A geospatial raster processing library for machine learning

Python-based extractor of vegetation metrics from satellite-based vegetation time-series imagery.

Forest Vegetation Simulation (FVS) - Growth and Yield Modeling software

A collection of digital forestry tools for Matlab/Octave

A scalable implimentation of HANTS for time sereis reconstruction in remote sensing on Google Earth Engine platform

Create numerous stylized grass blades with this highly performant and scalable HDRP grass asset that makes use of VFX Graph.

It contains Google Earth Engine codes (JavaScript API) to process Sentinel-1 and Landsat 8 images to compute SAR and optical vegetation indices.

An early-stage, cross-platform interactive application and rendering framework.

Source code for the publications on "a non-linear Granger-causality framework to investigate climate–vegetation dynamics", by Papagiannopoulou et al., GMD & ERL 2017

Mapping vegetation properties in Google Earth Engine using GPR models and the Sentinel-2 L1C product.

Python interface to the ProSAIL leaf/canopy reflectance model

A framework for building next-generation differentiable and GPU-accelerated land and ecosystem models in Julia.

R package dedicated to the PROSAIL canopy reflectance model. The package allows running PROSAIL in direct and inverse modes, with various inversion strategies. A tutorial can be found on the gitlab website

Massive airborne laser altimetry (ALS) point cloud and digital elevation model (DEM) processing library.

Object-Based Image Analysis Tools for Radiative Transfer Modeling

Get Sentinel-2 data from Google Earth Engine or from cloud-optimized geotiffs in AWS Open data registry maintained by Element84, and compute biophysical parameters using SNAP Biophysical processor algorithm.

A runtime object scattering/vegetation authoring, streaming and rendering tool for Unity optimised for instanced rendering a very large number of placed items.

A Collection of Python Codes that work in QGIS (Quantum GIS) that work on Orthomosaic Maps Generated by Aerial Photogrammetry Software such as the free to use VisualSFM or commercial software DroneDeploy or PIX4D. The Goal of these codes is to create free to use classification and NDVI on orthomosaics generated using freeware or trial versions of software.

This repo contains the training webpage and hands-on tutorials for users to learn the fundamental characteristics of GEDI spaceborne lidar for real-world applications and explore GEDI data with tips for contextualized quality preparation.

A first order radiative transfer model for soil- and vegetation related parameter retrievals from radar-data

XType extension for WeeWX to provide solar energy, "Grünlandtemperatursumme" (a kind of growing degree days) and "dayET" and "ET24" as some kind of opposite to "dayRain" and "rain24"

Retrieval of plant traits from hyper- and multispectral remote sensing data with SCOPE model inversion

This repository contains a study how we can examine the vegetation cover of a region with the help of satellite data. The notebook in this repository aims to familiarise with the concept of satellite imagery data and how it can be analyzed to investigate real-world environmental and humanitarian challenges.

A procedural, obstacle avoiding, tree mesh generation tool for Unity.

This repository contains the code used for the analysis in the paper "Zhang et al. Direct and indirect impacts of urbanization on vegetation growth across the world’s cities" publised in Science Advances

3D satellite and airborne data archive search and analysis tools for NASA Surface Topography & Vegetation (STV) Precursor Coincident Datasets

Code for McCormick et al., 2021 (Nature), "Widespread woody plant use of water stored in bedrock"

Source code of my procedural distribution system of vegetation for my master thesis in 2019.

Sentinel-2 Top-Of-Atmosphere Radiometric Uncertainty Propagator (Graf et al., 2023, IEEE-JSTARS)

A series of jupyter notebook pipelines for processing lidar point clouds (LAS files) and deriving vegetation structure metrics.