Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 53, Issue 7, Pages 3737-3748Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2014.2382566
Keywords
Geographical information system; geoprocessing Web service; geospatial feature; object-based image analysis (OBIA); regular shape similarity index (RSSI); remote sensing (RS)
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Funding
- National Basic Research Program of China [2011CB707105]
- Program for New Century Excellent Talents in University [NCET-13-0435]
- Ministry of Education [201261909]
- U.S. Department of Energy [DE-NA0001123]
- Directorate For Geosciences
- ICER [1440294] Funding Source: National Science Foundation
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It still remains a big challenge to accurately identify the geospatial objects with well-regulated outlines within remote sensing (RS) images such as residential buildings, factory storage buildings, highways, local roads, cars, and planes. In this paper, a novel spatial feature index, which is named regular shape similarity index (RSSI), is defined to address the challenge. It represents the ratio between the area of an object and its minimum bounding shape area. The application of RSSI in identifying objects with different shapes is discussed, and its capability is found to be a great supplement to the existing spatial feature hierarchy. An approach combining RSSI with object-based image analysis (OBIA) technology is proposed for image object extraction. A Web service for RSSI calculation is developed and integrated into a Web OBIA system. In the system, four experiments extracting factory storage buildings, residential buildings, roads, and planes, respectively, are conducted on three large-scale high-resolution RS images. In each experiment, two tests, i.e., one using traditional spatial features and the other using RSSI, are performed and compared. The results show that RSSI improves the accuracy of regular object extraction.
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