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地表温度(land surface temperature,LST)是反映地表能量和水平衡物理过程的一个重要参数,受限于载荷量的限制以及传感器的技术瓶颈,当前的卫星平台均难以获取同时具有较高空间和时间分辨率的遥感地表温度影像,客观上影响了遥感地表温度影像的应用。针对地表异质性较高的城市区域,选取覆盖武汉城区的中分辨率成像光谱仪(moderate-resolution imaging spectroradiometer,MODIS)和增强型专题绘图仪(enhanced thematic mapper plus,ETM+)数据,结合时空反射率融合模型(enhanced spatial and temporala-daptive reflectance fusion model,ESTARFM)和非线性辐射温度分解算法(non-linear disaggregation procedure for radiometric surface temperature,NL-DisTrad)对地表温度影像进行时空融合研究,最终生成60m空间分辨率的逐日地表温度融合影像。将融合影像与2002年7月9日和10月13日的ETM+实际地表温度影像进行融合精度验证分析,其决定系数(r-squared,R2)分别为0.80和0.86,均方根误差(root mean square error,RMSE)分别为2.65K和1.78K。实验结果表明,所提出的地表温度时空融合模型在城市区域的地表温度时空融合应用中具有潜在的应用前景。
Land surface temperature (LST) is an important parameter that reflects the physical process of surface energy and water balance. Due to the limitation of load and the bottleneck of sensor technology, it is difficult for current satellite platforms to acquire both high space and time Resolution of remote sensing surface temperature images objectively affected the application of remote sensing surface temperature images. For urban areas with high surface heterogeneity, moderate-resolution imaging spectroradiometer (MODIS) and enhanced thematic mapper plus (ETM + The temporal and spatial fusion of the surface temperature image was finally completed by using the enhanced spatial and temporala-daptive reflectance fusion model (ESTARFM) and non-linear disaggregation procedure for radiometric surface temperature (NL-DisTrad) Resolution of daily surface temperature fusion images. The fusion images were fused and verified with ETM + actual surface temperature images on July 9 and October 13, 2002. The r-squared (R2) coefficients were 0.80 and 0.86, respectively. The root mean square error square error, RMSE) were 2.65K and 1.78K, respectively. The experimental results show that the proposed temporal and spatial fusion model of surface temperature has potential applications in space-time fusion of surface temperature in urban areas.