Status of land use intensity in China and its impacts on land carrying capacity |
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Authors: | Huimin Yan Fang Liu Jiyuan Liu Xiangming Xiao Yuanwei Qin |
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Affiliation: | 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China2. University of Chinese Academy of Sciences, Beijing 100049, China3. Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA4. Institute of Biodiversity Science, Fudan University, Shanghai 200433, China |
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Abstract: | Land use intensity quantifies the impacts of human activities on natural ecosystems, which have become the major driver of global environmental change, and thus it serves as an essential measurement for assessing land use sustainability. To date, land-change studies have mainly focused on changes in land cover and their effects on ecological processes, whereas land use intensity has not yet received the attention it deserves and for which spatially-explicit representation studies have only just begun. In this paper, according to the degree and reversibility of surface disturbance by human activities, there are four main classes of land use intensity: artificial land, semi-artificial land, semi-natural land, and natural land. These were further divided into 22 subclasses based on key indicators, such as human population density and the cropping intensity. Land use intensity map of China at a 1-km spatial resolution was obtained based on satellite images and statistical data. The area proportions of artificial land, semi-artificial land, semi-natural land, and natural land were 0.71%, 19.36%, 58.93%, and 21%, respectively. Human and economic carrying capacity increased with the increase of land use intensity. Artificial land supports 24.58% and 35.62% of the total population and GDP, using only 0.71% of the total land, while semi-artificial land supported 58.24% and 49.61% of human population and GDP with 19.36% of China’s total land area. |
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Keywords: | land use intensity land carrying capacity classification system spatial pattern |
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