Drones for Conservation
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Drones for Conservation
Drones, also known as unmanned aerial vehicles (UAVs) or uncrewed aerial systems (UAS), have become increasingly important tools for conservation. Equipped with conventional cameras, thermal sensors, multispectral and hyperspectral imaging, LiDAR, acoustic equipment, radio receivers, and increasingly artificial intelligence, drones can collect ecological information at scales that would often be difficult, expensive, dangerous, or impossible to obtain using traditional field methods.
Conservation applications now extend far beyond simple aerial photography. Researchers use drones to count wildlife, locate endangered species, monitor animal movements, examine breeding colonies, assess forests and wetlands, measure vegetation, map coral reefs and seagrass, estimate carbon stocks, monitor restoration projects, locate rare plants, detect environmental disturbance, and support wildlife-protection programs.
The rapid development of artificial intelligence and automated image analysis is further expanding these possibilities. At the same time, research shows that drones are not automatically superior to conventional methods. Detection bias, flight conditions, sensor limitations, wildlife disturbance, regulatory restrictions, and inconsistent research methods can influence their effectiveness.
Wildlife Monitoring and Population Surveys
One of the most widespread conservation uses of drones is wildlife monitoring. Traditional wildlife surveys may require researchers to walk through difficult terrain, climb trees, travel by boat, conduct expensive aircraft surveys, or repeatedly approach sensitive animals. Drones can often collect comparable or complementary information while reducing some of these logistical challenges.
Thermal imaging has become particularly important. Animals that are difficult to see against vegetation using ordinary cameras may appear clearly in thermal imagery because of differences between their body temperature and the surrounding environment. Researchers have used thermal drones to locate and count deer, koalas, tree kangaroos, gliders, elephants, primates, flying foxes, and numerous other species.
The effectiveness of thermal surveys nevertheless depends heavily on environmental conditions. Temperature, vegetation density, canopy structure, time of day, altitude, flight path, sensor settings, and the size and behavior of the target species can all influence detection.
Repeated drone surveys can also improve population estimates. Rather than assuming that every visible animal is detected during a single flight, researchers can combine repeated observations with statistical models that estimate animals missed during individual surveys.
For species inhabiting inaccessible landscapes, this capability can be particularly important. Drones have been tested in tropical forests, rugged mountains, polar environments, wetlands, coastal habitats, islands, and other areas where conventional field surveys are difficult.
Artificial Intelligence and Automated Wildlife Detection
The enormous quantity of imagery produced by conservation drones creates another problem: someone must examine it.
Artificial intelligence is increasingly being used to automate this process. Computer-vision systems can be trained to locate animals within aerial photographs and video, classify species, count individuals, identify groups, and sometimes distinguish demographic characteristics such as adults and calves.
Deep-learning systems have been developed for detecting wildlife ranging from deer and seabirds to endangered mammals and marine species. Specialized datasets are also being created to train algorithms to recognize animals that occupy only a small portion of an image or are partly hidden by vegetation.
Automated analysis could allow conservation programs to survey much larger areas because the amount of imagery collected would no longer be limited entirely by the number of people available to inspect photographs manually.
Artificial intelligence, however, does not eliminate detection problems. Algorithms can inherit biases from training datasets, perform differently under changing environmental conditions, or fail when animals look different from those represented in training images. Human verification and carefully designed validation studies therefore remain important.
Mammals, Primates, and Large Terrestrial Wildlife
Large mammals have become an important focus of drone conservation research.
Drones have been used to monitor elephants, deer, rhinoceroses, gazelles, koalas, primates, polar bears, bilbies, flying foxes, and other terrestrial mammals. Applications range from population counts to behavioral observations and habitat-use studies.
Elephants illustrate the diversity of these applications. Researchers and conservation organizations have used drones to locate animals in forests, follow collared elephants, investigate movement patterns, respond to human-elephant conflict, and study whether elephants become accustomed to repeated drone flights.
Thermal drones have also created opportunities for surveying arboreal mammals that are difficult to locate from the ground. Koalas and other tree-dwelling species can sometimes be detected through forest vegetation, allowing larger areas to be surveyed more rapidly than with conventional spotlighting or ground searches.
Primates are another important example. Thermal imagery has been tested for orangutans, gibbons, langurs, chimpanzees, and snub-nosed monkeys. In some environments drones can directly locate animals; in others they can help researchers identify nests or determine where animals are absent.
Wildlife Tracking and Radio Telemetry
Drones can do more than photograph animals. They can also carry radio receivers capable of locating tagged wildlife.
Traditional wildlife telemetry requires researchers to search for radio signals from the ground or from crewed aircraft. Drone-mounted receivers can search larger areas while reducing the need for researchers to travel repeatedly through difficult terrain.
Experimental systems can autonomously locate multiple radio-tagged animals and estimate their positions. These systems could eventually produce much more frequent information about animal movements, habitat use, migration, and survival.
Drones can also serve as a bridge between ground monitoring and satellite observation. For example, high-resolution drone imagery can provide measurements that help researchers interpret coarser satellite data or train satellite-based detection systems.
Anti-Poaching and Human-Wildlife Conflict
Wildlife protection was one of the early motivations for conservation-drone development.
Thermal and conventional cameras can potentially detect people moving through protected areas, including locations where dense vegetation makes visual surveillance difficult. Drone patrols can increase the area visible to rangers without requiring personnel to be physically present everywhere at once.
Research shows, however, that detecting people from drones depends on vegetation cover, altitude, camera type, image contrast, and environmental conditions. Drones therefore work best as components of broader ranger and surveillance systems rather than as automatic replacements for personnel on the ground.
Another application involves human-wildlife conflict. Wildlife managers have used drones to locate elephants near farms and settlements and, in some circumstances, encourage animals to move away from populated areas.
These applications demonstrate how conservation drones can serve both ecological and operational purposes: observing animals while also helping people respond to immediate conservation problems.
Birds, Nests, and Breeding Colonies
Bird monitoring is among the best-developed uses of conservation drones.
Large breeding colonies can contain thousands or even hundreds of thousands of animals spread across cliffs, islands, wetlands, or polar landscapes. Ground observers may be unable to see every nest or individual. High-resolution aerial imagery can provide a more complete view.
Drone surveys have been used to count seabirds, penguins, gulls, herons, ibises, raptors, and other colonial or nesting birds. Machine-learning systems can then automatically identify individuals or nests from the photographs.
Drones can also inspect nests located high in trees, reducing the need for researchers to climb or repeatedly approach breeding birds.
Some studies have found that aerial counts can be more precise than traditional observer counts, although accuracy varies among species and survey designs.
Wildlife Disturbance and Ethical Drone Use
A drone that helps researchers observe wildlife can itself become a source of disturbance.
Animals may respond to the sound, appearance, altitude, direction, or speed of an approaching aircraft. Responses differ greatly between species. Some animals appear relatively tolerant, while others may become alert, flee, abandon nests, or alter their behavior.
Birds have received particular attention because drones may approach nests and breeding colonies. Research suggests that altitude, approach direction, breeding stage, species behavior, and flight duration can influence responses.
Similar questions arise with marine mammals, terrestrial mammals, reptiles, and other wildlife.
Responsible drone conservation therefore requires species-specific operating protocols rather than assuming that one flight altitude or technique is safe for every animal. Researchers increasingly emphasize standardized measurements of disturbance so that evidence-based guidelines can be developed.
Bioacoustic Monitoring
Drones are also being adapted to listen rather than simply look.
Bioacoustic monitoring uses animal sounds to detect species and measure biodiversity. Birds, bats, frogs, insects, and many other organisms can potentially be identified acoustically.
The major challenge is obvious: drone propellers are extremely loud.
Researchers have therefore developed specialized microphones and signal-processing systems capable of suppressing propeller noise. More recent approaches use deep learning to recover biological sounds from extremely noisy recordings.
If these techniques continue improving, drones could carry acoustic sensors into forest canopies, wetlands, cliffs, and other locations where conventional recorders are difficult to install.
Marine Mammals and Ocean Wildlife
Marine conservation has become another major area of drone research.
Whales are particularly well suited to aerial observation because they periodically surface and their bodies can often be seen through clear water. Photogrammetry allows researchers to convert drone photographs into measurements of body length, width, condition, and sometimes estimated body mass.
Researchers have used these measurements to study humpback whales, sperm whales, right whales, belugas, and other cetaceans. Changes in body condition can provide information about reproduction, migration costs, prey availability, and population health.
Drone imagery can also be combined with biologging tags and artificial intelligence to automate measurements and estimate energy reserves.
Other marine applications include monitoring seals, sea otters, dugongs, manatees, sharks, and whale sharks. Drones allow researchers to observe many of these animals without capturing or physically handling them.
Sharks, Sea Turtles, Crocodiles, and Freshwater Wildlife
Drones are increasingly used to survey animals visible near the surface of oceans, rivers, lakes, and wetlands.
Shark-monitoring programs use drones to locate animals in nearshore waters. Research has examined both conservation applications and non-lethal approaches to reducing shark-human conflict.
Sea turtles can be surveyed from the air in feeding areas and on nesting beaches. Thermal cameras may detect turtles and nesting activity at night, while conventional aerial imagery can reveal habitat-use patterns.
Drones have also been tested for counting Nile crocodiles and large aggregations of river turtles.
In freshwater systems, aerial imagery can map fish habitat, aquatic vegetation, river channels, and other environmental features that influence aquatic biodiversity.
