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作 者:刘芳[1] 闫慧敏[1] 刘纪远[1] 肖向明[2,3] 秦元伟[2]
机构地区:[1]中国科学院地理科学与资源研究所,北京100101 [2]美国俄克拉荷马大学微生物与植物生物系空间分析中心,俄克拉荷马诺曼73019 [3]复旦大学生物多样性科学研究所,上海200433
出 处:《地理学报》2016年第7期1130-1143,共14页Acta Geographica Sinica
基 金:国家自然科学基金重点项目(41430861);中国科学院科技服务网络计划(KFJ-EW-STS-019)~~
摘 要:土地利用强度直接反映了人类活动对自然生态系统的影响程度,成为全球环境变化的重要驱动力,也是土地利用可持续程度的重要测度指标。当前土地科学研究主要关注土地覆被变化及其对生态环境的影响,而土地利用强度的高分辨率时空表达尚在探索阶段。本文基于土地利用栅格成分数据、遥感数据、社会经济数据等空间化指标要素,根据地表被人类活动干扰程度及其可逆性分为人工地类、半人工地类、半天然地类、天然地类4个一级类型;依据耕作强度、人口密度等人类活动强度指标分为22个二级类型,获得空间分辨率为1 km的中国土地利用强度图。21世纪初全国人工地类、半人工地类、半天然地类和天然地类的面积比例分别为0.71%、19.36%、58.93%和21%,人口分布密集的东南部土地利用强度类型多样,且整体高于人口稀疏的西北部;随着经度的增加,土地利用强度类型由以天然地类和半天然地类为主转变为半天然地类和半人工地类为主;东部省市区土地利用强度高于中、西部,西部省市区土地利用强度最低;土地利用强度类型呈区域性集聚分布。与已有研究相比,该研究有效刻画了中国土地利用强度的空间异质性,有助于深入理解人类与自然生态系统的交互格局及其生态环境效应,为可持续土地利用政策的制定提供科学依据。In this paper, according to the intensity of human impacts, a national hierarchical land use intensity classification system was designed based on comprehensive and high- resolution spatial datasets. According to the degree and reversibility of surface disturbance by human activities, we obtained data for four main groups of artificial land, semi-artificial land, semi-natural land and natural land, which were further divided into 22 classes based on indicators such as human population density, and cropping intensity. Land use intensity in China with a 1-km spatial resolution was obtained. 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. Besides, significant spatial variability was demonstrated at national, regional and provincial levels. The southeastern region with denser population had more classes of land use intensity and was more intensive than the northwestern region with sparse population. With the increase of longitude, a transition in dominated land use intensity type was detected from natural and semi-natural land to semi-natural and semi-artificial land. The land use intensity in provinces of eastern China was the highest, followed by those in central and western regions. The land use intensity types showed a remarkable spatial differentiation of clustered distribution. Compared with the previous studies, our research effectively characterizes the spatial heterogeneity of land use intensity, which can help us to get a better understanding of spatial pattern of human-environment interactions and its eco-environmental impacts, which can provide scientific basis for sustainable land use policies.
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