东北三省主要作物种植结构时空演变规律及驱动机制OA
Spatial and Temporal Evolution Law and Driving Mechanism of Major Crop Planting Structure in 3 Northeastern Provinces
为探究东北三省主要作物种植结构分布特征,分析其时空演变规律的驱动机制,采用数理统计等方法,以县域尺度和小流域尺度分别对水稻、玉米、大豆3种作物的种植比例确定组合类型,利用ArcGIS软件进行标准差椭圆分析,通过转移矩阵统计逐年面积变化情况,使用空间分析方法探究不同种植类型空间分布特征,并结合地理探测器揭示时空演变规律的驱动机制.结果表明,水稻、玉米、大豆3种作物的种植面积整体呈平稳增长的趋势,其中玉米的种植面积比重最高.以县域尺度和小流域尺度划分10种种植类型,发现小流域尺度具有更精细的分类结果.3种作物分布存在空间分异:水稻、玉米、大豆的数字高程模型依次升高,小流域尺度相比于县域尺度更低;大豆、水稻、玉米的气温依次升高,小流域尺度上3种作物的气温均高于县域尺度.种植结构在不同尺度上差异显著:水稻在像元尺度上呈稳定扩张,县域尺度方向性最强,而小流域尺度的种植中心最集中;玉米在县域尺度上方向性最明显;大豆在各尺度上方向性差异最大.大豆和玉米的种植面积转移量最大,达476.14万hm2.自然因素中高程对种植结构演变的影响较明显,政策、经济因素在一定程度上也会导致种植结构的变化,如农业机械化水平高的区域种植类型多为单一玉米型.研究结果为优化东北三省作物种植结构、提高粮食生产稳定性提供理论参考.
In order to explore the spatial and temporal distribution characteristics of major crop planting structures in 3 northeastern provinces and to analyze the driving mechanisms behind their evolution,methods such as mathematical statistics were employed.The combination types of planting proportions for rice,maize and soybean were determined at both the county scale and the small watershed scale.Standard deviation ellipse analysis was conducted using ArcGIS,while transition matrices were applied to quantify the annual changes in planting areas.Spatial analysis methods were further employed to investigate the spatial distribution characteristics of different planting types.Finally,in combination with the geographical detector,the driving mechanisms underlying the spatial-temporal evolution patterns were revealed.The results showed that the total planting area of rice,corn and soybean generally showed a steady growth trend,among which the proportion of corn planting area was the highest.By dividing the planting structure into 10 types at both the county and small watershed scales,it was found that the small watershed scale provided more refined classification results.3 crops showed spatial differentiation in their distribution.The digital elevation model values of rice,maize and soybean increased in sequence,and those at the small watershed scale were lower than that at the county scale.The temperature of soybean,rice and maize increased in sequence,and at the small watershed scale the temperatures of all 3 crops were higher than that at the county scale.The planting structures differed significantly across scales.Rice showed stable expansion at the pixel scale,the strongest orientation at the county scale,and the most concentrated planting center at the small watershed scale.Maize showed the most pronounced orientation at the county scale,and soybean exhibited the greatest variation in orientation across scales.The planting area transfer between soybean and maize was the largest,reaching up to 476.14×104 hm2.Among natural factors,the digital elevation model had significant influence on the evolution of planting structure,while policy and economic factors also contributed to changes in planting structure to some extent,such as the predominance of single-maize types in areas with higher levels of agricultural mechanization.Above results provided theoretical reference for optimizing the crop planting structure and improving the stability of grain production in the 3 northeastern provinces.
马菁芸;程彬;孟令华;戴喜龙;王一昊;刘焕军
长春师范大学地理科学学院,长春 130123||中国科学院东北地理与农业生态研究所,长春 130102长春师范大学地理科学学院,长春 130123中国科学院东北地理与农业生态研究所,长春 130102中国科学院东北地理与农业生态研究所,长春 130102中国科学院东北地理与农业生态研究所,长春 130102中国科学院东北地理与农业生态研究所,长春 130102
农业科技
东北三省种植结构时空演变地理探测器小流域
the northeast three provincesplanting structurespatial-temporal evolutiongeodetectorsmall watershed
《中国农业科技导报》 2026 (8)
200-213,14
国家重点研发计划项目(2021YFD1500100).
评论