USDA - Agricultural Research Service, Eastern Oregon Agricultural Research Center, Burns, OR, USA.
Environ Manage. 2011 May;47(5):766-76. doi: 10.1007/s00267-011-9634-3. Epub 2011 Mar 1.
Western North America is experiencing a dramatic expansion of piñon (Pinus spp.) and juniper (Juniperus spp.) (P-J) trees into shrub-steppe communities. Feature extracted data acquired from remotely sensed imagery can help managers rapidly and accurately assess this land cover change in order to manage rangeland ecosystems at a landscape-scale. The objectives of this study were to: (1) develop an effective and efficient method for accurately quantifying P-J tree canopy cover and density directly from high resolution photographs and (2) compare feature-extracted data to typical in-situ datasets used by land managers. Tree cover was extracted from aerial-photography using Feature Analyst®. Tree density was calculated as the sum of the total number of individual polygons (trees) within the tree cover output file after isolation using a negative buffer post-processing technique. Feature-extracted data were compared to ground reference measurements from Utah's Division of Wildlife Resources Range Trend Project (DWR-RTP). We found that the proposed feature-extraction techniques used for measuring cover and density were highly correlated to ground reference and DWR-RTP datasets. Feature-extracted measurements of cover generally showed a near 1:1 relationship to these data, while tree density was underestimated; however, after calibration for juvenile trees, a near 1:1 relationship was realized. Feature-extraction techniques used in this study provide an efficient method for assessing important rangeland indicators, including: density, cover, and extent of P-J tree encroachment. Correlations found between field and feature-extracted data provide evidence to support extrapolation between the two approaches when assessing woodland encroachment.
北美西部的松树（Pinus spp.）和杜松（Juniperus spp.）（P-J）正在大面积侵入灌丛草原群落。通过遥感图像获取的特征提取数据可以帮助管理者快速、准确地评估这种土地覆盖变化，从而在景观尺度上管理牧场生态系统。本研究的目的是：（1）开发一种从高分辨率照片中直接准确量化 P-J 树冠覆盖和密度的有效方法；（2）将特征提取数据与土地管理者常用的典型实地数据集进行比较。使用 Feature Analyst®从航空摄影中提取树木覆盖范围。使用负缓冲区后处理技术对隔离后的树木覆盖输出文件中的每个单独多边形（树木）的总数进行计算，从而得出树木密度。将特征提取数据与犹他州野生动物资源司的牧场趋势项目（DWR-RTP）的地面参考测量值进行比较。我们发现，用于测量覆盖度和密度的拟议特征提取技术与地面参考和 DWR-RTP 数据集高度相关。覆盖度的特征提取测量值与这些数据基本呈 1:1 关系，而树木密度则被低估；然而，在对幼树进行校准后，就实现了近乎 1:1 的关系。本研究中使用的特征提取技术为评估重要的牧场指标提供了一种高效的方法，包括：密度、覆盖度和 P-J 树侵入的范围。在实地和特征提取数据之间发现的相关性为评估林地侵入时，两种方法之间的推断提供了证据支持。
