with an Affordable Tech.pdf}
}

@article{cao2021,
  title = {Within-City Spatial and Temporal Heterogeneity of Air Temperature and Its Relationship with Land Surface Temperature},
  author = {Cao, J. and Zhou, W. and Zheng, Z. and Ren, T. and Wang, W.},
  date = {2021},
  journaltitle = {Landscape and Urban Planning},
  volume = {206},
  publisher = {{Elsevier B.V.}},
  issn = {01692046},
  doi = {10.1016/j.landurbplan.2020.103979},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095710527&doi=10.1016%2fj.landurbplan.2020.103979&partnerID=40&md5=fc5e233bc04d1f3245daace92f529532},
  abstract = {Using land surface temperatures (LST) derived from remotely sensed data, numerous studies have shown that not only urban areas are warmer than surrounding rural areas, but within urban areas, there are large spatial variations in temperature. Few studies, however, have investigated the spatial variation of air temperature within a city. Using air temperature data collected from 117 weather stations in Shenzhen for the year of 2017, we quantified the within-city spatial pattern of air temperature and its nocturnal and seasonal variability. We further investigated the quantitative relationship between air temperature and LST and compared their spatiotemporal patterns. We found that: 1) Air temperature varied greatly in space, showing very strong spatial heterogeneity and having large nocturnal and seasonal variability; 2) The spatial and temporal variation is more prominent during extreme heat days, during which the difference of hourly maximum temperature among stations could reach 8.7 °C around 16:00 and remain as high as 8.6 °C until 23:00, indicating that locations in cities with higher temperatures may suffer more intensive and longer excessive urban heat, and thereby global warming may exacerbate the difference in air temperature at the local scale; 3) LST had significantly positive correlations with air temperature, especially in the summer night, but their cool and hot spots did not always overlap in space. Results can enhance understanding of the spatial heterogeneity of the urban thermal environment and have practical implications on excessive urban heat mitigation and adaptation in an increasingly warming global climate. © 2020 Elsevier B.V.},
  langid = {english},
  keywords = {adaptive management,air temperature,China,global warming,Guangdong,heat island,heterogeneity,land surface,seasonal variation,Shenzhen,spatial analysis,spatial variation,temporal variation}
}

@article{caoa,
  title = {Automated {{Pollen Detection}} with an {{Affordable Technology}}†},
  author = {Cao, Matthias Meyer Nam},
  pages = {12},
  abstract = {Airborne pollen cause seasonal allergies and the number of people affected increases yearly due to global warming and urbanization. Governmental pollen sensing stations are sampling traps which require manual pollen identification and counting by trained personnel in the lab. In the past years, a number of researchers and startups started working towards automated pollen measurements by exploring a wide range of techniques. Many solutions reported in the literature are expensive or work for a limited number of pollen species. In this paper, we present the design of a prototype of an automated and affordable pollen detection device built from off-the-shelf components. The design consists of three subsystems operating in the field and communicating the data to the backend server: (1) a particle trap with automatic filtering, (2) a particle concentration subsystem, and (3) a digital transmitted light microscope with layer-wise focus. The prototype shows effective particle gathering, filtering and concentration in a tiny-sized area. As a result, we reduce particle loss and improve image quality taken by the optical system when searching and focusing on pollen grains. The test results show that our device achieves high efficiency with up to 150 l/min air flow rates, evaluates over 90 \% of captured pollen grains, and achieves 1 h measurement delay on average (2 h at maximum). The prototype collects raw time-stamped microscopic images of pollen with 5-60 depth layers per sample depending on the number of objects contained in one sample. All images are transmitted to the backend server where we run a pollen detection algorithm to extract individual pollen grains from every image. We achieve 0.90 average precision and F1-score of 0.88 when detecting pollen in the images of individual layers taken in the field. Our prototype successfully operated in the wild for 115 days between April and August 2019, and shows high stability under a wide range of varying weather conditions, little maintenance need and low device-to-device variation.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\Z4XYIXER\\Cao - Automated Pollen Detection with an Affordable Tech.pdf}
}

@article{carinanos2020,
  title = {Assessing Pollination Disservices of Urban Street-Trees: {{The}} Case of {{London-plane}} Tree ({{Platanus}} x Hispanica {{Mill}}. Ex {{Münchh}})},
  shorttitle = {Assessing Pollination Disservices of Urban Street-Trees},
  author = {Cariñanos, Paloma and Ruiz-Peñuela, Soledad and Valle, Ana M. and de la Guardia, Consuelo Díaz},
  options = {useprefix=true},
  date = {2020-10},
  journaltitle = {Science of The Total Environment},
  shortjournal = {Science of The Total Environment},
  volume = {737},
  pages = {139722},
  issn = {00489697},
  doi = {10.1016/j.scitotenv.2020.139722},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0048969720332423},
  urldate = {2021-06-07},
  abstract = {Platanusx hispanica (London plane) is a tree species widely used in urban areas due to the diversity of ecosystem services it provides. However, its functions also have some negative effects or associated disservices, such as the emission of Biogenic Volatile Organic Compounds (BVOCs) and allergens. This work aims to analyze the effect that urban environmental conditions and air pollutants have on pollen emissions of plane tree. The study has been carried out in Granada, in the southeast of the Iberian Peninsula, a city with a Mediterranean climate and one of the most polluted in Spain. Granada is also one of the Mediterranean cities in which the increase in the percentage of the population affected by allergy to Platanus pollen in recent decades has been most significant. The 1992–2019 Platanus pollen data series has been considered to establish the main aerobiological parameters, trends and correlations with meteorological variables and particulate and gaseous atmospheric pollutants, both before and during the flowering period. The average Seasonal Pollen Integral (SPIn) of about 2700 pollen grains has shown a significant increase throughout the series. This increase in allergen emissions could be related to the increase in crown volume associated with tree growth, but also to other environmental factors. Precipitation and minimum temperatures of the winter prior to flowering were the parameters that have shown the most influence with SPIn, while O3 and NOx are the pollutants that have the most effect on the peak value. Due to the good adaptation that London plane has to changing climatic conditions in urban environments, its hegemonic presence as an element of Urban Green infrastructure must be reviewed so that the net balance of ecosystem services is not diminished by the disservices.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\LYYH5IQ3\\Cariñanos et al. - 2020 - Assessing pollination disservices of urban street-.pdf}
}

