IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i10p1916-d1259370.html
   My bibliography  Save this article

A Big Data Grided Organization and Management Method for Cropland Quality Evaluation

Author

Listed:
  • Shuangxi Miao

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China
    These authors contributed equally to this work.)

  • Shuyu Wang

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    These authors contributed equally to this work.)

  • Chunyan Huang

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China)

  • Xiaohong Xia

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China)

  • Lingling Sang

    (Key Laboratory of Land Consolidation and Rehabilitation, Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, Beijing 100035, China
    Technology Innovation Center for Land Engineering, Ministry of Natural Resources, Beijing 100035, China)

  • Jianxi Huang

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China)

  • Han Liu

    (Key Laboratory of Land Consolidation and Rehabilitation, Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, Beijing 100035, China
    Technology Innovation Center for Land Engineering, Ministry of Natural Resources, Beijing 100035, China
    Key Laboratory of Digital Mapping and Land Information Application, Ministry of Natural Resources, Wuhan 430079, China)

  • Zheng Zhang

    (Key Laboratory of Land Consolidation and Rehabilitation, Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, Beijing 100035, China
    Technology Innovation Center for Land Engineering, Ministry of Natural Resources, Beijing 100035, China)

  • Junxiao Zhang

    (Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
    Qilu Aerospace Information Research Institute, Jinan 250100, China)

  • Xu Huang

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China)

  • Fei Gao

    (Department of Natural Resources, No. 263 Hongqi Street, Harbin 150030, China)

Abstract

A new gridded spatio-temporal big data fusion method is proposed for the organization and management of cropland big data, which could serve the analysis application of cropland quality evaluation and other analyses of geographic big data. Compared with traditional big data fusion methods, this method maps the spatio-temporal and attribute features of multi-source data to grid cells in order to achieve the structural unity and orderly organization of spatio-temporal big data with format differences, semantic ambiguities, and different coordinate projections. Firstly, this paper constructs a dissected cropland big data fusion model and completes the design of a conceptual model and logic model, constructs a cropland data organization model based on DGGS (discrete global grid system) and Hash coding, and realizes the unified management of vector data, raster data and text data by using multilevel grids. Secondly, this paper researches the evaluation methods of grid-scale adaptability, and generates distributed multilevel grid datasets to meet the needs of cropland area quality evaluation. Finally, typical data such as soil organic matter data, road network data, cropland area data, and statistic data in Da’an County, China, were selected to carry out the experiment. The experiment verifies that the method could not only realize the unified organization and efficient management of cultivated land big data with multimodal characteristics, but also support the evaluation of cropland quality.

