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Recent Advances in Forest Insect Pests and Diseases Monitoring Using UAV-Based Data: A Systematic Review

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-94-017-8663-8openalex-snapshot

Forestry applications of airborne laser scanning : concepts and case studies

inferredcites →https://doi.org/10.1007/s11192-009-0146-3openalex-snapshot

Software survey: VOSviewer, a computer program for bibliometric mapping

inferredcites →https://doi.org/10.1007/s11676-021-01420-xopenalex-snapshot

Pine wilt disease detection in high-resolution UAV images using object-oriented classification

inferredcites →https://doi.org/10.1007/s40725-019-00094-3openalex-snapshot

Structure from Motion Photogrammetry in Forestry: a Review

inferredcites →https://doi.org/10.1007/s41348-021-00502-6openalex-snapshot

Detection of mistletoe infected trees using UAV high spatial resolution images

inferredcites →https://doi.org/10.1016/j.cois.2019.07.010openalex-snapshot

Responses of forest insect pests to climate change: not so simple

inferredcites →https://doi.org/10.1016/j.eng.2020.07.001openalex-snapshot

Detection of the Pine Wilt Disease Tree Candidates for Drone Remote Sensing Using Artificial Intelligence Techniques

inferredcites →https://doi.org/10.1016/j.foreco.2013.07.043openalex-snapshot

Forecasting potential bark beetle outbreaks based on spruce forest vitality using hyperspectral remote-sensing techniques at different scales

inferredcites →https://doi.org/10.1016/j.foreco.2018.11.032openalex-snapshot

Canopy temperature from an Unmanned Aerial Vehicle as an indicator of tree stress associated with red band needle blight severity

inferredcites →https://doi.org/10.1016/j.foreco.2020.118365openalex-snapshot

Impacts and uncertainties of climate change projections on Eucalyptus plantations productivity across Brazil

inferredcites →https://doi.org/10.1016/j.foreco.2021.118986openalex-snapshot

Application of conventional UAV-based high-throughput object detection to the early diagnosis of pine wilt disease by deep learning

inferredcites →https://doi.org/10.1016/j.foreco.2021.119493openalex-snapshot

Early detection of pine wilt disease using deep learning algorithms and UAV-based multispectral imagery

inferredcites →https://doi.org/10.1016/j.isprsjprs.2009.04.002openalex-snapshot

3D segmentation of single trees exploiting full waveform LIDAR data

inferredcites →https://doi.org/10.1016/j.isprsjprs.2014.02.013openalex-snapshot

Unmanned aerial systems for photogrammetry and remote sensing: A review

inferredcites →https://doi.org/10.1016/j.isprsjprs.2014.12.026openalex-snapshot

Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery

inferredcites →https://doi.org/10.1016/j.isprsjprs.2017.06.001openalex-snapshot

A review of supervised object-based land-cover image classification

inferredcites →https://doi.org/10.1016/j.isprsjprs.2017.07.007openalex-snapshot

Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak

inferredcites →https://doi.org/10.1016/j.isprsjprs.2019.04.015openalex-snapshot

Deep learning in remote sensing applications: A meta-analysis and review

inferredcites →https://doi.org/10.1016/j.jag.2012.08.006openalex-snapshot

Predicting Thaumastocoris peregrinus damage using narrow band normalized indices and hyperspectral indices using field spectra resampled to the Hyperion sensor

inferredcites →https://doi.org/10.1016/j.jag.2017.04.004openalex-snapshot

Remote sensing of forest insect disturbances: Current state and future directions

inferredcites →https://doi.org/10.1016/j.jag.2021.102363openalex-snapshot

A machine learning algorithm to detect pine wilt disease using UAV-based hyperspectral imagery and LiDAR data at the tree level

inferredcites →https://doi.org/10.1016/j.jag.2021.102456openalex-snapshot

A review on deep learning in UAV remote sensing

inferredcites →https://doi.org/10.1016/j.joi.2017.08.007openalex-snapshot

bibliometrix : An R-tool for comprehensive science mapping analysis

inferredcites →https://doi.org/10.1016/j.rse.2018.08.024openalex-snapshot

Assessment of defoliation during the Dendrolimus tabulaeformis Tsai et Liu disaster outbreak using UAV-based hyperspectral images

inferredcites →https://doi.org/10.1016/j.rse.2021.112475openalex-snapshot

Using the 3D model RAPID to invert the shoot dieback ratio of vertically heterogeneous Yunnan pine forests to detect beetle damage

inferredcites →https://doi.org/10.1016/j.ufug.2018.01.010openalex-snapshot

Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft

inferredcites →https://doi.org/10.1016/s0924-2716(99)00040-4openalex-snapshot

Modelling and representation issues in automated feature extraction from aerial and satellite images

inferredcites →https://doi.org/10.1038/s41467-020-19924-1openalex-snapshot

Excess forest mortality is consistently linked to drought across Europe

inferredcites →https://doi.org/10.1038/s41598-021-97089-7openalex-snapshot

Geographical spatial distribution and productivity dynamic change of eucalyptus plantations in China

inferredcites →https://doi.org/10.1080/00049158.2019.1621588openalex-snapshot

Detection of necrotic foliage in a young Eucalyptus pellita plantation using unmanned aerial vehicle RGB photography – a demonstration of concept

inferredcites →https://doi.org/10.1080/01431160600746456openalex-snapshot

A survey of image classification methods and techniques for improving classification performance

inferredcites →https://doi.org/10.1080/01431160701736489openalex-snapshot

Review of methods of small‐footprint airborne laser scanning for extracting forest inventory data in boreal forests

