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首页> 外文期刊>International journal of applied earth observation and geoinformation >DisPATCh as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and AMSR-E data in Southeastern Australia
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DisPATCh as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and AMSR-E data in Southeastern Australia

机译：DisPATCh作为使用本地原位测量评估粗尺度遥感土壤湿度的工具：在澳大利亚东南部的SMOS和AMSR-E数据中的应用

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摘要

Validating coarse-scale satellite soil moisture data still represents a big challenge, notably due to the large mismatch existing between the spatial resolution (> 10 km) of microwave radiometers and the representativeness scale (several m) of localized in situ measurements. This study aims to examine the potential of DisPATCh (Disaggregation based on Physical and Theoretical scale Change) for validating SMOS (Soil Moisture and Ocean Salinity) and AMSR-E (Advanced Microwave Scanning Radiometer-Earth observation system) level-3 soil moisture products. The similar to 40-50 km resolution SMOS and AMSR-E data are disaggregated at 1 km resolution over the Murrumbidgee catchment in Southeastern Australia during a one year period in 2010-2011, and the satellite products are compared with the in situ measurements of 38 stations distributed within the study area. It is found that disaggregation improves the mean difference, correlation coefficient and slope of the linear regression between satellite and in situ data in 77%, 92% and 94% of cases, respectively. Nevertheless, the downscaling efficiency is lower in winter than during the hotter months when DisPATCh performance is optimal. Consistently, better results are obtained in the semi-arid than in a temperate zone of the catchment. In the semi-arid Yanco region, disaggregation in summer increases the correlation coefficient from 0.63 to 0.78 and from 0.42 to 0.71 for SMOS and AMSR-E in morning overpasses and from 0.37 to 0.63 and from 0.47 to 0.73 for SMOS and AMSR-E in afternoon overpasses, respectively. DisPATCh has strong potential in low vegetated semi-arid areas where it can be used as a tool to evaluate coarse-scale remotely sensed soil moisture by explicitly representing the sub-pixel variability. (C) 2015 Elsevier B.V. All rights reserved.
机译：验证粗尺度卫星土壤湿度数据仍然是一个巨大的挑战，这主要是由于微波辐射计的空间分辨率（> 10 km）与局部原位测量的代表性尺度（几m）之间存在巨大的不匹配。这项研究旨在检验DisPATCh（基于物理和理论尺度变化的分解）在验证SMOS（土壤水分和海洋盐度）和AMSR-E（高级微波扫描辐射计-地球观测系统）3级土壤水分产品方面的潜力。在2010-2011年的一年时间内，在澳大利亚东南部的Murrumbidgee流域以1 km的分辨率对类似于40-50 km分辨率的SMOS和AMSR-E数据进行了分解，并将卫星产品与38个原位测量值进行了比较。研究区域内分布的电台。发现分解可以分别改善77％，92％和94％的卫星和现场数据之间线性回归的均值差，相关系数和斜率。尽管如此，冬季的降尺度效率要比DisPATCh性能最佳的炎热月份低。一致地，在半干旱地区比在集水区的温带地区获得更好的结果。在半干旱的Yanco地区，夏季的分解将相关的系数从早上高架桥的SMOS和AMSR-E的相关系数从0.63增至0.78，从0.42增至0.71，而将SMOS和AMSR-E的相关系数从0.37增至0.63，从0.47增至0.73。下午分别立交桥。 DisPATCh在低植被的半干旱地区具有强大的潜力，可以通过明确表示亚像素变异性，将其用作评估粗尺度遥感土壤湿度的工具。 （C）2015 Elsevier B.V.保留所有权利。

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