Refined land-cover classification mapping using a multi-scale transformation method from remote sensing, unmanned aerial vehicle, and field surveys in Sanjiangyuan National Park, China

作者：Shuai Han, Qingkai Meng, Haocheng Liu, Ying Peng, Han Jian-ping, Jin Sheng-hong, Shixiong Fan, Bingchang Xin, Lili He, Hao Li · 发表于：Journal of Applied Remote Sensing · 年份：2021 · DOI：10.1117/1.jrs.15.014513 · 被引用次数：8 · 研究领域：Land Use and Ecosystem Services、Remote Sensing in Agriculture、Wildlife Ecology and Conservation

Mapping the refined land-cover classification mapping (RLCM) is a primary and essential strategy for evaluating the ecological change and understanding the ecosystem services. A common problem during the generation of RLCM is a scale mismatch between remote sensing (RS) data and field quadrat, which leads to inaccuracy of the classification result. A multi-scale transformation method was developed via integrating RS, unmanned aerial vehicle (UAV), and field surveys in Sanjiangyuan National Park (SNP). With the help of UAV, a large number of virtual biomass quadrats were resampled and interpolated, and the quantitative thresholds of different vegetation coverage in alpine meadow and steppe were determined to improve land-cover classification accuracy. Based on the spatial-temporal analysis of RLCM from 1990 to 2017, the whole ecological coverage was becoming better, and its driving factor was attributed to government policy and climate change. This study can provide a practical suggestion for the management and sustainable development in SNP.