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Above-ground biomass estimates based on active and passive microwave sensor imagery in low-biomass savanna ecosystems

机译:基于低生物量大草原生态系统的主动和被动微波传感器图像的地上生物量估计

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Although many studies exist on the estimation and monitoring of above-ground biomass (AGB) of forest ecosystems by methods of remote sensing, very little research has been carried out for ecosystems of low primary production, such as grasslands, steppes, or savannas. Our study intends to approach this gap and investigates the correlation between space-borne radar information and AGB at the scale of 10 tons per hectare and below. Additionally, we introduce the integration of passive brightness temperature as an additional covariate for biomass estimation, based on the hypothesis that it contains information complementary to microwave backscatter of the active sensors. Our findings show that large-scale estimates of AGB can be conducted for grasslands and savannas at high accuracy (R-2 up to 0.52). Additionally, we found that the integration of passive radar can increase the quality of AGB estimates in terms of explained variance for selected cases. We hope that these indications are a starting point for more integrated approaches toward biomass estimations based on Earth observation methods. (C) The Authors.
机译:尽管通过遥感方法对森林生态系统的地上生物量(AGB)的估计和监测存在许多研究,但对于低初级生产的生态系统进行了很少的研究,例如草原,草原或大草原。我们的研究打算探讨这种差距,并调查空间雷达信息与AGB的相关性,每公顷10吨和下方。此外,我们基于它包含与活动传感器微波反向散射的信息互补的信息,介绍被动亮度温度作为生物量估计的额外变性的额外协变量。我们的研究结果表明,AGB的大规模估计可以高精度地为草原和大草原进行(R-2高达0.52)。此外,我们发现无源雷达的集成可以在所选病例的解释方差方面增加AGB估计的质量。我们希望这些适应症是基于地球观察方法的更集成方法对生物量估计的更集成方法的起点。 (c)作者。

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