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Rapid Detection Method for Forestland Changes Based on Drones

https://doi.org/10.2139/ssrn.4898864
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781119752134.ch17openalex-snapshot
Exploration of Pixel‐Based and Object‐Based Change Detection Techniques by Analyzing ALOS PALSAR and LANDSAT Data
inferredcites →https://doi.org/10.1002/9781119793403.ch4openalex-snapshot
Forest Cover Change Detection Across Recent Three Decades in Persian Oak Forests Using Convolutional Neural Network
inferredcites →https://doi.org/10.1007/978-3-030-00665-5_59openalex-snapshot
Review of Feature Extraction and Matching Methods for Drone Image Stitching
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-78711-4_19openalex-snapshot
Remote Sensing and GIS in Agriculture and Forest Resource Monitoring
inferredcites →https://doi.org/10.1016/b978-0-323-85283-8.00011-4openalex-snapshot
Geometric correction and stabilization of images collected by UASs in river monitoring
inferredcites →https://doi.org/10.1016/j.envc.2021.100170openalex-snapshot
The role of forests in the mitigation of global climate change: Emprical evidence from Tanzania
inferredcites →https://doi.org/10.1016/j.isprsjprs.2020.10.015openalex-snapshot
Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks
inferredcites →https://doi.org/10.1016/j.jag.2023.103453openalex-snapshot
FCD-AttResU-Net: An improved forest change detection in Sentinel-2 satellite images using attention residual U-Net
inferredcites →https://doi.org/10.1016/j.rse.2006.01.013openalex-snapshot
Forest change detection by statistical object-based method
inferredcites →https://doi.org/10.1016/j.scitotenv.2021.148784openalex-snapshot
Air quality benefits of achieving carbon neutrality in China
inferredcites →https://doi.org/10.1016/j.scitotenv.2022.155897openalex-snapshot
Enhanced release, export, and transport of diffuse nutrients from litter in forested watersheds with climate warming
inferredcites →https://doi.org/10.1023/b:clim.0000018503.10080.89openalex-snapshot
A Review of Forest Carbon Sequestration Cost Studies: A Dozen Years of Research
inferredcites →https://doi.org/10.1080/01431161.2011.648285openalex-snapshot
Object-based change detection
inferredcites →https://doi.org/10.1088/1755-1315/19/1/012017openalex-snapshot
Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing
inferredcites →https://doi.org/10.1109/igarss47720.2021.9553859openalex-snapshot
An Unsupervised Change Detection Technique Based on a Super-Resolution Convolutional Autoencoder
inferredcites →https://doi.org/10.1109/jstars.2020.3034186openalex-snapshot
Deep Learning for Regular Change Detection in Ukrainian Forest Ecosystem With Sentinel-2
inferredcites →https://doi.org/10.1109/lgrs.2018.2802944openalex-snapshot
Road Extraction by Deep Residual U-Net
inferredcites →https://doi.org/10.1109/tgrs.2019.2901945openalex-snapshot
A Deep Learning Method for Change Detection in Synthetic Aperture Radar Images
inferredcites →https://doi.org/10.1109/tgrs.2019.2909781openalex-snapshot
Transferred Deep Learning-Based Change Detection in Remote Sensing Images
inferredcites →https://doi.org/10.1111/1365-2664.12772openalex-snapshot
Future ecosystem services from European mountain forests under climate change
inferredcites →https://doi.org/10.3390/f13060911openalex-snapshot
Recent Advances in Forest Insect Pests and Diseases Monitoring Using UAV-Based Data: A Systematic Review
inferredcites →https://doi.org/10.3390/f13122170openalex-snapshot
Generalization of U-Net Semantic Segmentation for Forest Change Detection in South Korea Using Airborne Imagery
inferredcites →https://doi.org/10.3390/rs12060901openalex-snapshot
Change Detection of Deforestation in the Brazilian Amazon Using Landsat Data and Convolutional Neural Networks
inferredcites →https://doi.org/10.3390/rs14071552openalex-snapshot
A Survey on Deep Learning-Based Change Detection from High-Resolution Remote Sensing Images
inferredcites →https://doi.org/10.3390/rs14133205openalex-snapshot
UAV-Based Forest Health Monitoring: A Systematic Review
inferredcites →https://doi.org/10.3390/rs9010088openalex-snapshot
The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data
inferredcites →https://doi.org/10.3785/j.issn.1008-9209.2009.01.016openalex-snapshot
Study on characteristics of land cover change using MODIS NDVI time series.
inferredcites →https://doi.org/10.5194/isprs-archives-xlii-2-w6-85-2017openalex-snapshot
UAV CAMERAS: OVERVIEW AND GEOMETRIC CALIBRATION BENCHMARK
inferredcites →https://doi.org/10.5194/isprs-archives-xliii-b1-2022-367-2022openalex-snapshot
UAV-BASED GLACIER MONITORING: GNSS KINEMATIC TRACK POST-PROCESSING AND DIRECT GEOREFERENCING FOR ACCURATE RECONSTRUCTIONS IN CHALLENGING ENVIRONMENTS
inferredcites →https://doi.org/10.5194/isprsarchives-xxxix-b7-499-2012openalex-snapshot
ASSESSING THE FEASIBILITY OF UAV-BASED LIDAR FOR HIGH RESOLUTION FOREST CHANGE DETECTION
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