Innovative Approaches to Biodiversity and Ecology Monitoring: Artificial Intelligence (AI) and Drone Technology

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drones in Ecology".

Deadline for manuscript submissions: 25 November 2025 | Viewed by 401

Special Issue Editor


E-Mail Website
Guest Editor

Special Issue Information

Dear Colleagues,

The rapid advancement of drone technology has revolutionized the field of ecological research, providing unprecedented opportunities for monitoring biodiversity and ecosystem health. Drones equipped with high-resolution cameras and sensors can capture detailed imagery of landscapes, enabling researchers to analyze and interpret ecological patterns at scales previously unattainable. The integration of Artificial Intelligence (AI) in processing drone imagery enhances the capability to extract meaningful information, facilitating the assessment of species distribution, habitat quality, and environmental changes. This research area is crucial as it supports conservation efforts, informs policy decisions, and contributes to our understanding of ecological dynamics in the face of climate change.

The goal of this Special Issue is to collect papers (original research articles and review papers) that provide insights into the application of AI techniques in analyzing drone imagery for biodiversity and ecological studies. By fostering interdisciplinary collaboration between ecologists, data scientists, and remote sensing experts, we aim to highlight innovative methodologies, case studies, and the implications of AI-driven analyses for ecological research and conservation strategies.

This Special Issue will welcome manuscripts that link the following themes:

  • AI Techniques in Image Processing: Studies focusing on the development and application of machine learning algorithms for analyzing drone imagery.
  • Biodiversity Monitoring: Research demonstrating the use of drones and AI to assess species richness, abundance, and distribution patterns.
  • Habitat Mapping and Assessment: Papers exploring how AI can enhance habitat classification and ecological modeling using drone data.
  • Ecological Applications: Case studies showcasing practical applications of drone imagery and AI in conservation, land management, and ecological restoration.
  • Data Integration and Analysis: Contributions discussing methods for integrating drone imagery with other data sources (e.g., satellite imagery, field surveys) to enhance ecological insights.

We look forward to receiving your original research articles and reviews.

Dr. Eben N. Broadbent
Guest Editor

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.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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

  • drone imagery
  • artificial intelligence
  • biodiversity monitoring
  • ecological assessment
  • remote sensing
  • machine learning
  • habitat mapping
  • species distribution
  • conservation technology
  • environmental change

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

24 pages, 2714 KB  
Article
Drone Monitoring and Behavioral Analysis of White-Beaked Dolphins (Lagenorhynchus albirostris)
by Ditte Grønnegaard Lauridsen, Niels Madsen, Sussie Pagh, Maria Glarou, Cino Pertoldi and Marianne Helene Rasmussen
Drones 2025, 9(9), 651; https://doi.org/10.3390/drones9090651 - 16 Sep 2025
Abstract
Marine mammals serve as indicator species for environmental and human health. However, they are increasingly exposed to pressure from human activities and climate change. The white-beaked dolphin (Lagenorhynchus albirostris) (WBD) is among the species negatively affected by these conditions. To support [...] Read more.
Marine mammals serve as indicator species for environmental and human health. However, they are increasingly exposed to pressure from human activities and climate change. The white-beaked dolphin (Lagenorhynchus albirostris) (WBD) is among the species negatively affected by these conditions. To support conservation and management efforts, a deeper understanding of their behavior and movement patterns is essential. One approach is drone-based monitoring combined with artificial intelligence (AI), allowing efficient data collection and large-scale analysis. This study aims to: (1) investigate the use of drone imagery and AI to monitor and analyze marine mammal behavior, and (2) test the application of machine learning (ML) to identify behavioral patterns. Data were collected in Skjálfandi Bay, Iceland, between 2021 and 2023. Three behavioral types were identified: Traveling, Milling, and Respiration. The AI_RGB model showed high performance on Traveling behavior (precision 92.3%, recall 96.9%), while the AI_gray model achieved higher precision (97.3%) but much lower recall (9.5%). The model struggled to classify Respiration accurately (recall 1%, F1-score 2%). A key challenge was misidentification of WBDs due to visual overlap with birds, waves, and reflections, resulting in high false positive rates. Multimodal AI systems may help reduce such errors in future research. Full article
Show Figures

Figure 1

Back to TopTop