A Synergetic Algorithm for Mid-Morning Land Surface Soil and Vegetation Temperatures Estimation Using MSG-SEVIRI Products and TERRA-MODIS Products
文献类型：SCI/SSCI论文
| 作者 | Zhao W. ; Li A. N. ; Bian J. H. ; Jin H. A. ; Zhang Z. J. |
| 发表日期 | 2014 |
| 关键词 | MODIS component temperature SEVIRI split-window algorithm thermal infrared radiance remotely-sensed data urban heat islands component temperatures air-temperature regional evapotranspiration emissivity retrieval msg1-seviri data water content |
| 英文摘要 | Land surface is normally considered as a mixture of soil and vegetation. Many applications, such as drought monitoring and crop-yield estimation, benefit from accurate retrieval of both soil and vegetation temperatures through satellite observation. A preliminary study has been conducted in this study on the estimation of land surface soil and vegetation component temperature using the geostationary satellite data acquired by Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) and TERRA-MODIS data. A synergetic algorithm is proposed to derive soil and vegetation temperatures by using the temporal and spatial information in SEVIRI and MODIS products. The approach is applied to both simulation data and satellite data. For simulation data, the component temperatures are well estimated with root mean squared error (RMSE) close to 0 K. For satellite data application, reasonable spatial distributions of the soil and vegetation temperatures are derived for eight cloud-free days in the Iberian Peninsula from June to August 2009. An evaluation is performed for the estimated vegetation temperature against the near surface air temperature. The correlation analysis between two datasets is found that the R-squareds are from 0.074 to 0.423 and RMSEs are within 4 K. Considering the impact of fraction of vegetation cover (FVC) on the validation, the pixels with FVC less than 30% are excluded in the total data comparison, and an obvious improvement is achieved with R-squared from 0.231 to 0.417 and RMSE from 2.9 K to 2.58 K. The validation indicates that the proposed algorithm is able to provide reasonable estimations of soil and vegetation temperatures. It is a potential way to map soil and vegetation temperature for large areas. |
| 出处 | Remote Sensing |
| 卷 | 6 |
| 期 | 3 |
| 页 | 2213-2238 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 2072-4292 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/29376]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Zhao W.,Li A. N.,Bian J. H.,et al. A Synergetic Algorithm for Mid-Morning Land Surface Soil and Vegetation Temperatures Estimation Using MSG-SEVIRI Products and TERRA-MODIS Products. 2014. |
入库方式： OAI收割
来源：地理科学与资源研究所
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