Regression-Kriging Technique to Downscale Satellite-Derived Land Surface Temperature in Heterogeneous Agricultural Landscape

被引:33
|
作者
Mukherjee, Sandip [1 ]
Joshi, Pawan Kumar [1 ]
Garg, Rahul Dev [2 ]
机构
[1] TERI Univ, Dept Nat Resources, New Delhi 110070, India
[2] Indian Inst Technol, Dept Civil Engn, Roorkee 247667, Uttar Pradesh, India
关键词
Downscaling; land surface temperature (LST); MODIS; NDVI; regression-kriging; spatial resolution; thermal data; DISAGGREGATION; VEGETATION; INDEX; IMAGERY;
D O I
10.1109/JSTARS.2015.2396032
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
The study introduces regression-kriging technique to downscale land surface temperature (LST) over a heterogeneous landscape of India and compares it with other models. All models are initially tested on aggregated 960 m Landsat LST and downscaled to 240 m (RMSE = 0.45 degrees C) and 120 m (RMSE = 0.68 degrees C) resolution. Finally, the MODIS LST is downscaled to 250 m (RMSE = 0.7 degrees C) resolution. The proposed model outperformed compared to other models. The qualitative assessment reveals appearance of box-like structure is not seen in the proposed model-derived LST due to reconstruction of residual.
引用
收藏
页码:1245 / 1250
页数:6
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