{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T21:03:39Z","timestamp":1781298219266,"version":"3.54.1"},"reference-count":95,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T00:00:00Z","timestamp":1664496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006595","name":"Ministry of Research, Innovation and Digitization, CNCS-UEFISCDI (Romania)","doi-asserted-by":"publisher","award":["PN-III-P1-1.1-TE-2019-1543"],"award-info":[{"award-number":["PN-III-P1-1.1-TE-2019-1543"]}],"id":[{"id":"10.13039\/501100006595","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The importance of small urban green areas has increased in the context of rapid urbanization and the densification of the urban tissue. The analysis of these areas through remote sensing has been limited due to the low spatial resolution of freely available satellite images. We propose a timeseries analysis on 3 m resolution Planet images, using GEOBIA and vegetation indices, with the aim of extracting and assessing the quality of small urban green areas in two different climatic and biogeographical regions: temperate (Bucharest, Romania) and mediterranean (Athens, Greece). Our results have shown high accuracy (over 91%) regarding the extraction of small urban green areas in both cities across all the analyzed images. The timeseries analysis showed consistency with respect to location for around 55% of the identified surfaces throughout the entire period. The vegetation indices registered higher values in the temperate region due to the vegetation characteristics and city plan of the two cities. For the same reasons, the increase in the vegetation density and quality, as a result of the distance from the city center, and the decrease in the density of built-up areas, is more obvious in Athens. The proposed method provides valuable insights into the distribution and quality of small urban green areas at the city level and can represent the basis for many analyses, which is currently limited by poor spatial resolution.<\/jats:p>","DOI":"10.3390\/rs14194888","type":"journal-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T03:07:28Z","timestamp":1665371248000},"page":"4888","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Using GEOBIA and Vegetation Indices to Assess Small Urban Green Areas in Two Climatic Regions"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2809-3176","authenticated-orcid":false,"given":"Ana Maria","family":"Popa","sequence":"first","affiliation":[{"name":"Centre for Environmental Research and Impact Studies, University of Bucharest, Bd. N. Balcescu 1, 010041 Bucharest, Romania"},{"name":"Faculty of Geography, University of Bucharest, Bd. N. Balcescu, 1, 010041 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5991-5502","authenticated-orcid":false,"given":"Diana Andreea","family":"Onose","sequence":"additional","affiliation":[{"name":"Centre for Environmental Research and Impact Studies, University of Bucharest, Bd. N. Balcescu 1, 010041 Bucharest, Romania"},{"name":"Faculty of Geography, University of Bucharest, Bd. N. Balcescu, 1, 010041 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9292-9479","authenticated-orcid":false,"given":"Ionut Cosmin","family":"Sandric","sequence":"additional","affiliation":[{"name":"Faculty of Geography, University of Bucharest, Bd. N. Balcescu, 1, 010041 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5505-1823","authenticated-orcid":false,"given":"Evangelos A.","family":"Dosiadis","sequence":"additional","affiliation":[{"name":"Department of Geography, Harokopio University of Athens, El. Venizelou 70, Kallithea, 17671 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1442-1423","authenticated-orcid":false,"given":"George P.","family":"Petropoulos","sequence":"additional","affiliation":[{"name":"Department of Geography, Harokopio University of Athens, El. Venizelou 70, Kallithea, 17671 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1628-6897","authenticated-orcid":false,"given":"Athanasios Alexandru","family":"Gavrilidis","sequence":"additional","affiliation":[{"name":"Centre for Environmental Research and Impact Studies, University of Bucharest, Bd. N. Balcescu 1, 010041 Bucharest, Romania"},{"name":"Faculty of Geography, University of Bucharest, Bd. N. Balcescu, 1, 010041 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7552-0359","authenticated-orcid":false,"given":"Antigoni","family":"Faka","sequence":"additional","affiliation":[{"name":"Department of Geography, Harokopio University of Athens, El. Venizelou 70, Kallithea, 17671 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,30]]},"reference":[{"key":"ref_1","unstructured":"United Nations (2017). Habitat III New Urban Agenda, United Nations."},{"key":"ref_2","unstructured":"(2019, May 16). United Nations Sustainable Development Goals. Available online: https:\/\/sustainabledevelopment.un.org\/index.php?menu=1300."