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The land use change detection methods using remote sensing data have been studied for a long term. All of these methods can be divided into three levels: pixel-level, feature-level and knowledge-level. In this paper, the advantages and disadvantages of these methods are analyzed, and a novel approach is proposed to detect the land use changes using the object-based feature consistency analysis. The...
Non-wood forest is a kind of important forest resource. This paper focused on the information extraction of non-wood forest based on Advanced Land Observation Satellite (ALOS) data. Band characteristics were analyzed to get understanding of this data wholly by information content, correlation coefficient and Optimum Index Factor (OIF). A new set of data with eight bands were obtained by the fusion...
In this paper, coastline has been extracted from remote sensing image using the supervised classification method through the research of remote sensing image features. The coastline extraction can be very accurate when the seawater features are obviously consistent in image. For the calm sea image, the coastline can be extracted accurately based on supervised classification. But for the images that...
With the high-speed urbanization in China today, the scale of urban and rural construction is expanding constantly. In this paper, with the help of remote sensing image processing software, Landsat TM and Spot4 remote sensing images from 1990-2006 were used to extract urban and rural construction land use information firstly. Then with literature, statistical yearbook and relevant information, GIS...
Estimating geographic information from an image is an excellent, difficult high-level computer vision problem whose time has come. The emergence of vast amounts of geographically calibrated image data is a great reason for computer vision to start looking globally on the scale of the entire planet. In this paper, we propose a correlated association rule based framework for querying an image database...
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