inferredcites →https://doi.org/10.1080/01431161.2010.494184openalex-snapshot

A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing

inferredcites →https://doi.org/10.1080/01431161.2016.1252477openalex-snapshot

Forestry applications of UAVs in Europe: a review

inferredcites →https://doi.org/10.1080/01431161.2016.1275059openalex-snapshot

Unmanned aircraft in nature conservation: an example from plant invasions

inferredcites →https://doi.org/10.1080/01431161.2017.1297548openalex-snapshot

UAS, sensors, and data processing in agroforestry: a review towards practical applications

inferredcites →https://doi.org/10.1080/01431161.2020.1766145openalex-snapshot

Deep learning-based dead pine tree detection from unmanned aerial vehicle images

inferredcites →https://doi.org/10.1080/01431161.2021.1954261openalex-snapshot

Advancements in satellite image classification : methodologies, techniques, approaches and applications

inferredcites →https://doi.org/10.1080/10095020.2017.1416994openalex-snapshot

Unmanned aerial vehicles (UAV) for assessment of qualitative classification of Norway spruce in temperate forest stands

inferredcites →https://doi.org/10.1109/34.87344openalex-snapshot

Watersheds in digital spaces: an efficient algorithm based on immersion simulations

inferredcites →https://doi.org/10.1109/36.921414openalex-snapshot

A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners

inferredcites →https://doi.org/10.1109/cec48606.2020.9185630openalex-snapshot

Improving the Detection of Burnt Areas in Remote Sensing using Hyper-features Evolved by M3GP

inferredcites →https://doi.org/10.1109/jstars.2021.3102218openalex-snapshot

Multichannel Object Detection for Detecting Suspected Trees With Pine Wilt Disease Using Multispectral Drone Imagery

inferredcites →https://doi.org/10.1109/mgrs.2021.3087445openalex-snapshot

Remotely Piloted Aircraft Systems to Identify Pests and Diseases in Forest Species: The global state of the art and future challenges

inferredcites →https://doi.org/10.1111/1365-2664.12511openalex-snapshot

REVIEW: Searching for resilience: addressing the impacts of changing disturbance regimes on forest ecosystem services

inferredcites →https://doi.org/10.1111/2041-210x.12575openalex-snapshot

Tree‐centric mapping of forest carbon density from airborne laser scanning and hyperspectral data

inferredcites →https://doi.org/10.1111/2041-210x.13296openalex-snapshot

Taking a closer look at invasive alien plant research: A review of the current state, opportunities, and future directions for UAVs

inferredcites →https://doi.org/10.1126/science.1155458openalex-snapshot

Managing Forests for Climate Change Mitigation

inferredcites →https://doi.org/10.1126/science.aaz7005openalex-snapshot

Climate-driven risks to the climate mitigation potential of forests

inferredcites →https://doi.org/10.1139/cjfr-2019-0375openalex-snapshot

Remotely piloted aircraft systems and forests: a global state of the art and future challenges

inferredcites →https://doi.org/10.1139/cjfr-2020-0125openalex-snapshot

Unmanned aerial vehicles (UAV)-based canopy height modeling under leaf-on and leaf-off conditions for determining tree height and crown diameter (case study: Hyrcanian mixed forest)

inferredcites →https://doi.org/10.1139/juvs-2018-0018openalex-snapshot

Vegetation monitoring using multispectral sensors — best practices and lessons learned from high latitudes

inferredcites →https://doi.org/10.1186/s13007-020-00678-2openalex-snapshot

Extraction of tree crowns damaged by Dendrolimus tabulaeformis Tsai et Liu via spectral-spatial classification using UAV-based hyperspectral images

inferredcites →https://doi.org/10.1186/s13643-021-01626-4openalex-snapshot

The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

inferredcites →https://doi.org/10.1186/s40663-021-00328-6openalex-snapshot

Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery

inferredcites →https://doi.org/10.1186/s40663-021-00342-8openalex-snapshot

Assessing a novel modelling approach with high resolution UAV imagery for monitoring health status in priority riparian forests

inferredcites →https://doi.org/10.1371/journal.pone.0159781openalex-snapshot

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

inferredcites →https://doi.org/10.1371/journal.pone.0213027openalex-snapshot

Quantifying pine processionary moth defoliation in a pine-oak mixed forest using unmanned aerial systems and multispectral imagery

inferredcites →https://doi.org/10.14358/pers.70.3.351openalex-snapshot

Individual Tree-Crown Delineation and Treetop Detection in High-Spatial-Resolution Aerial Imagery

inferredcites →https://doi.org/10.14358/pers.77.4.363openalex-snapshot

A Genetic Programming Approach to Estimate Vegetation Cover in the Context of Soil Erosion Assessment

inferredcites →https://doi.org/10.14358/pers.78.1.75openalex-snapshot

A New Method for Segmenting Individual Trees from the Lidar Point Cloud

inferredcites →https://doi.org/10.14358/pers.81.10.787openalex-snapshot

Applying ASPRS Accuracy Standards to Surveys from Small Unmanned Aircraft Systems (UAS)

inferredcites →https://doi.org/10.14358/pers.81.4.281openalex-snapshot

Overview and Current Status of Remote Sensing Applications Based on Unmanned Aerial Vehicles (UAVs)

inferredcites →https://doi.org/10.1641/0006-3568(2001)051[0723:ccafd]2.0.co;2openalex-snapshot

