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.
ICESat-2 ATL03/ATL08 Processing and Analysis
This project uses satellite images on Google Earth Engine to predict canopy height and estimate carbon content in the University of Malaya forest area.
Easy download of NEON LiDAR products in a scalable manner.
This repository is a fork of https://github.com/langnico/global-canopy-height-model/ and contains the code used to create the results presented in the paper: A high-resolution canopy height model of the Earth. The model estimates canopy top height for Sentinel-2 images
Tutorial for creating DSM from LiDAR data in R
R-based script for processing lidar point cloud data, generating and visualizing Digital Surface Model (DSM) and Digital Terrain Model (DTM), and extracting forest canopy metrics based on the lidR package.
R functions for extracting forest information from lidar-derived Canopy Height Models (CHMs). Based on carlos-alberto-silva/weblidar-treetop, the scripts have been refactored into standalone, modular functions better suited for automated or batch processing.
This repository...
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