Forest Monitoring and Biodiversity
Forests present both opportunities and limitations for drones.
High-resolution aerial imagery can reveal canopy height, crown structure, gaps, dead trees, vegetation condition, and other features associated with biodiversity. Multispectral, hyperspectral, and LiDAR sensors greatly expand the information that can be collected.
LiDAR is especially useful because laser measurements can describe three-dimensional forest structure. Researchers can examine canopy complexity, forest edges, biomass, and habitat characteristics that may be difficult to measure using ordinary photography.
Artificial intelligence can also classify individual trees or evaluate crown condition from repeated drone surveys.
Drones occupy an important scale between traditional field plots and satellites. Field measurements provide detailed information over small areas, while satellites provide repeated observations across enormous landscapes. Drone surveys can provide extremely detailed measurements over intermediate areas and can be used to calibrate or validate satellite models.
Rare Plants and Botanical Drones
Some of the most unusual conservation drones are being designed specifically for plants.
Rare species sometimes survive on cliffs, steep slopes, islands, or other locations that are dangerous or damaging for botanists to reach. Drones can photograph these sites at close range and help researchers locate previously overlooked populations.
Specialized botanical drones have even been developed to assist with collecting plant material from inaccessible cliffs.
These methods can reduce trampling and other disturbance associated with intensive ground searches in fragile ecosystems while allowing scientists to document plants growing in places that would otherwise be extremely difficult to examine.
Ecological Restoration and Reforestation
Drones can participate in nearly every stage of ecological restoration.
Before restoration begins, aerial mapping can document erosion, vegetation, drainage, topography, and existing habitat condition. During restoration, drones can monitor planting and vegetation development. Afterward, repeated surveys can measure changes in canopy structure, plant cover, biomass, hydrology, and habitat complexity.
Some projects use drones to distribute seeds or seed balls across degraded landscapes.
Aerial seeding is attractive because a drone can potentially reach large or inaccessible areas quickly. However, successful restoration involves much more than placing seeds on the ground. Germination, rainfall, soil conditions, herbivory, competition, seed quality, and long-term seedling survival ultimately determine whether new vegetation becomes established.
For this reason, drones are better understood as restoration tools rather than substitutes for ecological planning and long-term management.
Wetlands, Rivers, Peatlands, and Grasslands
Wetlands and rivers change continually, making repeated aerial monitoring especially valuable.
Drone photogrammetry can produce detailed maps of channels, vegetation, erosion, water flow, and small water bodies. Repeated flights can reveal how river-restoration projects evolve and whether restored channels remain connected and ecologically functional.
Peatland restoration can also be monitored using drone-derived terrain models and vegetation maps. Researchers can measure bare peat, water pathways, Sphagnum cover, drainage changes, and other indicators of restoration progress.
Grassland drones can map vegetation classes, biomass, woody encroachment, erosion, and species composition. Because grassland appearance changes seasonally, research also shows that the timing of drone surveys can strongly affect habitat classification.
Coral Reefs and Seagrass
Shallow coastal ecosystems are particularly suitable for aerial monitoring when water clarity permits.
Drone imagery can measure coral cover, bleaching, and reef growth forms at very fine spatial resolution. Such surveys may provide an affordable monitoring option for regions where repeated aircraft or boat surveys are too expensive.
Seagrass meadows can also be mapped repeatedly to measure changes in extent, fragmentation, and ecological condition.
Because drones can detect relatively small disturbances, they can complement satellite monitoring by identifying losses or changes that may occur below the spatial resolution of conventional satellite imagery.
Mangroves, Salt Marshes, and Blue Carbon
Coastal vegetation plays an important role in biodiversity, shoreline protection, and carbon storage.
Mangrove forests can be studied with conventional imagery, multispectral cameras, hyperspectral sensors, and LiDAR. These measurements can reveal forest structure, species composition, tree height, biomass, and carbon stocks.
Drone measurements can also be combined with satellite imagery to estimate mangrove carbon across much larger landscapes.
Salt-marsh monitoring uses similar techniques. Researchers can measure vegetation communities, biomass, erosion, sediment deposition, invasive plants, and restoration progress.
These applications are particularly important for studies of blue carbon—carbon stored in coastal ecosystems such as mangroves, salt marshes, and seagrass meadows.
Kelp and Coastal Ecosystem Change
Drones can also monitor vegetation floating or emerging at the ocean surface.
Kelp forests provide habitat for diverse marine communities but can undergo rapid decline following marine heat waves, ecological regime shifts, herbivore outbreaks, and other disturbances.
High-resolution drone surveys can map surviving and recovering kelp canopy along sections of coastline. These data can help conservation managers identify refuges, evaluate restoration projects, and follow ecosystem recovery at spatial scales finer than many satellite observations.
Advantages of Conservation Drones
The growing use of drones reflects several practical advantages.
They can often:
- Reach inaccessible or dangerous locations.
- Collect very high-resolution imagery.
- Survey larger areas than researchers working on foot.
- Reduce the need to physically capture or handle wildlife.
- Repeat identical surveys through time.
- Carry multiple types of sensors.
- Provide three-dimensional measurements through photogrammetry and LiDAR.
- Connect detailed field observations with larger satellite datasets.
- Support automated analysis using artificial intelligence.
- Reduce some costs associated with helicopters, aircraft, boats, and intensive ground surveys.
These advantages are especially important for endangered species and remote ecosystems where traditional monitoring is expensive or difficult to repeat frequently.
Limitations and Challenges
Despite their potential, drones are not universally superior conservation tools.
Battery endurance limits flight duration and geographic coverage. Wind, rain, heat, fog, vegetation, water conditions, and lighting can reduce data quality. Dense forest canopy may hide animals completely.
Detection itself can be imperfect. An animal may be present in an image but overlooked by a human observer or an artificial-intelligence system. Population estimates therefore require careful consideration of detection probability.
Regulations governing airspace and beyond-visual-line-of-sight operations may also limit conservation missions.
Processing large volumes of imagery requires computing resources, data storage, specialized software, and trained personnel.
Different research groups also use different aircraft, sensors, flight altitudes, analytical methods, and reporting standards. This methodological variation can make results difficult to compare.
Finally, drones can disturb the wildlife they are intended to protect. Conservation benefits therefore need to be balanced against behavioral and physiological impacts on animals.
The Future of Drones in Conservation
The next generation of conservation drones is likely to become increasingly autonomous.
Aircraft may automatically navigate survey routes, recognize wildlife while still in flight, adjust sensors to environmental conditions, locate radio-tagged animals, and identify areas requiring closer inspection.
Artificial intelligence may allow enormous imagery datasets to be processed rapidly, while improved thermal cameras, LiDAR, hyperspectral sensors, and acoustic systems will expand the kinds of ecological information drones can collect.
Integration with satellites, environmental DNA, biologging tags, ground sensors, and long-term ecological databases could create monitoring systems operating across multiple spatial scales.
The most important development may therefore be not the drone itself but its integration into a broader conservation-information system.
Conclusion
Drones have developed from experimental aerial cameras into versatile conservation platforms capable of monitoring wildlife, habitats, restoration projects, forests, wetlands, rivers, coral reefs, seagrass, mangroves, and other ecosystems.
Their greatest value often comes from reaching places that are difficult to survey conventionally and collecting detailed, repeatable observations without requiring researchers to remain physically close to wildlife or fragile habitats.
Thermal imaging, LiDAR, multispectral sensors, bioacoustics, radio telemetry, photogrammetry, and artificial intelligence are rapidly increasing what these aircraft can measure. At the same time, the research shows that conservation drones are not a universal solution. Detection bias, environmental conditions, regulation, methodological inconsistency, technical limitations, and wildlife disturbance all require careful consideration.
The strongest conservation programs are therefore likely to use drones as one component of a broader monitoring strategy combining field ecology, remote sensing, automated analysis, satellite observation, community knowledge, and long-term conservation management.
Used carefully, drones can give conservationists something that has historically been difficult to obtain: detailed and frequently repeated observations of animals and ecosystems across large, inaccessible, or rapidly changing landscapes.
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Reviews, Methods, AI, and Emerging Conservation-Drone Technology
1. Thermal Drones for Wildlife Research in Tropical Forests: A Review of Best Practices, Challenges, and Opportunities
This review examines 38 studies using thermal drones in tropical forests and identifies conditions, flight protocols, species traits, and environmental factors that influence wildlife detection.
2. Pre-Programming Thermal Sensors Improves Detection During Drone-Based Nocturnal Wildlife Surveys in Warm Weather
| Lori Massey et al. | Drones | 2026-02-11
Shows how carefully programmed thermal-camera settings can improve detection of wildlife such as white-tailed deer even when warm weather reduces temperature contrast.
3. WildDrone: Autonomous Drone Technology for Monitoring Wildlife Populations
| Ulrik P. S. Lundquist et al. | Frontiers in Robotics and AI | 2026-01-12
Autonomous drones combined with computer vision and machine learning could greatly expand the frequency and geographic scale of wildlife monitoring while reducing the amount of imagery that must be inspected manually.
4. Robots for Ecological Monitoring: A Review
| Various authors | Biodiversity and Conservation | 2026
Reviews robotic systems including autonomous and remotely operated drones that can collect ecological data, locate tagged animals, and monitor difficult-to-access environments.
