期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2009
卷号：XXXVIII-4/W10
出版社：Copernicus Publications
摘要：Extraction of urban land is one of the necessary process in the change detection of urban growth. This Paper build a unified conceptual model to make the extraction more effectively and accurately based on the model of V-I-S (Vegetation- Impervious surface- Soil). The unified conceptual model uses the Decision Tree Algorithm with characteristics of spectrum and texture, etc. Using this model, we found common and unique indices from multi-source image data according to their similarity and dissimilarity. These indices were to remove the other land-use information (e.g. vegetation and soil), then leave the urban information as the result. They follow the same procedures conducted by the decision tree. The TM-5 image (30m) and the SPOT-4 image (20m) from Chaoyang (Beijing) were used in this paper. The analysis results show that the overall accuracy of TM- extraction is 88%, while the SPOT- extraction 86.75%. It provides an appropriate method to meet the demand of the change detection of urban growth
关键词：Multi-Source Image Data; Decision Tree; Unified Conceptual Model
