Special Issue "Unmanned Aerial Vehicles in Geomatics"
A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).
Deadline for manuscript submissions: closed (30 April 2016)
Prof. Dr. Gonzalo Pajares Martinsanz
Department Software Engineering and Artificial Intelligence, Faculty of Informatics, University Complutense of Madrid, 28040 Madrid, Spain
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Interests: computer vision; image processing; pattern recognition; 3D image reconstruction, spatio-temporal image change detection and track movement; fusion and registering from imaging sensors; superresolution from low-resolution image sensors
Unmanned Aerial Vehicles (UAVs) offer an interesting opportunity to acquire geographic information that can be conveniently processed for subsequent data analysis. This can be achieved by sensing technologies installed onboard UAVs and specific tools. The huge amount of data collected from UAVs represents a new challenge regarding developments of processing, storage, and transmission techniques, where the confluence of multidisciplinary technologies is always welcome.
Therefore, UAVs, and the sensory technologies onboard such platforms, enable different applications for efficient Earth observation. An overview of sensory technologies and of UAVs, in collaboration with relevant geomatics applications, is provided in Pajares (2015), which can be used by authors as a guide.
This Special Issue will publish papers covering a broad variety of perspectives based on geo-information. Topics include, but are not limited, to UAVs for:
- Agriculture and forestry
- Disaster monitoring
- Environmental monitoring
- Land coverage and vegetation
- Atmospheric observation
- Urban environments
Pajares, G. An Overview and Current Status of Remote Sensing Applications Based on Unmanned Aerial Vehicles (UAVs). Photogrammetry Engineering and Remote Sensing, 2015 Vol. 81, No. 4, April 2015, pp. 281-329; doi: 10.14358/PERS.81.4.197.
Prof. Dr. Gonzalo Pajares Martinsanz
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 papers will be 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. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 900 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.
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Author: Duke Bulanon
Abstract: The uniform distribution of water and nutrients to fields of crops neglects the needs and health of individual plants, often resulting in waste. A system that can easily analyze and address the differing needs of each plant can help farmers save resources and produce healthier crops. The purpose of this research is to develop engineering technologies that will improve crop production efficiency. The Crop Monitoring and Assessment Platform (C-MAP) proposed in this research utilizes a multispectral camera attached to an unmanned aerial vehicle (UAV) designed to collect pictures of entire fields from a bird’s-eye view. An image processing algorithm based on vegetation indices is used in post processing to analyze these pictures and look for correlation between plant health and image color bands. One of the most promising correlations results from the Enhanced Normalized Difference Vegetation Index (ENDVI), which has helped detect variances in crop water and nitrogen levels. In the future this platform will help farmers decrease nutrient waste and cost while increasing crop yield.