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Remote Sensing Monitoring and Spatial Pattern Analysis of Non-Grain Production of Cultivated Land in Anhui Province, China

Author

Listed:
  • Junjun Zhi

    (School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
    Engineering Technology Research Center of Resources Environment and GIS, Anhui Province, Wuhu 241002, China)

  • Xinyue Cao

    (School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China)

  • Wangbing Liu

    (Key Laboratory of Jianghuai Arable Land Resources Protection and Eco-Restoration, Hefei 230088, China)

  • Yang Sun

    (School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China)

  • Da Xu

    (Urban and Rural Planning Management Service Center of Jin’an District, Lu’an 237100, China)

  • Caiwei Da

    (School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China)

  • Lei Jin

    (Key Laboratory of Jianghuai Arable Land Resources Protection and Eco-Restoration, Hefei 230088, China)

  • Jin Wang

    (Key Laboratory of Jianghuai Arable Land Resources Protection and Eco-Restoration, Hefei 230088, China)

  • Zihao Zheng

    (College of Letters and Science, University of California, Santa Barbara, CA 93106, USA)

  • Shuyuan Lai

    (School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China)

  • YongJiao Liu

    (School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China)

  • Guohai Zhu

    (School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China)

Abstract

In recent years, non-grain production of cultivated land (NGPCL) has become increasingly prominent in China, seriously affecting food production and threatening the country’s food security. However, there is a lack of large-scale and high-precision methods for remote sensing identification of NGPCL. From the perspective of effective management of cultivated land resources, the characteristics of the spatial patterns of NGPCL, both on a large scale and at a patch scale, need to be further studied. For solving this problem, this paper uses the Google Earth engine (GEE) cloud computing platform and multi-source remote sensing data with a machine learning algorithm to determine the occurrence of NGPCL in Anhui province in 2019, and then uses nine selected landscape pattern indexes to analyze the spatial patterns of NGPCL from two aspects, specifically, economic development level and topography. The results show that: (1) terrain features, radar features, and texture features are beneficial to the extraction of NGPCL; (2) the degree of separation obtained by using an importance evaluation approach shows that spectral features have the highest importance, followed by index features with red edges, texture features, index features without red edges, radar features, and terrain features; and (3) the cultivated land in Anhui province in 2019 is mainly planted with food crops, and the phenomenon of NGPCL is more likely to occur in areas with high economic development levels and flat terrain. Aided by the GEE cloud platform, multi-source remote sensing data, and machine learning algorithm, the remote sensing monitoring approach utilized in this study could accurately, quickly, and efficiently determine NGPCL on a regional scale.

Suggested Citation

  • Junjun Zhi & Xinyue Cao & Wangbing Liu & Yang Sun & Da Xu & Caiwei Da & Lei Jin & Jin Wang & Zihao Zheng & Shuyuan Lai & YongJiao Liu & Guohai Zhu, 2023. "Remote Sensing Monitoring and Spatial Pattern Analysis of Non-Grain Production of Cultivated Land in Anhui Province, China," Land, MDPI, vol. 12(8), pages 1-21, July.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:8:p:1497-:d:1204780
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    References listed on IDEAS

    as
    1. Qiu, Tongwei & Boris Choy, S.T. & Li, Shangpu & He, Qinying & Luo, Biliang, 2020. "Does land renting-in reduce grain production? Evidence from rural China," Land Use Policy, Elsevier, vol. 90(C).
    2. Yi, Fujin & Sun, Dingqiang & Zhou, Yingheng, 2015. "Grain subsidy, liquidity constraints and food security—Impact of the grain subsidy program on the grain-sown areas in China," Food Policy, Elsevier, vol. 50(C), pages 114-124.
    3. Su, Yue & Qian, Kui & Lin, Lin & Wang, Ke & Guan, Tao & Gan, Muye, 2020. "Identifying the driving forces of non-grain production expansion in rural China and its implications for policies on cultivated land protection," Land Use Policy, Elsevier, vol. 92(C).
    4. Zhou, Yang & Li, Xunhuan & Liu, Yansui, 2021. "Cultivated land protection and rational use in China," Land Use Policy, Elsevier, vol. 106(C).
    5. Liu, Yansui & Zhou, Yang, 2021. "Reflections on China's food security and land use policy under rapid urbanization," Land Use Policy, Elsevier, vol. 109(C).
    6. Zhang, Daojun & Yang, Wanjing & Kang, Dingrong & Zhang, Han, 2023. "Spatial-temporal characteristics and policy implication for non-grain production of cultivated land in Guanzhong Region," Land Use Policy, Elsevier, vol. 125(C).
    7. Xianbo Cheng & Yu Tao & Conghong Huang & Jialin Yi & Dan Yi & Fei Wang & Qin Tao & Henghui Xi & Weixin Ou, 2022. "Unraveling the Causal Mechanisms for Non-Grain Production of Cultivated Land: An Analysis Framework Applied in Liyang, China," Land, MDPI, vol. 11(11), pages 1-20, October.
    8. Duan Ran & Zhanlu Zhang & Yuhan Jing, 2022. "A Study on the Spatial–Temporal Evolution and Driving Factors of Non-Grain Production in China’s Major Grain-Producing Provinces," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    9. Yuanzhi Guo & Jieyong Wang, 2021. "Identifying the Determinants of Nongrain Farming in China and Its Implications for Agricultural Development," Land, MDPI, vol. 10(9), pages 1-16, August.
    10. Junhan Li & Kaichun Zhou & Huimin Dong & Binggeng Xie, 2020. "Cultivated Land Change, Driving Forces and Its Impact on Landscape Pattern Changes in the Dongting Lake Basin," IJERPH, MDPI, vol. 17(21), pages 1-25, October.
    11. Ashwani Kumar Tiwari & Enrico Suozzi & Carlos Silva & Marina De Maio & Mariachiara Zanetti, 2021. "Role of Integrated Approaches in Water Resources Management: Antofagasta Region, Chile," Sustainability, MDPI, vol. 13(3), pages 1-21, January.
    12. Su, Mo & Guo, Renzhong & Hong, Wuyang, 2019. "Institutional transition and implementation path for cultivated land protection in highly urbanized regions: A case study of Shenzhen, China," Land Use Policy, Elsevier, vol. 81(C), pages 493-501.
    13. Wang, Jieyong & Zhang, Ziwen & Liu, Yansui, 2018. "Spatial shifts in grain production increases in China and implications for food security," Land Use Policy, Elsevier, vol. 74(C), pages 204-213.
    14. Yongfu Li & Bochuan Zhao & An Huang & Binyu Xiong & Canfeng Song, 2021. "Characteristics and Driving Forces of Non-Grain Production of Cultivated Land from the Perspective of Food Security," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    15. Xinru Han & Ping Xue & Ningning Zhang, 2021. "Impact of Grain Subsidy Reform on the Land Use of Smallholder Farms: Evidence from Huang-Huai-Hai Plain in China," Land, MDPI, vol. 10(9), pages 1-15, September.
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    2. Huang, Dan & Lu, Yanchi & Liu, Yaolin & Liu, Yanfang & Tong, Zhaomin & Xing, Lijun & Dou, Chao, 2024. "Multifunctional evaluation and multiscenario regulation of non-grain farmlands from the grain security perspective: Evidence from the Wuhan Metropolitan Area, China," Land Use Policy, Elsevier, vol. 146(C).

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