Abstract
Land use change is an essential representation of the interaction between human activities and the natural environment as well as a vital part of global environmental change and sustainable research. Exemplified by the Gansu section of the Yellow River Basin, land-use transfer matrix, land-use change index and principal component analysis are used to study the spatiotemporal evolution pattern and driving mechanism of land use. The results revealed that during the study period, grassland, plowland and woodland are the primary type of land use in the Gansu section of the Yellow River Basin, land use transition was mainly based on the transfer between plowland, grassland and construction land. The comprehensive land use change index was 0.39%, showing a fluctuation trendency of the first rising, then falling and then rising; the individual land-use change index in different land use types was shown in descending order: Construction land > water > plowland > woodland > grassland > unused land. Population structure, economic level, and industrial structure are the main driving factors affecting the change of construction land and plowland area.
Publisher
Darcy & Roy Press Co. Ltd.
Reference26 articles.
1. Frenne D.; Pieter.; Maes.; et al. Global environmental change effects on ecosystems: the importance of land-use legacies[J]. Global change biology.2016.
2. Gueneralp, B.; Seto, K.C.; Ramachandran, M. Evidence of urban land teleconnections and impacts on hinterlands[J]. Current Opinion in Environmental Sustainability.2013,5(5).
3. LIU, J.Y.; KUANG, W.; ZHANG, Z.X.; et al. Spatiotemporal characteristics, patterns and causes of land use changes in China since the late 1980s [J].Journal of Geographical Sciences. 2014,24(02).
4. Thies, B.; Meyer, H,; Nauss, T.; et al. Projecting land-use and land-cover changes in a tropical mountain forest of Southern Ecuador[J]. Journal of Land Use Science. 2012,9(1).
5. Magesh, N.S.; Chandrasekar, N. Driving forces behind land transformations in the Tamiraparani sub-basin, South India[J]. Remote Sensing Applications Society & Environment. 2017,8.