Curran Michael F, Hodza Paddington, Cox Samuel E, Lanning Shawn G, Robertson Blair L, Robinson Timothy J, Stahl Peter D
Wyoming Reclamation and Restoration Center, University of Wyoming; Department of Ecosystem Science and Management, University of Wyoming; Program in Ecology, University of Wyoming;
Wyoming Geographic Information Science Center, University of Wyoming.
J Vis Exp. 2020 Jun 14(160). doi: 10.3791/61052.
Rangeland ecosystems cover 3.6 billion hectares globally with 239 million hectares located in the United States. These ecosystems are critical for maintaining global ecosystem services. Monitoring vegetation in these ecosystems is required to assess rangeland health, to gauge habitat suitability for wildlife and domestic livestock, to combat invasive weeds, and to elucidate temporal environmental changes. Although rangeland ecosystems cover vast areas, traditional monitoring techniques are often time-consuming and cost-inefficient, subject to high observer bias, and often lack adequate spatial information. Image-based vegetation monitoring is faster, produces permanent records (i.e., images), may result in reduced observer bias, and inherently includes adequate spatial information. Spatially balanced sampling designs are beneficial in monitoring natural resources. A protocol is presented for implementing a spatially balanced sampling design known as balanced acceptance sampling (BAS), with imagery acquired from ground-level cameras and unmanned aerial systems (UAS). A route optimization algorithm is used in addition to solve the 'travelling salesperson problem' (TSP) to increase time and cost efficiency. While UAS images can be acquired 2-3x faster than handheld images, both types of images are similar to each other in terms of accuracy and precision. Lastly, the pros and cons of each method are discussed and examples of potential applications for these methods in other ecosystems are provided.
全球牧场生态系统覆盖面积达36亿公顷，其中2.39亿公顷位于美国。这些生态系统对于维持全球生态系统服务至关重要。监测这些生态系统中的植被对于评估牧场健康状况、衡量野生动物和家畜的栖息地适宜性、对抗入侵杂草以及阐明环境随时间的变化是必要的。尽管牧场生态系统覆盖面积广阔，但传统监测技术往往耗时且成本低效，易受观察者偏差影响，且常常缺乏足够的空间信息。基于图像的植被监测速度更快，能产生永久记录（即图像），可能会减少观察者偏差，并且本身包含足够的空间信息。空间平衡抽样设计有助于自然资源监测。本文介绍了一种实施空间平衡抽样设计（称为平衡接受抽样，BAS）的方案，该方案使用从地面相机和无人机系统（UAS）获取的图像。此外，还使用了一种路线优化算法来解决“旅行商问题”（TSP），以提高时间和成本效率。虽然无人机图像的获取速度比手持图像快2至3倍，但就准确性和精度而言，这两种图像彼此相似。最后，讨论了每种方法的优缺点，并提供了这些方法在其他生态系统中的潜在应用示例。
