Assessment of cultivated land use change in Guilin using the GeoSOS-FLUS model
Information of spatiotemporal change in cultivated land and its future trends is an essential component for effective land use management. Here,we explore the spatiotemporal change pattern of cultivated land in Guilin with multi-temporal Landsat remote sensing images based on the Google Earth Engine (GEE)cloud platform. Firstly,we comprehensively evaluate five classification methods for their suitability in classifying land use in Guilin. Secondly,we analyze the land use changes,especially the spatiotemporal change pattern of cultivated land from 2000 to 2020. Furthermore,we simulate and predict change in cultivated land under different scenarios in 2030 using the GeoSOS-FLUS model. The results show that the random forest (RF)algorithm demonstrate the highest overall accuracy and Kappa coefficient for land use classification in Guilin. There was a continuous decrease in cultivated land area during 2000 to 2020,with the most pronounced decline observed between 2010 and 2015. Cultivated land was mainly converted to construction land and forests. The Grain for Green Program,the rapid expansion of tourism,and an increase in construction land are the key factors that impact the spatiotemporal change patterns of cultivated land. Under the natural development scenario,it is anticipated that the cultivated land will continue to decrease significantly,while construction land will expanse in 2030. This will have adverse impacts on the ecological environment. Under both the cultivated land protection and ecological control scenarios,an increase in cultivated land area is anticipated. Increase in cultivated land and optimization other land use types will have significant importance for safeguarding food security,promoting the sustainable development of tourism,and ensuring ecosystem stability in Guilin.
changes in cultivated landland use classificationGoogle Earth Enginescenario simulationGuilin
万方数据
维普
