GeoCDX: An Automated Change Detection and Exploitation System for High-Resolution Satellite Imagery
| Autor: | Curt H. Davis, Yonghong Li, N. J. Hudson, James M. Keller, Grant J. Scott, Matthew Nicholas Klaric, S. T. Barratt, Brian C. Claywell, O. Sjahputera |
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| Rok vydání: | 2013 |
| Předmět: |
Geographic information system
Contextual image classification Computer science business.industry Feature extraction Multispectral image Image registration Panchromatic film General Earth and Planetary Sciences Computer vision Satellite imagery Artificial intelligence Electrical and Electronic Engineering business Change detection |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing. 51:2067-2086 |
| ISSN: | 1558-0644 0196-2892 |
| Popis: | We have developed a fully automated system for change detection of high-resolution satellite imagery. Our system, GeoCDX, is sensor-agnostic, resolution-independent and designed to process the very large volumes of data collected by modern high resolution panchromatic and multispectral imaging satellites. GeoCDX performs fully automated coregistration of imagery; extracts high-level features from the satellite imagery; performs change detection processing to pinpoint locations of change; clusters image tiles to group similar regions of change; and presents results in a variety of ways in an easy-to-use web application that facilitates online discovery, analysis, and dissemination of the change detection results. We applied GeoCDX to 4121 image pairs and successfully coregistered over 91% of the pairs covering a total area greater than 370 000 km2; GeoCDX decreased the average coregistration error from 9.6 ± 8.6 m to 1.8 ± 1.2 m. We show that for some pairs, GeoCDX provides up to a 50% increase in users' efficiency compared to manually performing change detection in common GIS software. Moreover, the change detection assessment performed using GeoCDX was on average four times more accurate compared to the manual approach in large part due to the use of our change intensity map that provides visual cues to the user during exploitation. Finally, change detection analysis using GeoCDX resulted in a missed detection rate of less than 2%. |
| Databáze: | OpenAIRE |
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