ABSTRACT

Research and analysis of urban growth and its driving factors are crucial to the long-term sustainable development of cities. Based on the multi-temporal Landsat remote sensing data, this paper extracts urban information by interpreting and supervising classification, and makes a dynamic study on the urban expansion of Harbin in different temporal intervals. By analyzing the spatial determinants of urban growth, we deeply understand the process of urban growth, thus providing important help for urban planning and policy formulation. In this paper, four landscape metrics (total area, aggregation index, landscape shape index, and total edge) were selected to characterize the urban landscape characteristics from two spatial scales (2 and 5 km grid sizes), then the spatial regression model was used to explore the relationship between the urban landscape and its spatial determinants. These changes exhibit significant spatial variations and spatial autocorrelation at two spatial scales. Topography and proximity factors have important effects on urban landscape change. These research results may help us to better understand the process and driving factors of urban development, so as to help the underdeveloped cities in northeast China to formulate scientific and reasonable development plans and policies.