{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T22:21:59Z","timestamp":1781043719354,"version":"3.54.1"},"reference-count":42,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2020,7,26]],"date-time":"2020-07-26T00:00:00Z","timestamp":1595721600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NASA OCO-2 Science Team","award":["17-OCO2-17-0025"],"award-info":[{"award-number":["17-OCO2-17-0025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High spatial resolution maps of Los Angeles, California are needed to capture the heterogeneity of urban land cover while spanning the regional domain used in carbon and water cycle models. We present a simplified framework for developing a high spatial resolution map of urban vegetation cover in the Southern California Air Basin (SoCAB) with publicly available satellite imagery. This method uses Sentinel-2 (10\u201360 \u00d7 10\u201360 m) and National Agriculture Imagery Program (NAIP) (0.6 \u00d7 0.6 m) optical imagery to classify urban and non-urban areas of impervious surface, tree, grass, shrub, bare soil\/non-photosynthetic vegetation, and water. Our approach was designed for Los Angeles, a geographically complex megacity characterized by diverse Mediterranean land cover and a mix of high-rise buildings and topographic features that produce strong shadow effects. We show that a combined NAIP and Sentinel-2 classification reduces misclassified shadow pixels and resolves spatially heterogeneous vegetation gradients across urban and non-urban regions in SoCAB at 0.6\u201310 m resolution with 85% overall accuracy and 88% weighted overall accuracy. Results from this study will enable the long-term monitoring of land cover change associated with urbanization and quantification of biospheric contributions to carbon and water cycling in cities.<\/jats:p>","DOI":"10.3390\/rs12152399","type":"journal-article","created":{"date-parts":[[2020,7,27]],"date-time":"2020-07-27T04:39:50Z","timestamp":1595824790000},"page":"2399","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["A Simplified Framework for High-Resolution Urban Vegetation Classification with Optical Imagery in the Los Angeles Megacity"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6582-4922","authenticated-orcid":false,"given":"Red Willow","family":"Coleman","sequence":"first","affiliation":[{"name":"NASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA"},{"name":"Department of Biology, Harvey Mudd College, 301 Platt Boulevard, Claremont, CA 91711, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natasha","family":"Stavros","sequence":"additional","affiliation":[{"name":"NASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vineet","family":"Yadav","sequence":"additional","affiliation":[{"name":"NASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas","family":"Parazoo","sequence":"additional","affiliation":[{"name":"NASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2912","DOI":"10.1073\/pnas.1702393115","article-title":"Long-term urban carbon dioxide observations reveal spatial and temporal dynamics related to urban characteristics and growth","volume":"115","author":"Mitchell","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1111\/j.1365-2486.2010.02238.x","article-title":"Terrestrial carbon stocks across a gradient of urbanization: A study of the Seattle, WA region","volume":"17","author":"Hutyra","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"16083","DOI":"10.1073\/pnas.1211658109","article-title":"Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools","volume":"109","author":"Seto","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.landurbplan.2014.04.007","article-title":"Estimation of residential outdoor water use in Los Angeles, California","volume":"127","author":"Mini","year":"2014","journal-title":"Landsc. Urban. Plan."},{"key":"ref_5","unstructured":"Miller, J., Lehman, S., Verhulst, K., Miller, C., Duren, R., Yadav, V., and Sloop, C. Large and Seasonally Varying biospheric CO2 fluxes in the Los Angeles megacity revealed by atmospheric radiocarbon. Proc. Natl. Acad. Sci. USA, under review."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.envpol.2016.01.012","article-title":"Soil respiration contributes substantially to urban carbon fluxes in the greater Boston area","volume":"212","author":"Decina","year":"2016","journal-title":"Environ. Pollut."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2530","DOI":"10.1002\/2016JG003469","article-title":"Landscape position influences soil respiration variability and sensitivity to physiological drivers in mixed-use lands of Southern California, USA","volume":"121","author":"Crum","year":"2016","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1890\/09-1717.1","article-title":"Transpiration of urban forests in the Los Angeles metropolitan area","volume":"21","author":"Pataki","year":"2011","journal-title":"Ecol. Appl."},{"key":"ref_9","first-page":"346","article-title":"Completion of the 2011 national land cover database for the conterminous United States\u2014Representing a decade of land cover change information","volume":"81","author":"Homer","year":"2015","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.landurbplan.2010.08.011","article-title":"Million trees Los Angeles canopy cover and benefit assessment","volume":"99","author":"McPherson","year":"2011","journal-title":"Landsc. Urban. Plan."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Nowak, D.J., Hoehn, R.E.I., Crane, D.E., Stevens, J.C., and Cotrone, V. (2010). Assessing Urban Forest Effects and Values, Los Angeles\u2019 Urban Forest, USDA.","DOI":"10.2737\/NRS-RB-43"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2018.04.051","article-title":"Megacity-scale analysis of urban vegetation temperatures","volume":"213","author":"Wetherley","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"5637","DOI":"10.1080\/01431160412331291224","article-title":"Using AVIRIS data and multiple-masking techniques to map urban forest tree species","volume":"25","author":"Xiao","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1007\/s11252-016-0633-2","article-title":"Predicting tree species richness in urban forests","volume":"20","author":"Gillespie","year":"2017","journal-title":"Urban. Ecosyst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.rse.2017.04.013","article-title":"Mapping spectrally similar urban materials at sub-pixel scales","volume":"195","author":"Wetherley","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.ecoser.2015.04.005","article-title":"EnviroAtlas: A new geospatial tool to foster ecosystem services science and resource management","volume":"14","author":"Pickard","year":"2015","journal-title":"Ecosyst. Serv."