Remotely sensed data products depicting physical and ecological attributes of a landscape are becoming invaluable tools in wildlife and rangeland management. However, if such geospatial tools and data layers are to be used in management, their accuracy and appropriateness for such use needs to be vetted and validated. We assessed accuracy of two National Land Cover Database (NLCD) shrubland products for use in western South Dakota—percent sagebrush and sagebrush height—by comparing them to ground-truthed data. Western South Dakota sagebrush communities are an ecotone between sagebrush (Artemisia spp.) and grassland. This ecotone is typified by shorter- and lower-density sagebrush than interior sagebrush steppe ecosystem. This distinction could make it difficult to remotely detect and map sagebrush in this area. We determined NLCD correlations with ground estimates of sagebrush canopy cover (r = 0.17) and sagebrush height (r = 0.40). The NLCD percent sagebrush accurately predicted sagebrush presence ∼73‒76% of the time once resampled to 100-m pixels and 50-m mean values, respectively. Cohen’s kappa values were estimated to determine if the ground-truthed and remoted-sensed data were in agreement when determining sagebrush presence. Kappa values were 0.26 ± 0.06 and 0.28 ± 0.06 for mean values within 50-m and resampled 100-m pixels, respectively, indicating a “fair” level of agreement between the ground-truthed and remote-sensed data types when determining presence of sagebrush. The NLCD data sufficiently described the presence of sagebrush in South Dakota, which is useful for estimating geographic distributions of sagebrush obligate species, species distribution models in which presence or absence of sagebrush is of interest, or mapping the occurrence of sagebrush in South Dakota. Inaccuracies of the NLCD shrubland products in predicting sagebrush height and sagebrush canopy cover may limit their utility as continuous variables in species distribution models, habitat selection, and suitability models or when assessing rangeland quality in South Dakota.

描绘景观的物理和生态属性的遥感数据产品正在成为野生动植物和牧场管理中的宝贵工具。但是，如果要在管理中使用此类地理空间工具和数据层，则需要审查和验证其准确性和适用性。我们通过与实地数据进行比较，评估了在南达科他州西部使用的两种国家土地覆被数据库（NLCD）灌木丛产品的准确性-鼠尾草百分比和鼠尾草高度。南达科他州西部的鼠尾草群落是鼠尾草之间的过渡地带（Artemisiaspp。）和草原。该生态交错带的特征是比内部的鼠尾草草原生态系统短而密度低的鼠尾草。这种区别可能使得在该区域中远程检测和映射鼠尾草变得困难。我们确定了NLCD与鼠尾草冠层覆盖度（r  = 0.17）和鼠尾草高度（r  = 0.40）的地面估计值之间的相关性。NLCD百分比的鼠尾草一旦重新采样到100-m像素和50-m平均值，就可以准确地预测出大约73％〜76％的时间存在鼠尾草。估计科恩的kappa值以确定在确定鼠尾草的存在时地面真实数据和遥感数据是否一致。对于50-m像素以内和100-m像素重新采样的平均值，Kappa值分别为0.26±0.06和0.28±0.06，这表明在确定鼠尾草的存在时，地面真实数据和遥感数据类型之间的“公平”协议水平。NLCD数据充分描述了南达科他州的鼠尾草的存在，这对于估算鼠尾草专性物种的地理分布，存在或不存在的物种分布模型非常有用鼠尾草的数量很有趣，或者绘制了南达科他州鼠尾草的发生情况。NLCD灌木丛产品在预测鼠尾草高度和鼠尾草冠层覆盖率方面的准确性可能会限制其作为物种分布模型，生境选择和适宜性模型中的连续变量或评估南达科他州牧场的质量时的效用。