Quantitative assessment of coastal zone scene changes and drivers in the coastal zone of the Guangdong–Hong Kong–Macao Greater Bay Area

The intensification of coastal land-use change in rapidly urbanizing regions demands robust, quantitative approaches to attribute and measure driver impacts on landscape transformation. Advances in scene classification using geographic big data have enabled greater spatial and functional resolution in mapping such changes, yet the relative roles and quantification of anthropogenic versus natural drivers in coastal zones remain poorly resolved. Here, we integrate Landsat and Sentinel-2 remote sensing imagery (1990–2019), OpenStreetMap data, and urban and marine zoning information, employing random forest classification and trajectory analysis, to the coastal zone of the Guangdong–Hong Kong–Macao Greater Bay…

• NN
  National Natural Science Foundation of China

  Award: 42306245
• YI
  Youth Innovation Promotion Association of the Chinese Academy of Sciences

  Award: 2023060