Monitoring urban expending by space Remote Sensing
Wu Qiuhua
Institute of Remote Sensing Application, CAS P.O. BOX. 775, Beijing 100101, China
Abstract
The superiority of change detecting using space remote sensing data lies in the cyclicity of information acquisition. This paper presents several methods for monitoring urban expanding based on Landsat TM data in the case study of Beijing City, China.
As a result of image processing and recognization it was found that several methods, such as principal components analysis, multispectral image classification comparision , band ratio and logical calculation, and vegetation index difference, bring out relatively coincident effects for monitoring urban expanding. With all these research works, it was primarily realized to automatically, localizedly and semi-quantitatively montorurban expending. By comparing accuracies between/among these approaches, it was concluded that PCA method resulted in best monitoring effect which obtained a accuracy of 68.85% in presenting urban expanding information.
This study was accomplished using GEMSTONE image processing system (UK) , GIST geographic in formation system tools (UK) and Terr-mar microcomputer image processing system.
Introduction
Analysis of resource satellite images has been identified as an appropriate means of acquiring information on land-cover and land-use change for the rural-urban fringe, which is very important for administration especially in developing countries. Such information can be obtained from satellites at more frequent intervals and lower cost than by traditional methods, such as ground survey and analysis of aerial photographs. Because of the continued improvements being made in the spectral and spatial quality, the increase in used of satellite data to detect land-use and land-cover change may be anticipated.
Studies on the problems in monitoring urban areas from satellite platforms has been undertaken by B.C.F. Forester ( 1985). It was concluded that the poor spatial resolution of MSS data was the major obstruction for urban development monitoring excepted that Landsat
Thematic Mapper (TM ) data, which has higher spatial and spectral resolution, will lead to higher accuracy for urban expanding monitoring.
In order to achieve better effect in detecting change information ; new technique has been developed besides by using data with higherresulotion. The mathmatic description and mechanism of principal components analysis ( PCA) for change detection has been presented and discussed by Lu Jinju ( 1988), Ashbindu Singh et al ( 1985), Tung Fang et al ( 1987), and S.E. Ingebritsen et al ( 1985) . PCA was used to highlight regions of localized change evident in satellite multispectral imagery associated with bushfire damage and with vegetation regrowth following fires burns by J.A. Richards ( 1984). S.E. Ingrbritsen et al ( 1985) employed PCA to qualitatively indicate the expanding of mine area.
As comparisions with PCA, some other methods may be applied to monitor environment change (T.L. Coleman et al, 1990, Martin. L.R.G. et. al. 1989). The objective of this study is to find relatively efficient technique for monitoring urban expanding by using multitemporal Landsat TM data. In this paper, four change – detection methods are presented. The first is principal components analysis (PCA) of multitemporal TM data. The second method involves the image classification comparision between two dates TM data. The potential of image ratio and logical algorithm will be revealed in the third method. The final method represents urban expanding information via vegetation index difference between two dates. Results of first three methods be quantitatively compared with ground information. The change – detection accuracies are evaluated respectively for each method.
Study Area
The area selected for study is located in and around Beijing City, China. The area, approximating a rectangle of 1020 pixels x 1400 pixels ( almost 36km x 42km), contains a wide range of land-use types found within a rapidly growing city. Fig.1 ( omitted ) are false color composites of TM band 1,4,7 of 1984 and 1988 in which we have seven paris of corresponding sites where land-use changes have taken place during the period from 1984 to 1988. Site No. 1 is where the Asia Game Village now lies. Site No. 2 is where the Fangzhuang construction project locates. Xixiang highway project caused land-use change in the site No. 3. All these land-use change information are well detected by the techniques employed in this study.
Data
Landsat TM imagery was recorded over the study area on 13 October 1984 and on 22 August 1988. Geometric corrections for earth rotation, earth curvature distortion, sensor alignment on the satellite , and satellite position, velocity, and attitude variations was carried out by Beijing Landsat RSGS (Remote Sensing Ground Station ) of China. Radiometric calibrations are also performed on the data.