@article{Chang20115035,
  title = {Assessing Growing Season Beginning and End Dates and Their Relation to Climate in {{Taiwan}} Using Satellite Data},
  author = {Chang, C.-T. and Lin, T.-C. and Wang, S.-F. and Vadeboncoeur, M.A.},
  date = {2011},
  journaltitle = {International Journal of Remote Sensing},
  volume = {32},
  number = {18},
  pages = {5035--5058},
  doi = {10.1080/01431161.2010.494635},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80053110990&doi=10.1080%2f01431161.2010.494635&partnerID=40&md5=808a663c157798e6914e0e29c641fdf1},
  abstract = {Due to the close relationship between climate and plant phenology, changes in plant phenological patterns have been used as a surrogate of climate change. We analysed Moderate Resolution Imaging Spectroradiometer (MODIS) images to investigate the onset, offset and length of growing season, as well as spatial and inter-annual patterns of Normalized Difference Vegetation Index (NDVI) across six types of vegetation/land use in Taiwan. Regression models indicate that temperature was moderately to strongly related to NDVI for each of the six vegetation/ land-use types (coefficients of determination (R2) = 0.45-0.86). There was a 1-2 month lag time between changes in temperature and NDVI in the forests that are distributed in mid- to high-elevation areas, but not in low-elevation unirrigated fields, paddy fields and urban areas. The relationship between precipitation and changes in NDVI was only significant for unirrigated fields and urban areas (R2 = 0.37-0.43). Growing season ended considerably earlier at low elevations than at high elevations, possibly because of the earlier start and more severe dry period in low-elevation areas, such that the length of the growing season was longer in the forests than in the unirrigated fields, paddy fields and urban areas. © 2011 Taylor \& Francis.},
  affiliation = {Department of Life Science, National Taiwan Normal University, 88 Ting-Chow Road, Section 4, Taipei, 11677, Taiwan; Department of Geography, National Changhua University of Education, 1 Jin-Te Road, Changhua, 50007, Taiwan; Complex Systems Research Center, University of New Hampshire, 8 College Road, Durham, NH 03824, United States},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\chang_et_al_2011_assessing_growing_season_beginning_and_end_dates_and_their_relation_to_climate.pdf}
}

@article{chang2021,
  title = {Exploring Diurnal Cycles of Surface Urban Heat Island Intensity in {{Boston}} with Land Surface Temperature Data Derived from {{GOES-R}} Geostationary Satellites},
  author = {Chang, Y. and Xiao, J. and Li, X. and Frolking, S. and Zhou, D. and Schneider, A. and Weng, Q. and Yu, P. and Wang, X. and Li, X. and Liu, S. and Wu, Y.},
  date = {2021},
  journaltitle = {Science of the Total Environment},
  volume = {763},
  publisher = {{Elsevier B.V.}},
  issn = {00489697},
  doi = {10.1016/j.scitotenv.2020.144224},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098561333&doi=10.1016%2fj.scitotenv.2020.144224&partnerID=40&md5=b80eae2f1c66dfc0908a818891da097a},
  abstract = {The surface urban heat island (SUHI) is one of the most significant human-induced alterations to the Earth's surface climate and can aggravate health risks for city dwellers during heat waves. Although the SUHI effect has received growing attention, its diurnal cycles (i.e., the variations over the full 24 h within the diel cycle) are poorly understood because polar-orbiting satellites (e.g., Landsat Series, Sentinel, Terra, Aqua) only provide one or two observations over each repeat cycle (e.g., 16 days) with constant overpass time for the same area. Geostationary satellites provide high-frequency land surface temperature (LST) observations throughout the day and the night, and thereby offer unprecedented opportunities for exploring the diurnal cycles of SUHI. Here we examined how the SUHI intensity varied over the course of the diurnal cycle in the Boston Metropolitan Area using LST observations from the NOAA's latest generation of Geostationary Operational Environmental Satellites (GOES-R). GOES-R LST was strongly correlated with MODIS LST (R2 = 0.98, p \< 0.0001) across urban core, suburban, and rural areas. We calculated the SUHI intensity at an hourly time step for both the urban core and suburban areas using GOES-R LST data. The maximum SUHI intensity for the urban core occurred near noon, and was +3.0 °C (12:00), +5.4 °C (12:00), +4.9 °C (11:00), and +3.7 °C (12:00) in winter, spring, summer, and autumn, respectively. The maximum intensity for the suburban area was about 3.0 °C lower in spring and summer and 2.0 °C lower in autumn and winter than that of the urban-core area. The minimum SUHI intensity occurred at nighttime, and ranged from −1.0 °C to +1.0 °C. The difference in the nighttime SUHI intensity between urban core and suburban area was insignificant for all seasons except the summer. The SUHI intensity showed similar diurnal variations across the seasons. Throughout the year, the maximum SUHI intensity (+2.7–+5.8 °C) at the urban core occurred at 11:00–14:00 (local time), while the minimum SUHI intensity (−0.6–+0.9 °C) was commonly observed at 00:00–07:00 and 17:00–23:00. We also found different relationships between SUHI intensity and potential drivers within a diurnal cycle, characterized by the strongest correlation with impervious surface area and population size during the middle of the day, and with tree canopy cover at night. Our research highlights the great potential of the new-generation geostationary satellites in revealing the detailed diurnal variations of SUHI. Our findings have implications for informing urban planning and public health risk management. © 2020 Elsevier B.V.},
  langid = {english},
  keywords = {article,Atmospheric temperature,autumn,canopy,circadian rhythm,city planning,diurnal activity,Geostationary operational environmental satellites,Geostationary satellites,GOES,Health risks,heat,heat island,High frequency HF,human,Impervious surface area,Land surface temperature,Landforms,Massachusetts,Maximum intensities,Metropolitan area,MODIS,Orbits,Polar-orbiting satellites,population size,Population statistics,public health,remote sensing,risk management,Risk management,rural area,Satellites,spring,suburban area,summer,surface area,surface flux,Surface measurement,Surface properties,Surface urban heat islands,temperature anomaly,Tree canopy covers,Urban planning,Weather satellites,winter}
}

@article{charalampopoulos2018,
  title = {Quantifying the Relationship between Airborne Pollen and Vegetation in the Urban Environment},
  author = {Charalampopoulos, Athanasios and Lazarina, Maria and Tsiripidis, Ioannis and Vokou, Despoina},
  date = {2018-09-01},
  journaltitle = {Aerobiologia},
  shortjournal = {Aerobiologia},
  volume = {34},
  number = {3},
  pages = {285--300},
  issn = {1573-3025},
  doi = {10.1007/s10453-018-9513-y},
  url = {https://doi.org/10.1007/s10453-018-9513-y},
  urldate = {2021-06-07},
  abstract = {The goal of this study was to quantitatively assess the relationship linking vegetation and airborne pollen. For this, we established six sampling stations in the city of Thessaloniki, Greece. Once every week for 2~years, we recorded airborne pollen in them, at breast height, by use of a portable volumetric sampler. We also made a detailed analysis of the vegetation in each station by counting all existing individuals of the woody species contributing pollen to the air, in five zones of increasing size, from 4 to 40~ha. We found the local vegetation to be the driver of the spatial variation of pollen in the air of the city. Even at very neighbouring stations, only 500~m apart, considerable differences in vegetation composition were expressed in the pollen spectrum. We modelled the pollen concentration of each pollen taxon as a function of the abundance of the woody species corresponding to that taxon by use of a Generalized Linear Model. The relationship was significant for the five most abundantly represented taxa in the pollen spectrum of the city. It is estimated that every additional individual of Cupressaceae, Pinaceae, Platanus, Ulmus and Olea increases pollen in the air by approximately 0.7, 0.2, 2, 6 and 5\%, respectively. Whether the relationships detected for the above pollen taxa hold outside the domain for which we have data, as well as under different environmental conditions and/or with different assemblages of species representing them are issues to be explored in the future.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\charalampopoulos_et_al_2018_quantifying_the_relationship_between_airborne_pollen_and_vegetation_in_the.pdf}
}

