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3d-convolutional-neural-networks-with-lidar

Implementations of popular CNNs in 3D for developing forest inventories from LiDAR

allodb

An R package for biomass estimation at extratropical forest plots.

awesome-shiny-extensions

🐝 Awesome R packages that offer extended UI or server components for the R web framework Shiny

cast

Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models

custom-scripts

A repository of custom scripts to be used with Sentinel Hub

deeplidar

LIDAR and RGB Deep Learning Model for Individual Tree Segmentation

dl_tutorial_rs

Introduction to convolutional neural networks (CNNs) with a remote sensing example.

docs

dronelidarcode

Code (mostly R) to work with drone lidar data for forestry applications

fastai

R interface to fast.ai

forainet

official source code for paper entitled "Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning"

forest_3d_app

forestoolboxrs

Remote Sensing Tools for Forest Monitoring

fortls

Automatic Processing of TLS Point Cloud Data for Forestry Purposes

fsct

gedi-bdl

This repository provides the code used to create the results presented in "Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles".

gedi4r

An R package for NASA’s GEDI Level 4A data download, processing and visualization.

gedi_processing

Processing pipeline for downloading, analyzing, and gridding GEDI data

geocompr

Open source book: Geocomputation with R

geostat2018

Material for the course on machine-learning based environmental monitoring at geostat 2018

ggraptr

Rapid and Pretty Things in R : A shiny graphical user interface for your favourite ggplot graphics in R

gsgsim

Global Sampling Grid simulation framework

layer-stacking

Implementation of the LiDAR tree segmentation algorithm, Layer Stacking.

lidrbook

The lidR package tutorials book :book:

livroqgis2020

Documentos do Livro Explorando o QGIS 3.x

mamif

Modeling animal movement in forest

neontreeevaluation_package

R package for evaluating individual tree crown predictions against a diverse benchmark dataset

nyctrees

Here we produced an individual tree dataset including tree locations, height, crown area, crown volume, and biomass over the entire New York City, USA for 6,005,690 trees. Individual trees were detected and mapped from remotely sensed datasets along with their height and crown size information.

ogh_summer_school_2020

Material for the session "Introduction to Deep Learning in R for the analysis of UAV-based remote sensing data"

ogm

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