Climate Change and Forest Disturbances

inferredcites →https://doi.org/10.1641/b580607openalex-snapshot

Cross-scale Drivers of Natural Disturbances Prone to Anthropogenic Amplification: The Dynamics of Bark Beetle Eruptions

inferredcites →https://doi.org/10.3390/aerospace8090256openalex-snapshot

Evaluation and Comparison of Hybrid Wing VTOL UAV with Four Different Electric Propulsion Systems

inferredcites →https://doi.org/10.3390/drones1010002openalex-snapshot

Unmanned Aerial Systems for Civil Applications: A Review

inferredcites →https://doi.org/10.3390/drones3020040openalex-snapshot

A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses

inferredcites →https://doi.org/10.3390/drones3040080openalex-snapshot

Estimating the Threshold of Detection on Tree Crown Defoliation Using Vegetation Indices from UAS Multispectral Imagery

inferredcites →https://doi.org/10.3390/drones4030046openalex-snapshot

UAS-Based Archaeological Remote Sensing: Review, Meta-Analysis and State-of-the-Art

inferredcites →https://doi.org/10.3390/drones5030077openalex-snapshot

Individual Tree Crown Delineation for the Species Classification and Assessment of Vital Status of Forest Stands from UAV Images

inferredcites →https://doi.org/10.3390/f11121258openalex-snapshot

Discriminant Analysis of the Damage Degree Caused by Pine Shoot Beetle to Yunnan Pine Using UAV-Based Hyperspectral Images

inferredcites →https://doi.org/10.3390/f12040397openalex-snapshot

Recent Advances in Unmanned Aerial Vehicles Forest Remote Sensing—A Systematic Review. Part II: Research Applications

inferredcites →https://doi.org/10.3390/f12070957openalex-snapshot

A Systematic Review of Best Practices for UAS Data Collection in Forestry-Related Applications

inferredcites →https://doi.org/10.3390/f12081134openalex-snapshot

The Role of Remote Sensing for the Assessment and Monitoring of Forest Health: A Systematic Evidence Synthesis

inferredcites →https://doi.org/10.3390/f12091145openalex-snapshot

Mapping Boreal Forest Spruce Beetle Health Status at the Individual Crown Scale Using Fused Spectral and Structural Data

inferredcites →https://doi.org/10.3390/f12101393openalex-snapshot

Early Monitoring of Health Status of Plantation-Grown Eucalyptus pellita at Large Spatial Scale via Visible Spectrum Imaging of Canopy Foliage Using Unmanned Aerial Vehicles

inferredcites →https://doi.org/10.3390/f6030594openalex-snapshot

Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels

inferredcites →https://doi.org/10.3390/f8090340openalex-snapshot

Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest

inferredcites →https://doi.org/10.3390/f8100402openalex-snapshot

Assessing Pine Processionary Moth Defoliation Using Unmanned Aerial Systems

inferredcites →https://doi.org/10.3390/ijgi6020051openalex-snapshot

Evaluation of Feature Selection Methods for Object-Based Land Cover Mapping of Unmanned Aerial Vehicle Imagery Using Random Forest and Support Vector Machine Classifiers

inferredcites →https://doi.org/10.3390/rs10040641openalex-snapshot

On the Use of Unmanned Aerial Systems for Environmental Monitoring

inferredcites →https://doi.org/10.3390/rs10071120openalex-snapshot

Understanding Forest Health with Remote Sensing, Part III: Requirements for a Scalable Multi-Source Forest Health Monitoring Network Based on Data Science Approaches

inferredcites →https://doi.org/10.3390/rs10081216openalex-snapshot

UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health

inferredcites →https://doi.org/10.3390/rs10122062openalex-snapshot

Can UAV-Based Infrared Thermography Be Used to Study Plant-Parasite Interactions between Mistletoe and Eucalypt Trees?

inferredcites →https://doi.org/10.3390/rs11060643openalex-snapshot

Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning

inferredcites →https://doi.org/10.3390/rs11121443openalex-snapshot

Unmanned Aerial Vehicle for Remote Sensing Applications—A Review

inferredcites →https://doi.org/10.3390/rs11131561openalex-snapshot

The Use of UAV Mounted Sensors for Precise Detection of Bark Beetle Infestation

inferredcites →https://doi.org/10.3390/rs11212540openalex-snapshot

Detection of Pine Shoot Beetle (PSB) Stress on Pine Forests at Individual Tree Level using UAV-Based Hyperspectral Imagery and Lidar

inferredcites →https://doi.org/10.3390/rs12061001openalex-snapshot

Current Practices in UAS-based Environmental Monitoring

inferredcites →https://doi.org/10.3390/rs12061046openalex-snapshot

Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities

inferredcites →https://doi.org/10.3390/rs12071052openalex-snapshot

A Systematic Review of the Factors Influencing the Estimation of Vegetation Aboveground Biomass Using Unmanned Aerial Systems

inferredcites →https://doi.org/10.3390/rs12142280openalex-snapshot

A Machine Learning Approach to Detecting Pine Wilt Disease Using Airborne Spectral Imagery

inferredcites →https://doi.org/10.3390/rs12152363openalex-snapshot

Individual Tree Crown Delineation from UAS Imagery Based on Region Growing and Growth Space Considerations

inferredcites →https://doi.org/10.3390/rs12183032openalex-snapshot

Monitoring of Chestnut Trees Using Machine Learning Techniques Applied to UAV-Based Multispectral Data

inferredcites →https://doi.org/10.3390/rs12193153openalex-snapshot

Detection of Longhorned Borer Attack and Assessment in Eucalyptus Plantations Using UAV Imagery

inferredcites →https://doi.org/10.3390/rs12213511openalex-snapshot

Meta-analysis of Unmanned Aerial Vehicle (UAV) Imagery for Agro-environmental Monitoring Using Machine Learning and Statistical Models

inferredcites →https://doi.org/10.3390/rs12223722openalex-snapshot

Tree Species Classification and Health Status Assessment for a Mixed Broadleaf-Conifer Forest with UAS Multispectral Imaging

