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An Integrated Surface Parameter Inversion Scheme Over Agricultural Fields at Early Growing Stages by Means of C-Band Polarimetric RADARSAT-2 Imagery

机译:利用C波段极化RADARSAT-2成像技术的农田早期集成地表参数反演方案。

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Many research studies have investigated surface parameter inversion for bare soils. This paper attempts to take into account the agricultural fields with crop residues and fields under low vegetation cover in addition to bare soil fields. An integrated surface parameter inversion scheme (ISPIS) is proposed to invert surface parameters in these agricultural fields based on the analysis of parameters at the early crop growing stages, in which the calibrated integral equation model (CIEM) is adopted to invert surface parameters for bare soils, and an adaptive two-component decomposition combined with the CIEM and a simplified adaptive volume scattering model is developed for fields with crop residues and under low vegetation cover. Fully polarimetric RADARSAT-2 data with ground truth collected on April 29 and May 9 in 2013 and from May to June in 2014 are used for validation. Compared with other methods, the derived volumetric soil moisture (MV) and surface roughness (KS) of all agricultural fields are consistent with verifiable observations with the lowest overall root mean square error: 6.12 [vol.%] and 0.48, respectively, when all sample sites are considered.
机译:许多研究已经研究了裸土的表面参数反演。本文试图考虑到有农作物残留的农田和植被覆盖低的农田,以及裸露的土地。在作物生长初期对参数进行分析的基础上,提出了一种综合地表参数反演方案(ISPIS)对农田中的地表参数进行反演。土壤,针对作物残渣且植被覆盖度较低的田地,开发了一种结合了CIEM和简化的自适应体积散射模型的自适应两组分分解方法。于2013年4月29日和5月9日以及2014年5月至6月收集的具有地面真实性的全极化RADARSAT-2数据用于验证。与其他方法相比,所有农田的土壤体积含水量(MV)和表面粗糙度(KS)均与可验证的观测结果一致,且总均方根误差最低:分别为6.12 [vol。%]和0.48考虑了样本位置。

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