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The high-speed economic development inevitably led to rapid changes in land cover types, e.g., an increment in artificial features (built-up) and decrement in natural features (vegetation). However, (1) many previous studies focus on the land cover change in metropolis or at the global scale, yet few focus on underdeveloped but fast-growing cities; (2) land cover studies mainly focus on global variations, yet seldom on local characteristics. Thus, it is of great significance to monitor the land cover change for the city with the fastest economic growth in China based on the long time-series satellite images from both global and local perspectives. In this study, with support from huge amounts of data (including 719 Landsat TM\/ETM+\/OLI satellite images, land surface temperature, nighttime satellite images, DEM, multiple land cover products, and various auxiliary data), processing and parallel computing abilities of the GEE platform, classification maps of land cover in Hefei from 2000 to 2020 are produced based on a random forest machine learning method, and the spatio-temporal variations and driving factors are analyzed from both global and local viewpoints. The results show that: (1) the classification accuracy is excellent; the average overall accuracy is 93% and the Kappa coefficient is 0.88; (2) the general spatio-temporal variations in land cover in Hefei from 2000 to 2020 are obvious; the built-up area expanded from 419.72 km2 to 1530.20 km2, with a total growth rate of 264.58%. With the expansion of the built-up area, the vegetation coverage decreased by 16.61% (1652.56 km2); (3) the land surface temperature shows an increment trend in the new town yet a decrement trend in the old town due to the change in vegetation coverage and the decentration of administration centers; further analysis shows that the population and the social economy are two driving factors for land cover changes. It is worth noting that both the area and coverage of vegetation in the old town and water body area in Hefei increased significantly, although the fast urbanization inevitably caused a decrement in vegetation and water area in the whole city, indicating both the high-speed economic development and improvement in green surfaces simultaneously experienced in Hefei from 2000 to 2020.<\/jats:p>","DOI":"10.3390\/rs15061604","type":"journal-article","created":{"date-parts":[[2023,3,16]],"date-time":"2023-03-16T02:40:11Z","timestamp":1678934411000},"page":"1604","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Study of Land Cover Change in the City with the Fastest Economic Growth in China (Hefei) from 2000 to 2020 Based on Google Earth Engine Platform"],"prefix":"10.3390","volume":"15","author":[{"given":"Jun","family":"Geng","sequence":"first","affiliation":[{"name":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lichen","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"},{"name":"Anhui Institute of Geological Surveying and Mapping, Hefei 230022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuping","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Hefei University of Technology, Hefei 230009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Tu","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, Anhui Agricultural University, Hefei 230036, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.isprsjprs.2016.03.008","article-title":"Optical remotely sensed time series data for land cover classification: A review","volume":"116","author":"Cristina","year":"2016","journal-title":"ISPRS-J. 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