@article{chen2014,
  title = {{{RGB-NIR}} Multispectral Camera},
  author = {Chen, Zhenyue and Wang, Xia and Liang, Rongguang},
  date = {2014-03-10},
  journaltitle = {Optics Express},
  shortjournal = {Opt. Express, OE},
  volume = {22},
  number = {5},
  pages = {4985--4994},
  publisher = {{Optical Society of America}},
  issn = {1094-4087},
  doi = {10.1364/OE.22.004985},
  url = {https://www.osapublishing.org/oe/abstract.cfm?uri=oe-22-5-4985},
  urldate = {2021-07-01},
  abstract = {A multispectral imaging technique with a new CMOS camera is proposed. With a four channel Bayer patterns, the camera can acquire four spectral images simultaneously. We have developed a color correction process to obtain accurate color information, and we have also demonstrated its applications on portrait enhancement, shadow removal, and vein enhancement.},
  langid = {english},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\chen_et_al_2014_rgb-nir_multispectral_camera.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\ZGB2ERHE\\fulltext.html}
}

@inproceedings{chen2019,
  title = {Real {{Time Object Detection}}, {{Tracking}}, and {{Distance}} and {{Motion Estimation}} Based on {{Deep Learning}}: {{Application}} to {{Smart Mobility}}},
  shorttitle = {Real {{Time Object Detection}}, {{Tracking}}, and {{Distance}} and {{Motion Estimation}} Based on {{Deep Learning}}},
  booktitle = {2019 {{Eighth International Conference}} on {{Emerging Security Technologies}} ({{EST}})},
  author = {Chen, Z. and Khemmar, R. and Decoux, B. and Atahouet, A. and Ertaud, J.},
  date = {2019-07},
  pages = {1--6},
  issn = {2472-7601},
  doi = {10.1109/EST.2019.8806222},
  abstract = {In this paper, we will introduce our object detection, localization and tracking system for smart mobility applications like traffic road and railway environment. Firstly, an object detection and tracking approach was firstly carried out within two deep learning approaches: You Only Look Once (YOLO) V3 and Single Shot Detector (SSD). A comparison between the two methods allows us to identify their applicability in the traffic environment. Both the performances in road and in railway environments were evaluated. Secondly, object distance estimation based on Monodepth algorithm was developed. This model is trained on stereo images dataset but its inference uses monocular images. As the output data, we have a disparity map that we combine with the output of object detection. To validate our approach, we have tested two models with different backbones including VGG and ResNet used with two datasets: Cityscape and KITTI. As the last step of our approach, we have developed a new method-based SSD to analyse the behavior of pedestrian and vehicle by tracking their movements even in case of no detection on some images of a sequence. We have developed an algorithm based on the coordinates of the output bounding boxes of the SSD algorithm. The objective is to determine if the trajectory of a pedestrian or vehicle can lead to a dangerous situations. The whole of development is tested in real vehicle traffic conditions in Rouen city center, and with videos taken by embedded cameras along the Rouen tramway.},
  eventtitle = {2019 {{Eighth International Conference}} on {{Emerging Security Technologies}} ({{EST}})},
  keywords = {Automobiles,cameras,Cameras,deep learning,Deep learning,Deep Learning,Estimation,image matching,image sensors,image sequences,learning (artificial intelligence),method-based SSD,motion estimation,object detection,Object detection,Object Detection,object distance estimation,Pattern Recognition,Pedestrian Detection,railway environment,real time object detection,Real-time systems,road traffic,Sensors,smart mobility applications,SSD,stereo image processing,stereo images dataset,Tracking,tracking approach,traffic engineering computing,traffic environment,traffic road,YOLO V3},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\chen_et_al_2019_real_time_object_detection,_tracking,_and_distance_and_motion_estimation_based.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\YP7J3QSM\\8806222.html}
}

@article{chianucci2015,
  title = {Estimation of Leaf Area Index in Isolated Trees with Digital Photography and Its Application to Urban Forestry},
  author = {Chianucci, Francesco and Puletti, Nicola and Giacomello, Elena and Cutini, Andrea and Corona, Piermaria},
  date = {2015-01-01},
  journaltitle = {Urban Forestry \& Urban Greening},
  shortjournal = {Urban Forestry \& Urban Greening},
  volume = {14},
  number = {2},
  pages = {377--382},
  issn = {1618-8667},
  doi = {10.1016/j.ufug.2015.04.001},
  url = {http://www.sciencedirect.com/science/article/pii/S1618866715000412},
  urldate = {2021-01-26},
  abstract = {Accurate estimates of leaf area index (L) are strongly required for modelling ecophysiological processes within urban forests. The majority of methods available for estimating L is ideally applicable at stand scale and is therefore poorly suitable in urban settings, where trees are typically sparse and isolated. In addition, accurate measurements in urban settings are hindered by proximity of trees to infrastructure elements, which can strongly affect the accuracy of tree canopy analysis. In this study we tested whether digital photography can be used to obtain indirect estimate of L of isolated trees. The sampled species were Platanus orientalis, Liquidambar styraciflua and Juglans regia. Upward-facing photography was used to estimate gap fraction and foliage clumping from images collected in unobstructed (open areas) and obstructed (nearby buildings) settings; two image classification methods provided accurate estimates of gap fraction, based on comparison with measurements obtained from a high quality quantum sensor (LAI-2000). Leveled photography was used to characterize the leaf angle distribution of the examined tree species. L estimates obtained combining the two photographic methods agreed well with direct L measurements obtained from harvesting. We conclude that digital photography is suitable for estimating leaf area in isolated urban trees, due to its simple, fast and cost-effective procedures. Use of vegetation indices allows extending significantly the applicability of the photographic method in urban settings, including green roofs and vertical greenery systems.},
  langid = {english},
  keywords = {Image analysis,Leaf area index,Urban greening,Urban tree,Vegetation index},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\EM8VEFSA\\S1618866715000412.html}
}

@article{chianucci2020,
  title = {An Overview of in Situ Digital Canopy Photography in Forestry},
  author = {Chianucci, F.},
  date = {2020},
  journaltitle = {Canadian Journal of Forest Research},
  volume = {50},
  number = {3},
  pages = {227--242},
  publisher = {{Canadian Science Publishing}},
  issn = {00455067},
  doi = {10.1139/cjfr-2019-0055},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080024664&doi=10.1139%2fcjfr-2019-0055&partnerID=40&md5=77bb5d6efde20c1dd34a18bbb6a2491b},
  abbrev_source_title = {Can. J. For. Res.},
  abstract = {Since the 1960s, canopy photography has been widely used in forestry. Hemispherical photography has been the most widely used technique, but a great drawback of this method is its perceived sensitivity to hemispherical image acquisition and processing. Over the last decade, several alternative photographic approaches using restricted view angle have been proposed. Cover photography acquired via a normal lens was the first of the recently introduced photographic techniques. Use of a restricted view (often fixed) lens has subsequently contributed to the extension of canopy photography to new sensors and platforms, which ultimately have provided answers to some previous challenges regarding within-crown clumping correction, isolated and urban tree measurements, understory assessment, operational leaf inclination angle measurements, and phenological monitoring. This study provides a comprehensive review of the use of canopy photography in forestry and describes the theory and definitions of the variables used to quantify canopy structure. A case study is presented to illustrate and compare the different features and performance of the existing overstory photographic techniques; the results make it possible to suggest sampling strategies for consistent overstory canopy photographic measurements. Emerging operational fields of canopy photography are also described and discussed. © 2020, Canadian Science Publishing. All rights reserved.},
  affiliation = {CREA – Research Centre for Forestry and Wood, viale S. Margherita 80, Arezzo, Italy},
  author_keywords = {Canopy cover; Canopy openness; Canopy photography; Hemispherical sensors; Leaf area index; Restricted view angle sensors},
  coden = {CJFRA},
  correspondence_address1 = {Chianucci, F.; CREA – Research Centre for Forestry and Wood, viale S. Margherita 80, Italy; email: francesco.chianucci@crea.gov.it},
  document_type = {Review},
  funding_details = {Regione LombardiaRegione Lombardia},
  funding_text_1 = {I am indebted to Craig Macfarlane, who kindly shared his routines for image analysis and processing. I am grateful to the anonymous referees and editor, who helped to improve the manuscript with their comments. This study has been financially supported by the research project PRECISIONPOP (Sistema di monitoraggio multi-scalare a supporto della pioppicoltura di precisione nella Regione Lombardia) funded by the Lombardy Region.},
  langid = {english},
  source = {Scopus},
  keywords = {canopy architecture,Canopy cover,Canopy openness,canopy reflectance,Coverings,digital photogrammetry,Fixed platforms,Forestry,Hemispherical photography,leaf area index,Leaf Area Index,Monitoring,overstory,Performance,phenology,Photographic measurements,Photographic techniques,photography,Photography,Sampling strategies,satellite sensor,Slope,Techniques,Timber,Trees,understory,View angles}
}

