| 山区过渡性地理空间人文自然交互性识别与分异解析 |
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| 引用本文： | 张少尧,邓伟,胡茂桂,张昊,王占韵,彭立.山区过渡性地理空间人文自然交互性识别与分异解析[J].地理学报,2022,77(5):1225-1243. |
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| 作者姓名： | 张少尧 邓伟 胡茂桂 张昊 王占韵 彭立 |
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| 作者单位： | 1.四川师范大学地理与资源科学学院,成都 6100662.中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 1001013.中国科学院成都山地灾害与环境研究所,成都 6100414.四川师范大学川西高原资源环境与可持续发展研究中心,成都 610066 |
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| 基金项目： | 国家自然科学基金项目(41930651)~~； |
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| 摘 要： | 山区因其人文自然交互过程具有显著的地域性、时空分异性与不确定性,成为典型的过渡性地理空间,其类型量化识别与分异特征的解析可为山区乡村振兴背景下国土空间高质量发展提供决策依据。本文基于地理不确定性的概念构建时空变率指数,识别出中国山区过渡性地理空间分布与分区,并运用地理探测器解析其地理时空变率的驱动力谱。结果发现：中国山区过渡性地理空间总面积为238.32×104 km2（约占中国陆表面积的1/4）,其地理时空变率从第一阶梯到第三阶梯呈递减趋势;全国山区过渡性地理空间可分为12个分区,其中昆仑—祁连山分区面积最大;人文驱动因子对人口与土地利用的时空变率解析力最强,基础地形因子对植被覆盖时空变率与地理时空变率指数的解析力最为显著,各因子中海拔与夜间灯光的解析驱动力最强。整体而言,人文要素的时空动态均对东南山区过渡性地理空间具有显著的塑造性,而西北山区过渡性地理空间主要受到自然要素的时间变化和人文要素的空间变化所驱动。本文为山区过渡性地理空间的不确定性、多样性与人地关系地域性的定量研究提供了新的见解与启示。
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| 关 键 词： | 人文自然交互 山区过渡性地理空间 时空变率 地理不确定性 信息熵 |
| 收稿时间： | 2021-09-17 |
| 修稿时间： | 2022-04-08 |
Identification and differentiation of human-nature interaction in mountainous transitional geospace of China |
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| ZHANG Shaoyao,DENG Wei,HU Maogui,ZHANG Hao,WANG Zhanyun,PENG Li.Identification and differentiation of human-nature interaction in mountainous transitional geospace of China[J].Acta Geographica Sinica,2022,77(5):1225-1243. |
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| Authors: | ZHANG Shaoyao DENG Wei HU Maogui ZHANG Hao WANG Zhanyun PENG Li |
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| Institution: | 1. College of Geography and Resources Science, Sichuan Normal University, Chengdu 610101, China2. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China3. Institute of Mountain Hazards and Environment, CAS, Chengdu 610041, China4. Sustainable Development Research Center of Resources and Environment in Western Sichuan, Sichuan Normal University, Chengdu 610101, China |
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| Abstract: | Regionalization, spatiotemporal differentiation and uncertainty are featured in the process of humanistic-natural interaction in Chinese mountain areas, making them typical mountainous transitional geospace (MTGs). Quantitative identification of MTGs types and consequent differentiation characteristics analysis can build a solid decision-making foundation for high-quality development of land space in mountainous areas under the background of rural revitalization strategy of China. This study introduced a spatiotemporal variability index based on the concept of geographic uncertainty, which was designed to work out identification, delineation and division of MTGs, and then it used the Geodetector to analyze the driving factors spectrum of the geographic spatiotemporal variability in each division of MTGs. It concludes the following points: (1) The total area of MTGs was 238.32×104 km2 (about 1/4 of the land surface area of China), with MTGs variability index in a decreasing trend from the First Gradient Terrain to the Third Gradient Terrain of China. (2) MTGs in China could be divided into 12 segmentations, of which the area of the Kunlun-Qilian Mountains subzone is the largest. (3) Humanistic driving factors had the strongest analytical power on spatiotemporal variability of population density and land-use intensity. The analytical power of the basic topographic variables, such as DEM, DEM_Relief, DEM_Slope and Topography index, had significant analytical effect on the spatiotemporal variability of vegetation coverage (NDVI) and MTGs geographic uncertainty, and the analytical driving force of altitude and night lighting brightness was the strongest among all the driving factors. (4) Generally, the spatiotemporal dynamics of human factors, such as the time variations and the spatial heterogeneities of humanistic geographical features, had a significant shaping effect on MTGs in the southeastern China, whereas in the northwestern China MTGs was mainly driven by the temporal variations of natural geographical features and the spatial heterogeneities of humanistic geographical features. This research provides an insight for quantitative analysis of geographical uncertainty and diversity in MTGs of China, and reveals the regionality of the human-nature interaction. |
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| Keywords: | human-nature interaction mountainous transitional geospace spatiotemporal variability geographic uncertainty information entropy |
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