A vegetation index based technique for spatial sharpening of thermal imagery

被引:379
作者
Agam, Nurit
Kustas, William P.
Anderson, Martha C.
Li, Fuqin
Neale, Christopher M. U.
机构
[1] USDA ARS, Hydrol & Remote Sensing Lab, Beltsville, MD 20705 USA
[2] Utah State Univ, Biol & Irrigat Engn Dept, Logan, UT 84322 USA
基金
美国国家航空航天局;
关键词
land surface temperature; spatial resolution; image sharpening; thermal remote sensing; radiometric temperature;
D O I
10.1016/j.rse.2006.10.006
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
High spatial resolution (similar to 100 m) thermal infrared band imagery has utility in a variety of applications in environmental monitoring. However, currently such data have limited availability and only at low temporal resolution, while coarser resolution thermal data (similar to 1000 m) are routinely available, but not as useful for identifying environmental features for many landscapes. An algorithm for sharpening thermal imagery (TsHARP) to higher resolutions typically associated with the shorter wavebands (visible and near-infrared) used to compute vegetation indices is examined over an extensive corn/soybean production area in central Iowa during a period of rapid crop growth. This algorithm is based on the assumption that a unique relationship between radiometric surface temperature (T-R) relationship and vegetation index (VI) exists at multiple resolutions. Four different methods for defining a VI-T-R basis function for sharpening were examined, and an optimal form involving a transformation to fractional vegetation cover was identified. The accuracy of the high-resolution temperature retrieval was evaluated using aircraft and Landsat thermal imagery, aggregated to simulate native and target resolutions associated with Landsat, MODIS, and GOES short- and longwave datasets. Applying TsHARP to simulated MODIS thermal maps at 1-km resolution and sharpening down to similar to 250 in (MODIS VI resolution) yielded root-mean-square errors (RMSE) of 0.67-1.35 degrees C compared to the 'observed' temperature fields, directly aggregated to 250 m. Sharpening simulated Landsat thermal maps (60 and 120 m) to Landsat VI resolution (30 m) yielded errors of 1.8-2.4 degrees C, while sharpening simulated GOES thermal maps from 5 km to I km and 250 m yielded RMSEs of 0.98 and 1.97, respectively. These results demonstrate the potential for improving the spatial resolution of thermal-band satellite imagery over this type of rainfed agricultural region. By combining GOES thermal data with shortwave VI data from polar orbiters, thermal imagery with 250-m spatial resolution and 15-min temporal resolution can be generated with reasonable accuracy. Further research is required to examine the performance of TsHARP over regions with different climatic and land-use characteristics at local and regional scales. (c) 2006 Published by Elsevier Inc.
引用
收藏
页码:545 / 558
页数:14
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