Monitoring of Rapid Urban Sprawl in Beijing with Time Series Remote Sensing Data and Analysis of Driving Forces

Abstract

Beijing has experienced a rapid urban sprawl over the past three decades, along with accelerated socio-economic development. This study investigated the change patterns and figured out the driving forces of urban expansion in the study area. To obtain urban class, decision tree classification techniques were used to identify the land cover types using four scenes of Landsat images from four periods of 1978-era, 1992-era, 2000-era and 2010-era. Then, the urban areas were identified by excluding water, agriculture, forest, grassland and bare land. The analysis results showed that: 1) urban construction land had been expanded very quickly and the urban area is mainly in the south-central part of the municipality; 2) the urban area increased by 96284.97 ha and the ratio was 5.88%; and 3) population growth, economic development, urban construction and industrial structure adjustment could explain the expansion. These analysis results can provide significant information on the monitoring and management of sustainable urban development.