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"102483","DOI":"10.1016\/j.cities.2019.102483","article-title":"Building Urban Resilience with Nature-Based Solutions: How Can Urban Planning Contribute?","volume":"95","author":"Bush","year":"2019","journal-title":"Cities"},{"key":"ref_4","unstructured":"United for Smart Sustainable Cities (2017). Implementing Sustainable Development Goal 11 by Connecting Sustainability Policies and Urban-Planning Practices through ICTs, United Nations."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.ufug.2012.04.002","article-title":"Use of Small Public Urban Green Spaces (SPUGS)","volume":"11","author":"Peschardt","year":"2012","journal-title":"Urban For. Urban Green."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"373","DOI":"10.26471\/cjees\/2022\/017\/229","article-title":"Urban Sustainability Assessment of Romanian Cities","volume":"17","author":"Popa","year":"2022","journal-title":"Carpathian J. Earth Environ. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"151123","DOI":"10.1016\/j.scitotenv.2021.151123","article-title":"Spatiotemporal Patterns and Inequity of Urban Green Space Accessibility and Its Relationship with Urban Spatial Expansion in China during Rapid Urbanization Period","volume":"809","author":"Huang","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"105974","DOI":"10.1016\/j.landusepol.2022.105974","article-title":"Green Space Dynamics in Response to Rapid Urbanization: Patterns, Transformations and Topographic Influence in Chattogram City, Bangladesh","volume":"114","author":"Siddique","year":"2022","journal-title":"Land Use Policy"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"102418","DOI":"10.1016\/j.jeem.2021.102418","article-title":"Small Urban Green Areas","volume":"106","author":"Picard","year":"2021","journal-title":"J. Environ. Econ. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"127273","DOI":"10.1016\/j.ufug.2021.127273","article-title":"Design Possibilities of Leftover Spaces as a Pocket Park in Relation to Planting Enclosure","volume":"64","author":"Naghibi","year":"2021","journal-title":"Urban For. Urban Green."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"126700","DOI":"10.1016\/j.ufug.2020.126700","article-title":"Public Perception and Preferences of Small Urban Green Infrastructures: A Case Study in Guangzhou, China","volume":"53","author":"Zhang","year":"2020","journal-title":"Urban For. Urban Green."},{"key":"ref_12","unstructured":"Parlamentul Romaniei (2012). Legea 24\/2007, Parlamentul Romaniei."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.ufug.2012.11.003","article-title":"Pocket Parks for People\u2014A Study of Park Design and Use","volume":"12","author":"Nordh","year":"2013","journal-title":"Urban For. Urban Green."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.ufug.2016.12.005","article-title":"The Influence of Small Green Space Type and Structure at the Street Level on Urban Heat Island Mitigation","volume":"21","author":"Park","year":"2017","journal-title":"Urban For. Urban Green."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.landurbplan.2013.02.007","article-title":"Are Small Greening Areas Enhancing Bird Diversity? Insights from Community-Driven Greening Projects in Boston","volume":"114","author":"Strohbach","year":"2013","journal-title":"Landsc. Urban Plan."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"103637","DOI":"10.1016\/j.landurbplan.2019.103637","article-title":"The Effect of Green Space Behaviour and per Capita Area in Small Urban Green Spaces on Psychophysiological Responses","volume":"192","author":"Lin","year":"2019","journal-title":"Landsc. Urban Plan."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"110527","DOI":"10.1016\/j.enbuild.2020.110527","article-title":"On the Impact of Nature-Based Solutions on Citizens\u2019 Health & Well Being","volume":"229","author":"Kolokotsa","year":"2020","journal-title":"Energy Build."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"126946","DOI":"10.1016\/j.ufug.2020.126946","article-title":"Remote Sensing of Urban Green Spaces: A Review","volume":"57","author":"Shahtahmassebia","year":"2021","journal-title":"Urban For. Urban Green."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.landurbplan.2012.12.013","article-title":"Associations between Park Characteristics and Perceived Restorativeness of Small Public Urban Green Spaces","volume":"112","author":"Peschardt","year":"2013","journal-title":"Landsc. Urban Plan."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"096088","DOI":"10.1117\/1.JRS.9.096088","article-title":"Urban Vegetation Cover Extraction from Hyperspectral Imagery and Geographic Information System Spatial Analysis Techniques: Case of Athens, Greece","volume":"9","author":"Petropoulos","year":"2015","journal-title":"J. Appl. