Water scarcity in densely populated areas is a global concern. In China, ensuring water supply and quality in the middle of the South-to-North Water Diversion Project has become a major challenge due to the complexity and diversity of landscape features and the trunk canal construction in the crossing area of this route. Precise assessments of the pressures on water protection along the route are urgently needed. This article provides a rigorous methodological framework to assess water quality protection, identifying the intensity of human disturbance along the route within 2-km radius buffer areas on both sides of the trunk canal, based on land-use changes from 2005 to 2015. The results show that more than 10,000 ha of pervious surfaces were transformed into impervious surfaces, leading to undesirable outcomes. The results of this study can be used for decisive support in China’s environmental management, such as with main functional zoning policy and ecological red lines policy.
Grazing intensity, characterized by high spatial heterogeneity, is a vital parameter to accurately depict human disturbance and its effects on grassland ecosystems. Grazing census data provide useful county-scale information; however, they do not accurately delineate spatial heterogeneity within counties, and a high-resolution dataset is urgently needed. Therefore, we built a methodological framework combining the cross-scale feature extraction method and a random forest model to spatialize census data after fully considering four features affecting grazing, and produced a high-resolution gridded grazing dataset on the Qinghai–Tibet Plateau in 1982–2015. The proposed method (R2 = 0.80) exhibited 35.59% higher accuracy than the traditional method. Our dataset were highly consistent with census data (R2 of spatial accuracy = 0.96, NSE of temporal accuracy = 0.96) and field data (R2 of spatial accuracy = 0.77). Compared with public datasets, our dataset featured a higher temporal resolution (1982–2015) and spatial resolution (over two times higher). Thus, it has the potential to elucidate the spatiotemporal variation in human activities and guide the sustainable management of grassland ecosystem.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.