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Advancement of Remote Sensing for Soil Measurements and Applications: A Comprehensive Review

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  • Mukhtar Iderawumi Abdulraheem

    (Department of Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China
    Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou 450002, China
    State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450002, China)

  • Wei Zhang

    (Department of Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China
    Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou 450002, China
    State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450002, China)

  • Shixin Li

    (Department of Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China)

  • Ata Jahangir Moshayedi

    (School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China)

  • Aitazaz A. Farooque

    (Faculty of Sustainable Design Engineering, University of Prince Edward Island, Charlottetown, PE C1A 4P3, Canada
    Canadian Centre for Climate Change and Adaptation, University of Prince Edward Island, St Peter’s Bay, PE C1A 4P3, Canada)

  • Jiandong Hu

    (Department of Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China
    Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou 450002, China
    State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou 450002, China)

Abstract

Remote sensing (RS) techniques offer advantages over other methods for measuring soil properties, including large-scale coverage, a non-destructive nature, temporal monitoring, multispectral capabilities, and rapid data acquisition. This review highlights the different detection methods, types, parts, and applications of RS techniques in soil measurements, as well as the advantages and disadvantages of the measurements of soil properties. The choice of the methods depends on the specific requirements of the soil measurements task because it is important to consider the advantages and limitations of each method, as well as the specific context and objective of the soil measurements, to determine the most suitable RS technique. This paper follows a well-structured arrangement after investigating the existing literature to ensure a well-organized, coherent review and covers all the essential aspects related to studying the advancement of using RS in the measurements of soil properties. While several remote sensing methods are available, this review suggests spectral reflectance, which entails satellite remote sensing and other tools based on its global coverage, high spatial resolution, long-term monitoring capabilities, non-invasiveness, and cost effectiveness. Conclusively, RS has improved soil property measurements using various methods, but more research is needed for calibration, sensor fusion, artificial intelligence, validation, and machine learning applications to enhance accuracy and applicability.

Suggested Citation

  • Mukhtar Iderawumi Abdulraheem & Wei Zhang & Shixin Li & Ata Jahangir Moshayedi & Aitazaz A. Farooque & Jiandong Hu, 2023. "Advancement of Remote Sensing for Soil Measurements and Applications: A Comprehensive Review," Sustainability, MDPI, vol. 15(21), pages 1-32, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15444-:d:1270726
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    References listed on IDEAS

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    1. Keith H Coble & Ashok K Mishra & Shannon Ferrell & Terry Griffin, 2018. "Big Data in Agriculture: A Challenge for the Future," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 40(1), pages 79-96.
    2. Köninger, Julia & Lugato, Emanuele & Panagos, Panos & Kochupillai, Mrinalini & Orgiazzi, Alberto & Briones, Maria J.I., 2021. "Manure management and soil biodiversity: Towards more sustainable food systems in the EU," Agricultural Systems, Elsevier, vol. 194(C).
    3. Chen, Qi & Li, Xinyuan & Zhang, Zhengjia & Zhou, Chao & Guo, Zhiling & Liu, Zhengguang & Zhang, Haoran, 2023. "Remote sensing of photovoltaic scenarios: Techniques, applications and future directions," Applied Energy, Elsevier, vol. 333(C).
    4. Tobias Ide, 2017. "Research methods for exploring the links between climate change and conflict," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 8(3), May.
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    Citations

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    Cited by:

    1. Zuming Cao & Xiaowei Luo & Xuemei Wang & Dun Li, 2025. "Spatial Prediction of Soil Organic Carbon Based on a Multivariate Feature Set and Stacking Ensemble Algorithm: A Case Study of Wei-Ku Oasis in China," Sustainability, MDPI, vol. 17(13), pages 1-25, July.
    2. Pooja Preetha & Naveen Joseph, 2025. "Evaluating Modified Soil Erodibility Factors with the Aid of Pedotransfer Functions and Dynamic Remote-Sensing Data for Soil Health Management," Land, MDPI, vol. 14(3), pages 1-22, March.
    3. Doaa M. Sobhy & Aavudai Anandhi, 2025. "Soil Nutrient Monitoring Technologies for Sustainable Agriculture: A Systematic Review," Sustainability, MDPI, vol. 17(18), pages 1-29, September.
    4. Hugo Rodrigues & Marcos Bacis Ceddia & Gustavo Mattos Vasques & Sabine Grunwald & Ebrahim Babaeian & André Luis Oliveira Villela, 2025. "autoRA: An Algorithm to Automatically Delineate Reference Areas—A Case Study to Map Soil Classes in Bahia, Brazil," Land, MDPI, vol. 14(3), pages 1-36, March.

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