5. Conservation Drones
| WWF | WWF Living Planet Technology Hub | 2026
Explains how conservation organizations use camera, thermal, multispectral, acoustic, and other drone sensors for surveying, tracking, monitoring, and anti-poaching operations.
6. Understanding the Efficacy and Efficiency of Thermal Infrared UAV for Wildlife Monitoring
| Various authors | Peer-Reviewed Wildlife Monitoring Research | 2026
Compares drone survey methods using thermal cameras in Chitwan National Park, Nepal, to determine how flight design affects wildlife counts, efficiency, and image quality.
7. Thermal Infrared UAV Applications for Spatially Explicit Wildlife Occupancy Modeling
| Various authors | Land | 2025-07-14
Demonstrates a workflow combining thermal drone surveys with occupancy modeling to map wildlife detection and species richness in conservation landscapes in Nepal.
8. Collectively Advancing Deep Learning for Animal Detection in Drone Imagery: Successes, Challenges, and Research Gaps
| Daniel Axford et al. | Ecological Informatics | 2024-11
Reviews artificial-intelligence systems for detecting, locating, identifying, and counting wildlife automatically in large collections of aerial imagery.
9. Drones for Conservation
| Serge A. Wich et al. | Oxford University Press | 2021-08-31
Reviews drone applications for measuring land-cover change, estimating animal distribution and density, mapping habitat, and detecting illegal activities.
10. Evaluating New Technology for Biodiversity Monitoring: Are Drone Surveys Biased?
| Evangeline Corcoran et al. | Ecology and Evolution | 2021-05-01
Investigates whether automated drone wildlife surveys introduce detection biases and emphasizes the importance of accounting for variation among animals and environmental conditions.
11. Development Perspectives for the Application of Autonomous, Unmanned Aerial Systems in Wildlife Conservation
| Various authors | Biological Conservation | 2020-01
Examines the technological advances needed for increasingly autonomous wildlife-survey drones and stresses the need for validated protocols and standardized conservation applications.
12. Drone Technologies for Conservation
| James Duffy et al. | WWF Conservation Technology Series | 2020
A practitioner-oriented guide describes conservation drone platforms, sensors, mission planning, regulations, mapping workflows, and field case studies ranging from whales to mangroves.
13. Drones for Biodiversity Conservation and Ecological Monitoring
| Ricardo Díaz-Delgado and C. A. Mücher, editors | MDPI Books | 2019-12
Collects research on drones for biodiversity mapping, ecological monitoring, invasive species detection, wildlife tracking, habitat assessment, and ecosystem change.
14. Integrating UAV Technology in an Ecological Monitoring System for Community Wildlife Management Areas in Tanzania
| Various authors | Sustainability | 2019-11-03
Evaluates how drones could be incorporated into practical monitoring systems for wildlife and habitats in Tanzanian community-managed conservation landscapes.
15. Drones for Conservation in Protected Areas: Present and Future
| Ricardo Díaz-Delgado et al. | Drones | 2019
A review of hundreds of drone studies classifies conservation applications into wildlife monitoring, ecosystem monitoring, law enforcement, ecotourism, and environmental management.
16. Conservation Drones: Mapping and Monitoring Biodiversity
| Serge A. Wich and Lian Pin Koh | Oxford University Press | 2018-06-21
A book-length introduction to conservation drones covering sensors, mapping, surveillance, wildlife counts, image processing, and the practical design of drone conservation projects.
17. Unmanned Aerial Vehicles in Environmental Biology: A Review
| Maciej M. Nowak, Katarzyna Dziob, and Pawel Bogawski | European Journal of Ecology | 2018
Reviews more than one hundred ecological drone studies covering vegetation measurement, habitat change, bird surveys, mammal counts, and environmental monitoring.
18. Unmanned Aerial Vehicles and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation
| Luis F. Gonzalez et al. | Sensors | 2016-01-14
Explores how drones, imaging sensors, and artificial intelligence can automate detection and population estimation for threatened and invasive wildlife.
19. Are Unmanned Aircraft Systems the Future of Wildlife Monitoring? A Review of Accomplishments and Challenges
| Julie Linchant et al. | Mammal Review | 2015
An influential early review describes the advantages of drones for wildlife monitoring while examining endurance limits, detection methods, anti-poaching uses, legislation, and ethics.
Mammals, Primates, Terrestrial Wildlife, Tracking, and Protection
20. Thermal Drones for White-Tailed Deer: Precision and Accuracy, Seasonal Limitations, Best Practices, and Spatial Applications
| Kevin Gerena | Auburn University | 2026-07-27
Evaluates how season, vegetation, flight spacing, and survey design affect thermal-drone estimates of white-tailed deer density and distribution.
21. Using Drones for Large Mammal Monitoring
| Chaim Chai Elchik | Mammal Review | 2026-07-10
Reviews drone platforms, sensors, field protocols, data processing, and practical applications for monitoring large terrestrial mammals.
22. Effective Fine-Scale Drone Monitoring of Wild Asian Elephants for Conflict Mitigation and Ecological Research
| Deng et al. | Journal of Applied Ecology | 2026-06-25
Infrared drones repeatedly located wild Asian elephants in tropical forest, demonstrating potential for behavioral research and rapid responses to human-elephant conflict.
23. Low-Disturbance UAV-AI Monitoring of the Endangered Przewalski's Gazelle on the Qinghai-Tibetan Plateau
| Various authors | Ecological Informatics | 2026-06
Combines a vertical-takeoff drone with artificial intelligence to count endangered Przewalski's gazelles and map habitat connectivity threats including roads, railways, and fences.
24. AEWD: A Weakly Observable Object Detection Benchmark for UAV-Based Endangered Wildlife Monitoring
| Menglu Ma et al. | Ecological Informatics | 2026-03
Introduces thousands of annotated drone images of Amur tigers, giant pandas, golden snub-nosed monkeys, and Sichuan takins to improve artificial-intelligence detection of endangered wildlife in cluttered forests.
25. Tracking Collared Elephants with Drones
Describes how WWF-Kenya and the Kenya Wildlife Service use drones to locate and monitor collared elephants moving through the greater Mara ecosystem.
26. An Algorithm for Animal Detection and Counting in Unmanned Aerial Imagery under Complex Environments
| Shaowen Wang, Dongliang Wang, and Jinbang Peng | Measurement | 2026
Develops a hybrid artificial-intelligence architecture designed to improve automated detection and counting of small animals in complex drone imagery.
27. KWS Enhances Wildlife Conservation Through Deployment of Drones
| Kenya Wildlife Service | Kenya Wildlife Service | 2026
Kenya Wildlife Service describes expanding drone surveillance across protected areas to strengthen wildlife monitoring, deter poaching and bushmeat hunting, and improve ranger operational efficiency.
28. Drones in Conservation Project
| Global Conservation Tech & Drone Forum | Global Conservation Tech & Drone Forum | 2026
This international conservation-drone project map documents applications ranging from elephant monitoring and anti-poaching to habitat restoration, environmental management, and community-based conservation.
29. SORA 2.5-Guided BVLOS UAS for Wildlife Conservation in Kenya: Reducing Friction Between Safety and Field Operations
| Guy Maalouf et al. | Drones | 2026
Examines beyond-visual-line-of-sight drone operations in Kenyan conservation areas and shows how risk-based aviation procedures can enable longer-range wildlife monitoring while maintaining airspace safety.
30. Q1 2026 Ranger Report
| Mara Elephant Project | Mara Elephant Project | 2026
Reports how conservation drones were used not only for elephant conflict response but also for giraffe veterinary operations and structured surveys supporting recovery of Kenya's remaining wild roan antelope population.
31. Wildlife Responses to Drone Noise: A Preliminary Approach for Quantifying Disturbance During Single- and Dual-Drone Flights
| Various authors | Ecology and Evolution | 2026
Investigates behavioral responses of savanna wildlife to single and multiple drones and highlights the need to understand cumulative acoustic and visual disturbance.
32. New Study Finds That Drones Can Be a Valuable Ally in Elephant Conservation
| University of Oxford and Save the Elephants | University of Oxford | 2025-11-28
Reports research showing that elephants can become accustomed to carefully operated drones, potentially allowing researchers to observe them with reduced disturbance.
33. Cutting-Edge Thermal Drones Reveal Hidden Strongholds of Endangered Koalas and Gliders
| Kevin Fallon and India Glyde | University of Wollongong | 2025-11-13
Reports large-scale thermal drone surveys that discovered important populations of koalas and greater gliders across the Illawarra Escarpment and Plateau.
34. Orangutan Population Monitoring Methods: Strengths, Challenges, and Opportunities
| Various authors | Biological Conservation | 2025-09
Reviews orangutan monitoring approaches and highlights thermal drones and machine learning as promising ways to improve direct population estimates.
35. Acoustic Monitoring with Miniature Drones Shows Reduced Myotis Bat Occurrence with Altitude and Drone Movement
| Lauren Dobie, David M. Bird, and Kyle H. Elliott | Scientific Reports | 2025-04-10
Mounts acoustic equipment on small drones to sample bats in the air column and finds that hovering surveys can outperform moving flight transects for some bat groups.
36. Developing a New Method Using Thermal Drones for Population Surveys of the World's Rarest Great Ape Species, Pongo tapanuliensis
| Various authors | Global Ecology and Conservation | 2025-04
Shows that thermal drones can detect and count critically endangered Tapanuli orangutans in forest canopies while covering more ground than observers on foot.
