Evaluation on the Two Filling Functions for the Recovery of Forest Information in Mountainous Shadows on Landsat ETM ＋ Image

• Published in: Journal of mountain science 2011-06, Vol.8 (3), p.414-426
• Main Authors: Shahtahmassebi, Amir reza, Wang, Ke, Shen, Zhangquan, Deng, Jinsong, Zhu, Wenjuan, Han, Ning, Lin, Fengfang, Moore, Nathan
• Format: Article
• Language: English
• Subjects: classification; Earth and Environmental Science; Earth Sciences; Ecology; Environment; ETM图像; Forests; Geography; Landsat; Landsat satellites; Mapping; Mountain regions; Mountains; Remote sensing; Topography; 信息合成; 填充函数; 山区森林; 灌装技术; 评价; 阴影校正; 陆地卫星
• ISSN: 1672-6316; 1993-0321; 1008-2786
• DOI: 10.1007/s11629-011-2051-5

In general,topographic shadow may reduce performance of forest mapping over mountainous regions in remotely sensed images.In this paper,information in shadow was synthesized by using two filling techniques,namely,roifill and imfill,in order to improve the accuracy of forest mapping over mountainous regions.These two methods were applied to Landsat Enhanced Thematic Mapper （ETM ＋） multispectral image from Dong Yang County,Zhejiang Province,China.The performance of these methods was compared with two conventional techniques,including cosine correction and multisource classification.The results showed that by applying filling approaches,average overall accuracy of classification was improved by 14 percent.However,through conventional methods this value increased only by 9 percent.The results also revealed that estimated forest area on the basis of shadow-corrected images by ＇roifill＇ technique was much closer to the survey data compared to traditional algorithms.Apart from this finding,our finding indicated that topographic shadow was an accentuated problem in medium resolution images such as Landsat ETM＋ over mountainous regions.