Emerging UAS-Based Remote Sensing Applications for DRR (Disaster Risk Reduction) and Ecosystem Dynamics
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 31 March 2026
Special Issue Editors
Interests: photogrammetry; artificial intelligence; remote sensing; LiDAR; plant science
Special Issues, Collections and Topics in MDPI journals
Interests: digital agriculture; plant phenotyping; machine/deep learning; 2D/3D computer vision; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: LiDAR; geomatics; natural resources; natural hazard; risk
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The accelerating frequency and intensity of disasters—both natural and human-induced—pose unprecedented challenges to ecosystems and societies worldwide. Addressing these challenges demands innovative tools and integrated approaches that link disaster risk reduction (DRR) with the understanding and management of ecosystem dynamics.
Unmanned Aerial Systems (UAS) have rapidly emerged as versatile and transformative technologies, offering unparalleled capabilities for high-resolution data acquisition and environmental assessment. This Special Issue seeks to showcase the latest scientific advances and practical innovations in the application of UAS technologies for DRR and ecosystem dynamics, encompassing the full spectrum from hazard mapping to ecosystem monitoring and adaptive management.
We invite contributions that illustrate how UAS platforms and their diverse sensor suites—such as RGB, multispectral, hyperspectral, LiDAR, Synthetic Aperture Radar (SAR), and thermal imaging—are being utilized to capture and analyze complex interactions between disasters and ecosystems across terrestrial, aquatic, and urban environments.
Topics of interest include, but are not limited to, the following:
- High-resolution spatial and temporal mapping of disaster-prone and dynamic ecosystems using UAS;
- Multi-sensor and multi-platform UAS deployments to support integrated DRR and ecosystem assessments;
- UAS-based monitoring and early detection of hazards such as wildfires, floods, landslides, droughts, and storms;
- Tracking ecosystem degradation, post-disturbance recovery, and resilience processes;
- Advanced analytical methods including AI, machine learning, and object-based image analysis applied to UAS datasets;
- Methodologies integrating UAS into DRR and ecosystem management.
While the primary focus is on disaster risk reduction and ecosystem dynamics, we also welcome submissions highlighting the role of UAS in NbS (Natural-based Solutions) and climate resilience strategies as complementary perspectives within this broader framework.
We encourage a range of article types, including the following:
- Original scientific research papers;
- Technical advances and novel methodologies;
- Comprehensive review articles and meta-analyses;
- Demonstration projects and practical case studies.
By assembling cutting-edge research and innovative applications, this Special Issue aims to define the emerging frontier of UAS-enabled disaster risk reduction and ecosystem science—empowering more resilient and sustainable futures.
Dr. Monica Herrero-Huerta
Dr. Shangpeng Sun
Dr. Francesco Pirotti
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 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
- unmanned aerial systems (UAS) or unmanned aerial vehicles (UAV)
- disaster risk reduction (DRR)
- ecosystem dynamics
- remote sensing
- multi-sensor integration
- LiDAR
- AI and machine learning
- post-disturbance recovery
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