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Integrating remote sensing and GIS techniques with ecological models to map biological diversity in boreal forest.

机译:将遥感和GIS技术与生态模型相结合,以绘制北方森林中生物多样性的图。

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The primary objective of this work was to map biological diversity at the southern extent of the boreal forest in Prince Albert National Park, Saskatchewan, Canada. This was accomplished by using remote sensing and GIS techniques to spatially estimate the four input variables of an ecological model able to predict biological diversity. The variables of interest were (1) the distance from a forest stand to a watershed ridgeline, (2) the time since the last forest fire, (3) the canopy species type and (4) the canopy stem density. The methods used to map each variable are discussed in detail. The data used to estimate these variables included spaceborne imagery (electro-optical and synthetic aperture radar) and vector format elevation contours, streams and lakes. Close attention was paid to estimating the uncertainty associated with each input variable. The results are presented in the form of three maps of biological diversity in The Park. These maps include predicted biodiversity as well as an upper and lower bound map based on the propagation of all quantified uncertainties. The results show that combining spatially estimated input parameters with such a model was reasonably successful and is an innovative use of remote sensing and GIS.
机译:这项工作的主要目的是绘制加拿大萨斯喀彻温省阿尔伯特亲王国家公园北方森林南部地区的生物多样性分布图。这是通过使用遥感和GIS技术在空间上估算能够预测生物多样性的生态模型的四个输入变量来实现的。感兴趣的变量是(1)从林分到分水岭的距离,(2)自上次森林大火以来的时间,(3)冠层物种类型和(4)冠层茎密度。详细讨论了用于映射每个变量的方法。用于估计这些变量的数据包括空间影像(电光和合成孔径雷达)和矢量格式的仰角轮廓,溪流和湖泊。密切注意估计与每个输入变量相关的不确定性。结果以公园内三张生物多样性地图的形式呈现。这些图包括预测的生物多样性以及基于所有量化不确定性的传播的上限和下限图。结果表明,将空间估计的输入参数与这种模型相结合是相当成功的,并且是遥感和GIS的创新应用。

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