Performance of built-up area classifications using high-resolution SAR data

被引:3
|
作者
Molch, K. [1 ]
Gamba, P. [2 ]
Kayitakire, F. [3 ]
机构
[1] German Aerosp Ctr DLR, German Remote Sensing Data Ctr, D-82234 Wessling, Germany
[2] Univ Pavia, Dept Elect, Telecommun & Remote Sensing Lab, I-27100 Pavia, Italy
[3] Commiss European Communities, Joint Res Ctr, Inst Protect & Secur Citizen, I-21027 Ispra, Italy
来源
CANADIAN JOURNAL OF REMOTE SENSING | 2010年 / 36卷 / 03期
关键词
IMAGES;
D O I
10.5589/m10-040
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Identification of the built-up area from satellite imagery can provide a crucial information layer in disaster mitigation and management and for monitoring urban sprawl, e. g., in developing countries. Spaceborne radar imagery is at an advantage in regions where environmental conditions impede the acquisition of optical image data. Automated exploitation procedures are imperative for efficient, large-area coverage. However, methodologies must be developed or adapted to account for the specific characteristics of synthetic aperture radar (SAR) data. This study evaluates the identification of the built-up area on RADARSAT-1 fine mode and Environmental Satellite (ENVISAT) image mode data using the texture-based, anisotropic, rotation-invariant built-up presence index. Data selection and processing parameters are discussed. User's accuracies of up to 77.5% and overall accuracies of up to 81.3% were achieved in this comparative study without any postclassification editing.
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页码:197 / 210
页数:14
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