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foreststuff
Python Package for Airborne RGB machine learning
🌳 A curated list of ground-truth forest datasets for the machine learning and forestry community.
This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estima…
Tree detection from aerial imagery in Python
Automatic tree species classification from remote sensing data
This repository provides inference code to compute canopy height maps from aerial images, as described in the paper "Very high resolution canopy height maps from RGB imagery using self-supervised v…
A comprehensive and up-to-date compilation of datasets, tools, methods, review papers, and competitions for remote sensing change detection.
Speed up model training by fixing data loading.
Deep learning system; Docker image access; Pypi package; GEE access; image segmentation; density estimation; dataset open; pre-trained models open; PNAS Nexus publication
🌲 🌳 🌴 A catalogue of open access forest datasets
Restor's ML pipeline for tree crown mapping in aerial images
A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery (ICCV 2021) https://arxiv.org/abs/2108.07002
Code and experiments for the paper, "A Change Detection Reality Check", Corley et al.
Taper models for spruce, pine and birch in Norway
A Change Detection Repo Standing on the Shoulders of Giants
[IEEE GRSL] The official implementation of UNetMamba: An Efficient UNet-Like Mamba for Semantic Segmentation of High-Resolution Remote Sensing Images on PyTorch
Implementation of the multi-temporal UTAE for the task of satellite image time series semantic change detection (SITS-SCD)
Investigating attention masks learned from other tasks repurposed for cloud masking
Time series change detection dataset for paper "COUD: Continual Urbanization Detector for Time Series Building Change Detection"
Official Implementation (code and models) of: "SITS-Extreme: Leveraging Satellite Image Time Series for Accurate Extreme Event Detection"
Bayesian techniques for Earth observation post-classification data processing