@article{Chianucci2020227,
  title = {An Overview of in Situ Digital Canopy Photography in Forestry},
  author = {Chianucci, F.},
  date = {2020},
  journaltitle = {Canadian Journal of Forest Research},
  volume = {50},
  number = {3},
  pages = {227--242},
  doi = {10.1139/cjfr-2019-0055},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080024664&doi=10.1139%2fcjfr-2019-0055&partnerID=40&md5=77bb5d6efde20c1dd34a18bbb6a2491b},
  abstract = {Since the 1960s, canopy photography has been widely used in forestry. Hemispherical photography has been the most widely used technique, but a great drawback of this method is its perceived sensitivity to hemispherical image acquisition and processing. Over the last decade, several alternative photographic approaches using restricted view angle have been proposed. Cover photography acquired via a normal lens was the first of the recently introduced photographic techniques. Use of a restricted view (often fixed) lens has subsequently contributed to the extension of canopy photography to new sensors and platforms, which ultimately have provided answers to some previous challenges regarding within-crown clumping correction, isolated and urban tree measurements, understory assessment, operational leaf inclination angle measurements, and phenological monitoring. This study provides a comprehensive review of the use of canopy photography in forestry and describes the theory and definitions of the variables used to quantify canopy structure. A case study is presented to illustrate and compare the different features and performance of the existing overstory photographic techniques; the results make it possible to suggest sampling strategies for consistent overstory canopy photographic measurements. Emerging operational fields of canopy photography are also described and discussed. © 2020, Canadian Science Publishing. All rights reserved.},
  affiliation = {CREA – Research Centre for Forestry and Wood, viale S. Margherita 80, Arezzo, Italy},
  author_keywords = {Canopy cover; Canopy openness; Canopy photography; Hemispherical sensors; Leaf area index; Restricted view angle sensors},
  document_type = {Review},
  source = {Scopus}
}

@inproceedings{Choi20112286,
  title = {Effect of Green Spaces on Urban Heat Distribution Using Satellite Imagery},
  author = {Choi, H. and Lee, W.-K.},
  date = {2011},
  series = {32nd {{Asian Conference}} on {{Remote Sensing}} 2011, {{ACRS}} 2011},
  volume = {4},
  pages = {2286--2289},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865684893&partnerID=40&md5=7f22062b74a1373951f86ef733b741a0},
  abstract = {Urbanization has transformed the spatial pattern of urban land use by reducing green spaces. An increase of air temperature directly affects forest vegetation, phenology, and biodiversity in urban areas. In this paper, we analyzed the characterization of changing patterns and Urban Heat Distribution (UHD) in Seoul, based on a spatio-temporal assessment. It is necessary to understand green spaces changes, and this understanding is essential for monitoring and assessing green spaces functions. In addition we estimated the effect of green space on urban temperature using Landsat 7 ETM+ imagery and climatic data. Results of the assessment showed that UHD creates differences in the spatial and temporal extent of temperature reducing effects due to differences in urban green space. The ratio of urban heat area decreases rapidly from green space boundary. And it shows that the urban green space plays an important role for mitigating urban heating in central areas. This study demonstrated the importance of green spaces by characterizing the spatio-temporal variations of urban green spaces in cities.},
  affiliation = {Department of Environmental Science and Ecological Engineering, Korea University, Seoul, 136-713, South Korea},
  author_keywords = {Satellite imagery; Spatio-temporal; Urban green spaces; Urban Heat Distribution (UHD)},
  document_type = {Conference Paper},
  source = {Scopus}
}

@article{choi2012,
  title = {Determining the Effect of Green Spaces on {{Urban}} Heat Distribution Using Satellite Imagery},
  author = {Choi, H.-A. and Lee, W.-K. and Byun, W.-H.},
  date = {2012},
  journaltitle = {Asian Journal of Atmospheric Environment},
  volume = {6},
  number = {2},
  pages = {127--135},
  publisher = {{Korean Society for Atmospheric Environment}},
  issn = {19766912},
  doi = {10.5572/ajae.2012.6.2.127},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870038183&doi=10.5572%2fajae.2012.6.2.127&partnerID=40&md5=844327d16503b73d71a00b314c84d87d},
  abbrev_source_title = {Asian J. Atmos. Environ.},
  abstract = {Urbanization has led to a reduction in green spaces and thus transformed the spatial pattern of urban land use. An increase in air temperature directly affects forest vegetation, phenology, and biodiversity in urban areas. In this paper, we analyze the changing land use patterns and urban heat distribution (UHD) in Seoul on the basis of a spatial assessment. It is necessary to monitor and assess the functions of green spaces in order to understand the changes in the green space. In addition, we estimated the influence of green space on urban temperature using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery and climatic data. Results of the assessment showed that UHD differences cause differences in temperature variation and the spatial extent of temperature reducing effects due to urban green space. The ratio of urban heat area to green space cooling area increases rapidly with increasing distance from a green space boundary. This shows that urban green space plays an important role for mitigating urban heating in central areas. This study demonstrated the importance of green space by characterizing the spatiotemporal variations in temperature associated with urban green spaces.},
  affiliation = {Department of Environmental Science and Ecological Engineering, Graduate School, Korea University, Seoul 136-701, South Korea},
  author_keywords = {Satellite imagery; Spatio-temporal; Urban green space; Urban heat distribution (UHD)},
  correspondence_address1 = {Lee, W.-K.; Department of Environmental Science and Ecological Engineering, Graduate School, Korea University, Seoul 136-701, South Korea; email: leewk@korea.ac.kr},
  document_type = {Article},
  langid = {english},
  source = {Scopus}
}

