Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 157-162, 2016
https://doi.org/10.5194/isprs-archives-XLI-B1-157-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
02 Jun 2016
ASSESSMENT OF FOUR TYPICAL TOPOGRAPHIC CORRECTIONS IN LANDSAT TM DATA FOR SNOW COVER AREAS
Yan Zhou1,2, He Jiang1, Zhe Wang1, Xiaoxia Yang3, and Erhui Geng1 1School of Resources and Environment, University of Electric Science and Technology of China (UESTC)
2Institute of Remote Sensing Big Data, Big Data Research Center, UESTC, 2006 Xiyuan Avenue, West Hi-tech Zone, Chengdu, 611731, China
3College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
Keywords: Landsat TM, topographic correction, Cosine correction, C correction, SCS correction, SCS+C correction, snow cover, NDSI Abstract. The accuracy of snow cover information extraction in remote-sensing images dependent on a variety of factors, especially in mountain area with complex terrain. This paper aims at analyzing the accuracy of snow cover information extraction from remot esensing images, using Landsat5 TM images and DEM data, with the study area of Xinjiang Tianshan, measuring topographic correction effects of Cosine correction, C correction, SCS correction, and SCS + C correction from four aspects: visual comparison, standard deviation, correlation analysis and histogram, then extract snow cover area for study area. Results showed that C correction and SCS+C correction performed better among four classic terrain correction models, which indicated changes in snow pixel rat io after correction with variation range of 2% , and correlation coefficient of each band is highest before and after correction.
Conference paper (PDF, 1197 KB)


Citation: Zhou, Y., Jiang, H., Wang, Z., Yang, X., and Geng, E.: ASSESSMENT OF FOUR TYPICAL TOPOGRAPHIC CORRECTIONS IN LANDSAT TM DATA FOR SNOW COVER AREAS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 157-162, https://doi.org/10.5194/isprs-archives-XLI-B1-157-2016, 2016.

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