A Generalized Regression Neural Network Model of the Landscape Pattern in Yunnan Province, China

Based on the data of land use(LUCC), economic and social factors, and natural factors in 2000, 2005,2010, 2015 and 2018 for 129 counties(districts and cities) in Yunnan Province, a generalized regression neural network(GRNN) model of landscape pattern was established. The result showed that the GRNN model could better quantitatively describe the highly nonlinear relationship between the landscape indexes(PD、LSI、CONTAG、SPLIT、SHDI、SHEI、AI) and driving factors. The determinable coefficients(R₂) of test samples were greater than 0.8. The GRNN model of the landscape pattern could provide basic support for regional early warning of landscape ecological security pattern.