@article{Choi2012127,
  title = {Determining the Effect of Green Spaces on {{Urban}} Heat Distribution Using Satellite Imagery},
  author = {Choi, H.-A. and Lee, W.-K. and Byun, W.-H.},
  date = {2012},
  journaltitle = {Asian Journal of Atmospheric Environment},
  volume = {6},
  number = {2},
  pages = {127--135},
  doi = {10.5572/ajae.2012.6.2.127},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870038183&doi=10.5572%2fajae.2012.6.2.127&partnerID=40&md5=844327d16503b73d71a00b314c84d87d},
  abstract = {Urbanization has led to a reduction in green spaces and thus transformed the spatial pattern of urban land use. An increase in air temperature directly affects forest vegetation, phenology, and biodiversity in urban areas. In this paper, we analyze the changing land use patterns and urban heat distribution (UHD) in Seoul on the basis of a spatial assessment. It is necessary to monitor and assess the functions of green spaces in order to understand the changes in the green space. In addition, we estimated the influence of green space on urban temperature using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery and climatic data. Results of the assessment showed that UHD differences cause differences in temperature variation and the spatial extent of temperature reducing effects due to urban green space. The ratio of urban heat area to green space cooling area increases rapidly with increasing distance from a green space boundary. This shows that urban green space plays an important role for mitigating urban heating in central areas. This study demonstrated the importance of green space by characterizing the spatiotemporal variations in temperature associated with urban green spaces.},
  affiliation = {Department of Environmental Science and Ecological Engineering, Graduate School, Korea University, Seoul 136-701, South Korea},
  author_keywords = {Satellite imagery; Spatio-temporal; Urban green space; Urban heat distribution (UHD)},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\choi_et_al_2012_determining_the_effect_of_green_spaces_on_urban_heat_distribution_using.pdf}
}

@article{cole2017,
  title = {The Shifting Phenological Landscape: {{Within-}} and between-Species Variation in Leaf Emergence in a Mixed-Deciduous Woodland},
  shorttitle = {The Shifting Phenological Landscape},
  author = {Cole, Ella F. and Sheldon, Ben C.},
  date = {2017},
  journaltitle = {Ecology and Evolution},
  volume = {7},
  number = {4},
  pages = {1135--1147},
  issn = {2045-7758},
  doi = {10.1002/ece3.2718},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.2718},
  urldate = {2021-06-07},
  abstract = {Many organisms rely on synchronizing the timing of their life-history events with those of other trophic levels—known as phenological matching—for survival or successful reproduction. In temperate deciduous forests, the extent of matching with the budburst date of key tree species is of particular relevance for many herbivorous insects and, in turn, insectivorous birds. In order to understand the ecological and evolutionary forces operating in these systems, we require knowledge of the factors influencing leaf emergence of tree communities. However, little is known about how phenology at the level of individual trees varies across landscapes, or how consistent this spatial variation is between different tree species. Here, we use field observations, collected over 2 years, to characterize within- and between-species differences in spring phenology for 825 trees of six species (Quercus robur, Fraxinus excelsior, Fagus sylvatica, Betula pendula, Corylus avellana, and Acer pseudoplatanus) in a 385-ha woodland. We explore environmental predictors of individual variation in budburst date and bud development rate and establish how these phenological traits vary over space. Trees of all species showed markedly consistent individual differences in their budburst timing. Bud development rate also varied considerably between individuals and was repeatable in oak, beech, and sycamore. We identified multiple predictors of budburst date including altitude, local temperature, and soil type, but none were universal across species. Furthermore, we found no evidence for interspecific covariance of phenology over space within the woodland. These analyses suggest that phenological landscapes are highly complex, varying over small spatial scales both within and between species. Such spatial variation in vegetation phenology is likely to influence patterns of selection on phenology within populations of consumers. Knowledge of the factors shaping the phenological environments experienced by animals is therefore likely to be key in understanding how these evolutionary processes operate.},
  langid = {english},
  keywords = {budburst date,individual variation,phenology,small spatial scale,spring timing},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.2718},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\cole_sheldon_2017_the_shifting_phenological_landscape.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\QGPRXRWB\\ece3.html}
}

@report{collins2018,
  title = {Turning {{FAIR}} into Reality: {{Final}} Report and Action Plan from the {{European Commission}} Expert Group on {{FAIR}} Data},
  author = {Collins, Sandra and Genova, Françoise and Harrower, Natalie and Hodson, Simon and Jones, Sarah and Laaksonen, Leif and Mietchen, Daniel and Petrauskaitė, Rūta and Wittenburg, Peter},
  date = {2018},
  institution = {{European Commission, Directorate General for Research and Innovation,}},
  location = {{Luxembourg}},
  url = {https://doi.org/10.2777/1524}
}

@article{Comber2015972,
  title = {A Spatial Analysis of Plant Phenophase Changes and the Impact of Increases in Urban Land Use},
  author = {Comber, A. and Brunsdon, C.},
  date = {2015},
  journaltitle = {International Journal of Climatology},
  volume = {35},
  number = {6},
  pages = {972--980},
  doi = {10.1002/joc.4030},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84928577941&doi=10.1002%2fjoc.4030&partnerID=40&md5=ce7719752cecbe5094ae460a49774ad8},
  abstract = {Changes in phenology are indicators of climate change. Urban land use influences local climates through mechanisms such as urban heat island (UHI) effects. This research examined the spatio-temporal variations in first flowering with changes in urban land use in England and Wales. It used standard ordinary least squares (OLSs) regressions and geographically weighted regressions (GWRs) to analyse changes in phenophase observation date between 1934 and 2007 for three tree species. The OLS models suggested that first flowering was getting earlier: blackthorn by 0.28 days per year, hawthorn by 0.16 days per year and horse chestnut by 0.13 days per year. These rates were found to vary spatially when GWR was used and the greatest rates of change were found to be highly localized. The addition of land use change was found to improve the model fit and suggested that a 10\% increase in urban land use was also associated with phenophase advancement of 1.20 days for blackthorn, 0.57 days for hawthorn and 0.90 days for horse chestnut. When the impacts of urban land use changes was analysed using GWR, the associations with phenophase advancement were found to vary spatially, strongest associations were generally more pronounced in the north and especially in the extreme south-west and the north for all species. The results of this research suggest that the impacts of climate changes and the effects of urban land use changes on phenology vary spatially and that the impacts of urban expansion, such as UHI effects, may not be uniform. These findings suggest the need for spatially explicit analyses to quantify the local impacts and drivers of climate changes and their associated feedbacks. © 2014 Royal Meteorological Society.},
  affiliation = {Department of Geography, University of Leicester, United Kingdom; National Centre for Geocomputation, NUI Maynooth, Maynooth, Ireland},
  author_keywords = {Climate change; Geographically weighted model; Land use change; Phenology},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\comber_brunsdon_2015_a_spatial_analysis_of_plant_phenophase_changes_and_the_impact_of_increases_in.pdf}
}

