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Remote Sensing
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Advancing UAV-Based Remote Sensing: Innovations, Techniques and Applications (Second Edition)
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Advancing UAV-Based Remote Sensing: Innovations, Techniques and Applications (Second Edition)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: 28 May 2026 | Viewed by 905

Special Issue Editors

Dr. Rui Li

E-Mail Website
Guest Editor
School of Engineering, University of Warwick, Coventry CV4 7AL, UK
Interests: UAV and remote sensing image processing; computer vision; offshore wind energy
Special Issues, Collections and Topics in MDPI journals
Dr. Yinxia Cao

E-Mail Website
Guest Editor
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
Interests: building height; weakly-supervised learning; multi-view imagery; high-resolution; change detection
Special Issues, Collections and Topics in MDPI journals
Dr. Haoyang Yang

E-Mail Website
Guest Editor
Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong
Interests: embodied AI; machine learning; planning and navigation; UAV applications
Special Issues, Collections and Topics in MDPI journals
Dr. Dongyu Li

E-Mail Website
Guest Editor
School of Cyber Science and Technolgoy, Beihang University, Beijing 100191, China
Interests: UAV intelligent and application
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs) have revolutionized remote sensing, offering unprecedented opportunities for high-resolution, flexible, and cost-effective data collection. With advancements in UAV technology, sensors, and data processing algorithms, these systems are now have various critical environmental, agricultural, and urban applications. From efficient flight path planning to innovative image enhancement techniques, UAV-based remote sensing continues to expand the boundaries of research and acquire even more practical applications.

This Special Issue aims to showcase cutting-edge research and practical developments in the field of UAV-based remote sensing. We welcome studies addressing the full spectrum of UAV operations, including flight planning optimization, data acquisition, advanced image processing, and the diverse applications of UAVs in environmental monitoring, disaster response, and precision agriculture. Contributions exploring the integration of multispectral, hyperspectral, and thermal imaging, as well as innovative uses of machine learning and artificial intelligence in UAV applications, are highly encouraged.

Potential topics for this Special Issue include, but are not limited to, the following:

  • UAV path planning and autonomous navigation for remote sensing;
  • Image enhancement techniques, including denoising and super-resolution;
  • Multispectral and hyperspectral UAV applications;
  • Thermal imaging and its applications in environmental and industrial studies;
  • Precision agriculture using UAVs;
  • The use of UAVs for disaster monitoring and management;
  • Forest and vegetation monitoring;
  • Data fusion techniques for the integration of UAVs and satellites;
  • Innovations in UAV sensor design and payload optimization;
  • Ethical and regulatory considerations in UAV remote sensing.

We invite researchers and practitioners to contribute original research articles, reviews, and technical notes that will advance the art of UAV-based remote sensing.

Dr. Rui Li
Dr. Yinxia Cao
Dr. Haoyang Yang
Dr. Dongyu Li
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 250 words) can be sent to the Editorial Office for assessment.

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

  • UAV remote sensing
  • drone path planning
  • image enhancement
  • multispectral and hyperspectral imaging
  • thermal remote sensing
  • precision mapping
  • data fusion techniques
  • environmental monitoring
  • disaster response applications
  • machine learning in UAV data analysis

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

Related Special Issue

Published Papers (2 papers)

