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Spatiotemporal Evolution of Crop Planting Structure in the Black Soil Region of Northeast China: A Case Study in Hailun County

Author

Listed:
  • Quanfeng Li

    (School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China)

  • Wei Liu

    (School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China)

  • Guoming Du

    (School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China)

  • Bonoua Faye

    (School of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

  • Huanyuan Wang

    (School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China
    These authors contributed equally to this work.)

  • Yunkai Li

    (School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China
    These authors contributed equally to this work.)

  • Lu Wang

    (School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China)

  • Shijin Qu

    (School of Public Administration, China University of Geosciences, Wuhan 430074, China)

Abstract

Detailed characteristics of crop planting structure (CPS) evolution can inform the optimization of the crop yield proportion in the black soil region of Northeast China (BSRNC). Choosing Hailun County as an example, this study sought to analyze the geographic characteristics of CPS evolution from 2000 to 2020. Our analysis produced new spatiotemporal information based on the remote-sensing interpretation data, namely, Landsat4-5 TM, Landsat7 ETM+, and Landsat8 OLI images. The study characterized the temporal and spatial dynamics of CPS. Our results showed the following: (1) Soybean and maize were the main crops, with a total land area of 70%; they alternated as the most dominant crop. (2) The distribution breadth and aggregation intensity of soybean and maize were spatially complementary; rice had the smallest distribution range but strong water aggregation. (3) The evolution pattern of CPS was the interconversion between a single type of soybean and maize. Our results indicate that the future CPS adjustment of BSRNC needs to consider the county-level optimization of crop area proportion and crop spatial distribution. This context has excellent implications in geographically informing policymaking to adjust county-level CPS of BSRNC, thus safeguarding food security.

Suggested Citation

  • Quanfeng Li & Wei Liu & Guoming Du & Bonoua Faye & Huanyuan Wang & Yunkai Li & Lu Wang & Shijin Qu, 2022. "Spatiotemporal Evolution of Crop Planting Structure in the Black Soil Region of Northeast China: A Case Study in Hailun County," Land, MDPI, vol. 11(6), pages 1-14, May.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:6:p:785-:d:824365
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    References listed on IDEAS

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    1. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike & Wu, Wenbin, 2014. "Generating global crop distribution maps: From census to grid," Agricultural Systems, Elsevier, vol. 127(C), pages 53-60.
    2. Guo, Yuanzhi & Liu, Yansui, 2021. "Poverty alleviation through land assetization and its implications for rural revitalization in China," Land Use Policy, Elsevier, vol. 105(C).
    3. Chen, Yun & Guerschman, Juan P & Cheng, Zhibo & Guo, Longzhu, 2019. "Remote sensing for vegetation monitoring in carbon capture storage regions: A review," Applied Energy, Elsevier, vol. 240(C), pages 312-326.
    4. Janet Ranganathan & Daniel Vennard, 2016. "Shifting Diets for a Sustainable Food Future," Working Papers id:10890, eSocialSciences.
    5. Ge Song & Hongmei Zhang, 2021. "Cultivated Land Use Layout Adjustment Based on Crop Planting Suitability: A Case Study of Typical Counties in Northeast China," Land, MDPI, vol. 10(2), pages 1-19, January.
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    Cited by:

    1. Bonoua Faye & Guoming Du & Edmée Mbaye & Chang’an Liang & Tidiane Sané & Ruhao Xue, 2023. "Assessing the Spatial Agricultural Land Use Transition in Thiès Region, Senegal, and Its Potential Driving Factors," Land, MDPI, vol. 12(4), pages 1-20, March.
    2. Guoming Du & Longcheng Yao & Le Han & Faye Bonoua, 2023. "What Should Be Learned from the Dynamic Evolution of Cropping Patterns in the Black Soil Region of Northeast China? A Case Study of Wangkui County, Heilongjiang Province," Land, MDPI, vol. 12(8), pages 1-17, August.

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