DATA FUSION FOR IMPROVING THERMAL EMISSIVITY SEPARATION FROM HYPERSPECTRAL DATA

被引：0
|
作者：
Shimoni, M. [1 ]
Haelterman, R. [2 ]
Lodewyckx, P. [3 ]
机构：
[1] Royal Mil Acad, Signal & Image Ctr SIC RMA, Brussels, Belgium
[2] Royal Mil Acad, Dept Math, Brussels, Belgium
[3] Royal Mil Acad, Dept Chem, Brussels, Belgium
来源：
2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2015年
关键词：
Thermal hyperspectral; Land Surface Temperature (LST); Land Surface Emissivity (LSE); Temperature Emissivity Separation (TES); Digital Elevation Model (DEM); TEMPERATURE; ALGORITHM; IMAGES;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Land Surface Temperature (LST) and Land Surface Emissivity (LSE) are common retrievals from thermal hyperspectral imaging. However, their retrieval is not a straightforward procedure because the mathematical problem is ill-posed. This procedure becomes more challenging in an urban area where the spatial distribution of temperature varies substantially in space and time. In this study we propose a new method which integrates 3D surface information from LIDAR data in an attempt to improve the temperature and emissivity separation (TES) procedure for thermal hyperspectral scene. The experimental results prove the high accuracy of the proposed method in comparison to another conventional TES model.
引用
收藏
页码：2955 / 2958
页数：4
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