Dynamic Analysis Of Urban Expansion In Inner Mongolia During 1992 To 2013 Based On Nighttime Light Data

Geographical conditions which can be monitored by urban expansion and urbanization is a vital basic national condition of China. With the fast step of the urbanization across the nationwide, urban expansion of Inner Mongolia autonomous region expended quickly. As "3S" integration technology used in urban remote sensing, the application of remote sensing methods in growing numbers are beginning to applied to the analysis of the development and expansion of cities. Nowadays remote sensing has formed a shape which from the ground to the space, from geographic information data collection,processing to the topology analysis and application of superposition, as a significant mean to obtained the resources environment information and urban basic geographic information. DMSP/OLS nighttime light images can monitor the nighttime lights in the world as a remote sensing method. Night lights changed significantly in the built-up areas, so we can extract urban and country easily through the DN value variations from 0-63, it is useful to the urban expansion analysis.In this research, we performed a case study of urban expansion analysis in Inner Mongolia using time series nighttime lights. Twenty-two annual stable DMSP/OLS data (from 1992 to 2013) are chose in this paper. All the data are calibrated through rational function model. Then we developed a novel optimal threshold selected method. Built-up areas are extracted based on the dynamic binary threshold method and support vector machine (SVM) classification algorithm. The extracted built-up areas are analyzing by spatial overlay analysis and mapping a series of urban expansion overlaid pictures and typical urban gravity migration angle and migration distance diagrams from 1992 to 2013.Finally, the most important driving factors of the built-up areas expansion are found out. We obtained the following conclusions:(1) Through the calculation of probability and statistics and the correction parameters of rational function model fitting correction parameters, verified the method of "one based on stable mapping point lights at nighttime images radiation correction method" can calibration DMSP/OLS nighttime lights image data in a high precision, fast and efficient correction way are verified.(2) According to the characteristics of the Mongolian plateau nighttime lights, creating a new dynamic binary threshold method and combining support vector machine (SVM) classification algorithm are created to determine the optimal threshold value. With the combination of these two methods, we can extract the urban built-up figures of Inner Mongolia cities in a quick and high precision way.(3) Through the overlay analysis of built-up areas during 1992 to 2013,and combined with the natural condition and the region policy factors to evaluate the typical areas expansion, the results showed that: with the policy support and economic development in recent years, which make twelve cities of Inner Mongolia autonomous region have expanded in varying degrees.Among them, we can draw a conclusion that Hohhot city sprawl mainly to the southeast direction 26.35° after the year of 1996, and the migration distance is 22941m during 1996 to 2008. Besides the gravity migration distance in Baotou city is 13888m, and has a direction to the southeast 48.47° after 2008. In addition, Ordos city shows expansion as "two cities" mode, the built-up areas center of gravity moved towards the direction of the southwest 105.53° and the distance is 26788 m during 2004 to 2013.(4) Due to the varying degrees of expansion extent varies largely in the twelve cities of Inner Mongolia autonomous region. In order to find out the main driving factors which influence the Inner Mongolia autonomous region city expansion, four factors are processed with correlation analysis and linear regression analysis in this paper. Results showed that power consumption has the highest correlation with built-up areas in single factors. By combining the multiple linear regression analysis, we find that the combination of total population as enhancement factor which combine with power consumption are the biggest driving factors of all the influential driving factors combination.Meanwhile, the decision of government also has much impact on the built-up areas development and sprawl.