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

来源：

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING | 2015年 / 8卷 / 03期

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

页码：1245 / 1250

页数：6

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