{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T07:01:07Z","timestamp":1780297267777,"version":"3.54.0"},"reference-count":50,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T00:00:00Z","timestamp":1778544000000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Transactions in GIS"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Rapid urban expansion poses significant threats to peri\u2010urban ecosystems, driving land use change, thermal intensification, and degradation of air quality in transitional landscapes. In this study, we used the Google Earth Engine (GEE) platform to track environmental dynamics in Changsha District, China a rapidly urbanizing city in Hunan Province across 5\u2009years (2018\u20132022) using Sentinel\u20102 satellite images and atmospheric data derived from Sentinel\u20105P TROPOMI. Supervised classification was applied to create land use\/land cover (LULC) maps, and several spectral indices were calculated such as NDVI, NDWI, along with land surface temperature (LST) and atmospheric pollutants (NO\n                    <jats:sub>2<\/jats:sub>\n                    , SO\n                    <jats:sub>2<\/jats:sub>\n                    , CO) to assess vegetation health, water condition, thermal patterns, and air quality pressure. The findings show that NDVI values ranged from \u22120.23 to 0.62 during the study period, with the highest vegetation vigor observed in 2020 (NDVI max: 0.62) and declining slightly by 2022 (NDVI max: 0.59). NDWI values indicated variable water content, ranging from \u22120.56 to 0.30, with peak water availability in 2020. Land surface temperature increased notably from 2018 (15.18\u00b0C\u201330.24\u00b0C) to 2022 (17.61\u00b0C\u201333.85\u00b0C), indicating intensified urban heat island effects. LULC analysis revealed substantial urbanization, with built\u2010up areas expanding across the central corridor while vegetation cover showed spatial reorganization. Atmospheric pollutants exhibited concerning patterns: NO\n                    <jats:sub>2<\/jats:sub>\n                    concentrations peaked in urban cores with values reaching 0.22 in 2018 and 0.14 in 2020\u20132022, SO\n                    <jats:sub>2<\/jats:sub>\n                    showed highly variable spatial distribution with values from \u22126.93 to 0.39, and CO levels remained consistently high (0.03\u20130.49) throughout the study period, particularly in central urban zones. Overall, the study highlights the usefulness of GEE for monitoring environmental changes on a large scale and gives a closer look at the complex interactions affecting ecosystem sustainability under rising human pressure.\n                  <\/jats:p>","DOI":"10.1111\/tgis.70283","type":"journal-article","created":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T03:26:09Z","timestamp":1778642769000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning Driven Monitoring of Landscape Dynamics Under Urban Expansion Using Cloud\u2010Based Satellite Analytics"],"prefix":"10.1111","volume":"30","author":[{"given":"Abubaker","family":"Ahmed","sequence":"first","affiliation":[{"name":"School of Automation Engineering Wuxi University  Wuxi China"},{"name":"College of Engineering Karary University  Omdurman Sudan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sardar 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