@article{dahlhausen2018,
  title = {Urban Climate Modifies Tree Growth in {{Berlin}}},
  author = {Dahlhausen, Jens and Rötzer, Thomas and Biber, Peter and Uhl, Enno and Pretzsch, Hans},
  date = {2018-05-01},
  journaltitle = {International Journal of Biometeorology},
  shortjournal = {Int J Biometeorol},
  volume = {62},
  number = {5},
  pages = {795--808},
  issn = {1432-1254},
  doi = {10.1007/s00484-017-1481-3},
  url = {https://doi.org/10.1007/s00484-017-1481-3},
  urldate = {2019-12-06},
  abstract = {Climate, e.g., air temperature and precipitation, differs strongly between urban and peripheral areas, which causes diverse life conditions for trees. In order to compare tree growth, we sampled in total 252 small-leaved lime trees (Tilia cordata Mill) in the city of Berlin along a gradient from the city center to the surroundings. By means of increment cores, we are able to trace back their growth for the last 50 to 100 years. A general growth trend can be shown by comparing recent basal area growth with estimates from extrapolating a growth function that had been fitted with growth data from earlier years. Estimating a linear model, we show that air temperature and precipitation significantly influence tree growth within the last 20 years. Under consideration of housing density, the results reveal that higher air temperature and less precipitation led to higher growth rates in high-dense areas, but not in low-dense areas. In addition, our data reveal a significantly higher variance of the ring width index in areas with medium housing density compared to low housing density, but no temporal trend. Transferring the results to forest stands, climate change is expected to lead to higher tree growth rates.},
  langid = {english},
  keywords = {Growth trend,Lime trees,Urban heat island effect,Urban trees},
  file = {C\:\\Users\\ahurl\\Zotero\\storage\\RQK6CM9I\\Dahlhausen et al_2018_Urban climate modifies tree growth in Berlin.pdf}
}

@article{Dallimer20161942,
  title = {The Extent of Shifts in Vegetation Phenology between Rural and Urban Areas within a Human-Dominated Region},
  author = {Dallimer, M. and Tang, Z. and Gaston, K.J. and Davies, Z.G.},
  date = {2016},
  journaltitle = {Ecology and Evolution},
  volume = {6},
  number = {7},
  pages = {1942--1953},
  doi = {10.1002/ece3.1990},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959377623&doi=10.1002%2fece3.1990&partnerID=40&md5=2a90f5cf1c67da0d572c1bd009bb16c6},
  abstract = {Urbanization is one of the major environmental challenges facing the world today. One of its particularly pressing effects is alterations to local and regional climate through, for example, the Urban Heat Island. Such changes in conditions are likely to have an impact on the phenology of urban vegetation, which will have knock-on implications for the role that urban green infrastructure can play in delivering multiple ecosystem services. Here, in a human-dominated region, we undertake an explicit comparison of vegetation phenology between urban and rural zones. Using satellite-derived MODIS-EVI data from the first decade of the 20th century, we extract metrics of vegetation phenology (date of start of growing season, date of end of growing season, and length of season) for Britain's 15 largest cities and their rural surrounds. On average, urban areas experienced a growing season 8.8 days longer than surrounding rural zones. As would be expected, there was a significant decline in growing season length with latitude (by 3.4 and 2.4 days/degree latitude in rural and urban areas respectively). Although there is considerable variability in how phenology in urban and rural areas differs across our study cities, we found no evidence that built urban form influences the start, end, or length of the growing season. However, the difference in the length of the growing season between rural and urban areas was significantly negatively associated with the mean disposable household income for a city. Vegetation in urban areas deliver many ecosystem services such as temperature mitigation, pollution removal, carbon uptake and storage, the provision of amenity value for humans and habitat for biodiversity. Given the rapid pace of urbanization and ongoing climate change, understanding how vegetation phenology will alter in the future is important if we wish to be able to manage urban greenspaces effectively. © 2016 Published by John Wiley \& Sons Ltd.},
  affiliation = {Sustainability Research Institute, School of Earth and Environment, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT, United Kingdom; Department of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China; Environment and Sustainability Institute, University of Exeter, Penryn, Cornwall, TR10 9EZ, United Kingdom; Durrell Institute of Conservation and Ecology (DICE), School of Anthropology and Conservation, University of Kent, Canterbury, Kent, CT2 7NR, United Kingdom},
  author_keywords = {Enhanced Vegetation Index; Green infrastructure; Greenspace; Growing season; Urban ecology; Urban heat island; Urbanization},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\dallimer_et_al_2016_the_extent_of_shifts_in_vegetation_phenology_between_rural_and_urban_areas.pdf}
}

@article{David2018133,
  title = {Street Trees in {{Paris}} Are Sensitive to Spring and Autumn Precipitation and Recent Climate Changes},
  author = {David, A.A.J. and Boura, A. and Lata, J.-C. and Rankovic, A. and Kraepiel, Y. and Charlot, C. and Barot, S. and Abbadie, L. and Ngao, J.},
  date = {2018},
  journaltitle = {Urban Ecosystems},
  volume = {21},
  number = {1},
  pages = {133--145},
  doi = {10.1007/s11252-017-0704-z},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030179889&doi=10.1007%2fs11252-017-0704-z&partnerID=40&md5=741099377fe7ab42718115f28d9d6abc},
  abstract = {Determining the main factors causing urban tree decline is becoming essential for sustaining their health and survival. Understanding responses of tree growth to urban environments and climate change throughout tree life span is thus necessary. To explore these questions, a dendrochronological study exploring past climate-tree growth relationships was conducted on street and park silver lindens in Paris, according to different DBH classes used as a proxy of tree age, and using climatic data for the 1970–2013 period. Younger urban silver lindens presented high sensitivity to climate with highest growth rate. In comparison with park trees, street trees had higher sensitivity to climate and lower growth rates. Climatic and pointer years analysis pointed out the importance of drought characterization in order to understand its potential impact on tree annual growth and functioning. Urban silver lindens growth is mainly and strongly correlated with precipitations and especially in autumn and spring. Finally, our study on temporal evolution between climatic factors and growth through 1970–2013 periods showed a stronger stability between growth and precipitation only in October and revealed quick climatic changes since 40 years impacting the relation between tree growth and climate. Our study highlights that an optimized irrigation management, specifically in respect of tree phenology, could contribute to maximizing silver linden functioning and survival in Paris under climate change. © 2017, Springer Science+Business Media, LLC.},
  affiliation = {Sorbonne Universités, UPMC Univ. Paris 06, IRD, CNRS, INRA, UPEC, Univ Paris Diderot, Institute of Ecology and Environmental Sciences, iEESParis, 4 place Jussieu, Paris, 75005, France; Center for Research on Palaeobiodiversity and Palaeoenvironments, 57 rue Cuvier, Paris Cedex 5, 75231, France; Department of Geoecology and Geochemistry, Institute of Natural Resources, Tomsk Polytechnic University, Lenin Avenue, 30, Tomsk, 634050, Russian Federation; Institute for Sustainable Development and International Relations, Sciences Po, 27 rue Saint Guillaume, Paris, F-75007, France; UCA, INRA, UMR 547 PIAF, Clermont-Ferrand, 63000, France},
  author_keywords = {Climate change; Climate-growth relationship; Dendrochronology; Pointer years; Street trees; Tilia tomentosa Moench; Water stress},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\david_et_al_2018_street_trees_in_paris_are_sensitive_to_spring_and_autumn_precipitation_and.pdf}
}

