Turkmenistan methane point source detections and retrievals from Landsat 5 (1986-2011)

Global atmospheric methane concentrations rose by 10-15 ppb/yr in the 1980s before abruptly slowing to 2-8 ppb/yr in the early 1990s. This period in the 1990s is known as the \"methane slowdown\" and has been attributed to the collapse of the former Soviet Union (USSR) in December 1991, which may have decreased the methane emissions from oil and gas operations. Here we develop a methane plume detection system based on probabilistic deep learning and human-labelled training data. We use this method to detect methane plumes from Landsat 5 satellite observations over Turkmenistan from 1986 to 2011. We focus on Turkmenistan because economic data suggest it could account for half of the decline in oil and gas emissions from the former USSR. We find an increase in both the frequency of methane plume detections and the magnitude of methane emissions following the collapse of the USSR. We estimate a national loss rate from oil and gas infrastructure in Turkmenistan of more than 10% at times, whic..., , , # Turkmenistan methane point source detections and retrievals from Landsat 5 (1986-2011)

This dataset contains replication data for our paper entitled \"[Space-borne assessment of the Soviet Union collapse on the methane slowdown](https://doi.org/10.31223/X5G67G)\".

## Usage notes

To open and visualize the data files in `augmented_labelled_data.tar.gz`, a Python environment with the NumPy and PyTorch libraries is required. Files archived in `retrieval_and_masks.tar.gz` could be opened and visualized using [NASA's Panoply data viewer](https://www.giss.nasa.gov/tools/panoply/).

## Description of the data and file structure

1\) `augmented_labelled_data.tar.gz` contains human-labelled plume masks and the corresponding Landsat 5 measurements.

* The package includes both positive (with plume) and negative (without plume) satellite scenes. The methane plumes were labeled by the two leading authors of this dataset. Four folders are archived:
* 'neg_labeller_1' contains **2326** ne...