Abstract
Abstract. Digital Surface Models (DSMs) can assist building change detection in a variety of approaches. Limited to the quality of DSMs from satellite stereo imagery, it is hard to reach precise change detection results using only DSMs. Therefore, DSMs should be used in combination with the spectral information from original stereo imagery. For that purpose, two fusion based methods, one using feature level fusion and the other using decision level fusion are proposed in our previous research. In this paper, these two methods are further evaluated and compared based on two different data sets. One test site features a typical urban environment which is captured by two pairs of very high resolution stereo imagery (IKONOS and WorldView-2). The other test site is located in an industrial area, the corresponding stereo imagery of the two dates are both from Cartosat-1. Quantitative and qualitative experiment results obtained from each dataset are analyzed in detail. Over all, the proposed feature fusion model give better results for the industrial area, while the decision fusion method works much better for the urban environment based on very high resolution imagery.
Highlights
Fast-paced urban and rural developments, as well as more frequent natural disasters have increased the demand for efficient urban monitoring and disaster assessment
Limited to the quality of the Digital Surface Models (DSMs) generated from stereo imagery, it is hard to reach precise change detection results using only the DSMs
DSMs should be used in combination with the spectral information from the original stereo images
Summary
Fast-paced urban and rural developments, as well as more frequent natural disasters (e.g., earthquakes, hurricanes, and tsunamis) have increased the demand for efficient urban monitoring and disaster assessment. Even though 2D data obtained from satellite images from different dates can already provide plenty of useful information, it is usually insufficient when dealing with changes in the vertical direction, especially building changes. Height information provided by Digital Surface Models (DSMs) is indispensable when analyzing these changes. Limited to the quality of the DSMs generated from stereo imagery, it is hard to reach precise change detection results using only the DSMs. DSMs should be used in combination with the spectral information from the original stereo images. As the DSMs are generated using stereo images, spectral information of the same time and area is always available. After orthorectification of these images using the generated DSM, the ortho-image and DSM are well coregistered and can be used together. The main challenge here is how to fuse the information from DSMs and orthoimages
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