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"100672","DOI":"10.1016\/j.polar.2021.100672","article-title":"Green Spaces as an Indicator of Urban Sustainability in the Arctic Cities: Case of Nadym","volume":"29","author":"Kuklina","year":"2021","journal-title":"Polar Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"103857","DOI":"10.1016\/j.landurbplan.2020.103857","article-title":"Green Growth? On the Relation between Population Density, Land Use and Vegetation Cover Fractions in a City Using a 30-Years Landsat Time Series","volume":"202","author":"Wellmann","year":"2020","journal-title":"Landsc. Urban Plan."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1016\/j.rse.2012.06.011","article-title":"A Comparative Analysis of High Spatial Resolution IKONOS and WorldView-2 Imagery for Mapping Urban Tree Species","volume":"124","author":"Pu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"100425","DOI":"10.1016\/j.envc.2021.100425","article-title":"Present Status and Historical Changes of Urban Green Space in Dhaka City, Bangladesh: A Remote Sensing Driven Approach","volume":"6","author":"Nawar","year":"2022","journal-title":"Environ. Chall."},{"key":"ref_25","first-page":"343","article-title":"Estimating Urban Greenness Index Using Remote Sensing Data: A Case Study of an Affluent vs Poor Suburbs in the City of Johannesburg","volume":"24","author":"Abutaleb","year":"2021","journal-title":"Egypt. J. Remote Sens. Sp. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.ecolind.2017.06.022","article-title":"Using Multi-Seasonal Landsat Imagery for Rapid Identification of Abandoned Land in Areas Affected by Urban Sprawl","volume":"96","author":"Kienast","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kranj\u010di\u0107, N., Medak, D., \u017dupan, R., and Rezo, M. (2019). Support Vector Machine Accuracy Assessment for Extracting Green Urban Areas in Towns. Remote Sens., 11.","DOI":"10.3390\/rs11060655"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Lebourgeois, V., Dupuy, S., Vintrou, \u00c9., Ameline, M., Butler, S., and B\u00e9gu\u00e9, A. (2017). A Combined Random Forest and OBIA Classification Scheme for Mapping Smallholder Agriculture at Different Nomenclature Levels Using Multisource Data (Simulated Sentinel-2 Time Series, VHRS and DEM). Remote Sens., 9.","DOI":"10.3390\/rs9030259"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1007\/s40808-016-0108-8","article-title":"A Support Vector Machine Object Based Image Analysis Approach on Urban Green Space Extraction Using Pleiades-1A Imagery","volume":"2","author":"Zylshal","year":"2016","journal-title":"Model. Earth Syst. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ma, L., Schmitt, M., and Zhu, X. (2020). Uncertainty analysis of object-based land-cover classification using Sentinel-2 time-series data. Remote Sens., 12.","DOI":"10.3390\/rs12223798"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"107058","DOI":"10.1016\/j.ecolind.2020.107058","article-title":"Mapping Regulating Ecosystem Service Deprivation in Urban Areas: A Transferable High-Spatial Resolution Uncertainty Aware Approach","volume":"121","author":"Baker","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_32","unstructured":"Yang, Z., Willis, P., and Mueller, R. (2008, January 18\u201320). Impact of Band-Ratio Enhanced AWiFS Image to Crop Classification Accuracy. Proceedings of the Pecora 17\u2014The Future of Land Imaging\u2026 Going Operational, Denver, CO, USA."},{"key":"ref_33","unstructured":"(2020, November 26). INS Baze de Date Statistice. Available online: http:\/\/statistici.insse.ro:8077\/tempo-online\/#\/pages\/tables\/insse-table."},{"key":"ref_34","unstructured":"Hellenic Statistical Authority (2020). Statistical Database, Hellenic Statistical Authority."},{"key":"ref_35","unstructured":"Atlas, U. (2018). Copernicus Land Monitoring Service, European Environment Agency (EEA)."},{"key":"ref_36","unstructured":"Dumitrescu, E. (2007). Clima Municipiului Bucure\u0219ti, Editura Ars Docendi."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1177\/0143624410394518","article-title":"Improving the Microclimate in Urban Areas: A Case Study in the Centre of Athens","volume":"32","author":"Gaitani","year":"2011","journal-title":"Build. Serv. Eng. Res. Technol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"100696","DOI":"10.1016\/j.uclim.2020.100696","article-title":"Exploratory Analysis of Cooling Effect of Urban Lakes on Land Surface Temperature in Bucharest (Romania) Using Landsat Imagery","volume":"34","author":"Cheval","year":"2020","journal-title":"Urban Clim."},{"key":"ref_39","unstructured":"ANM (2018). Geografie, ANM."},{"key":"ref_40","unstructured":"Hellenic National Meteorological Service (2010). Climatic Data for Nea Filadefia Station, Hellenic National Meteorological Service."