@inproceedings{DeAbreu2011245,
  title = {Trees and Heat Fluxes: {{How}} Much Do They Contribute to the Energy Balance at Urban Spaces?},
  author = {De Abreu, L.V. and Labaki, L.C.},
  date = {2011},
  series = {{{PLEA}} 2011 - {{Architecture}} and {{Sustainable Development}}, {{Conference Proceedings}} of the 27th {{International Conference}} on {{Passive}} and {{Low Energy Architecture}}},
  pages = {245--250},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864147789&partnerID=40&md5=951613541ea7531ba3f51732d50bdbfb},
  abstract = {Results of local-scale surface energy balance observations reveal that latent heat fluxes, Qe, provided by trees are important in the surface energy control of cities. Arboreal species provide different storage latent heat, a characteristic related with the mitigation of air temperature in local-scale provided by them. The aim of this work is to compare heat fluxes in different arboreal species along the day and verify their contribution for thermal comfort inside and outside buildings. The required data are: net radiation flux density retained by sunlit and shaded layers (W/m 2) (collected by tube solarimeters), air temperature and relative humidity, atmospheric pressure and vegetation phenology (size of crown, leaves and foliar area). The measurements were carried out during the day, from sunrise to sunset, in three-day periods, throughout the year, covering different seasons. The energy balance scheme is based in the big-leaf model by Penman-Monteith (FAO056). In the research four tree species were analyzed, chosen from the most used trees in urban forestry in the South-East region of Brazil. Results showed that Qe by each trees varied between 116, 68 and 1208,89 W.h/m 2 during the year. The greatest contribution of trees for the energy balance was observed in the afternoon period. The different results obtained were due to the characteristics of the sample individual, such as structure and density of the treetop, size, shape and color of leaves, tree age and growth stage. Trees with higher tops have a good contribution in the cities, due to their energy consumption and higher solar radiation attenuation. Deciduous species are excellent in sub-tropical climate, because they can reduce heat fluxes in summer and allow them in winter. The trees around building, on streets and parks can reduce air temperature, by diminishing the conductive and convective heat gains. This effect provides thermal comfort and can reduce the energy for cooling of the buildings. These characteristics of vegetation should be taken in account by professionals of the urban built environment to improve thermal comfort outdoors, reducing the effect of heat island so ensuring better quality of life for people.},
  affiliation = {School of Civil Engineering, University of Campinas, Campinas, Brazil},
  author_keywords = {Heat flux; Solar radiation; Thermal comfort},
  document_type = {Conference Paper},
  source = {Scopus}
}

@article{deng2019,
  title = {Urban Plant Phenology Monitoring: {{Expanding}} the Functions of Widespread Surveillance Cameras to Nature Rhythm Understanding},
  author = {Deng, L. and Lin, Y. and Yan, L. and Tesfamichael, S. and Billen, R. and Yao, Y. and Yao, W. and Chen, X. and Fang, X. and Wang, C. and Jing, X.},
  date = {2019},
  journaltitle = {Remote Sensing Applications: Society and Environment},
  volume = {15},
  doi = {10.1016/j.rsase.2019.05.001},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065526502&doi=10.1016%2fj.rsase.2019.05.001&partnerID=40&md5=9da261256e7c80c797ecd9ce62e1d0b9},
  abstract = {Phenology is an important ecological indicator for understanding the feedback of plants to climate changes, but observation of plant phenology is not a trivial task, particularly for the large-scale areas of interest. Urban plant phenology monitoring is such a typical case, since massive residents do not necessarily mean enough eligible phenology observers. To handle this traditional challenge, this study attempted those surveillance cameras (SCs)widespread almost in any city all over the world. The schematic plan is to install an automatic software module, which has the function of plant phenology monitoring, as a plug-in into any central unit that wire-controls RGB SCs. The kernel of the module is a general-purposed algorithm capable of deriving the starting and ending dates of the key phenological events of different plants that stand in the field of view of each telecontrolled SC. The kernels of the algorithm comprise deriving phenological indices from the digital number (DN)records by a SC from all of its RGB channels and, then, modeling of plant dynamics based on the proposed novel phase-limited multi-Gaussian model for curve-fitting of phenological phases. In the case of determining the key phenological dates regarding flowering and foliation in this study, tests suggested that the proposed scheme and phenological indices and the programmed software plug-in all worked well. Overall, the feasibility of using the widespread SCs for urban plant phenology monitoring was validated, and the scheme can be further extended to composing phenology observation networks at local or global scales. The solution is of implications for more understanding the interannual rhythms of terrestrial ecosystems as well as the inherent mechanisms of vegetation-climate interactions. © 2019 Elsevier B.V.},
  affiliation = {Institute of Remote Sensing and GIS, Beijing Key Lab of Spatial Information Integration and Its Applications, School of Earth and Space Sciences, Peking University, Beijing, 100871, China; School of Earth Sciences and Resources, China University of Geosciences, Beijing, 100083, China; Department of Geography, Environment Management \& Energy Studies, University of Johannesburg, Johannesburg, South Africa; Department of Geography, University of Liège, Liège, 4000, Belgium; School of Geography, Beijing Normal University, Beijing, 100875, China; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong; School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, China; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China},
  art_number = {100232},
  author_keywords = {Phenological index; Phenology model; Software plug-in; Surveillance camera; Urban plant phenology monitoring},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\deng_et_al_2019_urban_plant_phenology_monitoring.pdf}
}

@article{Dhami2011507,
  title = {Phenology of Trees and Urbanization: {{A}} Comparative Study between New York City and Ithaca, New York},
  author = {Dhami, I. and Arano, K.G. and Warner, T.A. and Gazal, R.M. and Joshi, S.},
  date = {2011},
  journaltitle = {Geocarto International},
  volume = {26},
  number = {7},
  pages = {507--526},
  doi = {10.1080/10106049.2011.607517},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859013303&doi=10.1080%2f10106049.2011.607517&partnerID=40&md5=eb3e13b484df428b7f2c627f02635cb0},
  abstract = {The 'global warming' effect has been found to influence vegetation phenological processes. Heat island phenomenon associated with urbanized area presents a unique place to investigate its local warming effects. This study compares the date of budburst (DOBB) of street London plane trees (Platanus × acerifolia) between highly urbanized New York City (NYC) and relatively less urbanized Ithaca, New York in 2007 and 2008. It also linked DOBB with land surface temperature and fractional vegetation cover derived from Landsat satellite images. The DOBB in NYC and Ithaca differed significantly as budburst occurred 3 and 4 days earlier in NYC than in Ithaca in 2007 and 2008, respectively. The intensity of the heat island effect and its effect on tree phenology were greater in NYC. Results show that DOBB can be explained by temperature, and findings could be extrapolated to make inferences on the potential impact of global warming on vegetation communities. © 2011 Copyright Taylor and Francis Group, LLC.},
  affiliation = {Division of Forestry and Natural Resources, West Virginia University, P.O. Box 6125, Morgantown, 26506-6125, United States; Department of Geology and Geography, West Virginia University, P.O. Box 6300, Morgantown, 26506-6300, United States; Department of Land Resources, Glenville State College, 200 High Street, Glenville, 26351, United States; Division of Resource Management, West Virginia University, P.O. Box 6108, Morgantown, 26506-6108, United States},
  author_keywords = {budburst; fractional vegetation cover; land surface temperature; urban heat island effect; urbanization},
  document_type = {Article},
  source = {Scopus}
}

