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Analysis On The Characteristics And Driving Forces Of Spatial And Temporal Changes Of ZhangGong District City Expansion In Ganzhou City

Posted on:2022-01-10Degree:MasterType:Thesis
Country:ChinaCandidate:X C LuoFull Text:PDF
GTID:2480306557460964Subject:Geography
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The accelerating urbanization process has brought a series of problems such as overconcentration of urban population,shortage of resources,urban heat island effect,traffic jam,etc.Therefore,it is of great significance to monitor the dynamic changes of urban development and study the driving factors of urban expansion in time for mastering the urban development process,making rational use of land,and making systematic urban planning decisions.In this paper,the Zhang Gong district of Ganzhou City is taken as the research area.Based on GIS and RS,the remote sensing images and luminous remote sensing data of Zhang Gong district of Ganzhou City in 1998,2003,2008,2013 and 2018 are used to extract the boundary of urban built-up area of Zhang Gong district of Ganzhou City.On this basis,using the methods of urban expansion intensity,expansion speed,fractal dimension,urban center of gravity and buffer zone analysis,the dynamic changes and spatial expansion characteristics of Zhang Gong district city in Ganzhou city are analyzed.Through the combination of quantitative and qualitative methods,this paper analyzes the driving mechanism of urban expansion in Zhang Gong district of Ganzhou City from the aspects of economy,population,nature and transportation.The main contents and achievements of this study are as follows:(1)The extraction method of urban built-up area is studied.At first,the DMSP?OLS night light data is corrected by using the invariant target area method,and the NPP?VIIRS night light data is subjected to annual average image synthesis,negative value elimination,unstable light source and background noise elimination,and Landsat images are preprocessed by ENVI 5.3 software.Spectral features,texture features and VANUI features are extracted from Landsat images and night light data.Then,three groups of experimental schemes were designed.Random forest algorithm was used to extract urban built-up area information based on Landsat spectral features,combining Landsat spectral features with texture features,and integrating Landsat spectral features,texture features and VANUI features.The results show that scheme 3 can effectively extract the information of urban built-up areas,and the extraction accuracy is greatly improved compared with scheme 1 and scheme 2.In addition,the data combination of spectral features,texture features and VANUI features can effectively distinguish rural residential land,bare soil and cultivated land from urban built-up areas,and can reduce the small noise often found in classification,while preserving the internal spatial details of urban built-up areas.This paper discusses the classification and extraction accuracy of the optimal data combination by random forest algorithm,support vector machine and maximum likelihood method.The experimental results show that the random forest algorithm has the highest accuracy in urban built-up area extraction.Based on the random forest algorithm,five land use classification maps of Zhang Gong district in Ganzhou City from 1998 to 2018 were extracted from the data combination of Scheme 3,and the boundaries of urban built-up areas were extracted.(2)The change of the number of urban expansion in Zhang Gong district of Ganzhou City is analyzed.This paper analyzes the urban expansion dynamics of Zhang Gong district in Ganzhou City by using the expansion area change,expansion speed and expansion intensity.The results show that from 1998 to 2018,the urban built-up area of Zhang Gong district in Ganzhou City increased from 16.24 [km] 2 in 1998 to 97.93 [km] 2 in 2018,with an average annual expansion speed of 4.08 [km] 2/a.Among them,the urban expansion was the fastest in 2013-2018,while the urban expansion was the slowest in 1998-2003;On the whole,the changing trend of urban expansion area,expansion speed and expansion intensity in Zhang Gong district of Ganzhou City showed an increasing trend year by year from 1998 to 2018.(3)The spatial form of urban expansion in Zhang Gong district of Ganzhou City is analyzed.Fractal dimension,center of gravity shift,equal fan analysis and buffer zone analysis are used to analyze the spatial form of urban expansion in Zhang Gong district of Ganzhou City.The results show that from 1998 to 2018,the urban expansion direction of Zhang Gong district of Ganzhou City mainly concentrated in the west,southwest and south directions;In the past 20 years,the center of gravity of the urban built-up area in Zhang Gong district,Ganzhou City has shifted from west to south as a whole.The urban fractal dimension of Zhang Gong district in Ganzhou city shows a trend of rising first and then falling,which indicates that the urban form has become regular and complete at present.Through the analysis of buffer zone,it is found that the most obvious area of urban expansion occurred4-6km away from the center of gravity of the city from 1998 to 2018.(4)Using quantitative and qualitative methods to explore the driving factors of urban expansion.Selecting a number of socio-economic indicators,using SPSS 25 software to carry out principal component analysis and regression analysis,it is found that the improvement of residents' living standards,GDP,fiscal revenue,investment in fixed assets,population,traffic construction and industrial structure are the main driving factors of urban expansion in Zhang Gong district,Ganzhou City.It qualitatively analyzes and describes the driving forces of urban expansion in Zhang Gong district,Ganzhou City from the aspects of economy,population,transportation and nature.The growth of GNP and tertiary industry,the growth of urban population and the improvement of transportation facilities promote the urban expansion of Zhang Gong district,Ganzhou City,while the natural environment restricts the outward expansion of the city.
Keywords/Search Tags:Urban expansion, nighttime lighting data, spatiotemporal evolution, driving force analysis
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