IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i8p3484-d1380211.html
   My bibliography  Save this article

Condition Information Entropy and Rough Set Method Based on Particle Swarm Optimization Applied in the Natural Quality Evaluation of Cultivated Land

Author

Listed:
  • Hongmei Yu

    (Science and Technology on Complex Land System Simulation Laboratory, Beijing 100012, China)

  • Zhaokun Yu

    (School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China)

  • Xubing Zhang

    (School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China)

Abstract

The evaluation of the natural quality of cultivated land is crucial for preserving arable land and achieving a balance between the quantity and quality of arable land. Therefore, a timely assessment of the natural quality of cultivated land is needed to monitor its changes. However, current methods often focus on a single specified crop, neglecting the variations that occur across different specified crops. Since the indicator weight recognition method is only suitable for a single crop, this paper proposes a novel model evaluating the natural quality of cultivated land based on the method of “hidden light–temperature index and yield ratio coefficient”. In addition, the condition information entropy and rough set method based on particle swarm optimization (CIERS-PSO) were proposed to evaluate the natural quality of cultivated land in Enshi. Firstly, condition information entropy and rough set are adopted to determine the importance of the indicator automatically. Then, particle swarm optimization (PSO) is utilized to obtain the optimal weights of the first-level and second-level indicators. Finally, the proposed model and evaluation method were adopted to evaluate the natural qualities of the cultivated land. The experimental results demonstrated that the combination of the “hidden light–temperature index and yield ratio coefficient” model and the CIERS-PSO method can automatically identify the indicator weights for the evaluation of natural quality in multi-crop cultivated land. It could obtain better evaluation accuracy even if the sample size is small.

Suggested Citation

  • Hongmei Yu & Zhaokun Yu & Xubing Zhang, 2024. "Condition Information Entropy and Rough Set Method Based on Particle Swarm Optimization Applied in the Natural Quality Evaluation of Cultivated Land," Sustainability, MDPI, vol. 16(8), pages 1-13, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3484-:d:1380211
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/8/3484/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/8/3484/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohamed S. Shokr & Mostafa. A. Abdellatif & Ahmed A. El Baroudy & Abdelrazek Elnashar & Esmat F. Ali & Abdelaziz A. Belal & Wael. Attia & Mukhtar Ahmed & Ali A. Aldosari & Zoltan Szantoi & Mohamed E. , 2021. "Development of a Spatial Model for Soil Quality Assessment under Arid and Semi-Arid Conditions," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    2. Di Zhao & Junyu Dong & Shuping Ji & Miansong Huang & Quan Quan & Jian Liu, 2020. "Effects of Contemporary Land Use Types and Conversions from Wetland to Paddy Field or Dry Land on Soil Organic Carbon Fractions," Sustainability, MDPI, vol. 12(5), pages 1-15, March.
    3. Mengmeng Tang & Cuiting Wang & Chunyang Ying & Shuai Mei & Tong Tong & Youhua Ma & Qiang Wang, 2023. "Research on Cultivated Land Quality Restriction Factors Based on Cultivated Land Quality Level Evaluation," Sustainability, MDPI, vol. 15(9), pages 1-12, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Radwa A. El Behairy & Ahmed A. El Baroudy & Mahmoud M. Ibrahim & Elsayed Said Mohamed & Dmitry E. Kucher & Mohamed S. Shokr, 2022. "Assessment of Soil Capability and Crop Suitability Using Integrated Multivariate and GIS Approaches toward Agricultural Sustainability," Land, MDPI, vol. 11(7), pages 1-18, July.
    2. Elsayed A. Abdelsamie & Mostafa A. Abdellatif & Farag O. Hassan & Ahmed A. El Baroudy & Elsayed Said Mohamed & Dmitry E. Kucher & Mohamed S. Shokr, 2022. "Integration of RUSLE Model, Remote Sensing and GIS Techniques for Assessing Soil Erosion Hazards in Arid Zones," Agriculture, MDPI, vol. 13(1), pages 1-19, December.
    3. Fan Wang & Pengtao Zhang & Guijun Zhang & Jiahao Cui, 2023. "Agricultural Land Quality Evaluation and Utilization Zoning Based on the Production–Ecology–Health Dimension: A Case Study of Huanghua City," Land, MDPI, vol. 12(7), pages 1-16, July.
    4. Radwa A. El Behairy & Hasnaa M. El Arwash & Ahmed A. El Baroudy & Mahmoud M. Ibrahim & Elsayed Said Mohamed & Nazih Y. Rebouh & Mohamed S. Shokr, 2024. "An Accurate Approach for Predicting Soil Quality Based on Machine Learning in Drylands," Agriculture, MDPI, vol. 14(4), pages 1-24, April.
    5. Xiaoni You & Xiangying Li & Mika Sillanpää & Rong Wang & Chengyong Wu & Qiangqiang Xu, 2022. "Export of Dissolved Organic Carbon from the Source Region of Yangtze River in the Tibetan Plateau," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    6. Sayed Fakhreddin Afzali & Ali Khanamani & Ehsan Kamali Maskooni & Ronny Berndtsson, 2021. "Quantitative Assessment of Environmental Sensitivity to Desertification Using the Modified MEDALUS Model in a Semiarid Area," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    7. Gerson Meza Mori & Cristóbal Torres Guzmán & Manuel Oliva-Cruz & Rolando Salas López & Gladys Marlo & Elgar Barboza, 2022. "Spatial Analysis of Environmentally Sensitive Areas to Soil Degradation Using MEDALUS Model and GIS in Amazonas (Peru): An Alternative for Ecological Restoration," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    8. Mostafa A. Abdellatif & Farag O. Hassan & Heba S. A. Rashed & Ahmed A. El Baroudy & Elsayed Said Mohamed & Dmitry E. Kucher & Sameh Kotb Abd-Elmabod & Mohamed S. Shokr & Ahmed S. Abuzaid, 2023. "Assessing Soil Organic Carbon Pool for Potential Climate-Change Mitigation in Agricultural Soils—A Case Study Fayoum Depression, Egypt," Land, MDPI, vol. 12(9), pages 1-19, September.
    9. Mwehe Mathenge & Ben G. J. S. Sonneveld & Jacqueline E. W. Broerse, 2022. "Application of GIS in Agriculture in Promoting Evidence-Informed Decision Making for Improving Agriculture Sustainability: A Systematic Review," Sustainability, MDPI, vol. 14(16), pages 1-15, August.
    10. Mostafa A. Abdellatif & Ahmed A. El Baroudy & Muhammad Arshad & Esawy K. Mahmoud & Ahmed M. Saleh & Farahat S. Moghanm & Kamal H. Shaltout & Ebrahem M. Eid & Mohamed S. Shokr, 2021. "A GIS-Based Approach for the Quantitative Assessment of Soil Quality and Sustainable Agriculture," Sustainability, MDPI, vol. 13(23), pages 1-24, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3484-:d:1380211. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.