{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T14:42:30Z","timestamp":1775054550940,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T00:00:00Z","timestamp":1683676800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003130","name":"FWO research foundation","doi-asserted-by":"publisher","award":["1S11218N"],"award-info":[{"award-number":["1S11218N"]}],"id":[{"id":"10.13039\/501100003130","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Geomatics Section of the Department of Civil Engineering of KU Leuven","award":["1S11218N"],"award-info":[{"award-number":["1S11218N"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land Use\/Land Cover (LULC) mapping is the first step in monitoring urban sprawl and its environmental, economic and societal impacts. While satellite imagery and vegetation indices are commonly used for LULC mapping, the limited resolution of these images can hamper object recognition for Geographic Object-Based Image Analysis (GEOBIA). In this study, we utilize very high-resolution (VHR) optical imagery with a resolution of 50 cm to improve object recognition for GEOBIA LULC classification. We focused on the city of Nice, France, and identified ten LULC classes using a Random Forest classifier in Google Earth Engine. We investigate the impact of adding Gray-Level Co-Occurrence Matrix (GLCM) texture information and spectral indices with their temporal components, such as maximum value, standard deviation, phase and amplitude from the multi-spectral and multi-temporal Sentinel-2 imagery. This work focuses on identifying which input features result in the highest increase in accuracy. The results show that adding a single VHR image improves the classification accuracy from 62.62% to 67.05%, especially when the spectral indices and temporal analysis are not included. The impact of the GLCM is similar but smaller than the VHR image. Overall, the inclusion of temporal analysis improves the classification accuracy to 74.30%. The blue band of the VHR image had the largest impact on the classification, followed by the amplitude of the green-red vegetation index and the phase of the normalized multi-band drought index.<\/jats:p>","DOI":"10.3390\/rs15102501","type":"journal-article","created":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T01:57:51Z","timestamp":1683683871000},"page":"2501","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Land Use and Land Cover Mapping with VHR and Multi-Temporal Sentinel-2 Imagery"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9196-2912","authenticated-orcid":false,"given":"Suzanna","family":"Cuypers","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, Geomatics Section, Faculty of Engineering Technology, KU Leuven, 3001 Leuven, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9692-8636","authenticated-orcid":false,"given":"Andrea","family":"Nascetti","sequence":"additional","affiliation":[{"name":"Department of Geography, Faculty of Science, University of Li\u00e8ge, Place du 20 Ao\u00fbt 7, 4000 Li\u00e8ge, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3465-9033","authenticated-orcid":false,"given":"Maarten","family":"Vergauwen","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Geomatics Section, Faculty of Engineering Technology, KU Leuven, 3001 Leuven, Belgium"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"105902","DOI":"10.1016\/j.landusepol.2021.105902","article-title":"Modelling urban sprawl and assessing its costs in the planning process: A case study in Flanders, Belgium","volume":"113","author":"Vermeiren","year":"2022","journal-title":"Land Use Policy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1080\/17445647.2017.1372316","article-title":"Fusion of sentinel-1a and sentinel-2A data for land cover mapping: A case study in the lower Magdalena region, Colombia","volume":"13","author":"Clerici","year":"2017","journal-title":"J. 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