Analysis Of Land Use Change And Driving Force In Chenzhou Based On Google Earth Engine

As people recognize that land surface processes affectes climate change,concerns about land use/cover change appear on the global environmental change research agenda.Land use change research is the core content of global environmental change research.Only by identifying the types of land use changes and analyzing the characteristics of land use changes in time and space can we better understand the land use change process,so as to formulate reasonable policies and take corresponding environmental protection measures To mitigate the negative impact of land use change on environmental changes.In recent years,with the rapid development of social economy,the continuous improvement of urbanization level,the increase of population density and urban expansion,the development of land resources has been increased,the relationship between human and land has been deteriorated and a series of social problems have been brought about.The environmental damage caused by the exploitation of mineral resources is also very serious,and the pressure of environmental protection is increasing.Therefore,the analysis of the temporal and spatial characteristics of land use change and the driving force of land use change in Chenzhou is of great significance for the rational allocation of land resources,the coordination of human land relations,and the corresponding measures for environmental protection to achieve the coordinated development of economy,society,resources and environmental protection.In this paper,Chenzhou City,Hunan Province is taken as the research area.Based on the Google Earth Engine platform,with its advantages of efficient and fast processing and analysis of remote sensing image data,the minimum cloud image of the target year is synthesized.The land use classification data of Chenzhou City from 2000 to 2017 is obtained by using the random forest algorithm.With the help of GIS platform,the single land use dynamic degree,land use comprehensive degree model and land use transfer matrix are used to analyze the temporal and spatial change characteristics of land use in Chenzhou City.Using the principal component analysis method,combined with the social and economic statistical data of Chenzhou City,the paper analyzes the driving factors of land use change in Chenzhou City.The conclusion is as follows:(1)Based on the Google Earth engine platform,the random forest algorithm is used to classify the land use of the image,and the land use classification map of Chenzhou City is extracted.The average overall classification accuracy of the land use classification results obtained in this study is up to 95.09%,kappa coefficient reached 92.64% ?(2)In the past 20 years,the spatial and temporal characteristics of land use in Chenzhou are obvious.From the time point of view,the trend of change is the slow decrease of forest land,the rapid increase of cultivated land,the rapid expansion of construction land,the decrease of water area and the increase of unused land.From the perspective of space,the increased area of cultivated land is mainly distributed in the middle and west of lower altitude,showing a trend of continuous expansion from west to East.The construction land mainly takes the urban area as the core and expands outwards.The construction land of counties and cities also expands outwards around the county seat.Forest land mainly flows to cultivated land,and the reduced areas are Guiyang County and Jiahe County in the west,Yizhang County and Linwu County in the south,Anren County in the northeast,and Rucheng County in the southeast.(3)According to the situation of land use change in Chenzhou,the driving force index system of land use change in Chenzhou is constructed.Principal component analysis is used to analyze the driving force of land use change in Chenzhou and extract the main driving force and secondary driving force of land use change in Chenzhou.The driving factors of land use change in Chenzhou can be summarized as social and economic development,population structure adjustment and industrial structure adjustment.