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Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation

机译:用于中等分辨率监测陆地植被的全球植被指数分析

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Abstract: Vegetation indices have emerged as important tools in the seasonal and inter-annual monitoring of the Earth's vegetation. They are radiometric measures of the amount and condition of vegetation. In this study, the Sea-viewing Wide Field-of-View sensor (SeaWiFS) is used to investigate coarse resolution monitoring of vegetation with multiple indices. A 30-day series of SeaWiFS data, corrected for molecular scattering and absorption, was composited to cloud-free, single channel reflectance images. The normalized difference vegetation index (NDVI) and an optimized index, the enhanced vegetation index (EVI), were computed over various 'continental' regions. The EVI had a normal distribution of values over the continental set of biomes while the NDVI was skewed toward higher values and saturated over forested regions. The NDVI resembled the skewed distributions found in the red band while the EVI resembled the normal distributions found in the NIR band. The EVI minimized smoke contamination over extensive portions of the tropics. As a result, major biome types with continental regions were discriminable in both the EVI imagery and histograms, whereas smoke and saturation considerably degraded the NDVI histogram structure preventing reliable discrimination of biome types. !9
机译:摘要:植被指数已成为对地球植被进行季节性和年度监测的重要工具。它们是对植被数量和状况的辐射测量。在这项研究中,海景宽视野传感器(SeaWiFS)用于研究具有多个指标的植被的粗分辨率监测。经过30天的一系列SeaWiFS数据校正(针对分子散射和吸收),将其合成为无云的单通道反射率图像。计算了各个“大陆”区域的归一化植被指数(NDVI)和优化指数(增强植被指数(EVI))。 EVI在整个生物群落大陆上具有正态分布,而NDVI则偏向更高的数值,并在森林区域内趋于饱和。 NDVI类似于在红色波段中发现的偏态分布,而EVI类似于在NIR波段中发现的正态分布。 EVI将热带大部分地区的烟雾污染降至最低。结果,在EVI图像和直方图中都可以识别出具有大陆区域的主要生物群落类型,而烟雾和饱和度则使NDVI直方图结构大大降低,从而无法可靠地区分生物群落类型。 !9

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