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UAV-Processing-Toolbox
LEGACY - Use CIRN-Quantitative-Coastal-Imaging-Toolbox instead. Codes, documentation and discussion for the use of single stationary cameras and small drones for Argus-like sampling.CoastSnap-Toolbox
This repository contains code, documentation and discussion forum for the CoastSnap community beach monitoring networkcBathy-Toolbox
Routines needed to run cBathy + demosCIRN-Quantitative-Coastal-Imaging-Toolbox
The CIRN Introduction to Quantitative Coastal Imaging Toolbox is a collection of MATLAB scripts to produce geo-rectified images specifically tailored for quantitative analysis of coastal environments.coastal-imaging-research-network.github.io
Website repo for the Coastal Imaging Research NetworkForum-Wiki
Repository for the Forum and WikiShoreline-Mapping-Toolbox
A repository for any code related to shorelines mapping from coastal imagesSupport-Routines
This repository contains general routines needed for processing dataguiBathy-Source-Code
Source code of guiBathy executable. guiBathy is a graphical user interface (GUI) to estimate nearshore bathymetry from imagery collected via a hovering Unmanned Aerial System (UAS). Please cite included publication PDF if used.runupTool-Toolbox
A repository containing code and documentation to use the runupTool to digitize wave runup time stacks.PIXel-Toolbox
Routines to create pixel lists for stack collectionspycBathy-Toolbox
Translation of cBathy toolbox in python.Station-Design-Toolbox
This repository contains a code to plan a coastal monitoring station, coastal drone data collection, and create synthetic time series of the sea surface, imagery, and pixel instrument data.hotm2
GitHub-hosted version of John Stanley's HotM svn repositorycoastal-glare-estimation
This repository contains python code to calculate when glare will be an issue for a coastal camera. A glare chart is produced for a given location and field of view.T-Cor-Toolbox
This repository contains code and documentation for a temporal method for celerity detection and bathymetry inversion following Almar et al., 2008. Including the use of multiple frequencies and error estimates (Bergsma and Almar, 2018; Thuan et al, 2019; Abessolo et al., 2019; Abessolo et al, 2020). It is under development and has not had an official release yet.Love Open Source and this site? Check out how you can help us