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A Novel Method for Separating Woody and Herbaceous Time Series

机译:一种分离木质和草本时间序列的新方法

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摘要

Mapping the spatial distribution of woody and herbaceous vegetation in high temporal resolution in savannas would be beneficial for modeling interrelationships between trees and grasses, and monitoring fuel loads and biomass for livestock. In this study, we developed a frequency decomposition method to separate woody and herbaceous vegetation components using Normalized Difference Vegetation Index (NDVI) time series. The results were validated using fractional cover data derived from high-resolution images. The validation revealed a close relationship between our decomposed NDVI and corresponding fractional cover (R-2 = 0.55 and 0.64 for woody and herbaceous components, respectively). We examined the spatial and temporal patterns of the decomposed NDVI, where woody and herbaceous NDVI showed different responses to precipitation. The methods proposed in this study can be used to separate the woody and herbaceous NDVI time series as an alternative approach for monitoring woody and herbaceous vegetation interrelationships related to climatic drivers.
机译:在大草原的高时分辨率下映射木质和草本植物的空间分布将有利于树木和草之间的相互关系,以及监测牲畜的燃料载荷和生物量。在这项研究中,我们开发了一种使用归一化差异植被指数(NDVI)时间序列分离木本和草本植物部件的频率分解方法。使用从高分辨率图像衍生的分数覆盖数据进行验证。验证揭示了我们分解的NDVI和相应的分数盖(R-2 = 0.55和0.64分别用于木质和草本组分)之间的密切关系。我们检查了分解的NDVI的空间和时间模式,其中木质和草本NDVI显示出对沉淀的不同反应。本研究中提出的方法可用于将木质和草本NDVI时间序列分离为用于监测与气候司机相关的木质和草本植物相互关系的替代方法。

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