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Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China

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  • Cheng Han

    (College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China)

  • Shengbo Chen

    (College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China)

  • Yan Yu

    (College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China)

  • Zhengyuan Xu

    (College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China)

  • Bingxue Zhu

    (College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China)

  • Xitong Xu

    (College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China)

  • Zibo Wang

    (College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China)

Abstract

The suitability evaluation of agricultural land at the regional scale is of great significance for protecting land and water resources and building sustainable agricultural systems. Based on climate, soil, topographical, and surface water resources, land suitability index (LSI) data for maize, rice, and soybeans are established using an analytical hierarchy process and matter element analysis (AHP–MEA) model in Jilin Province, China. The results show that there is a significant positive linear correlation between the LSI and the measured yield, which indicates that the model has an ideal effect and certain reference and extension significance. The main limiting factors for maize and soybean planting are pH, total nitrogen (TN), available phosphorus (AP), and soil texture, while water shortage limits rice planting. Different spatial structure optimization schemes for planting are established using the LSI and measured yield, along with economic indices. This study shows that the scheme that integrates policy and cost can make full use of land and water resources and promote the economic growth of agriculture. After optimization, the planting areas of maize, rice, and soybeans were 7.22, 2.44, and 0.71 million ha, respectively, representing an increase of 15.71 billion yuan over the agricultural GDP for the existing planting structure. It is expected that this study will provide a basis for follow-up studies on crop cultivation suitability.

Suggested Citation

  • Cheng Han & Shengbo Chen & Yan Yu & Zhengyuan Xu & Bingxue Zhu & Xitong Xu & Zibo Wang, 2021. "Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China," Agriculture, MDPI, vol. 11(4), pages 1-23, April.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:4:p:370-:d:538915
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    References listed on IDEAS

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    1. Colak, H. Ebru & Memisoglu, Tugba & Gercek, Yasin, 2020. "Optimal site selection for solar photovoltaic (PV) power plants using GIS and AHP: A case study of Malatya Province, Turkey," Renewable Energy, Elsevier, vol. 149(C), pages 565-576.
    2. Ebrahim Jahanshiri & Nur Marahaini Mohd Nizar & Tengku Adhwa Syaherah Tengku Mohd Suhairi & Peter J. Gregory & Ayman Salama Mohamed & Eranga M. Wimalasiri & Sayed N. Azam-Ali, 2020. "A Land Evaluation Framework for Agricultural Diversification," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
    3. Ceballos-Silva, Alejandro & Lopez-Blanco, Jorge, 2003. "Delineation of suitable areas for crops using a Multi-Criteria Evaluation approach and land use/cover mapping: a case study in Central Mexico," Agricultural Systems, Elsevier, vol. 77(2), pages 117-136, August.
    4. Quan Xiao & Shanshan Wan & Fucai Lu & Shun Li, 2019. "Risk Assessment for Engagement in Sharing Economy of Manufacturing Enterprises: A Matter–Element Extension Based Approach," Sustainability, MDPI, vol. 11(17), pages 1-29, September.
    5. F Wang, 1994. "The Use of Artificial Neural Networks in a Geographical Information System for Agricultural Land-Suitability Assessment," Environment and Planning A, , vol. 26(2), pages 265-284, February.
    6. Mardani Najafabadi, Mostafa & Ziaee, Saman & Nikouei, Alireza & Ahmadpour Borazjani, Mahmoud, 2019. "Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study," Agricultural Systems, Elsevier, vol. 173(C), pages 218-232.
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    7. Yan Zhang & Xiaoyong Lu, 2022. "A Comprehensive Evaluation of Food Security in China and Its Obstacle Factors," IJERPH, MDPI, vol. 20(1), pages 1-17, December.

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