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Nae, M., Dumitrache, L., Suditu, B., and Matei, E. (2019). Housing Activism Initiatives and Land-Use Conflicts: Pathways for Participatory Planning and Urban Sustainable Development in Bucharest City, Romania. Sustainability, 11.","DOI":"10.3390\/su11226211"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.landusepol.2016.10.030","article-title":"Incoherence of Urban Planning Policy in Bucharest: Its Potential for Land Use Conflict","volume":"60","author":"Sorensen","year":"2017","journal-title":"Land Use Policy"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.ufug.2018.07.001","article-title":"Integrating Urban Blue and Green Areas Based on Historical Evidence","volume":"34","author":"Breuste","year":"2018","journal-title":"Urban For. Urban Green."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.landurbplan.2018.07.015","article-title":"From \u201cRed\u201d to Green? A Look into the Evolution of Green Spaces in a Post-Socialist City","volume":"187","author":"Badiu","year":"2019","journal-title":"Landsc. Urban Plan."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.cities.2009.12.011","article-title":"Planning, Competitiveness and Sprawl in the Mediterranean City: The Case of Athens","volume":"27","author":"Chorianopoulos","year":"2010","journal-title":"Cities"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"153071","DOI":"10.1016\/j.scitotenv.2022.153071","article-title":"The Influence of Daily Weather Types on the Development and Intensity of the Urban Heat Island in Two Mediterranean Coastal Metropolises","volume":"819","author":"Kassomenos","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_47","unstructured":"European Environment Agency (2022). How Green Are European Cities? Green Space Key to Well-Being\u2014But Access Varies, European Environment Agency."},{"key":"ref_48","unstructured":"Greek Ministry of Environment and Energy (2014). Law 4280\/2014: Environmental Upgrade and Private Urban Planning\u2014Sustainable Development of Settlements\u2014Regulations of Forest Legislation and Other Provisions, Greek Ministry of Environment and Energy."},{"key":"ref_49","unstructured":"Planet Team (2021). Planet Application Program Interface: In Space for Life on Earth, Planet Team."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Timilsina, S., Aryal, J., and Kirkpatrick, J.B. (2020). Mapping Urban Tree Cover Changes Using Object-Based Convolution Neural Network (OB-CNN). Remote Sens., 12.","DOI":"10.3390\/rs12183017"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Degerickx, J., Hermy, M., and Somers, B. (2020). Mapping Functional Urban Green Types Using High Resolution Remote Sensing Data. Sustainability, 12.","DOI":"10.3390\/su12052144"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"71","DOI":"10.30516\/bilgesci.486893","article-title":"Mapping Urban Green Spaces Based on an Object-Oriented Approach","volume":"2","author":"Gulcin","year":"2018","journal-title":"Bilge Int. J. Sci. Technol. Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object Based Image Analysis for Remote Sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_54","first-page":"235","article-title":"Object-Oriented Mapping of Urban Trees Using Random Forest Classifiers","volume":"26","author":"Puissant","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2016.01.011","article-title":"Random Forest in Remote Sensing: A Review of Applications and Future Directions","volume":"114","author":"Belgiu","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_56","unstructured":"(2021, October 15). OpenStreetMap Contributors Roads, Buildings, Land Use. Available online: https:\/\/planet.openstreetmap.org."},{"key":"ref_57","unstructured":"Rouse, J.W., Haas, R.H., Schell, J.A., and Deering, D.W. (1973, January 1\u201314). Monitoring Vegetation Systems in the Great Plains with ERTS. Proceedings of the Third ERTS Symposium, Washington, DC, USA."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/0034-4257(94)90134-1","article-title":"A Modified Soil Adjusted Vegetation Index","volume":"48","author":"Qi","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_59","unstructured":"Planet Team (2022). Planet Imagery Product Specification, Planet Team."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1461","DOI":"10.1109\/JSTARS.2019.2909129","article-title":"A Hierarchical Extraction Method of Impervious Surface Based on NDVI Thresholding Integrated with Multispectral and High-Resolution Remote Sensing Imageries","volume":"12","author":"Feng","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_61","first-page":"237","article-title":"Urban Vegetation Classification with NDVI Threshold Value Method with Very High Resolution (VHR) PLEIADES Imagery","volume":"42","author":"Hashim","year":"2019","journal-title":"Environ. Sci."