Sustainability | |
Simulation of Biocapacity and Spatial-Temporal Evolution Analysis of Loess Plateau in Northern Shaanxi Based on the CA–Markov Model | |
Yunfeng Hu1  Hao Wang1  | |
[1] State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; | |
关键词: land use/cover; biocapacity; CA–Markov; Loess Plateau; | |
DOI : 10.3390/su13115901 | |
来源: DOAJ |
【 摘 要 】
Biocapacity evaluation is an important part of sustainable development research, but quantitative and spatial evaluation and future scenario analysis still have model and methodological difficulties. Based on the high-resolution Globeland30 dataset, the authors analyzed the characteristics of land use/cover changes of the Loess Plateau in Northern Shaanxi from 2000 to 2020. Then, comprehensively considering the driving factors of social development, topography, climatic conditions, and spatial distance, the logistic regression method and the CA–Markov model were used to simulate the land use scenario in 2030. Finally, the biocapacity model was used to describe the spatial distribution and spatial-temporal evolution of the regional biocapacity in detail. The results showed the following: (1) Biocapacity was jointly restricted by land use types, yield factors, and equivalence factors. The high values were mainly distributed in the riparian areas of the central and eastern regions, the ridges and valleys of the central and western regions, and the farmland patches of the southern valleys; the median values were mainly distributed in the forest of the southern mountains; the low values were mainly distributed in the grassland and unused land in the hilly and gully areas of the central and northern regions. (2) The biocapacity of Loess Plateau in Northern Shaanxi increased by 9.98% from 2000 to 2010, and decreased by 4.14% from 2010 to 2020, and the total amount remained stable. It is predicted that by 2030, the regional biocapacity will continue to increase by 0.03%, reaching 16.52 × 106 gha.
【 授权许可】
Unknown