RBC-SatImg: Sentinel-2 Imagery and WatData Labels for Water Mapping

Data Description

This dataset is linked to the publication "Recursive classification of satellite imaging time-series: An application to land cover mapping". In this paper, we introduce the recursive Bayesian classifier (RBC), which converts any instantaneous classifier into a robust online method through a probabilistic framework that is resilient to non-informative image variations. To reproduce the results presented in the paper, the RBC-SatImg folder and the code in the GitHub repository RBC-SatImg are required.

The RBC-SatImg folder contains:

Sentinel-2 time-series imagery from three key regions: Oroville Dam (CA, USA) and Charles River (Boston, MA, USA) for water mapping, and the Amazon Rainforest (Brazil) for deforestation detection.

The RBC-WatData dataset with manually generated water mapping labels for the Oroville Dam and Charles River regions. This dataset is well-suited for multitemporal land cover and water mapping research, as it accounts for the dynamic evolution of true class labels over time.

Pickle files with output to reproduce the results in the paper, including:

Instantaneous classification results for GMM, LR, SIC, WN, DWM

Posterior results obtained with the RBC framework

The Sentinel-2 images and forest labels used in the deforestation detection experiment for the Amazon Rainforest have been obtained from the MultiEarth Challenge dataset.

Folder Structure

The following paths can be changed in the configuration file from the GitHub repository as desired. The RBC-SatImg is organized as follows:

`./log/` (EMPTY): Default path for storing log files generated during code execution.

`./evaluation_results/`: Contains the results to reproduce the findings in the paper, including two sub-folders:

`./classification/`:  For each test site, four sub-folders are included as:

`./accuracy/`: Each sub-folder corresponding to an experimental configuration contains pickle files with balanced classification accuracy results and information about the models. The default configuration used in the paper is "conf_00."

`./figures/`: Includes result figures from the manuscript in SVG format.

`./likelihoods/`: Contains pickle files with instantaneous classification results.

`./posteriors/`: Contains pickle files with posterior results generated by the RBC framework.

`./sensitivity_analysis/`: Contains sensitivity analysis results, organized by different test sites and epsilon values.

 `./Sentinel2_data/`: Contains Sentinel-2 images used for training and evaluation, organized by scenarios (Oroville Dam, Charles River, Amazon Rainforest). Selected images have been filtered and processed as explained in the manuscript. The Amazon Rainforest images and labels have been obtained from the MultiEarth dataset, and consequently, the labels are included in this folder instead of the RBC-WatData folder.

`./RBC-WatData/`: Contains the water labels that we manually generated with the LabelStudio tool.