inferredcites →https://doi.org/10.3390/rs12244081openalex-snapshot

Automatic Tree Crown Extraction from UAS Multispectral Imagery for the Detection of Bark Beetle Disturbance in Mixed Forests

inferredcites →https://doi.org/10.3390/rs13020162openalex-snapshot

Identifying Pine Wood Nematode Disease Using UAV Images and Deep Learning Algorithms

inferredcites →https://doi.org/10.3390/rs13020260openalex-snapshot

Individual Sick Fir Tree (Abies mariesii) Identification in Insect Infested Forests by Means of UAV Images and Deep Learning

inferredcites →https://doi.org/10.3390/rs13091623openalex-snapshot

Improving Land Cover Classification Using Genetic Programming for Feature Construction

inferredcites →https://doi.org/10.3390/rs13183594openalex-snapshot

Evaluation of Deep Learning Segmentation Models for Detection of Pine Wilt Disease in Unmanned Aerial Vehicle Images

inferredcites →https://doi.org/10.3390/rs13204065openalex-snapshot

Three-Dimensional Convolutional Neural Network Model for Early Detection of Pine Wilt Disease Using UAV-Based Hyperspectral Images

inferredcites →https://doi.org/10.3390/rs13234768openalex-snapshot

Detection of Bark Beetle Disturbance at Tree Level Using UAS Multispectral Imagery and Deep Learning

inferredcites →https://doi.org/10.3390/rs13234873openalex-snapshot

Monitoring Fine-Scale Forest Health Using Unmanned Aerial Systems (UAS) Multispectral Models

inferredcites →https://doi.org/10.3390/rs14030801openalex-snapshot

Genetic Programming Approach for the Detection of Mistletoe Based on UAV Multispectral Imagery in the Conservation Area of Mexico City

inferredcites →https://doi.org/10.3390/rs4061671openalex-snapshot

Unmanned Aircraft Systems in Remote Sensing and Scientific Research: Classification and Considerations of Use

inferredcites →https://doi.org/10.3390/rs71115467openalex-snapshot

Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level

inferredcites →https://doi.org/10.3390/rs8040333openalex-snapshot

Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data

inferredcites →https://doi.org/10.3390/rs9020129openalex-snapshot

Understanding Forest Health with Remote Sensing-Part II—A Review of Approaches and Data Models

inferredcites →https://doi.org/10.3390/rs9050459openalex-snapshot

Review of the Current State of UAV Regulations

inferredcites →https://doi.org/10.3390/rs9111110openalex-snapshot

Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry

inferredcites →https://doi.org/10.3390/s17122852openalex-snapshot

Observing Spring and Fall Phenology in a Deciduous Forest with Aerial Drone Imagery

inferredcites →https://doi.org/10.3390/s18040944openalex-snapshot

Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence

inferredcites →https://doi.org/10.3390/s18072013openalex-snapshot

Feature Selection Method Based on High-Resolution Remote Sensing Images and the Effect of Sensitive Features on Classification Accuracy

inferredcites →https://doi.org/10.3390/s18103278openalex-snapshot

Calibrating the Severity of Forest Defoliation by Pine Processionary Moth with Landsat and UAV Imagery

inferredcites →https://doi.org/10.3390/s19143071openalex-snapshot

Hyperspectral Imaging in Environmental Monitoring: A Review of Recent Developments and Technological Advances in Compact Field Deployable Systems

inferredcites →https://doi.org/10.4039/tce.2016.11openalex-snapshot

Remote sensing of forest pest damage: a review and lessons learned from a Canadian perspective

inferredcites →https://doi.org/10.5194/isprs-annals-v-2-2020-203-2020openalex-snapshot

CLASSIFICATION OF TREE SPECIES AND STANDING DEAD TREES BY FUSING UAV-BASED LIDAR DATA AND MULTISPECTRAL IMAGERY IN THE 3D DEEP NEURAL NETWORK POINTNET++

inferredcites →https://doi.org/10.5194/isprs-archives-xli-b8-711-2016openalex-snapshot

USE OF A MULTISPECTRAL UAV PHOTOGRAMMETRY FOR DETECTION AND TRACKING OF FOREST DISTURBANCE DYNAMICS

inferredcites →https://doi.org/10.5194/isprs-archives-xliii-b3-2020-429-2020openalex-snapshot

USING MULTITEMPORAL HYPER- AND MULTISPECTRAL UAV IMAGING FOR DETECTING BARK BEETLE INFESTATION ON NORWAY SPRUCE

inferredcites →https://doi.org/10.5194/isprsarchives-xl-3-w3-349-2015openalex-snapshot

UAV-BORNE THERMAL IMAGING FOR FOREST HEALTH MONITORING: DETECTION OF DISEASE-INDUCED CANOPY TEMPERATURE INCREASE

inferredcites →https://doi.org/10.5424/fs/2013223-04417openalex-snapshot

Remote Monitoring of Forest Insect Defoliation -A Review-

inferredcites →https://doi.org/10.5424/fs/2019281-14221openalex-snapshot

Remote sensing for the Spanish forests in the 21st century: a review of advances, needs, and opportunities

inferredcites →https://doi.org/10.5721/eujrs20154821openalex-snapshot

Delineation of Individual Tree Crowns from ALS and Hyperspectral data: a comparison among four methods

