Application of Remote Sensing in Agroforestry (Third Edition)
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ecological Remote Sensing".
Deadline for manuscript submissions: 28 February 2025 | Viewed by 1541
Special Issue Editors
Interests: remote sensing; precision agriculture; in-field data processing; remote monitoring; UAV; UAS; precision forestry; sensors and data processing; human–computer interfaces; augmented reality; virtual reality; embedded systems
Special Issues, Collections and Topics in MDPI journals
Interests: UAV; image processing algorithms (RGB, NIR, multi- and hyperspectral, thermal and LiDAR sensors); InSAR; precision agriculture; precision forestry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
As innovation continues to expand in agriculture and forestry, the integration of advanced technologies plays a pivotal role in reshaping management practices. The management of agricultural and forestry ecosystems requires a nuanced approach to enhance crop yield and quality, adopt sustainable methods, mitigate disease prevalence and reduce reliance on chemical treatments. This necessitates an in-depth understanding of the various factors influencing complex variability.
Remote sensing technology has revolutionized our ability to gather nuanced data across a spectrum of detail levels in both fields. The use of satellites, manned and unmanned aerial vehicles equipped with various sensors, including RGB, NIR, LiDAR, GPR, multi- or hyperspectral and thermal imaging, is becoming increasingly important in agriculture and forestry management.
In addition, the increasing amount of data generated by remote sensing technologies requires advanced systems that can process and integrate this information into useful insights for stakeholders. The use of deep learning and decision support systems enables the conversion of large datasets into understandable and valuable information through automated or semi-automated processes.
The third edition of this Special Issue aims to showcase the latest research, methodologies, algorithms, best practices and novel applications in remote sensing. The focus is on pushing the envelope in data analysis, visualization and practical application. Contributions are invited to advance the field through innovations in deep learning for remote sensing, decision support and management systems tailored to agroforestry, precise forecasting models for the yield and disease prediction, innovative precision agriculture and forestry approaches, and pioneering techniques for automatic yield and disease mapping and data visualization.
Dr. Emanuel Peres
Dr. Joaquim João Sousa
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- remote sensing technologies
- unmanned aerial vehicles (UAVs)
- deep learning applications
- decision support systems
- yield and disease forecasting models
- sustainable management practices
- data visualization and analysis
- sensor fusion and integration
- climate impact assessment on agroforestry
- ecological and environmental monitoring
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Related Special Issue
- Application of Remote Sensing in Agroforestry II in Remote Sensing (7 articles)
