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A quick screening method: Modeling tree species spatial patterns using DEM and WorldView-II image

机译:快速筛选方法:使用DEM和WorldView-II图像对树种空间格局进行建模

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Species distribution model (SDM) has been the core of spatial ecology and it can provide a measure of a species' occupancy potential in areas not covered by biological surveys and consequently is becoming an essential tool to forest management. This study developed a framework for modeling two representative tree species in central Taiwan. The SDMs based on topographic variables and vegetation index derived from SPOT and WorldView-2 images for predicting potential habitat of two tree species in a GIS by using maximum entropy, DOMAIN and BIOCLIM). The results showed the variance in model accuracy across species was greater than that across techniques. Besides, SDM models merely based on topographic variables and sample distributions corresponding to them could not be applied on a larger spatial scale. More importantly, Adding spectral variable might offer high potential value, improving model prediction on a small and large spatial scale especially using Worldview-II image data.
机译:物种分布模型(SDM)已经成为空间生态学的核心,它可以提供一种在生物调查未涵盖的区域中物种占用潜力的度量,因此正成为森林管理的重要工具。这项研究开发了一个框架,用于对台湾中部的两种代表性树种进行建模。基于来自SPOT和WorldView-2图像的地形变量和植被指数的SDM,可通过使用最大熵DOMAIN和BIOCLIM来预测GIS中两个树种的潜在栖息地。结果表明,跨物种的模型准确性方差大于跨技术的方差。此外,仅基于地形变量和与之对应的样本分布的SDM模型无法在较大的空间规模上应用。更重要的是,添加光谱变量可能会提供较高的潜在价值,尤其是使用Worldview-II图像数据时,可以在较小和较大的空间尺度上改善模型预测。

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