Special Issue "Drones for Biodiversity Conservation and Ecological Monitoring"
A special issue of Drones (ISSN 2504-446X).
Deadline for manuscript submissions: 31 October 2018
Dr. Ricardo Díaz-Delgado
Remote Sensing and GIS lab (LAST-EBD), Estación Biológica de Doñana, CSIC, Avda. Américo Vespucio s/n, 41092 - Seville, Spain
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Interests: Multi and hyperspectral remote sensing for monitoring vegetation; wetlands and landscape changes; Multitemporal analysis of remote sensing images; Predictive mapping of species habitat distribution; Landscape dynamics and interactions with disturbances; carbon and water fluxes with remote sensing imagery
Dr. C.A. Mücher
Wageningen Environmental Research (Alterra) Wageningen Campus, Building 101, Droevendaalsesteeg 3 P.O Box 47, 6700 AA Wageningen, The Netherlands
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Phone: +31 (0) 317 481607
Interests: Biodiversity, Geographical information systems, Landscape ecology, Remote sensing, Monitoring, Land use, Geoinformation, Habitats
Unmanned Aerial Vehicles (UAV) have already become an affordable and cost-efficient tool to quickly map a targeted area for many emerging applications in the arena of Ecological Monitoring and Biodiversity Conservation. Managers, owners, companies and scientists are using professional drones equipped with high-resolution visible, multispectral or thermal cameras to assess the state of ecosystems, the effect of disturbances, or the dynamics and changes of biological communities inter alia. We are now at a tipping point on the use of drones for these type of applications over natural areas. UAV missions are increasing but most of them testing applicability. It is time now to move to frequent revisiting missions, aiding in the retrieval of important biophysical parameters in ecosystems or mapping species distributions.
This Special Issue aims at collecting UAV applications contributing to a better understanding of biodiversity and ecosystem status, threats, changes and trends. We welcome submissions from purely scientific missions to operational management missions, evidencing the enhancement of knowledge in:
- Essential Biodiversity Variables and Ecosystem Services mapping
- Ecological Integrity parameters mapping
- Long-term ecological monitoring based on UAVs
- Mapping of alien species spread and distribution
- Upscaling ecological variables from drone to satellite images: methods and approaches
- Rapid risk and disturbance assessment using drones
- Ecosystem structure and processes assessment by using UAVs
- Mapping threats, vulnerability and conservation issues of biological communities and species
- Mapping of phenological and temporal trends
- Habitat mapping, monitoring and reporting of conservation status
Dr. Ricardo Díaz-Delgado
Dr. C.A. Mücher
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. Drones is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. 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.
Title: Calibrating Sentinel-2 Imagery with Multispectral UAV Derived Information to Quantify Damages in Rice Crops Caused by Western Swamphen in Ebro Delta (NW Mediterranean)
Authors: Magda Pla 1,*, Lluís Brotons 1,2,3, Jaume Balaguer 2, Antoni Cuscó 4, Ricard Gutiérrez 4
Affiliations: 1 Forest Sciences Center of Catalonia (CTFC-InFOREST), Carretera de Sant Llorenç de Morunys Km 2, 25280 Solsona, Lleida, Spain
2 Center for Ecological Research and Forestry Applications (CREAF), 08193 Cerdanyola del Vallès, Spain
3 Spanish National Research Council (CSIC), 08193 Cerdanyola del Vallès, Spain
4 Ministry of Territory and Sustainability, Government of Catalonia, Dr. Roux, 80, 08017 Barcelona, Spain
* Correspondence: email@example.com
Abstract: Making agricultural production compatible with the conservation of the biological wealth of the Ebro Delta is a priority objective of Catalan Government both from the point of view of biological conservation of an endangered species but also due to economic impact of any compensation policy. The threatened Western Swamphen (Porphyrio porphyrio) damages rice crops causing the decrease of rice production, producing lacks of vegetation and plant vigor decrease in rice crops. Economic compensation policies due to Swamphen protection status require an accurate damage evaluation. Sentinel-2 images are increasingly used to quantify damages in vegetation cover, but its spatial resolution requires ground-truth information to calibrate and validate the generated cartography. We used multispectral information captured from a UAV equipped with a Parrot SEQUOIA camera as ground-truth information to calibrate the Sentinel-2 NDVI and NDWI1 indices. Statistical relations between them were applied to the whole Sentinel-2 image. We assessed the final maps with random selected UAV pixels. Additionally, we calculate the damages at the level of the agrarian plot and we assessed the results with agrarian plots ground information from Government records on damages compiled by rural agents. NDWI1 presented the best fit. It was very important to consider only the pixels strictly within the agricultural plots with the objective to remove noise such as water channels or roads adjacent to crops. UAV multispectral derived information could be a viable alternative to calibrate Sentinel-2 imagery to identify and quantify damages in rice crops.