"DAFI"
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The Daytime Approach for gas Flaring Investigation (DAFI) has been developed for detecting hotspots related to gas flaring activity, at global scale [Faruolo et al., 2022a,b,2023,2024]. Daytime infrared radiances acquired by OLI-Landsat 8/9 (i.e., B1 - VIS, 0.443µm, B5 - NIR, 0.865µm, B6 - SWIR1, 1.610µm) and MSI-Sentinel 2 (i.e., B5 - VIS, 0.705µm, B8A - NIR, 0.865µm, B11 - SWIR1, 1.610µm, B12 - SWIR2, 2.190µm), in the temporal range 2013 - 2025, have been processed to achieve this aim. The temporal persistence of two combined signals (the NHISWNIR and the Extreme Pixel (block a), expressed as a Occurrence Frequency (%), is the criterion used to select the candidates GF hotspots (OF≥ 5%, block b), avoiding false positives due to high reflective materials (e.g., rooftops). Analyzing OLI and MSI datasetes provides, each year, the gas flaring sites active in that period (block c). A persistence level (from low to high) is assigned to each identified GF, according to its OF value (block d). It should reveal the GF type, i.e. intermittent or continuous process.
The DAFI method consists of a 4-module cascade, shown below.
The DAFI App for global gas flaring visualization at 2021, 2022, 2023, 2024, 2025
The DAFI App for global gas flaring visualization at 2021, 2022, 2023, 2024, 2025
The Global Gas Flares Explorer GEE App provides an interactive visualization and exploration tool for the global catalogue of gas flaring sites detected through the DAFI approach. The app allows users to visualize the spatial distribution of detected gas flaring sites over different temporal windows (2013–2021, 2013–2022, 2013–2023, 2013–2024, and 2013–2025) and to investigate the temporal evolution and intensity characteristics of individual sites.
Users can select the temporal window of interest, visualize the corresponding gas flaring catalogue, and download the related ESRI Shapefile datasets. By clicking on a gas flaring site on the map, the app provides detailed information on its geographic location, country, detection source, and gas flaring occurrence frequency derived from OLI and MSI observations.
Each gas flaring site is classified according to the detection source as “Both”, “OLI”, or “MSI”, depending on whether the site is identified by both satellite sensors or by OLI- or MSI-based observations only. Furthermore, each site is assigned to one of four long-term persistence classes based on its occurrence frequency (OF) value: low (OF < 15%), mid-low (15% ≤ OF < 20%), mid-high (20% ≤ OF < 30%), and high (OF ≥ 30%).
The app provides a user-friendly environment for exploring the spatial distribution, temporal persistence, and sensor-based characterization of global gas flaring activity.
The DAFI App for gas flaring thermal investigation
The DAFI App for gas flaring thermal investigation
By selecting a GF of interest on the global map, the user can access the corresponding site location and use the OLI- and MSI-based GEE applications to calculate and visualize the daily and annual radiative power (RP) values of the selected GF. The MSI-based application provides RP values for the 2017–2025 period, whereas the OLI-based application covers the 2013–2025 period. The results are provided as plots, allowing the temporal evolution of the GF radiative power to be inspected at both daily and annual scales.
When using the data please credit the product generation to the CNR-IMIOT, with proper citations as below:
Faruolo M., Genzano N., Pergola N., Marchese F. The first global catalogue of gas flaring sources derived from a multi-temporal time series of OLI and MSI daytime data: the DAFI v2 algorithm. Environ. Res. Lett. 2024, 19 114053; DOI 10.1088/1748-9326/ad82fb.
Faruolo M., Genzano N., Marchese F., Pergola N. Multi-Temporal Satellite Investigation of gas Flaring in Iraq and Iran: The DAFI Porting on Collection 2 Landsat 8/9 and Sentinel 2A/B. Sensors 2023, 23(12), 5734; https://doi.org/10.3390/s23125734.
Faruolo, M.; Genzano, N.; Marchese, F.; Pergola, N. A Tailored Approach for the Global Gas Flaring Investigation by Means of Daytime Satellite Imagery. Remote Sensing, 14(24), 6319, 2022; https://doi.org/10.3390/rs14246319
Faruolo, M.; Falconieri, A.; Genzano, N.; Lacava, T.; Marchese, F.; Pergola, N. A Daytime Multisensor Satellite System for Global Gas Flaring Monitoring. IEEE Transactions on Geoscience and Remote Sensing, 60, 5001717, 2022.
Contact: mariapia.faruolo @ cnr.it
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