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Research

25 pages, 3777 KB  
Article
Separation of Overlapped Direct and Reflected Waveforms for Low-Altitude UAV-Based GNSS-R Altimetry
by Ziyin Xu, Xianyi Wang, Junming Xia, Yueqiang Sun, Cheng Liu, Zhuoyan Wang, Yusen Tian, Tongsheng Qiu and Dongwei Wang
Remote Sens. 2026, 18(6), 893; https://doi.org/10.3390/rs18060893 - 14 Mar 2026
Viewed by 218
Abstract
GNSS reflectometry (GNSS-R) altimetry has been widely used for retrieving surface elevation over oceans, cryosphere, and land. Recently, UAV-borne GNSS-R systems have gained attention due to their flexibility for low-altitude and localized observations. However, lightweight UAV platforms impose strict payload and real-time processing [...] Read more.
GNSS reflectometry (GNSS-R) altimetry has been widely used for retrieving surface elevation over oceans, cryosphere, and land. Recently, UAV-borne GNSS-R systems have gained attention due to their flexibility for low-altitude and localized observations. However, lightweight UAV platforms impose strict payload and real-time processing constraints. At low altitudes, the small geometric delay between direct and reflected signals often leads to waveform overlap, degrading conventional altimetry algorithms. In this study, a lightweight UAV-borne GNSS-R receiver and a signal-separation-based altimetry method are proposed. Direct and reflected signals are separated using waveform characteristics without relying on external height information, mitigating the impact of waveform overlap. Simulations and experiments using a SPIRENT 9000 GNSS simulator demonstrate stable height retrieval under dynamic low-altitude conditions while maintaining real-time capability, confirming the feasibility of lightweight UAV GNSS-R altimetry for rapid elevation monitoring. Full article
(This article belongs to the Special Issue Advancing UAV-Based Remote Sensing: Innovations, Techniques and Applications (Second Edition))
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29 pages, 7535 KB  
Article
Comparative Assessment of UAV-Based TSEB and Field-Calibrated AquaCrop for Evapotranspiration on the Arid Coast of Peru
by Roxana Peña-Amaro, José Huanuqueño-Murillo, Lia Ramos-Fernández, Abel Ramos-Ayala, David Quispe-Tito, Lena Cruz-Villacorta, Elizabeth Heros-Aguilar, Edwin Pino-Vargas and Alfonso Torres-Rua
Remote Sens. 2026, 18(6), 856; https://doi.org/10.3390/rs18060856 - 10 Mar 2026
Viewed by 341
Abstract
Precise estimation of evapotranspiration (ET) is essential for sustainable water management in arid agroecosystems, particularly for high-water-demand crops such as rice. This study integrated very-high-resolution UAV thermal–multispectral imagery with a Two-Source Energy Balance model (UAV–TSEB) and a field-calibrated AquaCrop model to quantify daily [...] Read more.
Precise estimation of evapotranspiration (ET) is essential for sustainable water management in arid agroecosystems, particularly for high-water-demand crops such as rice. This study integrated very-high-resolution UAV thermal–multispectral imagery with a Two-Source Energy Balance model (UAV–TSEB) and a field-calibrated AquaCrop model to quantify daily ET and its components under continuous flooding on the arid Peruvian coast during the 2024–2025 season. A network of 24 drainage lysimeters provided an independent observational benchmark (ETlys); to represent the treatment-level response, lysimeter observations were aggregated as the mean across the 24 units for each UAV campaign. Thirteen UAV surveys supplied radiometric surface temperature and biophysical inputs (e.g., NDVI and fractional cover) to derive spatially explicit ET, while AquaCrop provided continuous daily simulations between flight dates. Direct lysimeter-based validation indicated high agreement for AquaCrop (R2 = 0.85; RMSE = 0.26 mm d−1; MBE = 0.01 mm d−1) and moderate agreement for UAV–TSEB (R2 = 0.66; RMSE = 0.81 mm d−1; MBE = 1.01 mm d−1). Model intercomparison further showed consistent temporal dynamics of ET (R2 = 0.70; RMSE = 1.35 mm d−1) and robust partitioning of crop transpiration (R2 = 0.79; RMSE = 0.99 mm d−1) and soil evaporation (R2 = 0.76; RMSE = 1.03 mm d−1) while revealing a systematic divergence under near-complete canopy cover: AquaCrop tended to suppress evaporation, whereas UAV–TSEB detected residual evaporation from the flooded surface. Overall, the results highlight the complementarity of both approaches—UAV–TSEB as a spatial diagnostic tool and AquaCrop as a temporally continuous simulator—providing a robust framework for ET monitoring, flux partitioning, and water-use-efficiency assessment in water-scarce rice systems. Full article
(This article belongs to the Special Issue Advancing UAV-Based Remote Sensing: Innovations, Techniques and Applications (Second Edition))
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