Data, Pre- and Post- processing scripts for shallow-water photogrammetry applications

<h1>Description</h1> <p>This repository contains the data and scripts to reproduce the results of Casella et al. (Remote Sensing, 2024). The scripts are in python, two of them are wrapped in Jupyter Notebooks with explanatory notes.<br><br>Please read the paper for further information on the platform used to collect the data shared in this repository.</p> <h2>Folder structure</h2> <p>The main folder contains two subfolders:</p> <ol> <li><strong>Data</strong>: this folder includes all the original data, and the results of the preprocessing and post-processing notebooks. Note that the original photos, included in the "Camera/all_photos" folder must be unzipped before running the preprocessing Jupyter&nbsp; Notebooks.</li> <li><strong>Precision_Analysis</strong>: this folder includes the digital bathymetric models that were co-registered as described in the paper. The co-registration was done offline with Quantum GIS. In this folder are also stored the results of the "Compare_DBMs.py" script, that makes the precision analysis (differences between co-registered DBMs).</li> </ol> <h2>Installation</h2> <p>Refer to the README.md file for a quick installation guide using Anaconda.&nbsp;</p> <h2>Credits</h2> <p>The code included in this work has been improved with the assistance of ChatGPT, which provided guidance on optimization, debugging, and documentation to enhance clarity and functionality. All the code has been reviewed and supervised by humans to ensure consistency and correctness.</p>