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Remote Sensing: An Advanced Technique for Crop Condition Assessment

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  • Karim Ennouri
  • Abdelaziz Kallel

Abstract

Actually, cultivators are increasingly arranging innovative high technical and scientific estimations in the aim to enhance agricultural sustainability, effectiveness, and/or plant health. Innovative farming technologies incorporate biology with smart agriculture: computers and devices exchange with one another autonomously in a structured farm management system. Throughout this structure, smart agriculture can be accomplished; cultivators decrease plantation inputs (pesticides and fertilizers) and increase yields via integrated pest management and/or biological control. The emerging concept of remote sensing may provide a framework to systematically consider these issues of smart farming technology and to embed high-tech agriculture better. The impact(s) may be beneficial depending on how tools, such as data mining, and imagery technologies, such as picture treatment and analysis, are applied. Remote sensing technology is discussed in this review and demonstrates its possibility to create novel opportunities for scientists (and agronomists) to explore aspects of biological phenomena that cannot be accessed through usual mechanisms or processes.

Suggested Citation

  • Karim Ennouri & Abdelaziz Kallel, 2019. "Remote Sensing: An Advanced Technique for Crop Condition Assessment," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-8, July.
  • Handle: RePEc:hin:jnlmpe:9404565
    DOI: 10.1155/2019/9404565
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    Cited by:

    1. Rubaiya Binte Mostafiz & Ryozo Noguchi & Tofael Ahamed, 2021. "Agricultural Land Suitability Assessment Using Satellite Remote Sensing-Derived Soil-Vegetation Indices," Land, MDPI, vol. 10(2), pages 1-26, February.
    2. Muthumanickam Dhanaraju & Poongodi Chenniappan & Kumaraperumal Ramalingam & Sellaperumal Pazhanivelan & Ragunath Kaliaperumal, 2022. "Smart Farming: Internet of Things (IoT)-Based Sustainable Agriculture," Agriculture, MDPI, vol. 12(10), pages 1-26, October.
    3. Huaquan Zhang & Abbas Ali Chandio & Fan Yang & Yashuang Tang & Martinson Ankrah Twumasi & Ghulam Raza Sargani, 2022. "Modeling the Impact of Climatological Factors and Technological Revolution on Soybean Yield: Evidence from 13-Major Provinces of China," IJERPH, MDPI, vol. 19(9), pages 1-16, May.

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