37. Enhancing Wildlife Detection Using Thermal Imaging Drones: Designing the Flight Path
| Various authors | Drones | 2025-01-13
Develops habitat-based flight paths for thermal drone wildlife surveys and demonstrates the method with Formosan sika deer on a South Korean island.
38. Elephant Habituation to Drones as a Behavioural Observation Tool
| Various authors | Scientific Reports | 2025
Repeated drone trials with African savannah elephants found evidence of habituation, suggesting drones may become useful observation tools when flights are designed to minimize disturbance.
39. Estimating the Landscape-Scale Abundance of an Arboreal Folivore Using Thermal Imaging Drones and Binomial N-Mixture Modelling
| Various authors | Biological Conservation | 2025
Uses repeated thermal drone surveys and statistical models to estimate thousands of koalas across more than 670 square kilometers of protected land.
40. Thermal Drones Are Highly Effective for Detecting Elusive Bennett's Tree Kangaroos in Australia's Tropical Rainforests
| Various authors | Australian Mammalogy | 2025
Demonstrates rapid thermal-drone detection of Bennett's tree kangaroos in dense tropical rainforest where conventional wildlife surveys are difficult.
41. Feasibility of Nocturnal Thermal Drone Surveys for Detecting Endangered Mahogany Gliders
| Various authors | Australian Mammalogy | 2025
Tests thermal drones for locating the endangered mahogany glider and suggests the technology could complement conventional presence-absence and population surveys.
42. Thermal Drone Surveys to Detect Arboreal Fauna: Improving Population Estimates and Threatened Species Monitoring
| Benjamin Wagner et al. | Ecological Applications | 2025
Compares thermal drones with ground spotlight surveys and finds drones particularly valuable for detecting threatened arboreal mammals over large or inaccessible forest areas.
43. A Drone-Based Population Survey of Delacour's Langur in the Karst Forests of Northern Vietnam
| Hoang Trinh-Dinh et al. | Biological Conservation | 2024-12
Thermal and optical drone surveys produced a substantially larger population estimate for critically endangered Delacour's langurs than earlier ground-based surveys.
44. Development of a Global Thermal Detection Index to Prioritize Primate Research with Thermal Drones
| Eva Gazagne et al. | Scientific Reports | 2024-11-14
Creates a global framework for identifying primate species and geographic regions where thermal drone monitoring is most likely to succeed.
45. Exploring Drone-Based Koala Surveys
| NSW Natural Resources Commission | NSW Government | 2024-04-18
Examines the practicality of using thermal drones to measure koala population responses to forestry operations and discusses cost and survey-design considerations.
46. Deer Survey from Drone Thermal Imagery Using Enhanced Faster R-CNN
| Various authors | Ecological Informatics | 2024-03
Develops an artificial-intelligence system for identifying deer as very small objects in drone thermal imagery, improving automated wildlife census capabilities.
47. Drone with Mounted Thermal Infrared Cameras for Monitoring Terrestrial Mammals
| Various authors | Drones | 2023-11-18
Tests thermal drones for identifying and counting red deer, roe deer, and other mammals and examines whether body measurements can help distinguish species from above.
48. Mapping Potential Human-Elephant Conflict Hotspots with UAV Monitoring Data
| Various authors | Global Ecology and Conservation | 2023-06
Uses drone-derived elephant locations to map potential conflict hotspots and links them with settlements, rivers, highways, slopes, and food-rich habitats.
49. Unmanned Aerial Vehicles with Thermal Infrared Sensors Are Effective for Monitoring and Counting Threatened Vietnamese Primates
| Various authors | Peer-Reviewed Primate Research | 2023
Tests thermal drones on endangered langurs and gibbons and finds substantially better detection than conventional RGB aerial imagery.
50. Undertaking Wildlife Surveys with Unmanned Aerial Vehicles in Rugged Mountains with Dense Vegetation: A Tentative Model Using Sichuan Snub-Nosed Monkeys
| Various authors | Global Ecology and Conservation | 2023
Tests drone-based methods for surveying primates in steep, densely vegetated mountain environments where conventional population surveys are particularly difficult.
51. Using Drones to Determine Chimpanzee Absences at the Edge of Their Distribution in Western Tanzania
| Various authors | Remote Sensing / UCL Discovery | 2023
Demonstrates how drone imagery can supplement conventional surveys by helping conservationists determine where chimpanzee nests are genuinely absent.
52. Using Drones to Protect the Endangered Mauritian Flying Fox
Describes a conservation project using thermal drones to estimate flying-fox numbers, study behavior, and improve management of human-wildlife conflict in Mauritius.
53. Using Drones to Track Reintroduced Species and Estimate Population Size
| Australian Wildlife Conservancy | Australian Wildlife Conservancy | 2022
Thermal drone estimates of reintroduced bilbies closely matched estimates produced by intensive live-trapping surveys, suggesting a less invasive monitoring alternative.
54. Thermal Infrared Imaging from Drones Can Detect Individuals and Nocturnal Behavior of the World's Rarest Primate
| Various authors | Global Ecology and Conservation | 2020-09
Demonstrates that thermal drone imagery can locate Hainan gibbons and record behavior that is otherwise extremely difficult for conservation researchers to observe.
55. A Bespoke Low-Cost System for Radio Tracking Animals Using Multi-Rotor and Fixed-Wing Unmanned Aerial Vehicles
| Benjamin Roberts et al. | Methods in Ecology and Evolution | 2020-08-08
Develops inexpensive radio-tracking equipment compatible with both fixed-wing and multirotor drones and demonstrates the system using tagged animals.
56. Real-Time Drone Derived Thermal Imagery Outperforms Traditional Survey Methods for an Arboreal Forest Mammal
| Various authors | PLOS ONE | 2020
Finds that thermal drones can detect koalas efficiently across forest landscapes and compares their performance with spotlighting and traditional ground-search methods.
57. Investigating the Use of Drone-Acquired Thermal Imagery to Inform the Management and Conservation of Flying-Fox Colonies
| Eliane D. McCarthy | Western Sydney University | 2020
Finds that thermal orthomosaics can reveal flying-fox colony size, density, and spatial distribution that may be underestimated through conventional ground counting.
58. Measuring the Spectral Signature of Polar Bears from a Drone to Improve Their Detection from Space
| Various authors | Biological Conservation | 2019-09
Uses multispectral drone imagery of polar bears to determine how their spectral characteristics could improve automated detection in satellite imagery across remote Arctic landscapes.
59. Detecting ‘Poachers’ with Drones: Factors Influencing the Probability of Detection with TIR and RGB Imaging in Miombo Woodlands, Tanzania
| Various authors | Biological Conservation | 2019-05
Tests thermal and visible-light drone cameras for detecting people concealed in woodland and identifies canopy cover, altitude, image contrast, and sensor type as important factors affecting anti-poaching surveillance.
60. TrackerBots: Autonomous Unmanned Aerial Vehicle for Real-Time Localization and Tracking of Multiple Radio-Tagged Animals
| Hoa Van Nguyen et al. | Journal of Field Robotics | 2019-01-04
Describes an autonomous drone capable of locating multiple radio-tagged animals, potentially enabling much more frequent movement and habitat-use observations.
61. Using Drones and Sirens to Elicit Avoidance Behaviour in White Rhinoceros as an Anti-Poaching Tactic
| Various authors | Proceedings of the Royal Society B / PMC | 2019
Tests whether drones and other deterrents can move rhinos away from high-risk areas such as reserve boundaries where poaching threats may be greater.
62. UAV Wildlife Radiotelemetry: System and Methods of Localization
| Michael W. Shafer et al. | Methods in Ecology and Evolution | 2019
Demonstrates an open-source drone system for locating VHF-tagged wildlife and shows that aerial receivers can improve signal strength, search speed, and localization accuracy.
63. UAV-RT: An SDR Based Aerial Platform for Wildlife Tracking
| Amir Torabi et al. | IEEE Vehicular Technology Conference | 2018-07-02
Integrates drone flight with software-defined radio and directional antennas to detect radio-tagged animals over larger distances than ground-based receivers.
64. Assessment of Chimpanzee Nest Detectability in Drone-Acquired Images
| Various authors | Drones | 2018
Tests whether fixed-wing drones can detect chimpanzee nests in Tanzanian forests and identifies image resolution as a major determinant of successful detection.
65. Unmanned Aerial Vehicles Mitigate Human-Elephant Conflict on the Borders of Tanzanian Parks: A Case Study
| Nathan Hahn et al. | Oryx | 2017
Field trials in northern Tanzania found that trained wildlife managers could use inexpensive drones to move crop-raiding elephants away from farms and settlements while maintaining safer distances for people and elephants.
66. Eyes over Kenya: The Use of Drones for Conservation
| Chelsea Barabas et al. | MIT | 2015-03-10
Reports field work with Kenyan conservancies examining the potential and social requirements for using drones in wildlife protection and anti-poaching programs.
67. Remotely Piloted Aircraft Systems as a Rhinoceros Anti-Poaching Tool in Africa
| Various authors | PLOS ONE | 2014-01-08
Evaluates drones as surveillance tools for detecting suspected poaching activity and improving protection of African rhinoceros populations.
Birds, Nests, Colonial Wildlife, Bioacoustics, and Disturbance
68. Drone Use for Raptor Conservation and Monitoring Applications: Review and Best Practices
| Convention on Migratory Species | UNEP/CMS Raptors MOU | 2026-08-26
Provides current best-practice recommendations for using multirotor drones to monitor raptors while minimizing disturbance and standardizing operations across countries.
