利用主成分分析改善土地利用变化的遥感监测精度——以珠江三角洲城市用地扩张为例

Accuracy Improvement of Land Use Change Detection Using Principal Components Analysis: A Case Study in the Pearl River Delta

近年来,珠江三角洲由于经济的快速发展,城市用地急剧增加。利用多时相的遥感图象,可以定量地监测这种城市化的现象。但是,由一般的遥感动态监测方法所得的结果往往夸大变化的程度,以及获得一些不合理的结论。该文提出利用主成分分析的方法来改善遥感动态监测的精度。将该方法应用于珠江三角洲发展最快的东莞市,获得了较满意的结果。

The Pearl River Delta is experiencing a fast urban growth in recent years which is responsible for rapid loss of the valuable agricultural land in the region. There is a great need to monitor the urban expansion using remote sensing for urban planning and management purposes. However, it has been well recognized that there is significant over-estimation of land use change inusing multitemporal images in change detection. The problem is due to inadequate creation of classification signatures in the classification of remote sensing images. This paper presents an improved method using principal components analysis of stacked multi-temporal images. It is found that this method can reduce the errors in land use change detection and provide a very useful method in monitoring land use changes in the Pearl River Dalta.