Effects of atmospheric correction and pansharpening on LULC classification accuracy using WorldView-2 imagery

被引：104
作者：
Department of Forestry and Natural Resources, National Chiayi University, 300 University Rd., Chiayi [1 ]
60004, Taiwan
不详 [2 ]
10608, Taiwan
不详 [3 ]
402, Taiwan
不详 [4 ]
MD
20250, United States
机构：
[1] Department of Forestry and Natural Resources, National Chiayi University, 300 University Rd., Chiayi
[2] Department of Electrical Engineering, National Taipei University of Technology, 1 Zhongxiao E. Rd., Sec. 3, Taipei
[3] Department of Electrical Engineering, National Chung Hsing University, 250, Kuo Kuang Rd., Taichung
[4] Department of Computer Science and Electrical Engineering, UMBC, 1000 Hilltop Circle, Baltimore, 20250, MD
来源：
Inf. Process. Agric. | / 1卷 / 25-36期
关键词：
LULC; Maximum likelihood classifier (MLC); Object-based image analysis; Pixel-based image analysis; Remote sensing; Support vector machine (SVM);
D O I：
10.1016/j.inpa.2015.01.003
中图分类号：
学科分类号：
摘要：
Changes of Land Use and Land Cover (LULC) affect atmospheric, climatic, and biological spheres of the earth. Accurate LULC map offers detail information for resources management and intergovernmental cooperation to debate global warming and biodiversity reduction. This paper examined effects of pansharpening and atmospheric correction on LULC classification. Object-Based Support Vector Machine (OB-SVM) and Pixel-Based Maximum Likelihood Classifier (PB-MLC) were applied for LULC classification. Results showed that atmospheric correction is not necessary for LULC classification if it is conducted in the original multispectral image. Nevertheless, pansharpening plays much more important roles on the classification accuracy than the atmospheric correction. It can help to increase classification accuracy by 12% on average compared to the ones without pansharpening. PB-MLC and OB-SVM achieved similar classification rate. This study indicated that the LULC classification accuracy using PB-MLC and OB-SVM is 82% and 89% respectively. A combination of atmospheric correction, pansharpening, and OB-SVM could offer promising LULC maps from WorldView-2 multispectral and panchromatic images. © 2015 China Agricultural University. Production and hosting by Elsevier B.V.
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页码：25 / 36
页数：11
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