69. In Situ Aerial Bioacoustic Monitoring from Extremely Noisy Drone Recordings
| Lin Wang, Michael Clayton, and Axel G. Rossberg | Methods in Ecology and Evolution | 2026-05-19
Uses deep-learning noise reduction to recover bird vocalizations from drone recordings made under realistic field conditions.
70. Behavioural Responses of Neotropical Raptors to Drone Approaches to Nests
| Various authors | Scientific Reports | 2026
Analyzes hundreds of flights near raptor nests across Central and South America and identifies flight distance, duration, breeding stage, and species traits associated with disturbance.
71. From Pictures to Numbers: Multi-Species Seabird Surveys Using Drone Imagery and Neural Networks
| Various authors | Ecological Informatics | 2026
Uses deep learning to identify and count thousands of seabirds photographed across more than 160 colonies along the Norwegian coast.
72. First Full Census in 45 Years of a Large Colony of Breeding Penguins at False Round Point
| Various authors | Polar Biology | 2025
Uses drone photogrammetry to conduct a comprehensive census of a remote Antarctic penguin colony that had been difficult to survey completely for decades.
73. Bass Rock Colony Counts
| Scottish Seabird Centre | Scottish Seabird Centre | 2025
Drone imagery enabled nearly complete coverage of the famous Bass Rock northern gannet colony and improved assessment of population change following avian influenza.
74. Best Practice Guidance for Recreational and Professional Drones Near Colonial Breeding Birds
| Various authors | Peer-Reviewed Ornithological Research | 2025
Analyzes nearly 1,500 drone flights around colonial nesting birds and develops species-specific recommendations based on flight-initiation distances.
75. Inconsistent Scientific Methods Hamper the Management of Drone Use Near Birds
| Various authors | Journal of Wildlife Management | 2025
Reviews studies covering hundreds of bird species and argues that standardized measures of drone disturbance are needed before managers can establish reliable buffer distances.
76. Advancing Animal Behaviour Research Using Drone Technology
| Various authors | Animal Behaviour | 2025
Reviews how overhead imagery can reveal group organization, movement, interaction, and behavior while emphasizing legal, ethical, and disturbance considerations.
77. Impact of Drone Disturbances on Wildlife: A Review
| Various authors | Drones | 2025
Synthesizes evidence on visual and acoustic disturbance across terrestrial, aerial, and aquatic wildlife and proposes flight practices intended to minimize stress.
78. Using a Drone to Monitor Arboreal Nests of Birds of Prey
| Grzegorz Zawadzki and Dorota Zawadzka | Scandinavian Journal of Forest Research | 2024-10-04
Evaluates drones as safer alternatives to climbing trees when conservationists need breeding data from difficult-to-reach raptor nests.
79. Conservation Letter: The Use of Drones in Raptor Research
| David M. Bird et al. | Journal of Raptor Research | 2024
Reviews benefits and risks of drones for monitoring raptor nests and proposes practical precautions for reducing disturbance, nest abandonment risk, and collisions.
80. Drone Audition for Bioacoustic Monitoring
| Lin Wang et al. | Methods in Ecology and Evolution | 2023-10-25
Develops hardware and signal-processing methods that suppress propeller noise sufficiently for a hovering drone to identify bird calls during aerial biodiversity surveys.
81. A Meta-Analysis of Disturbance Caused by Drones on Nesting Birds
| A. Cantu de Leija et al. | Journal of Field Ornithology | 2023
Synthesizes studies of drone disturbance and finds that flight altitude and nesting behavior strongly influence how birds respond to UAV surveys.
82. Using Drone Imagery to Obtain Population Data of Colony-Nesting Seabirds for Canada's Key Biodiversity Areas Program
| Various authors | Avian Conservation Research | 2023
Explores drone orthomosaics as a way of producing standardized population estimates for seabird colonies important to Canada's Key Biodiversity Areas network.
83. A Colonial-Nesting Seabird Shows No Heart-Rate Response to Drone-Based Population Surveys
| Various authors | Scientific Reports | 2022-11-05
Physiological monitoring of common eider ducks found no detectable heart-rate response during standardized drone surveys flown over their nesting colony.
84. Monitoring Colonies of Large Gulls Using UAVs: From Individuals to Breeding Pairs
| Alejandro Corregidor-Castro et al. | Micromachines | 2022-10-28
Finds that drones can efficiently census very large gull colonies and may produce more complete estimates than traditional observers working from the ground.
85. Using Drones and Citizen Science Counts to Track Colonial Waterbird Breeding on the Chobe River, Botswana
| Various authors | Global Ecology and Conservation | 2022-10
Combines aerial colony surveys with citizen-science observations to evaluate waterbird reproduction as an indicator of freshwater ecosystem health.
86. Rapid Assessment of Productivity of Purple Herons by Drone-Conducted Monitoring
| Roberto G. Valle and Francesco Scarton | Ardeola | 2022-07
Drone monitoring accurately measured nesting productivity in wetland colonies while producing little visible disturbance to adult Purple Herons or their young.
87. Keeping Wildlife Safe from Drones
| U.S. Fish and Wildlife Service | U.S. Fish and Wildlife Service | 2022
Explains U.S. wildlife-protection concerns surrounding recreational and research drones, with particular emphasis on disturbance of eagles and animals using national wildlife refuges.
88. Drones and Deep Learning Produce Accurate and Efficient Monitoring of Large-Scale Seabird Colonies
| Various authors | Ornithological Applications | 2021-05-22
Combines drone imagery and convolutional neural networks to count black-browed albatrosses and southern rockhopper penguins in large remote colonies.
89. Using Drones to Reduce Human Disturbance While Monitoring Breeding Status of an Endangered Raptor
| Various authors | Remote Sensing in Ecology and Conservation | 2021
Uses drones to inspect Chaco Eagle nests and breeding status while avoiding the tree climbing and repeated close approaches required by conventional nest monitoring.
90. Integrating Drone-Borne Thermal Imaging with Artificial Intelligence to Locate Bird Nests on Agricultural Land
| Various authors | Scientific Reports | 2020
Combines thermal cameras and machine learning to automatically locate ground-nesting birds, potentially allowing farmers to protect nests during agricultural operations.
91. Real-Time Thermal Imagery from an Unmanned Aerial Vehicle Can Locate Ground Nests of a Grassland Songbird at Rates Similar to Traditional Methods
| Various authors | Biological Conservation | 2019-05
Compares thermal drone nest searches with conventional field searching and finds drones can locate hidden grassland nests while reducing human disturbance.
92. All Atwitter About Drones
| Amy Johnson | Smithsonian's National Zoo and Conservation Biology Institute | 2018-07-20
Describes experiments using thermal cameras to locate nests of declining grassland birds before mowing or other agricultural activities destroy them.
93. Drone Monitoring of Breeding Waterbird Populations: The Case of the Glossy Ibis
| Various authors | Drones | 2018
Develops repeatable drone-based methods for counting glossy ibis nests and explores automated classification for long-term bird population monitoring.
94. Seabird Species Vary in Behavioural Response to Drone Census
| Émile Brisson-Curadeau et al. | Scientific Reports | 2017-12-20
Shows that drone reactions differ among Arctic seabirds and emphasizes species-specific flight protocols when using UAVs for population counts.
95. Unmanned Aircraft Systems as a New Source of Disturbance for Wildlife: A Systematic Review
| Margarita Mulero-Pázmány et al. | PLOS ONE | 2017
Reviews wildlife responses to drone size, engine type, flight path, life-history stage, and animal aggregation and proposes safeguards for conservation operations.
96. Precision Wildlife Monitoring Using Unmanned Aerial Vehicles
| Jarrod C. Hodgson et al. | Scientific Reports | 2016-03-17
Demonstrates that drone-derived counts of nesting birds can be much more precise than conventional ground counts, helping improve long-term population monitoring.
97. Approaching Birds with Drones: First Experiments and Ethical Guidelines
| David Grémillet et al. | Biology Letters | 2015
Tests hundreds of drone approaches to ducks, flamingos, and shorebirds and develops early recommendations for reducing disturbance during aerial research.
Marine Mammals, Sharks, Reptiles, Penguins, and Freshwater Wildlife
98. Navigating the Skies and Seas: A Drone Pilot's Perspective on Sperm Whales
| NOAA Fisheries | NOAA | 2026-08-24
Describes drone photogrammetry used to document the size and body condition of endangered sperm whales as part of long-term Gulf ecosystem restoration research.
99. Drone-Based Surveillance Methods for Non-Lethal Shark Mitigation in Nearshore Environments
| Kim I. Monteforte, Paul A. Butcher, and Brendan P. Kelaher | Drones | 2026-07-22
Reviews the growing use of drones as non-lethal tools for locating sharks near beaches and discusses detection accuracy, species identification, and operational limitations.
100. Dual Colour and Thermal Drone Surveys Improve Detection of Marine Debris Entanglements in Fur Seals
| Adam Yaney-Keller et al. | Marine Pollution Bulletin | 2026-06
Finds that combining visible and thermal drone imagery can reveal fishing line, debris, wounds, and heat anomalies associated with entangled Australian fur seals.
101. A New Way to “Sea” Otters: Drone Monitoring of Washington's Sea Otters
| Seattle Aquarium | Seattle Aquarium | 2026-05-29
Describes a new drone program intended to improve monitoring of Washington sea otter numbers, distribution, foraging behavior, and habitat use.
