Multi-temporal remote sensing of land cover change and urban sprawl in the coastal city of Yantai, China

Abstract

The importance of accurately mapping and monitoring land cover changes over time is increasing, especially in rapidly growing coastal cities. In this study, three pairs of Landsat images of Yantai, a representative coastal city in China, from 1989, 1999, and 2009 were selected to monitor land cover changes and urban sprawl dynamics. To improve the classification accuracy, three classification methods together with the minimum noise fraction (MNF) and pixel purity index (PPI) calculations were performed on the images. The classification results showed that the overall five-class classification accuracies averaged 91.38% for the 20-year period, which produced an accuracy of 83.78% for change maps. The analysis of change maps indicated that from 1989 to 2009, the percentage of urban area increased from 31.41% to 50.28% of the total area, and the newly urbanized area was mainly located in residential areas and the reclaimed harbor region. Analysis of the relationships between urban area and its driving forces obtained from statistical data found that the urban sprawl of Yantai before 2000 was relatively extensive, which is consistent with the conclusion drawn by using remote sensing techniques. The research results could be used as inputs for sustainable urban management and establishing Digital Earth database.