Genetic inverse algorithm for retrieval of component temperature of mixed pixel by multi-angle thermal infrared remote sensing data |
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Authors: | Xiru Xu Liangfu Chen and Jiali Zhuang |
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Institution: | LARSIS, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China |
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Abstract: | After carefully studying the results of retrieval of land surface temperature(LST) by multi-channel thermal infrared remote
sensing data, the authors of this paper point out that its accuracy and significance for applications are seriously damaged
by the high correlation coefficient among multi-channel information and its disablement of direct retrieval of component temperature.
Based on the model of directional radiation of non-isothermal mixed pixel, the authors point out that multi-angle thermal
infrared remote sensing can offer the possibility to directly retrieve component temperature, but it is also a multi-parameter
synchronous inverse problem. The results of digital simulation and field experiments show that the genetic inverse algorithm
(GIA) is an effective method to fulfill multi-parameter synchronous retrieval. So it is possible to realize retrieval of component
temperature with error less than 1K by multi-angle thermal infrared remote sensing data and GIA. |
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Keywords: | multi-angle thermal infrared remote sensing component temperature of mixed pixel genetic inverse algorithm |
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