4.7 Article

Continental-scale validation of MODIS-based and LEDAPS Landsat ETM plus atmospheric correction methods

期刊

REMOTE SENSING OF ENVIRONMENT
卷 122, 期 -, 页码 175-184

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2011.12.025

关键词

Landsat; MODIS; Atmospheric correction; Web-enabled Landsat Data (WELD); Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

资金

  1. NASA's Terrestrial Ecology Program
  2. NASA [NNX08AL93A]
  3. NASA [NNX08AL93A, 98671] Funding Source: Federal RePORTER

向作者/读者索取更多资源

The potential of Landsat data processing to provide systematic continental scale products has been demonstrated by several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent free availability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicable to large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correction methods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmospheric characterization approaches. The MODIS-based method uses the MODIS Terra derived dynamic aerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions in each coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from each Landsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validation results are presented comparing ETM+ atmospherically corrected data generated using these two methods with AERONET corrected ETM+ data for 95 10 km x 10 km 30 m subsets, a total of nearly 8 million 30 m pixels, located across the conterminous United States. The results indicate that the MODIS-based method has better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands. (C) 2012 Elsevier Inc. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据