Li Huidan, Shi Dongmei, Xia Rui, Ni Shuhui, Zhang Jianle, Wang Ronghao. Evolution characteristics and driving mechanism for the spatiotemporal pattern of sloping farmland in Chongqing based on geodetector[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(12): 280-290. DOI: 10.11975/j.issn.1002-6819.2022.12.032
    Citation: Li Huidan, Shi Dongmei, Xia Rui, Ni Shuhui, Zhang Jianle, Wang Ronghao. Evolution characteristics and driving mechanism for the spatiotemporal pattern of sloping farmland in Chongqing based on geodetector[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(12): 280-290. DOI: 10.11975/j.issn.1002-6819.2022.12.032

    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 22 300 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.
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