Suggested Citation

  • Shuangxi Miao & Shuyu Wang & Chunyan Huang & Xiaohong Xia & Lingling Sang & Jianxi Huang & Han Liu & Zheng Zhang & Junxiao Zhang & Xu Huang & Fei Gao, 2023. "A Big Data Grided Organization and Management Method for Cropland Quality Evaluation," Land, MDPI, vol. 12(10), pages 1-20, October.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:10:p:1916-:d:1259370
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/10/1916/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/12/10/1916/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ania Cravero & Sebastián Pardo & Patricio Galeas & Julio López Fenner & Mónica Caniupán, 2022. "Data Type and Data Sources for Agricultural Big Data and Machine Learning," Sustainability, MDPI, vol. 14(23), pages 1-37, December.
    2. Liu, Chenyu & Song, Changqing & Ye, Sijing & Cheng, Feng & Zhang, Leina & Li, Chao, 2023. "Estimate provincial-level effectiveness of the arable land requisition-compensation balance policy in mainland China in the last 20 years," Land Use Policy, Elsevier, vol. 131(C).
    3. Li Wang & Yong Zhou & Qing Li & Tao Xu & Zhengxiang Wu & Jingyi Liu, 2021. "Application of Three Deep Machine-Learning Algorithms in a Construction Assessment Model of Farmland Quality at the County Scale: Case Study of Xiangzhou, Hubei Province, China," Agriculture, MDPI, vol. 11(1), pages 1-23, January.
    4. Jed O. Kaplan & Kristen M. Krumhardt & Marie-José Gaillard & Shinya Sugita & Anna-Kari Trondman & Ralph Fyfe & Laurent Marquer & Florence Mazier & Anne Birgitte Nielsen, 2017. "Constraining the Deforestation History of Europe: Evaluation of Historical Land Use Scenarios with Pollen-Based Land Cover Reconstructions," Land, MDPI, vol. 6(4), pages 1-20, December.
    5. Xiaoyan Li & Huiying Li & Limin Yang & Yongxing Ren, 2018. "Assessment of Soil Quality of Croplands in the Corn Belt of Northeast China," Sustainability, MDPI, vol. 10(1), pages 1-16, January.
    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. Rui Zhao & Kening Wu, 2021. "Soil Health Evaluation of Farmland Based on Functional Soil Management—A Case Study of Yixing City, Jiangsu Province, China," Agriculture, MDPI, vol. 11(7), pages 1-27, June.
    2. Ryan E. Hughes & Erika Weiberg & Anton Bonnier & Martin Finné & Jed O. Kaplan, 2018. "Quantifying Land Use in Past Societies from Cultural Practice and Archaeological Data," Land, MDPI, vol. 7(1), pages 1-21, January.
    3. Yingying Xing & Ning Wang & Xiaoli Niu & Wenting Jiang & Xiukang Wang, 2021. "Assessment of Potato Farmland Soil Nutrient Based on MDS-SQI Model in the Loess Plateau," Sustainability, MDPI, vol. 13(7), pages 1-13, April.
    4. Salar Rezapour & Amin Nouri & Hawzhin M. Jalil & Shawn A. Hawkins & Scott B. Lukas, 2021. "Influence of Treated Wastewater Irrigation on Soil Nutritional-Chemical Attributes Using Soil Quality Index," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    5. Fan Yang & Fanneng He & Shicheng Li, 2020. "Spatially Explicit Reconstruction of Anthropogenic Grassland Cover Change in China from 1700 to 2000," Land, MDPI, vol. 9(8), pages 1-15, August.
    6. Fuqiang Dai & Zhiqiang Lv & Gangcai Liu, 2018. "Assessing Soil Quality for Sustainable Cropland Management Based on Factor Analysis and Fuzzy Sets: A Case Study in the Lhasa River Valley, Tibetan Plateau," Sustainability, MDPI, vol. 10(10), pages 1-17, September.
    7. Wenyu Ma & Yuchun Pan & Zaijin Sun & Changhua Liu & Xiaolan Li & Li Xu & Yunbing Gao, 2023. "Input Flux and the Risk of Heavy Metal(Loid) of Agricultural Soil in China: Based on Spatiotemporal Heterogeneity from 2000 to 2021," Land, MDPI, vol. 12(6), pages 1-22, June.
    8. Giulio Fusco & Benedetta Coluccia & Federica De Leo, 2020. "Effect of Trade Openness on Food Security in the EU: A Dynamic Panel Analysis," IJERPH, MDPI, vol. 17(12), pages 1-13, June.
    9. Yiming Fu & Yaoping Cui & Yaochen Qin & Nan Li & Liangyu Chen & Haoming Xia, 2019. "Continued Hydrothermal and Radiative Pressure on Changed Cropland in China," Sustainability, MDPI, vol. 11(14), pages 1-14, July.
    10. Fan Yang & Fanneng He & Shicheng Li & Meijiao Li, 2019. "Exploring Spatiotemporal Pattern of Grassland Cover in Western China from 1661 to 1996," IJERPH, MDPI, vol. 16(17), pages 1-17, August.
    11. Fabián Santos & Nicole Acosta, 2023. "An Approach Based on Web Scraping and Denoising Encoders to Curate Food Security Datasets," Agriculture, MDPI, vol. 13(5), pages 1-19, May.
    12. Xiaoyan Li & Limin Yang & Yongxing Ren & Huiying Li & Zongming Wang, 2018. "Impacts of Urban Sprawl on Soil Resources in the Changchun–Jilin Economic Zone, China, 2000–2015," IJERPH, MDPI, vol. 15(6), pages 1-16, June.
    13. Fengkui Qian & Yuanjun Yu & Xiuru Dong & Hanlong Gu, 2023. "Soil Quality Evaluation Based on a Minimum Data Set (MDS)—A Case Study of Tieling County, Northeast China," Land, MDPI, vol. 12(6), pages 1-16, June.
    14. Wei Fang & Xuemei Zhong & Xinhua Peng & Linyuan Li & Shaoliang Zhang & Lei Gao, 2023. "Soil Quality Mediates the Corn Yield in a Thin-Layer Mollisol in Northeast China," Land, MDPI, vol. 12(6), pages 1-15, June.
    15. 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.
    16. Han Liu & Yu Wang & Lingling Sang & Caisheng Zhao & Tengyun Hu & Hongtao Liu & Zheng Zhang & Shuyu Wang & Shuangxi Miao & Zhengshan Ju, 2023. "Evaluation of Spatiotemporal Changes in Cropland Quantity and Quality with Multi-Source Remote Sensing," Land, MDPI, vol. 12(9), pages 1-22, September.

    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:jlands:v:12:y:2023:i:10:p:1916-:d:1259370. 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.