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SMAP Multi-Temporal vegetation optical depth retrieval as an indicator of crop yield trends and crop composition

机译：SMAP多时相植被光学深度检索可作为作物产量趋势和作物组成的指标

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Vegetation Optical Depth (VOD) is related to Vegetation Water Content (VWC). This provides new and highly valuable information for ecological and agricultural studies. In this work, VOD from the Soil Moisture Active-Passive (SMAP) satellite has been retrieved with the new Multi-Temporal Dual-Channel Algorithm (MT-DCA). Then, it has been applied to the study of crop yield trends and crop composition. The increase on VOD (ΔVOD) during crop development has been compared to yield data in two selected regions located in the United States. The first region presents a heterogeneous crop composition and weak ΔVOD-yield relationship (r2=0.21). The second region presents a highly homogenous cover and a strong exponential relationship (r2=0.65) between ΔVOD and yield. A saturation of yield is observed at a certain ΔVOD value. This pattern is probably due to an increasing plant density, which limits the crop yield due to plant physiological stress.
机译：植被光学深度（VOD）与植被含水量（VWC）有关。这为生态和农业研究提供了新的和极有价值的信息。在这项工作中，使用新的多时相双通道算法（MT-DCA）检索了土壤水分主动-被动（SMAP）卫星的VOD。然后，将其应用于作物产量趋势和作物组成的研究。已将作物发育过程中VOD（ΔVOD）的增加与美国两个选定区域的产量数据进行了比较。第一区域呈现出非均质的作物组成和较弱的ΔVOD-产量关系（r2 = 0.21）。第二个区域呈现出高度均匀的覆盖率和ΔVOD与成品率之间的指数关系（r2 = 0.65）。在一定的ΔVOD值处观察到产率饱和。这种模式可能是由于植物密度增加，由于植物生理胁迫而限制了作物产量。

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