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

Abstract

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.

近年來,珠江三角洲由于經濟的快速發展,城市用地急劇增加。利用多時相的遙感圖象,可以定量地監測這種城市化的現象。但是,由一般的遙感動態監測方法所得的結果往往夸大變化的程度,以及獲得一些不合理的結論。該文提出利用主成分分析的方法來改善遙感動態監測的精度。將該方法應用于珠江三角洲發展最快的東莞市,獲得了較滿意的結果。