},{"key":"ref_62","first-page":"100721","article-title":"Spatial Correlations of NDVI and MSAVI2 Indices of Green and Forested Areas of Urban Agglomeration, Case Study Warsaw, Poland","volume":"26","author":"Zawadzki","year":"2022","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.isprsjprs.2021.06.017","article-title":"Mapping Landscape Canopy Nitrogen Content from Space Using PRISMA Data","volume":"178","author":"Verrelst","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.coal.2010.12.009","article-title":"Remote Sensing of Vegetation Health for Reclaimed Areas of Seyit\u00f6mer Open Cast Coal Mine","volume":"86","author":"Erener","year":"2011","journal-title":"Int. J. Coal Geol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"101032","DOI":"10.1016\/j.ecoinf.2019.101032","article-title":"Identifying Urban Vegetation Stress Factors Based on Open Access Remote Sensing Imagery and Field Observations","volume":"55","author":"Mihai","year":"2020","journal-title":"Ecol. Inform."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.ecoser.2016.12.004","article-title":"Analysing Scale, Quality and Diversity of Green Infrastructure and the Provision of Urban Ecosystem Services: A Case from Mexico City","volume":"23","year":"2017","journal-title":"Ecosyst. Serv."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"111407","DOI":"10.1016\/j.rse.2019.111407","article-title":"Carotenoid Based Vegetation Indices for Accurate Monitoring of the Phenology of Photosynthesis at the Leaf-Scale in Deciduous and Evergreen Trees","volume":"233","author":"Wong","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_68","unstructured":"(2021, October 03). L3Harris Geospatial Broadband Greenness Vegetation Indexes. Available online: https:\/\/www.l3harrisgeospatial.com\/docs\/broadbandgreenness.html#Green7."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1111\/j.1538-4632.1992.tb00261.x","article-title":"The Analysis of Spatial Association by Use of Distance Statistics","volume":"24","author":"Getis","year":"1992","journal-title":"Geogr. Anal."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1111\/j.1538-4632.1995.tb00912.x","article-title":"Local Spatial Autocorrelation Statistics: Distributional Issues and an Application","volume":"27","author":"Ord","year":"1995","journal-title":"Geogr. Anal."},{"key":"ref_71","unstructured":"Esri Inc (2022, March 03). Optimized Hot Spot Analysis (Spatial Statistics)\u2014ArcGIS Pro | Documentation. Available online: https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/spatial-statistics\/optimized-hot-spot-analysis.htm."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"129488","DOI":"10.1016\/j.jclepro.2021.129488","article-title":"An Improved Approach for Monitoring Urban Built-up Areas by Combining NPP-VIIRS Nighttime Light, NDVI, NDWI, and NDBI","volume":"328","author":"Zheng","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_73","unstructured":"Esri Inc (2022, March 03). Zonal Statistics as Table (Spatial Analyst)\u2014ArcGIS Pro. Documentation. Available online: https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/spatial-analyst\/zonal-statistics-as-table.htm."},{"key":"ref_74","unstructured":"IBM Corporation (2013). IBM SPSS Statistics for Windows, IBM Corporation."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"153","DOI":"10.2307\/2345050","article-title":"Statistical Analysis in Psychology and Education","volume":"135","author":"Jackson","year":"1972","journal-title":"J. R. Stat. Soc. Ser. A"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.isprsjprs.2019.02.009","article-title":"Segmentation for Object-Based Image Anaalysis (OBIA): A Review of Algorithms and Challenges from Remote Sensing Perspective","volume":"150","author":"Hossain","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.ufug.2018.11.008","article-title":"Mapping and Classifying Green Infrastructure Typologies for Climate-Related Studies Based on Remote Sensing Data","volume":"37","author":"Osmond","year":"2019","journal-title":"Urban For. Urban Green."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.rse.2017.08.010","article-title":"Mapping Urban Tree Species Using Integrated Airborne Hyperspectral and LiDAR Remote Sensing Data","volume":"200","author":"Liu","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Sun, Y., Meng, Q., Sun, Z., Zhang, J., and Zhang, L. (2017, January 4\u20136). Assessing the Impacts of Grain Sizes on Landscape Pattern of Urban Green Space. Proceedings of the AOPC 2017: Optical Sensing and Imaging Technology and Applications, Beijing, China.","DOI":"10.1117\/12.2285177"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"114804","DOI":"10.1016\/j.jenvman.2022.114804","article-title":"High-Resolution Planet Satellite Imagery and Multi-Temporal Surveys to Predict Risk of Tree Mortality in Tropical Eucalypt Forestry","volume":"310","author":"Pascual","year":"2022","journal-title":"J. Environ. Manag."