Sustainable development evaluation of counties emerging from poverty in Chengde based on multi-source data
In order to study the potential of sustainable development in counties that emerged from poverty,this paper studied Chengde City,Hebei Province and constructed the sustainable development index of the counties that emerged from poverty by using the hierarchical analysis method and objective assignment entropy weighting method and combining with the local characteristics of Chengde City. By using multi-source data such as nighttime light images and Gaofen-6,the spatial population,resources,industry,traffic,livelihood,geographic environment,and other factors affecting the sustainable development ability of counties and districts were analyzed. The results of the study show that ① the spatial population element has the greatest influence on the sustainable development of poverty-stricken counties and is the main driving force for the sustainable development of poverty-stricken counties. ② The use of high-resolution image data,GlobeLand30 data,and points of interest can effectively obtain urban geophysical information. ③ The use of multi-source data and the construction of sustainable development indexes can reflect the sustainable development vitality of counties and districts more objectively and comprehensively. ④ There is a certain similarity in the distribution of various indexes,which basically radiates in all directions from the central town in the county. ⑤ The CA-ANN model can be used to effectively predict changes in the development vitality of counties and districts.
remote sensingcounties emerging from povertysustainable developmentcellular automataartificial neural networks
万方数据
维普
