【作者】 曾紫怡； 洪宇婷； 陈果； 张烜僮； 胡梦凡； 聂艳； 王聪；

【Author】 Zeng Ziyi;Hong Yuting;Chen Guo;Zhang Xuantong;Hu Mengfan;Nie Yan;Wang Cong;School of Urban and Environmental Sciences,Central China Normal University;

【机构】 华中师范大学城市与环境科学学院；

【摘要】 本研究以江汉平原为典型区,通过景观格局指数、耦合协调度、多尺度地理加权回归模型等多维技术手段,揭示2000–2020年耕地利用形态与功能协同演变的时空规律与驱动机制。结果表明:(1)研究区耕地破碎化呈"西高东低"分异,经历"快速下降—平稳波动—显s著反弹"三阶段,且空间集聚性增强(Moran’s I由0.21升至0.27);(2)集约化水平呈"中部高、四周低"格局,综合分值由0.29升至0.38,高值区集中于沙市区、荆州区等经济核心县(市、区),2015年后出现"东降西升"分化;(3)二者耦合度从0.92升至0.95,但协调度长期处于0.54—0.50的"高度冲突—中度对抗"区间,仅当阳、枝江迈入"优质均衡";(4)坡度、人口密度对耦合协调度呈全局负向影响,人均GDP与二三产业占比呈显著正向驱动,且社会经济因子贡献率逐年上升。研究成果为国土空间智能治理、耕地资源可持续利用与农业绿色低碳转型提供精准时空决策支持,彰显数智科技在服务国家粮食安全与农业现代化中的关键作用。更多还原

【Abstract】 In this study, taking the Jianghan Plain as a typical area, the spatio-temporal laws and driving mechanisms of the coordinated evolution of cultivated land use form and function from 2000 to 2020 were revealed through multi-dimensional technical means such as landscape pattern index, coupling coordination degree and multi-scale geographically weighted regression model. The results showed that:(1) the cultivated land fragmentation in the study area showed a differentiation of "high in the west and low in the east", and experienced three stages of "rapid decline, stable fluctuation, and significant rebound", and the spatial agglomeration was enhanced(Moran’s I increased from 0.21 to 0.27);(2) the intensification level showed a pattern of "high in the middle and low in the four directions", with the comprehensive score from 0.29 to 0.38, and the high-value areas were concentrated in Shacheng District, Jingzhou District and other economic core counties(cities, districts), and after 2015, there was a differentiation of "east down and west rise".(3) The coupling degree of the two increased from 0.92 to 0.95, but the coordination degree was in the range of "high conflict-moderate confrontation" of 0.54-0.50 for a long time, and only Dangyang and Zhijiang entered the "high-quality balance".(4) Slope and population density have a global negative impact on the coupling coordination, and the proportion of per capita GDP and secondary and tertiary industries is significantly positively driven, and the contribution rate of socio-economic factors is increasing year by year. The research results provide accurate spatio-temporal decision-making support for intelligent governance of land space, sustainable use of cultivated land resources, and green and low-carbon transformation of agriculture, highlighting the key role of digital intelligence technology in serving national food security and agricultural modernization.更多还原