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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps
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The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

机译:北部斑点猫头鹰(Strix occidentalis caurina)栖息地制图的演变:照片解释型,基于Landsat的和基于激光雷达的栖息地图的比较

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摘要

Wildlife habitat mapping has evolved at a rapid pace over the last few decades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data For species that inhabit large geographic areas, remote sensing technology is often essential for producing range wide maps. Habitat monitoring for northern spotted owls (Strix occidentalis caurina), whose geographic covers about 23 million ha, is based on SDMs that use Landsat Thematic Mapper imagery to create forest vegetation data layers using gradient nearest neighbor (GNN) methods. Vegetation data layers derived from GNN are modeled relationships between forest inventory plot data, climate and topographic data, and the spectral signatures acquired by the satellite. When used as predictor variables for SDMs, there is some transference of the GNN modeling error to the final habitat map.
机译:在过去的几十年中,野生生物栖息地制图的发展迅速。从简单的,通常是主观的手绘地图开始,栖息地地图现在涉及到复杂的物种分布模型(SDM),该模型使用从遥感数据得出的映射的预测变量来进行搜索。地图。对北部斑点猫头鹰(Strix occidentalis caurina)的栖息地进行监测,其地理覆盖范围约为2300万公顷,基于使用Landsat Thematic Mapper影像的SDM,使用梯度最近邻(GNN)方法创建森林植被数据层。从GNN派生的植被数据层是森林清单样地数据,气候和地形数据与卫星获取的光谱特征之间的建模关系。当用作SDM的预测变量时,GNN建模误差会向最终栖息地地图转移。

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