102. A Comparison of Uncrewed Aerial Vehicle and On-Ground Surveys of Penguin Populations on the Antarctic Peninsula
| Mairi Hilton et al. | Polar Biology | 2026-04-22
Compares drone-derived penguin population counts with traditional ground surveys at multiple Antarctic Peninsula colonies to evaluate compatibility with long-term monitoring datasets.
103. Spatial Resolution Impact Assessment for Long-Term Population Monitoring of Adélie Penguin Guano
| Jeong-Hoon Kim and Hyun-Cheol Kim | New Zealand Journal of Geology and Geophysics | 2026-02-08
Uses drone imagery as a high-resolution reference for determining how satellite resolution affects detection of penguin guano and resulting estimates of breeding abundance.
104. Drone Monitoring of Endangered Scalloped Hammerhead Shark Movements and Habitat Use on a Dynamic Urbanised Coastline in Australia
| Maddison Cross et al. | Research Square | 2026-02
Uses aerial surveys to investigate movements and habitat use of endangered scalloped hammerhead sharks along a heavily developed coastline.
105. Drone Monitoring Helps Dolphins
| Flinders University | Flinders University | 2026-01-07
Reports research using tens of thousands of thermal drone images to investigate whether dolphin surface temperature and respiration can be monitored non-invasively.
106. Drone Multispectral Imaging Reveals Seasonal Microphytobenthos Drivers at Shorebird Foraging Sites
| Various authors | Remote Sensing Applications: Society and Environment | 2026-01
Maps hundreds of hectares of intertidal biofilm habitat to identify seasonal patterns affecting food availability for migratory shorebirds.
107. Quantifying Southern Sea Otter Reactions to a Quadcopter Drone in Central California
| Young et al. | Marine Mammal Science | 2026
Measures behavioral responses of southern sea otters to drones at different altitudes, providing evidence for designing lower-disturbance monitoring protocols.
108. Drone-Based Assessment of Sea Turtle Habitat Utilization in the Diani-Chale National Marine Reserve, Kenya
| Various authors | Oceans | 2026
Uses aerial surveys and geospatial analysis to identify sea turtle habitat-use patterns that can guide no-take zones and marine protected-area management.
109. Automated Whale Shark Recognition and Tracking Using Drones and Deep Learning
| Various authors | Peer-Reviewed Marine Research | 2026
Combines aerial drone surveys with neural networks to automatically identify and track vulnerable whale sharks while reducing reliance on invasive or labor-intensive monitoring.
110. Insights into Site Fidelity of a Low-Density Dugong Population Using Small-Drone Imagery and Photo-Identification
| Various authors | Frontiers in Marine Science | 2026
Uses repeated drone imagery and scars or tail markings to identify individual dugongs in the Red Sea and document repeated use of relatively small home areas.
111. Rockhopper Penguin Census in 2026
| South Atlantic Environmental Research Institute | SAERI | 2026
Describes a large Falkland Islands census combining drone surveys and artificial intelligence to improve estimates of declining Southern Rockhopper penguin populations.
112. MAPPPD: Mapping Application for Penguin Populations and Projected Dynamics
| Oceanites | Oceanites | 2026
Oceanites integrates drone imagery, satellite observations, field surveys, and citizen science into an open Antarctic penguin database used for conservation and treaty decision-making.
113. Estimating Abundance of Aggregated Populations with Drones: Giant South American River Turtles
| Ismael V. Brack et al. | Journal of Applied Ecology | 2025-06-17
Develops methods for correcting detection errors when drones are used to estimate enormous aggregations of nesting river turtles.
114. Cook Inlet Beluga UAS Photogrammetry and Photo-Identification Survey
| NOAA Fisheries | NOAA Fisheries | 2025-06-04
Describes drone photogrammetry and photo-identification surveys designed to estimate calf production, body length, and abundance of endangered Cook Inlet belugas.
115. Drone-Based Detection and Classification of Greater Caribbean Manatees in the Panama Canal Basin
| Various authors | Drones | 2025-03-21
Applies deep-learning algorithms to drone imagery to identify individual manatees, groups, and mother-calf pairs in a complex aquatic environment.
116. Automated Extraction of Right Whale Morphometric Data from Drone Aerial Photographs
| Chhandak Bagchi et al. | Remote Sensing in Ecology and Conservation | 2025-03-10
Develops machine-learning tools to automatically measure southern right whales in thousands of drone photographs for population-health monitoring.
117. Drone-Based Photogrammetry Provides Estimates of the Energetic Cost of Migration for Humpback Whales
| Bernier-Graveline et al. | Marine Mammal Science | 2025
Estimates changes in humpback whale body condition during migrations between Antarctic feeding grounds and tropical breeding areas.
118. Estimating Total Body Lipid Store of Free-Ranging Whales In Vivo Using Drone Photogrammetry and Biologging Tags
| Alec Burslem et al. | Ecology and Evolution | 2025
Combines drone-based measurements with biologging data to estimate energy reserves in free-ranging sperm whales without capturing the animals.
119. Drones Used to Monitor Seals Without Disturbance
| University of Oxford | University of Oxford | 2024-11-15
Describes drone photogrammetry methods capable of reconstructing three-dimensional seal body size without approaching, capturing, sedating, or physically measuring animals.
120. Drone-Based Photogrammetry Reveals Differences in Humpback Whale Body Condition and Mass across North Atlantic Foraging Grounds
| Chelsi Napoli et al. | Frontiers in Marine Science | 2024-06-26
Uses aerial measurements to compare humpback whale body size and condition among feeding areas, providing a non-invasive indicator of ecosystem and population health.
121. An Assessment of Survey Techniques Using Unmanned Aerial Vehicles to Monitor Nile Crocodiles
| Various authors | Drone Systems and Applications | 2024-06-05
Compares drone photographs, photomosaics, and video for counting and measuring Nile crocodiles along reservoir shoreline habitat.
122. Automated Body Length and Body Condition Measurements of Whales from Drone Videos for Rapid Assessment of Population Health
| Kevin Charles Bierlich et al. | Marine Mammal Science | 2024-05-10
Uses artificial intelligence to automate measurements from whale drone video, greatly reducing processing time for monitoring body condition and population health.
123. Q&A: New Drone-Based Method Helps Monitor Walrus Health
| U.S. Geological Survey | USGS | 2024
Explains how high-altitude drone imagery can measure female walruses and calves at coastal haulouts, creating new indicators of Arctic population health.
124. Successful Citizen Science Tools to Monitor Animal Populations Require Innovation and Communication: SealSpotter as a Case Study
| Various authors | Frontiers in Conservation Science | 2024
Combines drone surveys with citizen scientists who counted hundreds of thousands of seals, demonstrating a scalable approach to processing conservation imagery.
125. Drones in Fish Fauna Assessment of Rivers
| Katarzyna Suska | Ecohydrology & Hydrobiology | 2023
Uses UAV imagery to map river habitat characteristics important for fish communities and to support habitat modeling at different water levels.
126. Warm Beach, Warmer Turtles: Using Drone-Mounted Thermal Infrared Sensors to Monitor Sea Turtle Nesting Activity
| Bárbara Sellés-Ríos et al. | Frontiers in Conservation Science | 2022-07-28
Tests thermal drones at night on Costa Rican nesting beaches and shows they can locate turtles, tracks, and nests that normally require labor-intensive patrols.
127. Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia
| Various authors | Drones | 2022
Analyzes thousands of drone patrol flights and identifies location, season, time of day, and marine-life presence as factors influencing shark detection.
128. Monitoring Abundance of Aggregated Animals: Florida Manatees Using an Unmanned Aerial System
| Holly H. Edwards et al. | Scientific Reports | 2021-06-21
Uses repeated drone surveys and statistical models to estimate manatee abundance while explicitly accounting for animals missed during individual surveys.
129. Finally Within Reach: A Drone Census of an Important, but Practically Inaccessible, Antarctic Fur Seal Colony
| Douglas J. Krause and Jefferson T. Hinke | Aquatic Mammals | 2021
Demonstrates how drones can obtain population counts from an Antarctic fur seal colony that is extremely difficult to survey reliably from the ground.
130. Drones for Turtles
| Various authors | Sea Turtle Research and Conservation | 2021
Describes drone applications in sea turtle research including nighttime anti-poaching surveillance on important loggerhead nesting beaches in Cape Verde.
131. Demonstrating a Better Way to Count: Utilizing Drones for Manatee Synoptic Surveys
| B. J. Scharf and J. S. Strickland | University of Florida IFAS Extension | 2020-04-11
Demonstrates a lower-cost drone approach to collecting high-resolution manatee population data in coastal areas that conventional aircraft surveys may undersample.
132. Reliability of Marine Faunal Detections in Drone-Based Monitoring
| Andrew P. Colefax et al. | Ocean & Coastal Management | 2019
Evaluates observer error when detecting sharks and other marine animals from drone footage and shows that detection reliability varies among animal types.
133. Measuring Behavioral Responses of Sea Turtles, Saltwater Crocodiles, and Crested Terns to Drone Disturbance to Define Ethical Operating Thresholds
| Elizabeth Bevan et al. | PLOS ONE | 2018-03-21
Tests wildlife reactions at different drone altitudes and provides empirical guidance for choosing operating heights that minimize disturbance.
