Urban thematic information extraction and dynamic extension detection
Tian Lianghhu, Zhao Yuanhong, Zhang Fuxing
Dept.of earth Science, Zhejiang University
Hangzhou, China
Abstract
Urban remote sensing is an important direction of remote sensing. How to improve its application effectiveness is a problem of scientists. Most of previous classification was under the hypothesis of homogeneity in one landuse, which is much suitable to agricultural application. This assumption is not correct for urban thematic information extraction. Some more approaches available to classification are needed to be developed in order to meet the needs of urban remote sensing. This paper developed a contextual method to improve the accuracy of urban thematic information extraction and determination of city boundaries. Result analysis shows it accuracy is over 91.7%. This is significantly important to highly developing urban area for the administration and decision-making.
Introduction
In the urban remote sensing the problem how is to improve the classification of urban land use and its change detecting. Most of Classification approaches are primarily on the assumption that it is homogeneous in the landuse. This possesses obvious limits in the urban thematic information extraction because of the heterogeneity of urban landuse.
With the further development of high-resolution sensors as SPOT and thematic mapper, the problem above affects greatly the accuracy of urban landuse classification. Karkham and Town-send (1981) and David (1984)discovered that high resolution data (such as TM data) have lower accuracy than low resolution data (such MSS data) in urban classification.
In this paper we describe a contextual method to exploit the spatial-spectral context of a pixel to achieve more accurate classification over a 15x15 square kilometer region of yueyang urban area (see fig.1) Hunan province.
This procedure provides an urban thematic map extracted accurately from 1987's TM data and two boundaries of urban area determined from 1987's TM data. 1978's MSS data, and photographs of 1984's map. The extended changes of Yueyang from 1978 to 1984 and from 1984 to 1987 are detected. It is very successful that accuracy is over 91.7%.
Urban landuse classification
This work is realized by the contextual method applied to landuse classification to improve its accuracy. Contextual information is said to be the relationship of a pixel to any other pixels in the picture. Certain classes of ground cover arelikely to occur in the context of others . One does not expect to find wheat growing in the midst of a housing subdivision for example.
Fig.1 The study area centered on the city of Yueyang, Hunan province
Fig.2 The procedures of urban thematic extraction
Fig.3 The spectral reflection line. 1. vegetation 2.mixtural class 3.urban
