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Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling

机译:星载高光谱EnMAP任务绘制土壤侵蚀模型的分数覆盖率的能力

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摘要

Soil erosion can be linked to relative fractional cover of photosynthetic-active vegetation (PV), non-photosynthetic-active vegetation (NPV) and bare soil (BS), which can be integrated into erosion models as the cover-management C-factor. This study investigates the capability of EnMAP imagery to map fractional cover in a region near San Jose, Costa Rica, characterized by spatially extensive coffee plantations and grazing in a mountainous terrain. Simulated EnMAP imagery is based on airborne hyperspectral HyMap data. Fractional cover estimates are derived in an automated fashion by extracting image endmembers to be used with a Multiple End-member Spectral Mixture Analysis approach. The C-factor is calculated based on the fractional cover estimates determined independently for EnMAP and HyMap. Results demonstrate that with EnMAP imagery it is possible to extract quality endmember classes with important spectral features related to PV, NPV and soil, and be able to estimate relative cover fractions. This spectral information is critical to separate BS and NPV which greatly can impact the C-factor derivation. From a regional perspective, we can use EnMAP to provide good fractional cover estimates that can be integrated into soil erosion modeling.
机译:土壤侵蚀可以与光合活性植被(PV),非光合活性植被(NPV)和裸土(BS)的相对分数覆盖率相关,它们可以作为覆盖率管理C因子整合到侵蚀模型中。这项研究调查了EnMAP图像在哥斯达黎加圣何塞附近区域(覆盖范围广泛的咖啡种植园和山区地形上的草场)上绘制覆盖率的能力。模拟的EnMAP图像基于机载高光谱HyMap数据。分数覆盖率估计值是通过提取要与多端成员光谱混合分析方法一起使用的图像端成员以自动方式得出的。 C因子是根据为EnMAP和HyMap独立确定的覆盖率估算值计算得出的。结果表明,使用EnMAP图像可以提取具有与PV,NPV和土壤相关的重要光谱特征的优质端构件类别,并能够估算相对覆盖率。此光谱信息对于分离BS和NPV至关重要,这会极大影响C因子的推导。从区域角度来看,我们可以使用EnMAP提供良好的覆盖率估算值,并将其集成到土壤侵蚀模型中。

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