| 引用本文: | 雒艺欣,冯建中※,白林燕,曹 丹,李华林,于 涛,徐运杰.2007—2017 年美国大豆产量时空变化与分析[J].中国农业信息,2018,30(2):103-114 |
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| 2007—2017 年美国大豆产量时空变化与分析 |
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雒艺欣1,2,3, 冯建中※2, 白林燕1, 曹 丹1, 李华林1, 于 涛1, 徐运杰1
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1.中国科学院遥感与数字地球研究所，北京 100094;2.中国农业科学院农业信息研究所，北京 100081;3.中国矿业大学（北京），北京 100083
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| 摘要: |
| 【目的】掌握美国大豆种植状况及产量时间空间动态，辅助制定我国大豆生产政策、
调整大豆种植结构以及确定大豆国际贸易数量。【方法】基于2007—2017 年美国大豆产量
县域统计数据并协同运用地理信息技术，采用变化率法、空间自相关分析法、重心迁移法分
析了近10 年美国大豆产量年际变化、波动趋势及空间变化特征。【结果】美国大豆产量高值
区域，仍是传统的主产区，主要分布于中部平原的密西西比河流域和密苏里河流域。近10
年间大豆产量呈增加态势，且近5 年增长迅速，其中2009、2014 年增速较快；大豆产量全
局空间自相关Moran′s I 指数介于0.669~0.726 之间，存在显著的集聚效应。局域空间自相关
Moran′s Ii 指数聚集图中高—高（HH）聚集区和低—低（LL）聚集区占比最大且有不断扩张
的趋势；大豆产量空间重心先南移后北移再向西南方向迁移，向西南方向迁移明显，总体位
移87.71km。【结论】近10 年美国大豆产量总体呈现波动上升的趋势，集聚效应明显，产量
重心显著向西南方向迁移，其是自然因素和人为原因综合共同驱动的结果。文章为分析全球
大豆运行态势、预测国际大豆价格以及我国农业相关政策制定等提供有益的参考。 |
| 关键词: 美国 大豆产量 变化率 空间自相关 重心迁移 |
| DOI：10.12105/j.issn.1672-0423.20180210 |
| 分类号: |
| 基金项目:中国农业科学院农业信息研究所科技创新工程项目“智慧农业关键技术研究与应用”（CAAS-ASTIP-2017-
AII2017）；中国科学院战略性先导科技专项项目课题“海上丝绸之路海岸带生态环境监测与评估”（XDA19030302） |
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| Spatio-temporal dynamics and analysis of soybean producing yields in the United States from 2007 to 2017 |
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Luo Yixin1,2,3, Feng Jianzhong2, Bai Linyan1, Cao Dan1, Li Hualin1, Yu Tao1, Xu Yunjie1
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1.Institute of Remote Sensing and Digital Earth，Chinese Academy of Sciences，Beijing 100094，China;2.Agricultural Information Institute，Chinese Academy of Agricultural Sciences，Beijing 100081，China;3.China University of Mining and Technology，Beijing 100083，China）
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| Abstract: |
| ［Purpose］To well know the soybean production and the spatial and temporal
dynamics of soybean yields in the United States（ U.S.） serves as important information to help us
scientifically make the available policies of soybean production，adjust & optimize the planting
structures of and decide the import/export trade volume of soybeans.［ Method］In this paper，
using geographic information technology associated with the time-series statistical yields data
of U.S. county-level soybean production from 2007 to 2017，the spatial and temporal dynamics
of soybean yields are analyzed through the change rate，spatial autocorrelation analysis，and
gravity-center migration methods［. Result］The results show that the high-value areas of soybean
yields in the nation were still mainly distributed in the Central Plains，Mississippi River Basin
and Missouri River Basin，which are the traditional main producing areas of soybeans. During the
ten-year period，there was an increasing trend of the U.S. soybean yields while its growth rates
were faster in 2009 and 2014. Here，the global Moran’s I parameter of the U.S. soybean yields
was between 0.669 and 0.726，meaning that there are significant spatial clustering of soybean
yields. Meanwhile，the cluster plots of their local Moran’s Ii parameter present that the high-high
（HH） clustering and low-low（ LL） clustering areas of soybean yields had the largest percentage
of soybean cropping areas as well as their tendencies to expand outward. The gravity-center
migrations of soybean yields had shifted towards the southwest direction with a large displacement
of 87.71 kilometers in ten years，i.e.，a rough route from north through south and then through
north and to southwest.［ Conclusion］A fluctuating upward trend of the U.S. soybean yields
was obvious from 2007 to 2017. As for its spatial clustering，they were also significant，and
in general the gravity center of the yields had greatly moved towards the southwest direction.
Those showed the changes of the U.S. soybean production during the period，which might result
synthetically from natural and man-made factors. The research would be useful for us to analyze
and understand the world’s soybean production and trade，predict the international market
prices of soybeans，and make the relevant scientific decisions to promote China’s agricultural
development and so on. |
| Key words: U.S. soybean yields rate of change spatial autocorrelation gravity-center
migration |