Monitoring And Analysis Of Urban Expansion In Eastern Coastal Area Of China Based On DMSP/OLS Night Lights Image

A city is an important place for human life and an active part of the ecosystem. Since theinitiation of reform and opening up in1978, China has experienced rapid urbanization, anddevelopment speed and scale of construction land is continually expanding. In this paper,taking the well-developed east coastal area in China as the study area, based on DMSPnighttime lights imagery and SPOT-VGT data, the urban areas from1998to2010wasextracted using support vector machine (SVM) algorithm and the changes of urban extent infive periods were analyzed. The gray correlation analysis method and BP neural networkmodel were applied to explain the main socio-economic driving factors and mechanism ofurban sprawl in east coastal area during recent13years. Through the exploration on theextraction and analysis methods of macro scale urban areas from remote sensing images, thecharacteristics of urban sprawl were obtained and evaluated, which not only is the feedback ofrapid urbanization in the study area, but also provide a more scientific basis for futureurbanization construction. The study has important practical and theoretical significance topromote the sustainable development of social economy of coastal area and even the wholecountry.The main conclusions are as follows:1. The extracted macro-scale urban information from DMSP nighttime lights imageryand SPOT-VGT data using support vector machines (SVM) algorithm had greater accuracythan NDBI algorithm and threshold method. The result can accurately reflect urban areasextent.2. From1998to2010, both the amplitude and speed of urban sprawl in east coastalregion in China was high. The average annual growth rate was as high as13.31%, and thelowest value of8.11%was found in2007. In general, urban expansion ofBeijing-Tianjin-Hebei metropolitan region (Jing-Jin-Ji) and the Pearl River Deltacharacterized from the center to surrounding areas, whereas the urban land development ofYangtze River Delta showed a connecting pattern. During2007~2010, the rate of urbanexpansion was11237km2per year, and the urban sprawl intensity reached the peak value of2.565. From2004to2007, the dynamic degree of urban land expansion was only8.785%.Except for the period of1998~2001, the rate of urban expansion in Jiangsu Province hadbeen in a leading position. The rate and intensity of urban expansion in Hainan Province werethe lowest during2004~2007. From2001to2004, the dynamic degree of urban expansion ofJiangsu Province was highest, while the minimum value (2.163%) was found in Beijing forthe period of2004~2007. Compared to other provinces (municipalities), Shanghai has higher intensity of urban expansion and reached the maximum of4.174druing2004~2007.3. According to the analysis of spatial characteristics of urban expansion, the movingdirection and extent of urban gravities in major cities and urban agglomerations of easterncoastal areas were different. The urban development center gradually shifted to the northeastin Beijing, while the moving extent of Jing-Jin-Ji urban agglomeration gravity was small. Theurban land centers in Shanghai and Hangzhou moved towards southwest, and the centroid ofthe Yangtze River Delta shifted to the same direction but with greater moving magnitude.Generally speaking the center of Guangzhou City moved to the northeast, on the contrary, thecentroid of the Pearl River Delta city group shifted to the southwest. From1998to2010, therewere two land expansion patterns in Beijing, that is, from the city center to the surroundingarea and building expansion in internal urban, while the compact value of urban areasindicated that urban sprawl was very unstable. After2007, the fractal dimension of urbanareas in Shanghai and Hangzhou were gradually decreased. The development process ofGuangzhou was similar to Shanghai and Hangzhou. Since2001, Guangzhou began to focuson the construction of built-up area and urban sprawl tended to be reasonable.4. The grey correlation degree analysis of urban sprawl factor showed that urbanexpansion in the eastern coastal area were closely related to the following soci-economicfactors including GDP, fiscal revenue, construction output, total fixed asset investment andurban residents per capita annual disposable income. The most important impact factors ofurban expansion in the different provinces (municipalities) were different. Five influencefactors derived from gray correlation model were applied to build the BP neural networkmodel to simulate urban land. The results show that actual area had high correlation with theestimated values of the entire study area. The fitting residuals of urban land betweenprovinces (municipalities) were different and the relative errors between simulated and actualvalues were very small. The driving forces of urban expansion in eastern coastal area of Chinafrom1998to2010were revealed.