134. Use of an Unmanned Aerial Vehicle to Survey Nile Crocodile Populations
| Various authors | Biological Conservation | 2018
Tests drones as lower-cost alternatives to conventional aerial surveys for counting Nile crocodiles in South African protected areas.
135. Looking Without Landing—Using Remote Piloted Aircraft to Monitor Fur Seal Populations Without Disturbance
| Various authors | Frontiers in Marine Science | 2018
Shows that carefully operated drones can count fur seal pups at remote colonies with little observable disturbance and may detect more animals than ground observers.
136. Automated Detection and Enumeration of Marine Wildlife Using Unmanned Aircraft Systems and Thermal Imagery
| Various authors | Scientific Reports | 2017
Tests thermal and visible imagery for automated aerial detection and counting of seals, demonstrating the potential to reduce manual processing of large wildlife surveys.
137. Possibility of Applying Unmanned Aerial Vehicle and Mapping Software for the Monitoring of Waterbirds and Their Habitats
| Various authors | Journal of Ecology and Environment | 2017
Tests drones for simultaneously mapping waterbirds and wetland habitat in South Korea's internationally important Upo Wetland.
138. A Low-Cost Drone-Based Application for Identifying and Mapping Coastal Fish Nursery Grounds
| Various authors | Estuarine, Coastal and Shelf Science | 2016
Demonstrates inexpensive drone mapping of shallow coastal nursery habitat used by juvenile fishes, helping identify areas of high conservation importance.
Forest Conservation, Rare Plants, Restoration, and Habitat Monitoring
139. Designing a Drone-Based System for Optimized Seed Ball Deployment in Reforestation Applications
| Abhay Rajan et al. | European Journal of Forest Engineering | 2026-06-11
Designs a GPS-assisted drone capable of releasing seed balls in controlled locations as a tool for aerial reforestation.
140. Quantifying Carbon Stock and Tree Community Composition in Tropical Forests Through Combining Satellite and UAV Analyses
| Ryota Aoyagi et al. | Scientific Reports | 2026
Uses drone observations as high-resolution reference data to improve satellite estimates of tropical forest carbon and tree-community composition in Malaysia and Indonesia.
141. Classification of Tree Species and Standing Dead Trees in Boreal Forests Using UAV-Based RGB, Multispectral, and LiDAR Point Clouds
| Various authors | Remote Sensing in Ecology and Conservation | 2026
Combines multiple drone sensors to identify living tree species and standing dead trees, both important indicators of habitat quality and forest biodiversity.
142. Comprehensive Uncrewed Aerial System Data for Amazon Rainforest at Tiputini Biodiversity Station, Ecuador
| Various authors | Scientific Data | 2026
Releases high-resolution multispectral and LiDAR drone data across hundreds of hectares of exceptionally biodiverse Amazon forest for research on canopy structure, biomass, and biodiversity.
143. Assessing Drone-Based Direct Seeding with Bare and Encapsulated Seeds for Enriching Degraded Tropical Forest Fragments
| Various authors | Ecological Engineering | 2026
Tests tens of thousands of native-tree seeds deployed by drone in degraded Atlantic Forest fragments and compares seedling establishment and costs for bare versus encapsulated seeds.
144. AI-Driven Multispectral Drone Monitoring for Afforestation in Arid Environments
| Various authors | Results in Engineering | 2026
Applies drone multispectral imagery and artificial intelligence to classify tens of thousands of planting pits and identify where seedlings survived or replanting is required.
145. Comparison of Drone and Ground Surveys for the Detection of a Rare Plant in a Fragile Ecosystem
| Hernández Martínez de la Riva et al. | Ecological Solutions and Evidence | 2025-12-22
Directly compares drone and conventional field searches for detecting rare plants while considering the risk of damaging fragile habitat during ground surveys.
146. Advances in the Automated Identification of Individual Tree Species: A Systematic Review of Drone- and AI-Based Methods in Forest Environments
| Various authors | Technologies | 2025-05-06
Reviews artificial intelligence, RGB, multispectral, hyperspectral, and LiDAR approaches for identifying individual trees from drone imagery.
147. Effective Integration of Drone Technology for Mapping and Managing Palm Species in the Peruvian Amazon
| Various authors | Nature Communications | 2025
Demonstrates how conservationists and local stakeholders can use drone mapping to locate economically and ecologically important Amazonian palms over large landscapes.
148. Estimating Seasonal Fractional Green and Dead Vegetation Cover in Rehabilitated Ecosystems Using Drone Remote Sensing
| Various authors | Ecological Informatics | 2025
Uses inexpensive visible-light drone imagery to distinguish green and dead vegetation as indicators of ecological recovery at rehabilitated sites.
149. Towards Consistently Measuring and Monitoring Habitat Condition with Airborne Laser Scanning and Unmanned Aerial Vehicles
| Various authors | Ecological Indicators | 2024-12
Examines how standardized LiDAR and drone metrics could support repeatable indicators of habitat condition for conservation reporting.
150. The Use of Drones for Cost-Effective Surveys in Natura 2000 Protected Areas: A Case Study on Monitoring Plant Diversity in Sicily
| Gianmarco Tavilla et al. | Land | 2024-06-06
Uses drones to survey inaccessible Mediterranean cliffs and rediscovered a rare plant that had not been confirmed at the study site for more than a century.
151. The Conservation Impact of Botanical Drones: Documenting and Collecting Rare Plants from Vertical Cliffs and Other Hard-to-Reach Areas
| Various authors | Ecological Solutions and Evidence | 2024-03-28
Demonstrates drones designed to locate, map, photograph, and even assist collection of highly endangered plants growing on inaccessible cliffs in Hawaiʻi, Madeira, and Palau.
152. Coupling UAV and Satellite Data for Tree Species Identification to Map the Distribution of Caspian Poplar
| Various authors | Landscape Ecology | 2024-02-14
Uses drone observations to train broader satellite mapping of an endemic tree, illustrating how fine-scale UAV surveys can support endangered-plant conservation at landscape scales.
153. Systematic Review and Best Practices for Drone Remote Sensing of Invasive Plants
| Singh et al. | Methods in Ecology and Evolution | 2024
Synthesizes drone-based invasive-plant studies and provides recommendations for flight design, imagery, classification, reporting, and scalable conservation monitoring.
154. Towards Operational UAV-Based Forest Health Monitoring: Species Identification and Crown Condition Assessment by Means of Deep Learning
| Various authors | Computers and Electronics in Agriculture | 2024
Uses repeated multispectral drone surveys and neural networks to classify major tree species and evaluate crown condition across forest-monitoring plots.
155. How Have RPAS Helped Monitor Forests and What Can We Apply in Forest Restoration Monitoring?
| Various authors | Restoration Ecology | 2024
Systematically reviews drone sensors and indicators used in forests and evaluates which techniques can be transferred to large-scale restoration monitoring.
156. UAV-Assisted Seeding and Monitoring of Reforestation Sites: A Review
| Various authors | Australian Forestry | 2024
Reviews drone-assisted seed deployment, post-planting monitoring, artificial intelligence, and practical challenges associated with large-scale reforestation.
157. Distinguishing Forest Types in Restored Tropical Landscapes with UAV-Borne LIDAR
| Various authors | Remote Sensing of Environment | 2023
Demonstrates that drone LiDAR can distinguish conservation-oriented forests from production forests, providing a way to assess the ecological outcomes of landscape restoration.
158. UAV-Lidar Reveals That Canopy Structure Mediates the Influence of Edge Effects on Forest Diversity, Function and Microclimate
| Various authors | Journal of Ecology | 2023
Shows how forest fragmentation alters canopy structure, microclimate, biomass, and taxonomic and functional diversity in New Caledonia.
159. Forest Restoration Is More Than Firing Seeds from a Drone
| Jorge Castro | Restoration Ecology | 2022-05-18
Cautions that aerial seed dispersal alone cannot ensure forest restoration because germination, herbivory, drought, competition, and seedling survival determine long-term success.
160. Existing and Emerging Uses of Drones in Restoration Ecology
| Robinson et al. | Methods in Ecology and Evolution | 2022
Reviews drone applications throughout restoration projects, including planning, habitat mapping, seeding, wildfire management, plant-health assessment, and long-term monitoring.
161. Monitoring Restored Tropical Forest Diversity and Structure through UAV-Borne Hyperspectral and LiDAR Fusion
| D. R. A. Almeida et al. | Remote Sensing of Environment | 2021
Combines hyperspectral and LiDAR measurements from drones to evaluate tree diversity, biomass, and structural development in Brazilian Atlantic Forest restoration plots.
162. From Drones to Phenotype: Using UAV-LiDAR to Detect Species and Provenance Variation in Tree Productivity and Structure
| Various authors | Remote Sensing | 2020
Uses drone LiDAR to reveal structural and genetic differences among tree species and provenances that may influence ecological function and climate adaptation.
163. Greenness Indices from Low-Cost UAV Imagery as Tools for Monitoring Post-Fire Forest Recovery
| Various authors | Drones | 2019
Demonstrates that inexpensive drone imagery can measure vegetation recovery following fire, providing conservation managers with repeatable indicators of forest regeneration.
164. Methodological Ambiguity and Inconsistency Constrain Unmanned Aerial Vehicles as a Silver Bullet for Monitoring Ecological Restoration
| Various authors | Remote Sensing | 2019
Warns that inconsistent drone platforms, sensors, analytical workflows, and reporting methods can prevent comparison among restoration projects and calls for stronger standards.