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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UAV-based RGB imagery for assessing vegetation status in a Mediterranean area affected by Xylella fastidiosa

inferred← citeshttps://doi.org/10.1002/ece3.72823openalex-snapshot

A Detection Method of Pine Wilt Disease Based on Improved YOLOv11 With UAV Remote Sensing Images

inferred← citeshttps://doi.org/10.1002/ecs2.4877openalex-snapshot

A comparison and development of methods for estimating shrub volume using drone‐imagery‐derived point clouds

inferred← citeshttps://doi.org/10.1002/ps.70873openalex-snapshot

Unraveling spatiotemporal dynamics of pine wilt disease via time‐series UAV monitoring and deep learning

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Entomopathogens in the integrated management of forest insects: from science to practice

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Integrating LiDAR Data and Semi-empirical Fire Model in Mapping the Interaction Between Wildfire and Bark Beetle Outbreak

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PESTBERT: A Deep Learning-Inspired Model to Improve Plant Biosecurity and Agriculture Sustainability

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Towards Generalized UAV Object Detection: A Novel Perspective from Frequency Domain Disentanglement

inferred← citeshttps://doi.org/10.1007/s40725-026-00277-9openalex-snapshot

Remote Sensing of Foliar Insect Herbivory in Broadleaved Forests: A Systematic Review

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Information and communication technologies in sustainable crop protection: advancing towards sustainable agriculture

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Differential evolution with multi-strategies for UAV trajectory planning and point cloud registration

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Classifying adaxial and abaxial sides of diseased citrus leaves with selected hyperspectral bands and YOLOv8

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Hybrid receptive field network for small object detection on drone view

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Towards operational UAV-based forest health monitoring: Species identification and crown condition assessment by means of deep learning

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A learning-based approach for forest row orientation estimation from UAV LiDAR point clouds

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Application of machine learning in automatic image identification of insects - a review

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Image-based down cluster ratio prediction for quality grading of down content

inferred← citeshttps://doi.org/10.1016/j.foreco.2023.121595openalex-snapshot

Early detection of bark beetle (Ips typographus) infestations by remote sensing – A critical review of recent research

inferred← citeshttps://doi.org/10.1016/j.foreco.2025.122674openalex-snapshot

Harnessing stemflow as a diagnostic tool for canopy disease detection and monitoring

inferred← citeshttps://doi.org/10.1016/j.inpa.2025.02.001openalex-snapshot

Optimization of Sassafras tzumu leaves color quantification with UAV RGB imaging and Sassafras-net

inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2024.01.012openalex-snapshot

CaR3DMIC: A novel method for evaluating UAV-derived 3D forest models by tree features

inferred← citeshttps://doi.org/10.1016/j.jag.2024.104257openalex-snapshot

Species-specific machine learning models for UAV-based forest health monitoring: Revealing the importance of the BNDVI

inferred← citeshttps://doi.org/10.1016/j.jenvman.2024.123150openalex-snapshot

Modeling the interaction between wildfires and windthrows: A pilot case study for Italian Alps

inferred← citeshttps://doi.org/10.1016/j.napere.2025.100132openalex-snapshot

Microbial control of forest insect pests over 60 years (1964–2024): Network analysis and bibliometric mapping

inferred← citeshttps://doi.org/10.1016/j.neucom.2025.132020openalex-snapshot

Collision avoidance in UAV swarms: A learning-centric perspective on collaborative intelligence

inferred← citeshttps://doi.org/10.1016/j.pmpp.2026.103334openalex-snapshot

Physiological and molecular mechanisms underlying crop responses to pest attack and their implications for sustainable management

inferred← citeshttps://doi.org/10.1016/j.rsase.2024.101341openalex-snapshot

A systematic review of the application of remote sensing technologies in mapping forest insect pests and diseases at a tree-level

inferred← citeshttps://doi.org/10.1016/j.rsase.2025.101530openalex-snapshot

A monitoring method for pine wilt disease infected discolored and deceased pine trees removal information based on DDPTnet network and Bi-temporal UAV imagery

inferred← citeshttps://doi.org/10.1016/j.rsase.2026.101908openalex-snapshot

Remote-sensing methods for mapping eucalypt dieback: A systematic review

inferred← citeshttps://doi.org/10.1016/j.rsase.2026.102258openalex-snapshot

Integrating UAV multispectral and LiDAR data with field assessments to monitor chestnut ink disease severity

inferred← citeshttps://doi.org/10.1016/j.rse.2024.114454openalex-snapshot

Multitemporal UAV study of phenolic compounds in slash pine canopies

inferred← citeshttps://doi.org/10.1016/j.sciaf.2025.e02724openalex-snapshot

The use of UAV-based systems in monitoring forest health: Potentials and challenges

inferred← citeshttps://doi.org/10.1038/s41598-025-24854-3openalex-snapshot

A lightweight improved YOLOv8 method for intelligent detection of pine wilt disease

inferred← citeshttps://doi.org/10.1080/01431161.2024.2399327openalex-snapshot

Towards scalable wide area UAS monitoring of forest disturbance using hydrogen powered airships

inferred← citeshttps://doi.org/10.1080/03071375.2026.2691646openalex-snapshot

Using unoccupied aerial systems (UAS) and photogrammetry to estimate tree height and trunk diameter of urban American elm trees

inferred← citeshttps://doi.org/10.1080/17538947.2025.2509841openalex-snapshot

Mapping the distribution of pine wilt disease based on selected machine learning algorithms and high-resolution Gaofen-2/7 remote sensing

inferred← citeshttps://doi.org/10.1080/22797254.2026.2740475openalex-snapshot

Tree crown anomaly detection in UAV RGB-NIR imagery using an unsupervised cosine-distance-based approach in hemiboreal forests

inferred← citeshttps://doi.org/10.1109/access.2023.3326101openalex-snapshot

A Survey on Applications of Unmanned Aerial Vehicles Using Machine Learning

inferred← citeshttps://doi.org/10.1109/access.2024.3364676openalex-snapshot

Drone Technologies: A Tertiary Systematic Literature Review on a Decade of Improvements

inferred← citeshttps://doi.org/10.1109/aiit63112.2025.11082888openalex-snapshot

Sunflower Lodging Detection and Monitoring Through UAV-Based Multispectral Data

inferred← citeshttps://doi.org/10.1109/cait64506.2024.10963235openalex-snapshot

Review of Forest Pest and Disease Monitoring Technologies

inferred← citeshttps://doi.org/10.1109/icebe59045.2023.00054openalex-snapshot

Innovative Search and Rescue Methods Using Drones: An Algorithm Combining 3D Modeling and Laser Ranging Scanning

inferred← citeshttps://doi.org/10.1109/igarss55030.2025.11243941openalex-snapshot

