Remote Sensing in Ecology and Conservation

(The TQCC of Remote Sensing in Ecology and Conservation is 8. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)
Using very‐high‐resolution satellite imagery and deep learning to detect and count African elephants in heterogeneous landscapes66
Real‐time insect tracking and monitoring with computer vision and deep learning41
Monitoring spring phenology of individual tree crowns using drone‐acquired NDVI data37
Machine learning to detect marine animals in UAV imagery: effect of morphology, spacing, behaviour and habitat35
Extending deep learning approaches for forest disturbance segmentation on very high‐resolution satellite images34
Automated detection of Hainan gibbon calls for passive acoustic monitoring33
Ecoacoustics in the rain: understanding acoustic indices under the most common geophonic source in tropical rainforests30
Spatial resolution, spectral metrics and biomass are key aspects in estimating plant species richness from spectral diversity in species‐rich grasslands28
Quantifying large‐scale ecosystem stability with remote sensing data28
Characterizing spatial variability in coastal wetland biomass across multiple scales using UAV and satellite imagery28
Discovery of new colonies by Sentinel2 reveals good and bad news for emperor penguins27
Ecoacoustics: acoustic sensing for biodiversity monitoring at scale26
21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning25
Dual visible‐thermal camera approach facilitates drone surveys of colonial marshbirds24
Integration of close‐range underwater photogrammetry with inspection and mesh processing software: a novel approach for quantifying ecological dynamics of temperate biogenic reefs22
Regional matters: On the usefulness of regional land‐cover datasets in times of global change21
HydroMoth: Testing a prototype low‐cost acoustic recorder for aquatic environments19
Using drones to reduce human disturbance while monitoring breeding status of an endangered raptor18
Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation18
Remote sensing data fusion as a tool for biomass prediction in extensive grasslands invaded by L. polyphyllus18
Automatic flower detection and phenology monitoring using time‐lapse cameras and deep learning18
Ultra‐high‐resolution mapping of biocrusts with Unmanned Aerial Systems17
Multispecies detection and identification of African mammals in aerial imagery using convolutional neural networks17
Simultaneous monitoring of vegetation dynamics and wildlife activity with camera traps to assess habitat change16
Monitoring ash dieback (Hymenoscyphus fraxineus) in British forests using hyperspectral remote sensing16
Drone‐based thermal remote sensing provides an effective new tool for monitoring the abundance of roosting fruit bats16
Random encounter model is a reliable method for estimating population density of multiple species using camera traps16
Regional‐scale forest restoration effects on ecosystem resiliency to drought: a synthesis of vegetation and moisture trends on Google Earth Engine16
Estimating inundation of small waterbodies with sub‐pixel analysis of Landsat imagery: long‐term trends in surface water area and evaluation of common drought indices15
Mapping complex coastal wetland mosaics in Gabon for informed ecosystem management: use of object‐based classification15
Wildfire severity and vegetation recovery drive post‐fire evapotranspiration in a southwestern pine‐oak forest, Arizona, USA15
Arboreal camera trapping: a reliable tool to monitor plant‐frugivore interactions in the trees on large scales14
Spy in the sky: a method to identify pregnant small cetaceans14
Cloud‐native seascape mapping of Mozambique’s Quirimbas National Park with Sentinel‐214
Passive acoustic monitoring reveals the role of habitat affinity in sensitivity of sub‐tropical East Asian bats to fragmentation14
Classifying wetland‐related land cover types and habitats using fine‐scale lidar metrics derived from country‐wide Airborne Laser Scanning14
How can Sentinel‐2 contribute to seagrass mapping in shallow, turbid Baltic Sea waters?13
Optimizing tropical forest bird surveys using passive acoustic monitoring and high temporal resolution sampling13
Wildlife trail or systematic? Camera trap placement has little effect on estimates of mammal diversity in a tropical forest in Gabon13
Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems13
The effect of camera orientation on the detectability of wildlife: a case study from north‐western Australia13
Modelling species distribution from camera trap by‐catch using a scale‐optimized occupancy approach13
Deep learning detects invasive plant species across complex landscapes using Worldview‐2 and Planetscope satellite imagery13
SmallSats: a new technological frontier in ecology and conservation?11
Earth observation for ecosystem accounting: spatially explicit national seagrass extent and carbon stock in Kenya, Tanzania, Mozambique and Madagascar11
Do acoustically detectable species reflect overall diversity? A case study from Australia’s arid zone11
Camera trap distance sampling for terrestrial mammal population monitoring: lessons learnt from aUKcase study11
The real potential of current passive satellite data to map aboveground biomass in tropical forests11
Remotely sensed variables explain microhabitat selection and reveal buffering behaviours against warming in a climate‐sensitive bird species10
Tracking canopy gaps in mangroves remotely using deep learning10
Improved fire severity mapping in the North American boreal forest using a hybrid composite method10
Mainstreaming remotely sensed ecosystem functioning in ecological niche models10
Remote sensing of wildlife connectivity networks and priority locations for conservation in the Southern Agricultural Growth Corridor (SAGCOT) in Tanzania10
Are camera traps a reliable method for estimating activity patterns? A case study comparing technologies for estimating brown hyaena activity curves9
Seismic savanna: machine learning for classifying wildlife and behaviours using ground‐based vibration field recordings8
Underwater robots provide similar fish biodiversity assessments as divers on coral reefs8
Influence of altitude on tropical marine habitat classification using imagery from fixed‐wing, water‐landing UAVs8
Remote sensing‐supported mapping of the activity of a subterranean landscape engineer across an afro‐alpine ecosystem8
Impact of pile‐driving and offshore windfarm operational noise on fish chorusing8
Remote sensing liana infestation in an aseasonal tropical forest: addressing mismatch in spatial units of analyses8
Radar and multispectral remote sensing data accurately estimate vegetation vertical structure diversity as a fire resilience indicator8
Deep learning algorithm outperforms experienced human observer at detection of blue whale D‐calls: a double‐observer analysis8
Improving the efficiency and accuracy of evaluating aridland riparian habitat restoration using unmanned aerial vehicles8
Capturing hedgerow structure and flowering abundance with UAV remote sensing8