Abstract Methods for quantifying vegetative cover across landscapes have, until recently, been limited to ground-based surveys or remote sensing via satellites or aircraft, both of which can limit the spatial scale of resulting data. Unmanned Aircraft Systems (UAS) can efficiently collect high-resolution sub-decimeter imagery of landscapes; geographic, object-based image analysis (GEOBIA) of the collected imagery can then be used to estimate vegetation cover. To date, few researchers have utilized open-source programs for GEOBIA. We developed GEOBIA methods in the open-source Program R to analyze visible spectrum UAS imagery from four sites in the Chihuahuan Desert of North America. These desert grasslands are difficult to quantify due to the patchiness of ground cover at small scales (e.g.

中文翻译：

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一种使用基于对象的图像分析表征奇瓦瓦沙漠植被群落的开源方法

摘要 直到最近，量化景观植被覆盖的方法仅限于地面调查或通过卫星或飞机进行遥感，这两种方法都会限制结果数据的空间尺度。无人机系统 (UAS) 可以有效地收集高分辨率的亚分米景观图像；然后可以使用收集的图像的基于对象的地理图像分析 (GEOBIA) 来估计植被覆盖。迄今为止，很少有研究人员为 GEOBIA 使用开源程序。我们在开源程序 R 中开发了 GEOBIA 方法来分析来自北美奇瓦环沙漠四个地点的可见光谱 UAS 图像。由于小规模地表覆盖的斑块状（例如