UAV/Drones for Agriculture and Forestry
A special issue of Drones (ISSN 2504-446X).
Deadline for manuscript submissions: closed (28 February 2019) | Viewed by 58491
Special Issue Editors
Interests: ecology; UAV; geography; land degradation; remote sensing; 3D analysis; erosion; geomorphology; soil; spectroscopy; terrestrial laser scanning
Interests: image spectroscopy; unmanned aerial vehicle; agronomy; sensor integration; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: crop water requirements; soil–water management; irrigation management; soil science; fertility; precision viticulture; remote sensing; unmanned aerial vehicles; satellite imagery
Special Issues, Collections and Topics in MDPI journals
Interests: precision agriculture; neuronal networks; software implementation; remote sensing; geographic information systems
Special Issues, Collections and Topics in MDPI journals
Interests: UAV; remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
UAV technology is developing fast in terms of platforms, cameras and integrated systems. Increasingly, commercial systems allow fast and reliable access to this technology. Agriculture and forestry are seen as important domains that could benefit from the added value of flexibility and increased spatial resolution of UAVs. However, the processing of the raw UAV datasets towards tailor-made end-products and services is still a critical step.
Although remote sensing methods for vegetation and crop analysis have already been developed for decades from satellite-based images, the specific characteristics of data derived from on-board UAV sensors allows for new methods to be developed and alternative products to be created. Taking advantage of the increased spatial resolution of the images provides opportunities for machine vision approaches developed in other domains. Simultaneously deriving spectral and height information using either multispectral sensors alone or in combination with LiDAR sensors allows machine learning approaches to improve the retrieval of relevant plant traits.
This Special Issue focuses on innovative approaches in the processing chain of UAV acquired data for applications in agriculture and forestry, including, but not limited to, the following topics:
- Calibration and modelling sensors
- Methodologies to extract information at feature level from images
- Object recognition and machine vision
- Time series and change analysis methods
- Real time exploration
- Retrieval of plant traits including 3D measurements
- Sensor-based decision support systems
- Mechatronics, robotics
- Integration of UAVs with other systems/platforms; this is relevant when linking terrestrial sensors, UAV and/or satellite images when studying large areas such as forests
- Specific agricultural applications such as fertilization management, pest management, weed detection, disease detection, mapping of plant health, ...
- Specific forestry applications such as mapping of forest biomass, species identification, forest structure, biochemistry, ...
Dr. Harm Bartholomeus
Dr. Lammert Kooistra
Dr. Javier J. Cancela
Dr. Xesús P. González
Dr. Francisco Javier Mesas Carrascosa
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.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.
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