A Remote Sensing Method for Estimating Surface Air Temperature and Surface Vapor Pressure on a Regional Scale
文献类型：SCI/SSCI论文
| 作者 | Zhang R. H.; Rong, Y.; Tian, J.; Su, H. B.; Li, Z. L.; Liu, S. H. |
| 发表日期 | 2015 |
| 关键词 | north china plain modis lst data spatial interpolation window algorithm daily maximum landsat-tm water evapotranspiration retrieval model |
| 英文摘要 | This paper presents a method of estimating regional distributions of surface air temperature (T-a) and surface vapor pressure (e(a)), which uses remotely-sensed data and meteorological data as its inputs. The method takes into account the effects of both local driving force and horizontal advection on T-a and e(a). Good correlation coefficients (R-2) and root mean square error (RMSE) between the measurements of T-a/e(a) at weather stations and T-a/e(a) estimates were obtained; with R-2 of 0.77, 0.82 and 0.80 and RMSE of 0.42K, 0.35K and 0.20K for T-a and with R-2 of 0.85, 0.88, 0.88 and RMSE of 0.24hpa, 0.35hpa and 0.16hpa for e(a), respectively, for the three-day results. This result is much better than that estimated from the inverse distance weighted method (IDW). The performance of T-a/e(a) estimates at Dongping Lake illustrated that the method proposed in the paper also has good accuracy for a heterogeneous surface. The absolute biases of T-a and e(a) estimates at Dongping Lake from the proposed method are less than 0.5Kand 0.7hpa, respectively, while the absolute biases of them from the IDW method are more than 2K and 3hpa, respectively. Sensitivity analysis suggests that the T-a estimation method presented in the paper is most sensitive to surface temperature and that the e(a) estimation method is most sensitive to available energy. |
| 出处 | Remote Sensing |
| 卷 | 7 |
| 期 | 5 |
| 页 | 6005-6025 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 2072-4292 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/39029]  |
| 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 | Zhang R. H.,Rong, Y.,Tian, J.,et al. A Remote Sensing Method for Estimating Surface Air Temperature and Surface Vapor Pressure on a Regional Scale. 2015. |
入库方式： OAI收割
来源：地理科学与资源研究所
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