Spatiotemporal Dynamics of Urbanization, Rangeland, and Environmental Indicators Using Remote Sensing and Google Earth Engine

Rangeland ecosystems in rapidly urbanizing regions face unprecedented pressures from land use transitions, climate variability, and anthropogenic activities. This study examines the spatiotemporal dynamics of rangeland change in Hangzhou, China, using multitemporal satellite data and the Google Earth Engine (GEE) platform from 2016 to 2023. The research integrates Land Use Land Cover (LULC) classification, vegetation indices (NDVI, EVI), water availability indicators (NDWI), Land Surface Temperature (LST), and atmospheric pollutants (CO, NO₂, SO₂) to understand rangeland transformations in the context of urban expansion. Results reveal a remarkable expansion of rangeland from 52.7 km² (4%) in 2016 to 90.5 km² (7%) in 2023, representing a 71.7% increase over the study period. This expansion occurred simultaneously with a significant decline in cropland area from 464.2 km² (36%) to 346.8 km² (27%) and an increase in built area from 477.5 km² (37%) to 649.1 km² (51%). Spatial analysis indicates that rangeland gains predominantly occurred in areas previously used for agriculture, suggesting patterns of land abandonment or conversion. Environmental indicator analysis shows complex relationships between rangeland dynamics and atmospheric conditions, with CO concentrations remaining relatively stable (0.0334–0.0391), while NO₂ and SO₂ exhibited spatial heterogeneity across the study area. The integration of remote sensing data with the GEE platform proved effective for monitoring rangeland changes at the landscape scale, providing critical insights for sustainable land management and ecosystem conservation in rapidly changing urban-rural interfaces.