基于地理探测器的重庆坡耕地时空格局演变特征及驱动机制

坡耕地是耕地的重要组成部分，分析坡耕地时空格局演变规律及驱动因素，有益于为合理利用坡耕地资源及生态功能修复与保持提供参考。基于2000-2018年坡耕地空间分布信息，利用土地利用转移矩阵、局部空间自相关（Local Spatial Autocorrelation, LISA）、地理探测器（Geodetector）等方法，从坡耕地时空变化特征、坡耕地冷热点格局和坡耕地变化驱动因子等方面开展，揭示重庆坡耕地时空分布特征及驱动因素。结果表明：1）与2000年相比，2018年重庆坡耕地面积减少2.40%，坡耕地2.23 万km2，占耕地59.35%。6个区县（渝中、江北、江津、南岸、大渡口、石柱）年均坡耕地变化动态度大于1%，不同区县坡耕地面积变化趋势差异明显。2）近18年坡耕地与林地、草地、水田、建设用地等地类发生显著转移，转出、转入总体较均衡，其中坡耕地退为林地主要集中位于秦巴和武陵山区的石柱、武隆、丰都、云阳等区县，在土地利用转移过程中坡耕地面积呈小幅度减少趋势。3）坡耕地局部空间自相关异质性较显著，大多数区域坡耕地面积呈高-高和低-低聚集状态，热点区集中在渝东北区，冷点区分布在渝西区和主城区。4）林业产值、农村居民人均纯收入、粮食产量、乡村从业人员、农林水支出等经济、社会及政策因素是主要驱动因子，各因子间的交互作用大部分为非线性增强和双因子增强，其中解释力较大的交互驱动因子为粮食产量/坡度（2005年，0.927）、农村居民人均纯收入/常住人口（2018年，0.910），海拔、降雨等自然因素对坡耕地变化有一定影响，但经济发展、政策调控、农民收入、城市扩张等社会经济因素是坡耕地变化的主要驱动因子。研究结果可为重庆以及西南山地丘陵区坡耕地资源保护与格局优化提供科学依据。

Evolution characteristics and driving mechanism for the spatiotemporal pattern of sloping farmland in Chongqing based on geodetector

Abstract: Sloping farmland has been one of the most important parts of cultivated land in the hills and mountains areas. It is a high demand to clarify the evolution characteristics and driving factors of the temporal and spatial pattern of sloping farmland, in order to rationally utilize resources and ecological functions. This study aims to reveal the spatial distribution characteristics and driving factors of sloping farmland in Chongqing City in southwest China. The aspects covered the temporal and spatial change characteristics, cold and hot spot patterns, as well as the driving factors of sloping farmland. Firstly, the local spatial autocorrelation (LISA) and cold hot spot were selected to determine the local spatial agglomeration characteristics of sloping farmland using the remote sensing data from 2000 to 2018. Secondly, the transfer of land use was obtained to overlay the land use data of each period. A transfer matrix of land use was then used to determine the transfer direction of sloping farmland. Finally, four dimensions were selected as the indicators, including the natural environment foundation, social living conditions, economic development level, as well as policy and institution. A geodetector was then used to determine the driving mechanism of sloping farmland change. The results showed that: 1) The area of sloping farmland decreased by 2.40% and 22300 km2 in 2018, accounting for 59.35% of the cultivated land, compared with 2000. The average annual change dynamic degree of sloping farmland was greater than 1% in the six districts and counties (Yuzhong, Jiangbei, Jiangjin, Nan''an, Dadukou, and Shizhu). There was an outstandingly different change trend of sloping farmland areas in the different districts and counties. 2) Sloping farmland was significantly transferred from the forest land, grassland, paddy field, and construction land, where the transfer out and transfer in were generally balanced during the 18 years. The sloping farmland returning to the forest land was mainly concentrated in the regions of Shizhu, Wulong, Fengdu, and Yunyang counties in the Qin-Daba and Wuling Mountainous Areas. The area of sloping farmland showed a small decrease trend in the process of land use transfer. 3) There was significant heterogeneity of local spatial autocorrelation in the sloping farmland. The area of sloping farmland in most regions was in the state of high-high and low-low aggregation. The hot spots were concentrated in the northeast of the study area, whereas, the cold spots were distributed in the west and the main urban areas. 4) The factors in the forestry output value, per capita net income of rural residents, grain yield, rural employees, agriculture, forestry, and water expenditure greatly contributed to the slope farmland change, most of which were nonlinear and two-factor enhancement. Among them, the interactive driving factors with the greater explanatory power were the grain yield/slope (2005, 0.927), and per capita net income of rural residents/resident population (2018, 0.910). The leading factors of spatiotemporal characteristics were ranked as economic development, policy regulation, farmers'' income, urban expansion, and socio-economic factors. A relatively less impact on the sloping farmland was found in the natural factors, including the altitude and rainfall. The findings can provide a scientific basis for the protection and pattern optimization of slope farmland in the mountainous and hilly areas of southwest China.