1. State Key Laboratory of Remote Sensing Science, College of Remote Sensing Science and Engineering, Beijing Normal University, Beijing 100875, China 2. Satellite Environment Center, Ministry of Environmental Protection, Beijing 100094, China 3. USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville MD20705, USA
基于热红外遥感的潜热通量估算在农业干旱和水资源管理方面具有重要意义。利用Landsat卫星遥感热红外数据和单窗算法来获取地表温度,再通过改进地表粗糙度参数,提出基于地表粗糙度改进的基于高分辨率和内在校准的蒸散估算法(mapping evapotranspiration at high resolution and with internalized calibration, METRIC)估算农田潜热通量,并利用海河流域怀来和密云2个农田通量观测站的通量观测数据验证估算结果,实验结果表明: 改进的METRIC模型模拟值与观测值相关系数平方(R2)为0.97,优于传统的METRIC模型(R2=0.89),改进后模型具有更高的农田潜热通量估算精度; 此外,空间分布也表明改进后的模型估算值空间格局更加合理。由于数据获取的局限性,仅采用了北京2个站点数据对模型进行验证,在其他区域仍需要进一步验证。
Estimation of latent heat flux based on thermal infrared remote sensing is of great significance in agricultural drought and water resources management. This paper examined the applicability of using METRIC model to estimate latent heat flux over farmland from Landsat images. Land surface temperature (Ts) required for estimation of the flux was computed from Landsat thermal infrared data by the mono-window algorithm. Meanwhile, an improved METRIC algorithm based on surface roughness was proposed to estimate the latent heat flux of farmland by improving the surface roughness parameters. The result of the algorithm was verified by the flux observation data from two observation stations of Huailai and Miyun in the Haihe River basin. The results show that the square of correlation coefficient (R2) between simulated and observed values is 0.97, which is better than the conventional METRIC model (R2 = 0.89). The improved algorithm has higher estimation accuracy of latent heat flux. In addition, the spatial distribution of latent heat flux also shows that the spatial pattern of the improved model is more reasonable. However, due to the limitation of data acquisition, only two stations in Beijing have been used to validate the algorithm, and hence further verification in other areas is needed.
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2018, Vol. 30 
), 赵少华2, 贾坤1, 张晓通1, 赵祥1, 孙亮3