165. Seeing the Forest from Drones: Testing the Potential of Lightweight Drones as a Tool for Long-Term Forest Monitoring
| Various authors | Biological Conservation | 2016-06
Maps canopy structure across a subtropical forest and demonstrates relationships between drone-derived canopy characteristics and forest biodiversity.
166. Using Lightweight Unmanned Aerial Vehicles to Monitor Tropical Forest Recovery
| Various authors | Biological Conservation | 2015-06
Shows that low-cost UAV photogrammetry can quantify forest structure, above-ground biomass, and habitat characteristics associated with wildlife during tropical forest restoration.
Wetlands, Rivers, Peatlands, Grasslands, and Dunes
167. Accuracy of UAV-Based Natura 2000 Habitat Mapping: Seasonal and Spectral Drivers, with a PlanetScope Benchmark
| Various authors | Basic and Applied Ecology | 2026-05
Compares drone and satellite classification of European protected habitats and finds that season and sensor type strongly influence habitat-mapping accuracy.
168. Biodiversity Monitoring for Habitat Restoration
| University of Edinburgh | University of Edinburgh | 2026-04-08
Combines drone LiDAR and multispectral imagery with environmental DNA to track biodiversity changes at peatland restoration and woodland-creation projects.
169. Peatland ACTION Partnership Monitoring Strategy
| NatureScot | NatureScot | 2026
Describes operational use of drone imagery for estimating bare peat, Sphagnum cover, terrain, and water-flow pathways before and after peatland restoration.
170. Cost-Effective Drone Monitoring and Evaluating Toolkits for Stream Habitat Health: Development and Application
| Wei Wang, Boyuan Lu, and Chin H. Wu | Environmental Monitoring and Assessment | 2025-12-05
Develops practical drone-based tools for evaluating stream morphology and habitat condition at the spatial resolution needed for restoration and conservation decisions.
171. Conservation and Ecological Screening of Small Water Bodies in Temperate Riverine Wetlands Using UAV Photogrammetry
| Various authors | Nature Conservation | 2025
Tests whether drone-derived aquatic vegetation characteristics can indicate ecological and conservation condition in small floodplain water bodies.
172. Towards Standardised Large-Scale Monitoring of Peatland Habitats through Fine-Scale Drone-Derived Vegetation Mapping
| Various authors | Ecological Indicators | 2024-09
Develops a standardized drone mapping approach for classifying vegetation, habitat condition, and ecological status across entire peatland landscapes.
173. Using UAV Approach in Monitoring of Macrophytes and Their Habitats Within Small Water Bodies of Pristine Riparian Wetlands
| Maja Novković et al. | Biologia Serbica | 2024
Compares drone mapping with traditional fieldwork for monitoring aquatic plants and habitat condition in Danube floodplain wetlands.
174. Use of UAV Monitoring to Identify Factors Limiting the Sustainability of Stream Restoration Projects
| Jakub Langhammer, Theodora Lendzioch, and Jakub Šolc | Hydrology | 2023-02-10
Uses long-term drone imagery to measure channel dynamics, connectivity, vegetation development, and other factors determining whether stream restoration remains successful.
175. Integrating Low-Altitude Drone-Based Imagery and OBIA for Mapping and Managing Semi-Natural Grassland Habitats
| Various authors | Journal of Environmental Management | 2022-11-01
Produces centimeter-scale maps capable of distinguishing several grassland classes, woody vegetation, erosion, and a habitat type of special conservation concern.
176. Unmanned Aircraft System Structure-From-Motion for Monitoring Changed Flow Paths and Wetness in Minerotrophic Peatland Restoration
| Various authors | Remote Sensing | 2022
Uses drone-derived terrain models to measure how peatland restoration changes drainage routes, wetness, and hydrological connectivity.
177. A Nested Drone-Satellite Approach to Monitoring the Ecological Conditions of Wetlands
| Various authors | ISPRS Journal of Photogrammetry and Remote Sensing | 2021-04
Combines fine-scale drone maps with Sentinel-2 satellite imagery to extend detailed vegetation-community monitoring across larger wetland landscapes.
178. A Novel UAV-Based Approach for Biomass Prediction and Grassland Structure Assessment in Coastal Meadows
| Various authors | Ecological Indicators | 2021-03
Combines drone imagery and structural data to map biomass and vegetation complexity in conservation-important coastal meadow habitats.
179. Saving Species, Time and Money: Application of Unmanned Aerial Vehicles for Monitoring of an Endangered Alpine River Specialist in a Small Nature Reserve
| Various authors | Biological Conservation | 2019-05
Uses repeated drone mapping to measure erosion, stream-channel movement, vegetation, and habitat loss threatening one of Germany's last populations of an endangered alpine river plant.
180. Unmanned Aerial Vehicle Methods Makes Species Composition Monitoring Easier in Grasslands
| Various authors | Ecological Indicators | 2018-12
Tests drone-based monitoring of species composition along grazing gradients in alpine meadows and compares results with conventional vegetation surveys.
Coastal Habitats, Coral Reefs, Seagrass, Blue Carbon, Kelp, and Pollution
181. Evaluating UAV-Based Monitoring of Seagrass Meadows: Insights into Spatial Configuration and Temporal Change
| Various authors | Estuarine, Coastal and Shelf Science | 2026-06-06
Repeated monthly drone surveys reveal seasonal changes in seagrass extent, fragmentation, and meadow configuration that conventional surveys may miss.
182. Assessing Seagrass Ecological Health in Zanzibar Using an Integrated Index of Drone and In Situ Indicators
| Idrissa Y. Hamad, Mohammed Sheikh, and Peter A. U. Staehr | Marine Pollution Bulletin | 2026-05
Combines drone imagery with field indicators to evaluate seagrass condition and detect pressures from nutrients, seaweed farming, urchins, and coastal development.
183. Drone Imaging Can Accurately Assess Coral Cover, Bleaching, and Growth Form for Shallow Coral Reefs
| Lucian Himes and Theresa Rueger | Coral Reefs | 2026-04-09
Shows that inexpensive drone imagery can quantify coral cover, bleaching, and reef growth forms, potentially expanding monitoring in under-resourced coral regions.
184. Mapping and Monitoring Heterogeneous Plant Communities in Restored and Established Salt Marshes Using UAVs and Machine Learning
| Various authors | Remote Sensing | 2026-03-11
Classifies multiple salt-marsh plant communities with high accuracy, providing a repeatable method for evaluating restoration outcomes and biodiversity.
185. Enhanced Local Erosion in Newly Established Scirpus mariqueter Salt Marshes: Evidence from UAV Photogrammetry
| Tianyou Li et al. | Anthropocene Coasts | 2026-02-03
Repeated drone surveys reveal how newly colonizing salt-marsh vegetation alters local sediment deposition and erosion patterns.
186. Unmanned Aerial Vehicles for Assessing Biomass and Carbon Stocks in Mangrove Forests: A Systematic Review
| Various authors | Sustainable Futures | 2025-12
Reviews drone-based approaches for measuring mangrove biomass and carbon stocks using RGB, multispectral, and LiDAR sensors.
187. Tracking the Spatial and Temporal Evolution of Salt Marsh Vegetation Based on UAV Sampling and Seasonal Phenology from Landsat Data
| Various authors | Journal of Environmental Management | 2025-08
Uses drone reference data, satellite observations, and machine learning to reconstruct decades of salt-marsh vegetation change and invasive Spartina expansion.
188. Mapping and Estimating Blue Carbon in Mangrove Forests Using Drone and Field-Based Tree Height Data
| Various authors | Forests | 2025
Demonstrates a relatively inexpensive consumer-drone method for estimating mangrove biomass and blue-carbon stocks for conservation and climate-management programs.
189. Regional Mangrove Vegetation Carbon Stocks Predicted Integrating UAV-LiDAR and Satellite Data
| Various authors | Journal of Environmental Management | 2024-09
Uses drone LiDAR to calibrate satellite models of mangrove carbon, allowing detailed local measurements to support conservation assessments over much larger areas.
190. Mapping Fine-Scale Seagrass Disturbance Using Bi-Temporal UAV-Acquired Images and Multivariate Alteration Detection
| Jamie Simpson et al. | Scientific Reports | 2024-08-17
Compares drone imagery from different dates to identify small-scale seagrass loss and disturbance that can be difficult to detect with conventional satellite monitoring.
191. Enhancing Salt Marshes Monitoring: Estimating Biomass with Drone-Derived Habitat-Specific Models
| Various authors | Remote Sensing Applications: Society and Environment | 2024-08
Combines multispectral and LiDAR drone observations to estimate salt-marsh biomass, an important indicator of habitat condition and carbon storage.
192. Mangrove Biodiversity Assessment Using UAV Lidar and Hyperspectral Data in China's Pinglu Canal Estuary
| Various authors | Remote Sensing | 2023-05-18
Combines structural LiDAR measurements with hyperspectral imagery to map mangrove species and quantify forest biodiversity.
193. Using Unoccupied Aerial Vehicles to Map and Monitor Changes in Emergent Kelp Canopy After an Ecological Regime Shift
| Vienna R. Saccomanno et al. | Science for Conservation | 2022
Large-scale California drone surveys map remaining and recovering kelp canopy after major ecosystem decline, providing fine-resolution information for restoration planning and adaptive conservation management.