@article{diaz2021,
  title = {Toward Making Canopy Hemispherical Photography Independent of Illumination Conditions: {{A}} Deep-Learning-Based Approach},
  author = {Díaz, G.M. and Negri, P.A. and Lencinas, J.D.},
  date = {2021},
  journaltitle = {Agricultural and Forest Meteorology},
  volume = {296},
  publisher = {{Elsevier B.V.}},
  issn = {01681923},
  doi = {10.1016/j.agrformet.2020.108234},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095700535&doi=10.1016%2fj.agrformet.2020.108234&partnerID=40&md5=17ed4e609f91323e12beefc7f222ee16},
  abstract = {Hemispherical photography produces the most accurate results when working with well-exposed photographs acquired under diffuse light conditions (diffuse-light images). Obtaining such data can be prohibitively expensive when surveying hundreds of plots is required. A relatively inexpensive alternative is using photographs acquired under direct sunlight (sunlight images). However, this practice leads to high errors since the standard processing algorithms expect diffuse-light imagery. Here, instead of using classification algorithms, which is the unique dominant practice, we approached the processing of sunlight images using deep learning (DL) regression. We implemented DL systems by using the general-purpose convolutional neural networks known as VGGNet 16, VGGNet 19, Res-Net, and SE-ResNet. We trained them with 608 samples acquired in a South American temperate forest populated by Nothofagus pumilio. For their evaluation, we used 113 independent samples. Each sample (X, Y) consisted of one or several sunlight images (X), and the plant area index (PAI) and effective PAI (PAIe) extracted from a diffuse-light image (Y). The sunlight images include clear sky and broken clouds with sun elevation from 15° to 47°. We obtained the best results with the SE-ResNet architecture. The system requires a low-resolution input reprojected to cylindrical, and it can make predictions with 10\% root mean square error, even from pictures acquired with automatic exposure, which challenge previous findings. Furthermore, similar results (R2= 0.9, n = 104) can be obtained by feeding the system with photographs acquired with an inexpensive fisheye converter attached to a smartphone. Altogether, results indicate that our approach is a cost-efficient option for surveying hundreds of plots under direct sunlight. Therefore, combining our method with the traditional procedures provides processing solutions for virtually all kinds of illumination conditions. © 2020},
  langid = {english},
  keywords = {algorithm,canopy architecture,clear sky,data processing,machine learning,Nothofagus pumilio,photography,satellite imagery,surveying}
}

@article{Ding2020,
  title = {Vegetation Phenology Influenced by Rapid Urbanization of the {{Yangtze Delta Region}}},
  author = {Ding, H. and Xu, L. and Elmore, A.J. and Shi, Y.},
  date = {2020},
  journaltitle = {Remote Sensing},
  volume = {12},
  number = {11},
  doi = {10.3390/rs12111783},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086442466&doi=10.3390%2frs12111783&partnerID=40&md5=8afa4fab347f2bd34661d7c765072e40},
  abstract = {Impacts of urbanization and climate change on ecosystems are widely studied, but these drivers of change are often difficult to isolate from each other and interactions are complicated. Ecosystem responses to each of these drivers are perhaps most clearly seen in phenology changes due to global climate change (warming climate) and urbanization (heat island effect). The phenology of vegetation can influence many important ecological processes, including primary production, evapotranspiration, and plant fitness. Therefore, evaluating the interacting effects of urbanization and climate change on vegetation phenology has the potential to provide information about the long-term impact of global change. Using remotely sensed time series of vegetation on the Yangtze River Delta in China, this study evaluated the impacts of rapid urbanization and climate change on vegetation phenology along an urban to rural gradient over time. Phenology markers were extracted annually from an 18-year time series by fitting the asymmetric Gaussian function model. Thermal remote sensing acquired at daytime and nighttime was used to explore the relationship between land surface temperature and vegetation phenology. On average, the spring phenology marker was 9.6 days earlier and the autumn marker was 6.63 days later in urban areas compared with rural areas. The spring phenology of urban areas advanced and the autumn phenology delayed over time. Across space and time, warmer spring daytime and nighttime land surface temperatures were related to earlier spring, while autumn daytime and nighttime land surface temperatures were related to later autumn phenology. These results suggest that urbanization, through surface warming, compounds the effect of climate change on vegetation phenology. © 2020 by the authors.},
  affiliation = {School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; School of Geography Science, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Appalachian Laboratory, University of Maryland Center for Environmental Science, 301 Braddock Road, Frostburg, MD 21532, United States; National Socio-Environmental Synthesis Center (SESYNC), 1 Park PI, Suite 300, Annapolis, MD 21401, United States},
  art_number = {1783},
  author_keywords = {Climate change; Remote sensing; The yangtze river delta; Urbanization; Vegetation phenology},
  document_type = {Article},
  source = {Scopus},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\ding_et_al_2020_vegetation_phenology_influenced_by_rapid_urbanization_of_the_yangtze_delta.pdf}
}

@article{dixon2021,
  title = {Satellite Prediction of Forest Flowering Phenology},
  author = {Dixon, Dan J. and Callow, J. Nikolaus and Duncan, John M. A. and Setterfield, Samantha A. and Pauli, Natasha},
  date = {2021-03-15},
  journaltitle = {Remote Sensing of Environment},
  shortjournal = {Remote Sensing of Environment},
  volume = {255},
  pages = {112197},
  issn = {0034-4257},
  doi = {10.1016/j.rse.2020.112197},
  url = {https://www.sciencedirect.com/science/article/pii/S0034425720305708},
  urldate = {2021-04-26},
  abstract = {Knowledge of flowering phenology is essential for understanding the condition of forest ecosystems and responses to various anthropogenic and environmental drivers. However, monitoring the spatial and temporal variability in forest flowering at landscape scales is challenging (e.g. current monitoring is often highly localized and in-situ or for single dates). This study presents a method that combines drone and satellite images (PlanetScope) that can produce landscape-scale maps of flowering dynamics. This method is demonstrated in forest landscapes dominated by the eucalypt Corymbia calophylla (red gum or marri) in Western Australia. Drone-derived images of flowering eucalypt canopies, available for restricted temporal and spatial extents, are used to label satellite image pixels with the proportion of a pixel footprint that is flowering. The pixels labelled with flowering proportion, the response variable, are combined with various metrics that characterize time series of spectral indices sensitive to the presence of green vegetation and cream-colored flowers, the predictor variables. A machine learning model then predicts daily pixel-level flowering proportions. The model is trained with data from two sites and is tested with data from three sites and various dates throughout the Corymbia calophylla season. The model is able to accurately predict pixel-level flowering proportion throughout the flowering season (RMSE {$<$}4\% across all sites and dates), across sites with dense to sparse canopy, different background soil covers, and is robust to not detecting false positive flowering when no flowering events are occurring. Due to the spatiotemporal coverage of satellite images, this model can be deployed to generate regional maps of flowering dynamics in forest ecosystems that can be used for monitoring forest ecosystem condition and supporting research into drivers of eucalypt forest phenology.},
  langid = {english},
  keywords = {CubeSat,Drone/UAV/UAS,Flower mapping,Phenology,PlanetScope,Time series analysis},
  file = {C\:\\Users\\ahurl\\transfer\\OneDrive\\_literature\\dixon_et_al_2021_satellite_prediction_of_forest_flowering_phenology.pdf;C\:\\Users\\ahurl\\Zotero\\storage\\4YAHU5MI\\S0034425720305708.html}
}

@article{du2010,
  title = {Monitoring Urban Land Cover and Vegetation Change by Multi-Temporal Remote Sensing Information},
  author = {Du, P. and Li, X. and Cao, W. and Luo, Y. and Zhang, H.},
  date = {2010},
  journaltitle = {Mining Science and Technology},
  volume = {20},
  number = {6},
  pages = {922--932},
  issn = {16745264},
  doi = {10.1016/S1674-5264(09)60308-2},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-7864969