Simulation-based inference advances water quality mapping in shallow coral reef environments (dataset)

The dataset contains the following files: drone-measured reflectance over a brown coral sampling site (1 file), environmental parameters (chlorophyll-a, colored dissolved organic matter, suspended particulate matter, wind speed, and depth) (1 file), hyperspectral reflectance data with varying levels of noise (6 files), multispectral reflectance data with varying levels of noise (downsampled to correspond to the bands of a MicaSense RedEdge-MX Dual Camera System drone sensor) (3 files). 1. Field data 1.1. Drone-measured multispectral reflectance data • drone_data_tetiaroa_2022.csv 1.2. Environmental parameters • parameters_TET22.csv 1.3. Hyperspectral reflectance data • unprocessed_reflectance_tetiaroa_2022.csv • processed_reflectance_tetiaroa_2022.csv • interpolated_reflectance_tetiaroa_2022.csv • hyper_field_100SNR.csv • hyper_field_500SNR.csv • hyper_field_50SNR.csv 1.4. Multispectral reflectance data (downsampled) • multi_field_100SNR.csv • multi_field_500SNR.csv • multi_field_50SNR.csv 2. Code/software: • All of the code is freely available in the GitHub repository: https://github.com/pirtapalola/SIMA.git • The scripts are run in Python 3.10. A full list of Python packages used is provided in the requirements.txt file in the GitHub repository.