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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Application of a Combined Optical–Passive Microwave Method to Retrieve Soil Moisture at Regional Scale Over Chile
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Application of a Combined Optical–Passive Microwave Method to Retrieve Soil Moisture at Regional Scale Over Chile

机译：光学-被动微波组合方法在智利区域尺度上获取土壤水分的应用

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摘要

This work presents the calibration and evaluation of an optical–passive microwave method for retrieving soil moisture (SM) at regional scale using remote sensing and reanalysis data. Several data sets were used, such as the bipolarized brightness temperature provided by SM and Ocean Salinity (SMOS) L3 brightness temperature product, the Normalized Difference Vegetation Index (NDVI) from moderate resolution imaging spectroradiometer (MODIS), the soil temperature and water content of the first 0–7 cm of depth from the ERA-Interim reanalysis, and 13 land cover classes obtained from the ECOCLIMAP database. The method was applied over Chile between 28°S and 43°S for 2010–2012. The data set was used to calibrate and evaluate a semiempirical approach for estimating SM, first by using only the data from SMOS and ERA-Interim and then also including the MODIS vegetation indicator. Results were analyzed for every land cover class using the determination coefficient (), the coefficients obtained from the regressions, and the unbiased root-mean-square difference (ubRMSD). Results showed an increase in the average for all classes when a vegetation index was used in the calibration of the approach. The increases in ranged from 3% for the crop class, to 49% for the closed shrubland class. The ubRMSD presented a decrease in its value of up to 1% for the woodlands, open shrublands, and woody shrublands classes and up to 2% for the closed shrubland class. These results contribute to the use of si- gle linear and semiempirical regressions to estimate SM at regional scale based on SMOS -band bipolarized brightness temperature.
机译：这项工作介绍了使用遥感和再分析数据在区域尺度上检索土壤水分（SM）的光学无源微波方法的校准和评估。使用了多个数据集，例如SM提供的双极化亮度温度和海洋盐度（SMOS）L3亮度温度乘积，中分辨率成像光谱仪（MODIS）的归一化植被指数（NDVI），土壤温度和土壤水分ERA-Interim重新分析的前0-7厘米深度，以及从ECOCLIMAP数据库获得的13种土地覆盖类别。该方法于2010年至2012年在智利介于28°S和43°S之间的地方应用。该数据集被用于校准和评估估算SM的半经验方法，首先仅使用来自SMOS和ERA-Interim的数据，然后还包括MODIS植被指标。使用确定系数（），从回归获得的系数以及无偏方均根差（ubRMSD）对每种土地覆盖类别的结果进行分析。结果表明，当使用植被指数进行校准时，所有类别的平均值都有所增加。增长幅度从农作物类别的3％到封闭灌木丛类别的49％不等。 ubRMSD表示，林地，开放灌木丛和木质灌木丛类别的价值下降了1％，而封闭灌木丛类别的价值下降了2％。这些结果有助于使用单个线性和半经验回归来基于SMOS带双极化亮度温度在区域范围内估算SM。

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