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

Python interface to the ProSAIL leaf/canopy reflectance model

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

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

A collection of digital forestry tools for Matlab/Octave

A geospatial raster processing library for machine learning

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

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

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

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

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

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

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 o…

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

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

Repo for public use for science discovery using NASA AVIRIS-NG SHIFT data

Repo for NASA Surface Biology and Geology SHIFT campaign backend

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

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.

Do you want to classify satellite data into different levels of vegetation in an automated manner? Look no further because we got you covered!