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微波遥感土壤湿度产品是目前在大尺度水资源或气候变化研究中比较常用的地表土壤湿度数据,但其空间分辨率一般都较粗,不能满足区域或流域尺度相关研究要求.因而,在这些尺度的相关研究中需要对土壤湿度产品进行空间降尺度.UCLA法是一种土壤湿度降尺度方法,该方法使用地表温度和植被指数特征空间指数(Ts/VI指数)作为降尺度因子.本文以AMSR-E土壤湿度产品作为土壤湿度粗分辨率数据,使用MODIS地表温度产品(MYD11A1)和植被指数产品(MYD13A2)计算3种指数——土壤湿度指数(SW)、温度植被干旱指数(TVDI)和条件温度植被指数(VTCI),对比了3种Ts/VI指数分别作为UCLA法降尺度因子的效果.这3种指数均能得出合理的降尺度结果,但使用TVDI和VTCI的降尺度结果稍优于SW,说明TVDI和VTCI更适合作为UCLA法的降尺度因子.最后讨论了UCLA法的误差来源,如粗分辨率土壤湿度产品的测量误差、降尺度因子的计算误差以及UCLA法自身的误差,并对未来的研究做出展望.
Soil moisture in microwave remote sensing data is the most commonly used surface soil moisture data in large-scale water resources or climate change research, but its spatial resolution is generally coarse, which can not meet the relevant research requirements of regional or catchment scale. Therefore, at these scales , A method of spatial scaling of soil moisture products is needed.UCLA is a method of downscaling of soil moisture using the surface temperature and the Ts / VI index (Ts / VI) as the downscaling factor.In this paper, AMSR -E Soil Moisture Products As raw data for soil moisture resolution, three indices - soil moisture index (SW), TVDI and conditions were calculated using MODIS surface temperature product (MYD11A1) and vegetation index product (MYD13A2) Temperature Vegetation Index (VTCI) was used to compare the effects of the three Ts / VI indices on the downscaling factor of the UCLA method, respectively, all of which yielded reasonable downscaling results, but the downscaling results using TVDI and VTCI were slightly better At SW, TVDI and VTCI are more suitable as downscaling factors for the UCLA method.Finally, the sources of error of the UCLA method are discussed, such as the measurement error of coarse resolution soil moisture products The error downscaling factor calculation error and UCLA law itself, and make future research prospects.