amarcozzi

DeepForest

Python Package for Airborne RGB machine learning

MillionTrees

The MillionTreesBenchmark

robosat

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

tree-detection-evo

Code repository for the paper Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural networks

stac-api-spec

SpatioTemporal Asset Catalog API specification - an API to make geospatial assets openly searchable and crawlable

stac-fastapi

STAC API implementation with FastAPI.

progress-table

Display progress as a pretty table in the command line.

ndpyramid

A small utility for generating ND array pyramids using Xarray and Zarr.

uvcgan

Code accompanying UVCGAN paper

geocube

Tool to convert geopandas vector data into rasterized xarray data.

pystac

Python library for working with any SpatioTemporal Asset Catalog (STAC)

firebehavioR

Functions for estimating wildland fire hazard using common models in the US.

stemmaps

Collection of (x,y) mapped vegetation (stem-maps)

quicfire-tools

Input and output tools for working with QUIC-Fire

geoutils

Analysis of georeferenced rasters and vectors

odc-geo

GeoBox and geometry utilities extracted from datacube-core

datacube-core

Open Data Cube analyses continental scale Earth Observation data through time

odc-stac

Load STAC items into xarray Datasets.

fastfuels-core

Core algorithms for FastFuels

nsvb

National Scale Volume and Biomass Estimators

taichi

Productive, portable, and performant GPU programming in Python.

stackstac

Turn a STAC catalog into a dask-based xarray

TreeCountSegHeight

Code for paper

urban-tree-detection

detectree

Tree detection from aerial imagery in Python

Era3D

PlanetaryComputerExamples

Examples of using the Planetary Computer

global-canopy-height-model

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 estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.

HighResCanopyHeight

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 vision transformer and convolutional decoder trained on Aerial Lidar".

OpenSplat

Production-grade 3D gaussian splatting with CPU/GPU support for Windows, Mac and Linux 🚀