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Evaluate usage of decomposition technique in estimation of soil moisture with vegetated surface by multi-temporal measurements

机译:通过多时相测量评估分解技术在植被表面土壤水分估算中的应用

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Active microwave remote sensing as an important tool for soil physical properties. Despite the promise, its application to hydrological and agricultural sciences has been hampered by natural variability and the complexity of the vegetation canopy and surface roughness that significantly affect the sensitivity of radar backscattering to soil moisture. An operational algorithm for mapping soil moisture distribution has not been developed because of the effects of surface roughness and vegetation cover. The inversion of soil moisture information from radar backscatter became more rigorous after the availability of multi-polarization radar data. Several algorithms have been developed for measuring bare surface soil moisture quantitatively using either dual-polarization L-band SAR image data or three-polarization SAR measurements. The algorithms had been applied to a series of L-band SIR-C and JPL/AIRSAR image data successfully by using VV and HH polarization. However, all those algorithms were under the surface scattering consideration. They used the weighted combinations of the different polarization signatures to minimize the effect of surface roughness so that soil moisture can be directly inferred from SAR image data. The effect of vegetation cover has not been included in current available algorithms. It is clear that vegetation cover will cause an under-estimation of soil moisture and an overestimation of surface roughness when the authors apply the algorithm for bare surface soil moisture estimation to vegetation covered regions.
机译:主动微波遥感作为土壤物理性质的重要工具。尽管有希望,但是它在水文和农业科学中的应用受到自然可变性以及植被冠层和表面粗糙度的复杂性的阻碍,这极大地影响了雷达反向散射对土壤水分的敏感性。由于表面粗糙度和植被覆盖的影响,尚未开发出用于绘制土壤水分分布图的运算算法。在获得多极化雷达数据后,来自雷达反向散射的土壤水分信息反演变得更加严格。已经开发了几种算法,用于使用双极化L波段SAR图像数据或三极化SAR测量定量地测量裸露的土壤水分。该算法已通过VV和HH极化成功应用于一系列L波段SIR-C和JPL / AIRSAR图像数据。但是,所有这些算法都在表面散射考虑下。他们使用了不同极化特征的加权组合,以最大程度地减少表面粗糙度的影响,以便可以直接从SAR图像数据中推断出土壤水分。当前可用的算法中尚未包括植被覆盖的影响。很明显,当作者将裸露的土壤土壤水分估算算法应用到植被覆盖的区域时,植被覆盖将导致土壤水分的低估和表面粗糙度的高估。

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