EORez's repositories
satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
lidR
Airborne LiDAR data manipulation and visualisation for forestry application
Comparison-of-high-resolution-global-canopy-height-maps-and-their-applicability
Global Canopy Height Model Comparison in R
nrt
Near Real Time monitoring of satellite image time-series
rFIA
rFIA libraries for querying FIA plot data
aws-vegetation-management-workshop
Leveraging deep learning on satellite images and LiDAR data using AWS machine learning services can identify areas of risk. Utility companies can use the identified anomalies to monitor vegetation and proactively intervene to prevent wildfires and protect critical infrastructure. In this workshop, learn how to use Amazon SageMaker to process satellite images and LiDAR data and identify vegetation risks using deep learning.
eo-learn
Earth observation processing framework for machine learning in Python
JoeyAJamesPython
Python code for YouTube videos.
PointCloudLibrary
Point Cloud Library (PCL)
awesome-remote-sensing-change-detection
List of datasets, codes, and contests related to remote sensing change detection
BarkBeetle-Damage-Classification-DL
chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2207.07241v1.pdf
awesome-satellite-imagery-datasets
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
awesome-forests
🌳 A curated list of ground-truth forest datasets for the machine learning and forestry community.
sentinel-tree-cover
Image segmentations of trees outside forest
DeepTreeAttention
Implementation of Hang et al. 2020 "Hyperspectral Image Classification with Attention Aided CNNs" for tree species prediction
DeepForest
Python Package for Tree Crown Detection in Airborne RGB imagery
tree_detection
This package implements a simple tree detector from point cloud data. It makes no assumptions about the ground plane and can handle arbitrary terrains.
ForestLineMapper-RoadsandGaps
Forest Line Mapper: Series of script tools for facilitating the high-resolution mapping and studying of forest lines via processing canopy height models.
aerial-image-segmentation
Aerial Image segmentation by PyTorch
An-unexpectedly-large-count-of-trees
This repository contains the code for the paper "An unexpectedly large count of trees in the western Sahara and Sahel".
Unsupervised-Classification-SCAN
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
ea_lidar_download
Python code to bulk download UK Environment Agency LiDAR data
TreeMap2014_scripts
a national imputed dataset of Forest Inventory Analysis forest plots at 30x30m resolution in the US
allometree
allometree: Allometric scaling of urban trees
ForestedWetlands
Code for building raster files of elevation derivatives, python and R scripts for using these rasters for building and applying random forest models of wetland presence/absence in ArcGIS Pro
Counting-Trees-using-Satellite-Images
This study investigates the aspect of localizing and counting trees using satellite images to create an inventory of incoming and outgoing trees for an annual tree inspections.
bayts
Set of tools to apply the probabilistic approach of Reiche et al. (2015, 2018) to combine multiple optical and/or Radar satellite time series and to detect deforestation/forest cover loss in near real-time. The package includes functions to apply the approach to both, single pixel time series and raster time series.
3d-forest-classic
software for analysis of Lidar data from forest environment.