Remote Sensing: An Advanced Technique for Crop Condition Assessment

被引:31
|
作者
Ennouri, Karim [1 ,2 ]
Kallel, Abdelaziz [1 ]
机构
[1] Technopk Sfax, Digital Res Ctr Sfax, Sfax, Tunisia
[2] Univ Sfax, Olive Tree Inst, Lab Ameliorat & Protect Olive Genet Resources, Sfax, Tunisia
关键词
ARTIFICIAL NEURAL-NETWORKS; LAND-COVER; CLASSIFICATION; AGRICULTURE; ALGORITHMS; REGRESSION; MACHINE;
D O I
10.1155/2019/9404565
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页数:8
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