Detection of the sharp-toothed bark-beetle infection using UAV multispectral and LiDAR data in Scots pine forest of Kampinoski National Park, Poland

inferred← citeshttps://doi.org/10.1109/smartiot62235.2024.00047openalex-snapshot

Robust Identification Algorithm for Pine Wilt Disease Based on Frequency Domain Feature

inferred← citeshttps://doi.org/10.1111/2041-210x.70172openalex-snapshot

Application of unmanned aerial vehicles ( UAVs ) in farmland biodiversity monitoring: A systematic review protocol

inferred← citeshttps://doi.org/10.1111/efp.70061openalex-snapshot

Biology, Detection, and Management of Lecanosticta acicola : Emerging Challenges for the Management of Brown Spot Needle Blight in Pine Forests

inferred← citeshttps://doi.org/10.1117/1.jrs.18.014503openalex-snapshot

Extraction of pine wilt disease based on a two-stage unmanned aerial vehicle deep learning method

inferred← citeshttps://doi.org/10.1117/12.2684136openalex-snapshot

Texture descriptors and machine learning algorithms for mistletoe detection in urban forests using multispectral imagery

inferred← citeshttps://doi.org/10.1117/12.3021207openalex-snapshot

Classifying adaxial and abaxial sides of diseased citrus leaves with selected hyperspectral bands and YOLOv8

inferred← citeshttps://doi.org/10.1139/gen-2025-0065openalex-snapshot

The genomic impacts of rapid range expansions

inferred← citeshttps://doi.org/10.1145/3625387openalex-snapshot

Early Detection of Bark Beetle Attack Using Remote Sensing and Machine Learning: A Review

inferred← citeshttps://doi.org/10.1145/3671016.3671384openalex-snapshot

Intelligent Interference Information Fusion for Security of UAV Forest Remote Sensing Image Detection

inferred← citeshttps://doi.org/10.12677/sea.2024.132015openalex-snapshot

DA-YOLO: A Detection Model for Pine Wilt Disease Based on Dual Attention

inferred← citeshttps://doi.org/10.21105/joss.09497openalex-snapshot

Data-to-Science (D2S): An open-source ecosystem for collaborative geospatial data science research

inferred← citeshttps://doi.org/10.2139/ssrn.4898864openalex-snapshot

Rapid Detection Method for Forestland Changes Based on Drones

inferred← citeshttps://doi.org/10.2139/ssrn.6827660openalex-snapshot

Artificial Intelligence for Forest Carbon Accounting: A Scoping Review of Engineering Methodologies, Digital Twins, and Deployment Gaps

inferred← citeshttps://doi.org/10.2139/ssrn.6827663openalex-snapshot

Artificial Intelligence for Forest Carbon Accounting: A Scoping Review of Engineering Methodologies, Digital Twins, and Deployment Gaps

inferred← citeshttps://doi.org/10.3389/fenvs.2024.1412870openalex-snapshot

Remote sensing data fusion approach for estimating forest degradation: a case study of boreal forests damaged by Polygraphus proximus

inferred← citeshttps://doi.org/10.3389/fpls.2025.1619695openalex-snapshot

Erannis jacobsoni disturbance detection based on unmanned aerial vehicle red edge spectral features

inferred← citeshttps://doi.org/10.3389/fpls.2025.1633206openalex-snapshot

Spatiotemporal pattern analysis of juglans leaf necrosis disease occurrence and development in southern Xinjiang, China, based on UAV

inferred← citeshttps://doi.org/10.3389/fpls.2026.1958828openalex-snapshot

Deep learning-based automatic tree-level crown detection from high-resolution UAV imagery for aboveground carbon stock estimation

inferred← citeshttps://doi.org/10.3390/aerospace10030317openalex-snapshot

UAV Platforms for Data Acquisition and Intervention Practices in Forestry: Towards More Intelligent Applications

inferred← citeshttps://doi.org/10.3390/agriculture13061158openalex-snapshot

Detection of Residual Film on the Field Surface Based on Faster R-CNN Multiscale Feature Fusion

inferred← citeshttps://doi.org/10.3390/agriculture13101886openalex-snapshot

Detection of Bagworm Infestation Area in Oil Palm Plantation Based on UAV Remote Sensing Using Machine Learning Approach

inferred← citeshttps://doi.org/10.3390/agronomy12071692openalex-snapshot

Actions for Monitoring the Gonipterus Pest in Eucalyptus on the Cantabrian Coast

inferred← citeshttps://doi.org/10.3390/agronomy13030923openalex-snapshot

Leaf Trait Hyperspectral Characterization of Castanea sativa Miller Affected by Dryocosmus kuriphilus Yasumatsu

inferred← citeshttps://doi.org/10.3390/agronomy15051106openalex-snapshot

Detection of Leaf Miner Infestation in Chickpea Plants Using Hyperspectral Imaging in Morocco

inferred← citeshttps://doi.org/10.3390/agronomy15081837openalex-snapshot

Banana Fusarium Wilt Recognition Based on UAV Multi-Spectral Imagery and Automatically Constructed Enhanced Features

inferred← citeshttps://doi.org/10.3390/app15137317openalex-snapshot

MSFNet: A Multi-Source Fusion-Based Method with Enhanced Hierarchical Spectral Semantic Perception for Wheat Disease Region Classification

inferred← citeshttps://doi.org/10.3390/axioms13040232openalex-snapshot

Dynamic Analysis of a Delayed Differential Equation for Ips subelongatus Motschulsky-Larix spp.

