Remote Sensing in Precision Agriculture Production
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 7063
Special Issue Editors
Interests: remote sensing; precision agriculture; GIS; decision support systems; land management
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; multispectral and hyperspectral imaging; thermal imaging
Interests: precision agriculture; wireless sensors; IoT; digital agriculture; system analysis and control; agricultural modeling and simulation; agricultural robotics; greenhouse automation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Improving agricultural productivity requires innovative solutions that offer a better yield and quality for indoor and outdoor farming. Farmers require precision technology to obtain and interpret data to better control crop growth, preventing losses caused by adverse weather conditions or infectious pests and thus facilitating return on investments. Every year, plant diseases contribute to significant losses in global harvest, costing an estimated USD 220 billion. The abundant use of chemicals such as bactericides, fungicides, and nematicides to control plant diseases is causing adverse effects on many agroecosystems. Since the early years of precision agriculture, remote sensing has been one of the main methods for monitoring crop growth and generating data for predictive and prescriptive analytics, such as yield prediction and optimization of fertilizer use. Remote sensing plays an important role in site-specific management by providing technology and methodologies to respond to various challenges in modern farming, including precision crop monitoring, resource management, early disease detection, yield estimation, plant phenotyping, estimation of the leaf area index, and many more. With the advances in electronic and information technologies, various sensing systems and algorithms have been developed for remote sensing in precision agriculture. Currently, there are three main remote sensing platforms for this purpose: close-range, such as ground-based or handheld sensors; middle-range, such as drone-based sensors or imaging devices mounted on autonomous unmanned aerial vehicles (UAVs); and far-range platforms, such as piloted airplanes or satellite-based sensors. More recently, different customized algorithms and techniques, including artificial intelligence and machine learning methods, have been proposed to process remote sensing data.
This Special Issue aims to bring together research reports that describe new, recently developed perspectives in remote sensing for precision agriculture applications, based on innovative tools emerging from basic and applied research. The objective of the Special Issue is to increase awareness of the implications of using remote sensing solutions, including but not limited to (1) data generation and comparison using smart sensors and satellite imagery, (2) data analysis methods for estimation of crop trains, (3) monitoring of crop growth for the detection of crop stress, estimation of yield for recommending harvesting dates, and improving crop quality, (4) precision management of resources from different remote sensing platforms for managing plant disease problems in a balanced and optimized manner, and (5) the use of artificial intelligence, Internet-of-Things, digital twin, and other new cutting-edge research topics in the area of remote sensing for precision agriculture.
Prof. Dr. Abdul Rashid Mohamed Sharif
Dr. Sanaz Shafian
Dr. Redmond R. Shamshiri
Dr. Siva Kumar Balasundram
Guest Editors
Manuscript Submission Information
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Keywords
- precision farming
- remote sensing
- crop growth
- yield monitoring
- variable applicator
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