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"105196","DOI":"10.1016\/j.cageo.2022.105196","article-title":"Densely Multiscale Framework for Segmentation of High Resolution Remote Sensing Imagery","volume":"167","author":"Bello","year":"2022","journal-title":"Comput. Geosci."},{"key":"ref_82","first-page":"102525","article-title":"Spatio-Temporal Changes in Urban Green Space in 107 Chinese Cities (1990\u20132019): The Role of Economic Drivers and Policy","volume":"103","author":"Wu","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.isprsjprs.2018.09.016","article-title":"Detection of Individual Trees in Urban Alignment from Airborne Data and Contextual Information: A Marked Point Process Approach","volume":"146","author":"Aval","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"30","DOI":"10.3389\/fenvs.2022.823129","article-title":"Spatiotemporal Analysis of Urban Green Areas Using Change Detection: A Case Study of Kharkiv, Ukraine","volume":"10","author":"Morar","year":"2022","journal-title":"Front. Environ. Sci."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"102862","DOI":"10.1016\/j.cities.2020.102862","article-title":"Environmental Justice in the Context of Urban Green Space Availability, Accessibility, and Attractiveness in Postsocialist Cities","volume":"106","author":"Kronenberg","year":"2020","journal-title":"Cities"},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Breuste, J., Artmann, M., Ioja, I.C., and Qureshi, S. (2020). Green Struggle\u2014Environmental Conflicts Involving Urban Green Areas in Bucharest City. Making Green Cities\u2014Concepts, Challenges and Practice, Springer.","DOI":"10.1007\/978-3-030-37716-8"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"102236","DOI":"10.1016\/j.scs.2020.102236","article-title":"Residents\u2019 Awareness of the Role of Informal Green Spaces in a Post-Industrial City, with a Focus on Regulating Services and Urban Adaptation Potential","volume":"59","author":"Sikorska","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"127635","DOI":"10.1016\/j.ufug.2022.127635","article-title":"Efficient Cooling of Cities at Global Scale Using Urban Green Space to Mitigate Urban Heat Island Effects in Different Climatic Regions","volume":"74","author":"Wang","year":"2022","journal-title":"Urban For. Urban Green."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"109264","DOI":"10.1016\/j.buildenv.2022.109264","article-title":"On the Mitigation Potential and Urban Climate Impact of Increased Green Infrastructures in a Coastal Mediterranean City","volume":"221","author":"Khan","year":"2022","journal-title":"Build. Environ."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"100068","DOI":"10.1016\/j.atech.2022.100068","article-title":"Detecting Olive Grove Abandonment with Sentinel-2 and Machine Learning: The Development of a Web-Based Tool for Land Management","volume":"3","author":"Volpi","year":"2023","journal-title":"Smart Agric. Technol."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Stateras, D., and Kalivas, D. (2020). Assessment of Olive Tree Canopy Characteristics and Yield Forecast Model Using High Resolution Uav Imagery. Agriculture, 10.","DOI":"10.3390\/agriculture10090385"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"127381","DOI":"10.1016\/j.ufug.2021.127381","article-title":"Urban Green Space Quality in China: Quality Measurement, Spatial Heterogeneity Pattern and Influencing Factor","volume":"66","author":"Yang","year":"2021","journal-title":"Urban For. Urban Green."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1016\/j.agrformet.2017.08.020","article-title":"Retrieving Vegetation Canopy Water Content from Hyperspectral Thermal Measurements","volume":"247","author":"Neinavaz","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.agrformet.2014.04.006","article-title":"Start of the Dry Season as a Main Determinant of Inter-Annual Mediterranean Forest Production Variations","volume":"194","author":"Maselli","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_95","unstructured":"(2022, September 01). Raspisaniye Pogodi Weather. Available online: https:\/\/rp5.ru."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/19\/4888\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:44:28Z","timestamp":1760143468000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/19\/4888"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,30]]},"references-count":95,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["rs14194888"],"URL":"https:\/\/doi.org\/10.3390\/rs14194888","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints202209.0411.v1","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,30]]}}}