inferred← citeshttps://doi.org/10.3390/biology11111645openalex-snapshot

Mitigating the Mistletoe Menace: Biotechnological and Smart Management Approaches

inferred← citeshttps://doi.org/10.3390/biology14091108openalex-snapshot

Assessing Birds of Prey as Biological Pest Control: A Comparative Study with Hunting Perches and Rodenticides on Rodent Activity and Crop Health

inferred← citeshttps://doi.org/10.3390/drones7040260openalex-snapshot

A Survey on the Design Aspects and Opportunities in Age-Aware UAV-Aided Data Collection for Sensor Networks and Internet of Things Applications

inferred← citeshttps://doi.org/10.3390/f13081322openalex-snapshot

Detection of Eucalyptus Leaf Disease with UAV Multispectral Imagery

inferred← citeshttps://doi.org/10.3390/f13111765openalex-snapshot

Management of Forest Pests and Diseases

inferred← citeshttps://doi.org/10.3390/f13111884openalex-snapshot

Monitoring of Discolored Trees Caused by Pine Wilt Disease Based on Unsupervised Learning with Decision Fusion Using UAV Images

inferred← citeshttps://doi.org/10.3390/f14030588openalex-snapshot

Identification of Pine Wilt Disease Infected Wood Using UAV RGB Imagery and Improved YOLOv5 Models Integrated with Attention Mechanisms

inferred← citeshttps://doi.org/10.3390/f15010028openalex-snapshot

Detecting the Short-Term Effects of Water Stress on Radiata Pine Physiology Using Thermal Imagery

inferred← citeshttps://doi.org/10.3390/f15040644openalex-snapshot

Hierarchical Integration of UAS and Sentinel-2 Imagery for Spruce Bark Beetle Grey-Attack Detection by Vegetation Index Thresholding Approach

inferred← citeshttps://doi.org/10.3390/f15061050openalex-snapshot

A Lightweight Pine Wilt Disease Detection Method Based on Vision Transformer-Enhanced YOLO

inferred← citeshttps://doi.org/10.3390/f15091676openalex-snapshot

Rapid Forest Change Detection Using Unmanned Aerial Vehicles and Artificial Intelligence

inferred← citeshttps://doi.org/10.3390/f15122135openalex-snapshot

Effective UAV Photogrammetry for Forest Management: New Insights on Side Overlap and Flight Parameters

inferred← citeshttps://doi.org/10.3390/f15122147openalex-snapshot

Advances in Global Remote Sensing Monitoring of Discolored Pine Trees Caused by Pine Wilt Disease: Platforms, Methods, and Future Directions

inferred← citeshttps://doi.org/10.3390/f16020228openalex-snapshot

Assessment of Pine Tree Crown Delineation Algorithms on UAV Data: From K-Means Clustering to CNN Segmentation

inferred← citeshttps://doi.org/10.3390/f16030472openalex-snapshot

A Small-Scale Investigation into the Viability of Detecting Canopy Damage Caused by Acantholyda posticalis Disturbance Using High-Resolution Satellite Imagery in a Managed Pinus sylvestris Stand in Central Poland

inferred← citeshttps://doi.org/10.3390/f16050754openalex-snapshot

Preliminary Machine Learning-Based Classification of Ink Disease in Chestnut Orchards Using High-Resolution Multispectral Imagery from Unmanned Aerial Vehicles: A Comparison of Vegetation Indices and Classifiers

inferred← citeshttps://doi.org/10.3390/f16071200openalex-snapshot

Health Monitoring of Abies nebrodensis Combining UAV Remote Sensing Data, Climatological and Weather Observations, and Phytosanitary Inspections

inferred← citeshttps://doi.org/10.3390/f16081240openalex-snapshot

Early Detection of Herbicide-Induced Tree Stress Using UAV-Based Multispectral and Hyperspectral Imagery

inferred← citeshttps://doi.org/10.3390/futuretransp5020063openalex-snapshot

The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics

inferred← citeshttps://doi.org/10.3390/insects15030172openalex-snapshot

Potential of Unmanned Aerial Vehicle Red–Green–Blue Images for Detecting Needle Pests: A Case Study with Erannis jacobsoni Djak (Lepidoptera, Geometridae)

inferred← citeshttps://doi.org/10.3390/land14030630openalex-snapshot

Detecting Symptoms and Dispersal of Pine Tortoise Scale Pest in an Urban Forest by Remote Sensing

inferred← citeshttps://doi.org/10.3390/rs14246257openalex-snapshot

Estimating Tree Health Decline Caused by Ips typographus L. from UAS RGB Images Using a Deep One-Stage Object Detection Neural Network

inferred← citeshttps://doi.org/10.3390/rs15051178openalex-snapshot

Monitoring Ash Dieback in Europe—An Unrevealed Perspective for Remote Sensing?

