An Improved Annual Temperature Cycle Model With the Consideration of Vegetation Change
文献类型：期刊论文
| 作者 | Zhao, Wei2 ; Yang, Yujia1,2; Yang, Mengjiao1,2
|
| 刊名 | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
 |
| 出版日期 | 2022 |
| 卷号 | 19页码:5 |
| 关键词 | Land surface temperature Vegetation mapping Land surface Surface topography Surface fitting Temperature sensors Fitting Annual temperature cycle (ATC) land surface temperature (LST) moderate resolution imaging spectroradiometer (MODIS) vegetation cover |
| ISSN号 | 1545-598X |
| DOI | 10.1109/LGRS.2022.3145380 |
| 通讯作者 | Zhao, Wei(zhaow@imde.ac.cn) |
| 英文摘要 | Land surface temperature (LST) is an important parameter in land surface processes with strong relationship between surface energy and water exchange. To effectively capture the surface thermal dynamics, the annual temperature cycle model is a good option by depicting the annual variation as a constant term plus a sine function. However, this type model suffers from the assumption of constant surface thermal property which is hardly satisfied due to the changes in vegetation cover. To well address this issue, the normalized difference vegetation index (NDVI) is introduced as an indicator to characterize the variation in surface thermal property and added to the original form to propose an improved version. Through comparison between the fitting effects of the proposed model with the original one, the improvement shows good performance in suppressing the annual maximum temperature and elevating the annual minimum temperature with the increase in vegetation cover. The difference in the annual maximum and minimum temperature between the estimates from the proposed model and the original model shows good linear regression with NDVI difference when compared with the annual mean value, with the speed of -3.22 and 4.84, respectively. In addition, the fitting accuracy is also improved with a slight increase in the coefficient of determination (0.002) and a decrease in the root mean squared error (0.018 K). The application of the proposed model also provides reasonable distribution of the annual temperature parameters in the southwest of Europe and part of North Africa, confirming its potential effect in thermal dynamic monitoring. |
| WOS关键词 | LAND-SURFACE TEMPERATURE ; MODIS LST ; VARIABILITY |
| 资助项目 | National Key Research and Development Program of China[2020YFA0608702] ; National Natural Science Foundation of China[42071349] ; Sichuan Science and Technology Program[2020JDJQ0003] ; Chinese Academy of Sciences Light of West China Program |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000753457800006 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Sichuan Science and Technology Program ; Chinese Academy of Sciences Light of West China Program |
| 源URL | [http://ir.imde.ac.cn/handle/131551/56446]  |
| 专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
| 通讯作者 | Zhao, Wei |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Wei,Yang, Yujia,Yang, Mengjiao. An Improved Annual Temperature Cycle Model With the Consideration of Vegetation Change[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2022,19:5. |
| APA | Zhao, Wei,Yang, Yujia,&Yang, Mengjiao.(2022).An Improved Annual Temperature Cycle Model With the Consideration of Vegetation Change.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,19,5. |
| MLA | Zhao, Wei,et al."An Improved Annual Temperature Cycle Model With the Consideration of Vegetation Change".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 19(2022):5. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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。