Liding Wang , Mingyang Lv , Changyong Dou , Yue Cao , Steve Carver , Xiancai Lu , Shaochun Dong , Siming Deng , Huadong Guo
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引用次数: 0
Abstract
Long-distance hiking trails worldwide serve as vital ‘threads’ connecting vast wilderness areas, offering unique opportunities to evaluate progress toward the United Nations' Sustainable Development Goals (SDGs). However, their extensive lengths pose challenges for data collection, limiting their potential use in sustainable development research. Remote sensing technologies, such as high-spatial-resolution and color glimmer imager data from SDGSAT-1, hold promise in addressing these challenges. This study focuses on seven prominent U.S. long-distance trails: the Appalachian Trail, Arizona National Scenic Trail, Buckeye Trail, Hayduke Trail, Ice Age National Scenic Trail, Pacific Crest Trail, and Pacific Northwest Trail, along with 20 km buffer zones surrounding each trail. By integrating glimmer and population data, we introduce a method to quantify human populations within these wilderness areas. Anthropogenic indicators, including population density, land use, grazing intensity, and transportation networks, are used to develop a wilderness evaluation methodology, employing an enhanced human footprint index. Our findings offer a comparative assessment of the wilderness conditions across the selected trails, providing insights into varying levels of human impact and identifying areas where conservation efforts are most urgently needed.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.