inferred← citeshttps://doi.org/10.3390/rs15081964openalex-snapshot

Application of YOLOv5 for Point Label Based Object Detection of Black Pine Trees with Vitality Losses in UAV Data

inferred← citeshttps://doi.org/10.3390/rs15102653openalex-snapshot

Orthomosaicking Thermal Drone Images of Forests via Simultaneously Acquired RGB Images

inferred← citeshttps://doi.org/10.3390/rs15194672openalex-snapshot

A Systematic Review of UAV Applications for Mapping Neglected and Underutilised Crop Species’ Spatial Distribution and Health

inferred← citeshttps://doi.org/10.3390/rs15204928openalex-snapshot

Comparison of Deep Neural Networks in the Classification of Bark Beetle-Induced Spruce Damage Using UAS Images

inferred← citeshttps://doi.org/10.3390/rs16010132openalex-snapshot

Monitoring of Cotton Boll Opening Rate Based on UAV Multispectral Data

inferred← citeshttps://doi.org/10.3390/rs16020364openalex-snapshot

Detection of the Infection Stage of Pine Wilt Disease and Spread Distance Using Monthly UAV-Based Imagery and a Deep Learning Approach

inferred← citeshttps://doi.org/10.3390/rs16061050openalex-snapshot

Early Detection of Myrtle Rust on Pōhutukawa Using Indices Derived from Hyperspectral and Thermal Imagery

inferred← citeshttps://doi.org/10.3390/rs16081365openalex-snapshot

Evaluating a Novel Approach to Detect the Vertical Structure of Insect Damage in Trees Using Multispectral and Three-Dimensional Data from Drone Imagery in the Northern Rocky Mountains, USA

inferred← citeshttps://doi.org/10.3390/rs16193751openalex-snapshot

Discriminating between Biotic and Abiotic Stress in Poplar Forests Using Hyperspectral and LiDAR Data

inferred← citeshttps://doi.org/10.3390/rs17060962openalex-snapshot

Advanced Insect Detection Network for UAV-Based Biodiversity Monitoring

inferred← citeshttps://doi.org/10.3390/rs17111833openalex-snapshot

Early Detection of Pine Wilt Disease by Combining Pigment and Moisture Content Indices Using UAV-Based Hyperspectral Imagery

inferred← citeshttps://doi.org/10.3390/rs17183141openalex-snapshot

Assessing Pacific Madrone Blight with UAS Remote Sensing Under Different Skylight Conditions

inferred← citeshttps://doi.org/10.3390/rs18060880openalex-snapshot

Field-Scale Detection of Rice Bacterial Leaf Blight Using UAV-Based Multispectral Imagery: Via Cross-Scale Sample-Label Transfer and Spatial–Spectral Feature Fusion

inferred← citeshttps://doi.org/10.3390/rs18101559openalex-snapshot

Per-SAM-MCPA: A Lightweight Framework for Individual Tree Crown Segmentation from UAV Imagery

inferred← citeshttps://doi.org/10.3390/rs18172916openalex-snapshot

DROMAL-Net: A Forest Larch Casebearer Detection Model Focusing on Global Feature Enhancement and Positional Dynamic Clustering

inferred← citeshttps://doi.org/10.3390/s25041034openalex-snapshot

Supervised Hyperspectral Band Selection Using Texture Features for Classification of Citrus Leaf Diseases with YOLOv8

inferred← citeshttps://doi.org/10.3390/su162310731openalex-snapshot

Estimation of Damaged Regions by the Bark Beetle in a Mexican Forest Using UAV Images and Deep Learning

inferred← citeshttps://doi.org/10.3390/su18010507openalex-snapshot

A Review of Drones in Smart Agriculture: Issues, Models, Trends, and Challenges

inferred← citeshttps://doi.org/10.3390/su18063064openalex-snapshot

UAVs in Urban Blue–Green Infrastructure Management: A Comprehensive Review of Sensors, Methods, and Applications

inferred← citeshttps://doi.org/10.34220/issn.2222-7962/2025.4/11openalex-snapshot

Temporal patterns of wildfire occurrence in forests disturbed by pests in the subtaiga zone of Central Siberia

inferred← citeshttps://doi.org/10.3832/ifor4002-016openalex-snapshot

Use of unmanned aerial vehicles for the diagnosis of parasitic plant infestation at the crown level in Pinus hartwegii

inferred← citeshttps://doi.org/10.3897/neobiota.84.95692openalex-snapshot

Testing early detection of pine processionary moth Thaumetopoea pityocampa nests using UAV-based methods

inferred← citeshttps://doi.org/10.3934/era.2023352openalex-snapshot

Dynamic analysis of a delayed differential equation for Tropidothorax elegans pests

inferred← citeshttps://doi.org/10.5194/isprs-archives-xlviii-1-2024-443-2024openalex-snapshot

Monitoring the spread of a pathogenic insect on vineyards using UAS

inferred← citeshttps://doi.org/10.5424/fs/2025342-20940openalex-snapshot

High resolution thermal and multispectral remote sensing for detecting devitalized trees in Monarch Butterfly Biosphere Reserve

inferred← citeshttps://doi.org/10.58830/ozgur.pub1417.c5696openalex-snapshot

Zararlı Böceklerin Tanılanmasında Yapay Zekâ ve Görüntü İşleme Yaklaşımları

inferred← citeshttps://doi.org/10.62320/fm.v1.i1.14openalex-snapshot

Cost-effectiveness of remote sensing technology for spruce budworm monitoring in Maine, USA

inferred← citeshttps://doi.org/10.65372/ptapac10openalex-snapshot

A Multi-Year Assessment of Oak Response to Spongy Moth using Uncrewed Aerial Vehicles

inferred← citeshttps://doi.org/10.9787/kjbs.2024.56.4.439openalex-snapshot

The Trap of Presumption: A Case Study of Agricultural Research for Early Detection of Brown Planthopper Damage in Rice Fields

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