<b>Data Availability</b>

<b>Data Availability</b>

<p dir="ltr">Data Availability Statement:</p><p dir="ltr">The datasets and resources supporting this study are publicly available under the CC-BY 4.0 license via the following repositories:</p><p dir="ltr">Primary Data & Figures:</p&...

Full description

Saved in:
Bibliographic Details
Main Author: Bonyad Ahmadi (20750327) (author)
Other Authors: Mehdi Gholamalifard (13102527) (author), Seyed Mahmoud Ghasempouri (14620253) (author), Tiit Kutser (21085589) (author)
Published: 2025
Subjects:
Chemical oceanography
Photogrammetry and remote sensing
Data structures and algorithms
CTD
Machine learning
remote sensing approach
CDOM
Persian gulf
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:<p dir="ltr">Data Availability Statement:</p><p dir="ltr">The datasets and resources supporting this study are publicly available under the CC-BY 4.0 license via the following repositories:</p><p dir="ltr">Primary Data & Figures:</p><p dir="ltr">Raw in-situ measurements, satellite-derived CDOM products, and original figures (e.g., spatial maps, calibration plots) are hosted on Figshare.</p><p dir="ltr">Reproducibility Resources:</p><p dir="ltr">Python scripts for reproducing figures, preprocessing data, and training machine learning models (SVM, MLP, XGB, BRR, KRR).</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.</p><p dir="ltr">Model Outputs & Validation:</p><p dir="ltr">Pre-trained MDN model weights and architecture files.</p><p dir="ltr">Validation metrics for all algorithms, alongside cross-validation results.</p><p dir="ltr">This comprehensive archive ensures full transparency, reproducibility, and reuse potential for coastal CDOM retrieval studies.</p>

Similar Items