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首页> 外文期刊>Frequenz >Soil Moisture Retrievals in Aeolian Sand Mining Areas Using Temporal, Single-Polarization, High-Resolution SAR
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Soil Moisture Retrievals in Aeolian Sand Mining Areas Using Temporal, Single-Polarization, High-Resolution SAR

机译:基于时间,单极化,高分辨率SAR的风沙矿区土壤水分反演

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摘要

Changes in the soil moisture are a key factor in the deterioration of the ecological environment caused by mining geological disasters. In this study, which presents a case study of the arid and semi-arid aeolian sand mining area along the Inner Mongolia-Shaanxi Province boundary, a method for retrieving the soil moisture based on RADARSAT-2 SAR scattering data and Terra MODIS surface reflectance data was proposed. The retrieval of RADARSAT-2 mainly used the Alpha approximation model based on the change detection technique, a model proposed by Balenzano et al., which can effectively decouple the impact of surface vegetation and roughness on radar backscattering coefficient, when the volume scattering is not dominant. Using 12 periods of RADARSAT-2 HH polarization data in conjunction with the Alpha approximation model, a matrix equation was constructed, which contains 11 equations and 12 unknowns. To solve this underdetermined system, a bounded linear least-squares optimization was adopted. Once the unknowns were determined, the relative dielectric constant could be analytically derived and then the soil moisture could be estimated by using the dielectric mixing model and compared with the MODIS retrieval results based on the spatial feature method. Finally, the DInSAR results of RADARSAT-2 were used to investigate the effects of high-intensity underground mining activities on the surface soil moisture. The study found that the RADARSAT-2 soil moisture estimates demonstrated good consistency with the MODIS retrieval results. Among four comparison groups, the maximum correlation coefficient was 0.599, and the highest proportion of sampling points for which the absolute error was less than 3% was 55.6%. The absolute error of all of the sampling points did not exceed 10%, which demonstrates the reliability of the RADARSAT-2 retrieval results. A comparison among the 72 soil moisture values from six mining subsidence areas and corresponding non-subsidence areas in the study area in 2012 showed that 38 soil moisture values from the non-subsidence areas were higher than those from the subsidence areas. These values accounted for 53% of the total, indicating that high-intensity mining activities have a certain negative impact on the surface soil moisture, although this impact is slightly insignificant.
机译:土壤水分的变化是采矿地质灾害导致生态环境恶化的关键因素。本文以内蒙古-陕西省边界的干旱和半干旱风沙开采区为例,提出了一种基于RADARSAT-2 SAR散射数据和Terra MODIS表面反射率数据的土壤水分反演方法。被提出。 RADARSAT-2的检索主要使用基于变化检测技术的Alpha近似模型,这是Balenzano等人提出的模型,该模型可以在不进行体积散射的情况下有效地解耦表面植被和粗糙度对雷达反向散射系数的影响。优势。利用12个周期的RADARSAT-2 HH极化数据和Alpha逼近模型,构建了一个矩阵方程,其中包含11个方程和12个未知数。为了解决这个欠定系统,采用了有界线性最小二乘优化。一旦确定了未知数,就可以解析得出相对介电常数,然后可以使用介电混合模型估算土壤水分,并与基于空间特征方法的MODIS检索结果进行比较。最后,使用RADARSAT-2的DInSAR结果来研究高强度地下采矿活动对表层土壤水分的影响。研究发现,RADARSAT-2土壤湿度估算值与MODIS检索结果具有良好的一致性。在四个比较组中,最大相关系数为0.599,绝对误差小于3%的采样点的最高比例为55.6%。所有采样点的绝对误差均不超过10%,这证明了RADARSAT-2检索结果的可靠性。 2012年对研究区六个采煤沉陷区和相应的非沉陷区的72个土壤水分值进行了比较,结果表明,非沉陷区的38个土壤水分值高于沉陷区。这些值占总数的53%,这表明高强度采矿活动对表层土壤水分有一定的负面影响,尽管这种影响微不足道。

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