The assessment of different vegetation indices for spatial disaggregating of thermal imagery over the humid agricultural region
文献类型：期刊论文
| 作者 | Liu, Kai2,3; Wang, Shudong3; Li, Xueke1; Li, Yao4; Zhang, Bo1; Zhai, Ruiting1 |
| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2019-10-20 |
| 页码 | 20 |
| ISSN号 | 0143-1161 |
| DOI | 10.1080/01431161.2019.1677969 |
| 通讯作者 | Wang, Shudong(wangsd@radi.ac.cn) |
| 英文摘要 | Land surface temperature (LST) plays a significant role in surface water circulation and energy balance at both global and regional scales. Thermal disaggregation technique, which relies on vegetation indices, has been widely used due to its advantage in producing relatively high resolution LST data. However, the spatial enhancement of satellite LST using soil moisture delineated vegetation indices has not gained enough attention. Here we compared the performances of temperature vegetation dryness index (TVDI), normalized difference vegetation index (NDVI), and fractional vegetation coverage (FVC), in disaggregating LST over the humid agriculture region. The random forest (RF) regression was used to depict the relationship between LST and vegetation indices in implementing thermal disaggregating. To improve the model performance, we used the thin plate spline (TPS) approach to calibrate the RF residual estimation. Results suggested that the models based on TVDI performed better than those based on NDVI and FVC, with a reduced average root mean square error and mean absolute error of 0.20?K and 0.16?K, respectively. Moreover, based on the surface energy balance model, we found the surface evapotranspiration (ET) derived with the TVDI disaggregated LST as inputs achieved higher accuracy than those derived with NDVI and FVC disaggregated LST. It is indicated that TVDI, a soil moisture delineated vegetation indices, can improve the performance of LST enhancement and ET estimation over the humid agriculture region, when combining random forest regression and TPS calibration. This work is valuable for terrestrial hydrology related research. |
| WOS关键词 | LAND-SURFACE TEMPERATURE ; URBAN HEAT-ISLAND ; SOIL-MOISTURE ; RANDOM FOREST ; ENERGY FLUXES ; RESOLUTION ; SATELLITE ; EVAPOTRANSPIRATION ; FUSION ; LST |
| 资助项目 | Natural Science Foundation of China[41671362] |
| WOS研究方向 | Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000490969100001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/129745]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Shudong |
| 作者单位 | 1.Univ Connecticut, Dept Geog, Mansfield, CT USA 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China 4.Texas A&M Univ, Zachry Dept Civil & Environm Engn, College Stn, TX USA |
| 推荐引用方式 GB/T 7714 | Liu, Kai,Wang, Shudong,Li, Xueke,et al. The assessment of different vegetation indices for spatial disaggregating of thermal imagery over the humid agricultural region[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2019:20. |
| APA | Liu, Kai,Wang, Shudong,Li, Xueke,Li, Yao,Zhang, Bo,&Zhai, Ruiting.(2019).The assessment of different vegetation indices for spatial disaggregating of thermal imagery over the humid agricultural region.INTERNATIONAL JOURNAL OF REMOTE SENSING,20. |
| MLA | Liu, Kai,et al."The assessment of different vegetation indices for spatial disaggregating of thermal imagery over the humid agricultural region".INTERNATIONAL JOURNAL OF REMOTE SENSING (2019):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。