A MODIFIED VEGETATION INDEX BASED ALGORITHM FOR THERMAL IMAGERY SHARPENING

被引：8

作者：

Chen, Ling ^{[1
]}

Yan, Guangjian ^{[1
]}

Ren, Huazhong ^{[1
]}

Li, Aihua ^{[1
]}

机构：

[1] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Sch Geog, Beijing 100875, Peoples R China

来源：

2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2010年

关键词：

Land surface temperature; vegetation index; soil wetness index; Image sharpening; SOIL-WATER CONTENT;

D O I：

10.1109/IGARSS.2010.5651428

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Land surface temperature (LST) at both high spatial and high temporal resolution is required for routine monitoring of surface energy fluxes. Disaggregating LST to the NDVI-pixel resolution is possible because of significant inverse relationship between LST and vegetation indices. A modified algorithm (SWISF) has been proposed for thermal imagery sharpening, in which multiple least-squares regression relationships between LST and vegetation indices were acquired for bins of pixels with different soil wetness index values. Applying both SWISF and Distrad which is originally proposed by Kustas et al. to simulated thermal maps at 360m resolution and sharpening down to 90m shows that the new algorithm slightly outperform the old one. Moreover, DisTrad does not have the ability to consider the fact that two pairs of pixels with the same NDVI difference may have distinct LST difference under different soil moisture conditions, while SWISF algorithm could consider it to some extent.

引用

页码：2444 / 2447

页数：4

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