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.rse.2019.03.037","article-title":"A statewide urban tree canopy mapping method","volume":"229","author":"Erker","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"405","DOI":"10.5194\/bg-17-405-2020","article-title":"A double peak in the seasonality of California\u2019s photosynthesis as observed from space","volume":"17","author":"Turner","year":"2020","journal-title":"Biogeosciences"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1080\/01431169608948714","article-title":"The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features","volume":"17","author":"McFeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Du, Y., Zhang, Y., Ling, F., Wang, Q., Li, W., and Li, X. (2016). Water bodies\u2019 mapping from Sentinel-2 imagery with Modified Normalized Difference Water Index at 10-m spatial resolution produced by sharpening the swir band. Remote Sens., 8.","DOI":"10.3390\/rs8040354"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3544","DOI":"10.3390\/rs5073544","article-title":"Using the normalized difference water index (ndwi) within a geographic information system to detect swimming pools for mosquito abatement: A practical approach","volume":"5","author":"McFeeters","year":"2013","journal-title":"Remote Sens."},{"key":"ref_24","unstructured":"(2019, July 01). US Building Footprints. Available online: https:\/\/github.com\/Microsoft\/USBuildingFootprints."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"799","DOI":"10.14358\/PERS.72.7.799","article-title":"Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery","volume":"72","author":"Yu","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","article-title":"SLIC superpixels compared to state-of-the-art superpixel methods","volume":"34","author":"Achanta","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Achanta, R., and S\u00fcsstrunk, S. (2017, January 21\u201326). Superpixels and polygons using simple non-iterative clustering. Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.520"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural Features for Image Classification","volume":"3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.cageo.2015.06.023","article-title":"Using Google\u2019s cloud-based platform for digital soil mapping","volume":"83","author":"Padarian","year":"2015","journal-title":"Comput. Geosci."},{"key":"ref_30","first-page":"397","article-title":"Accuracy assessment: A user\u2019s perspective","volume":"52","author":"Story","year":"1986","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"063567-1","DOI":"10.1117\/1.JRS.6.063567","article-title":"High-resolution tree canopy mapping for New York City using LIDAR and object-based image analysis","volume":"6","author":"MacFaden","year":"2012","journal-title":"J. Appl. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"5763","DOI":"10.1080\/01431161.2017.1346403","article-title":"Subpixel land-cover classification for improved urban area estimates using landsat","volume":"38","author":"Maclachlan","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","unstructured":"Clerc, S., Devignot, O., and Pessiot, L. (2020). Sentinel-2 L1C Data Quality Report 2020, European Space Agency."},{"key":"ref_34","unstructured":"USDA Farm Service Agency, Aerial Photography Field Office (2009). National Agriculture Imagery Program Information Sheet 2009."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Aguilar, R., Zurita-Milla, R., Izquierdo-Verdiguier, E., and de By, R.A. (2018). A cloud-based multi-temporal ensemble classifier to map smallholder farming systems. Remote Sens., 10.","DOI":"10.3390\/rs10050729"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.rse.2017.02.021","article-title":"Mapping major land cover dynamics in Beijing using all Landsat images in Google Earth Engine","volume":"202","author":"Huang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_37","first-page":"199","article-title":"Multitemporal settlement and population mapping from landsatusing google earth engine","volume":"35","author":"Patela","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ravanelli, R., Nascetti, A., Cirigliano, R.V., Di Rico, C., Leuzzi, G., Monti, P., and Crespi, M. (2018). Monitoring the impact of land cover change on surface urban heat island through Google Earth Engine: Proposal of a global methodology, first applications and problems. Remote Sens., 10.","DOI":"10.3390\/rs10091488"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1016\/j.rse.2016.12.026","article-title":"Thematic accuracy assessment of the 2011 National Land Cover Database (NLCD)","volume":"191","author":"Wickham","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"GB2005","DOI":"10.1029\/2006GB002735","article-title":"A satellite-based biosphere parameterization for net ecosystem CO2 exchange: Vegetation Photosynthesis and Respiration Model (VPRM)","volume":"22","author":"Mahadevan","year":"2008","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3958","DOI":"10.1016\/j.rse.2008.07.003","article-title":"Spectral and chemical analysis of tropical forests: Scaling from leaf to canopy levels","volume":"112","author":"Asner","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2180","DOI":"10.1890\/14-2098.1","article-title":"Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties","volume":"25","author":"Singh","year":"2015","journal-title":"Ecol. Appl."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/15\/2399\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:51:53Z","timestamp":1760176313000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/15\/2399"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,26]]},"references-count":42,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2020,8]]}},"alternative-id":["rs12152399"],"URL":"https:\/\/doi.org\/10.3390\/rs12152399","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,26]]}}}