"DAFI"
Embedded Files
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]. 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 - 2023, have been processed to achieve this aim. The temporal persistence of two combined signals (the NHISWNIR and the Extreme Pixel, Figure 1 - block 1), expressed as a Occurrence Frequency (%), is the criterion used to select the candidates GF hotspots (OF≥ 10%, Figure 1 - block 2), 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 (Figure 1, block 3). A persistence level (from low to high) is assigned to each identified GF, according to its OF value (Figure 1 - block 4). It should reveal the GF type, i.e. intermittent or continuous process.
The DAFI method consists of a 4-module cascade, shown in Figure 1.
Figure 1. DAFI conditions for (a) detecting a potential sub-pixel hotspot over the single daytime OLI/MSI image ("Image Processing"); (b) flagging the pixel as a gas flaring site ("Collection Processing"); (c) single and joint datasets processing to pinpoint the onshore and offshore gas flares ("GF Catalogue Creation"); (d) assigning a persistence level to each GF, using a pre-defined long-term scale ("GF Site Long-Term Persistence Level Assignment").
Figure 1. DAFI conditions for (a) detecting a potential sub-pixel hotspot over the single daytime OLI/MSI image ("Image Processing"); (b) flagging the pixel as a gas flaring site ("Collection Processing"); (c) single and joint datasets processing to pinpoint the onshore and offshore gas flares ("GF Catalogue Creation"); (d) assigning a persistence level to each GF, using a pre-defined long-term scale ("GF Site Long-Term Persistence Level Assignment").
The DAFI App for global gas flaring visualization at 2021, 2022, 2023
The DAFI App for global gas flaring visualization at 2021, 2022, 2023
This tool provides an overview of the spatial distribution of gas flares (GFs) detected by following the DAFI v2 prescriptions, identified using the OLI and MSI collections (Figure 1), in years 2013-2021 (violet pointer), 2013-2022 (blue pointer) and 2013-2023 (yellow pointer). User can acquire information about the spatio/temporal dynamics of the single GF.
The DAFI App for gas flaring thermal investigation
The DAFI App for gas flaring thermal investigation
By selecting the GF to inspect using the ID name identified in the global map, the user can access to the GF geographic information (lat,lon, country) as well as the type of source, described by the occurrence frequency OF [%] and the long-term persistence level, for both the OLI- and MSI-based DAFI v2 configurations.
The temporal trends of GF thermal anomalies (i.e., the ratio of NHISWNIR + Extreme Pixel occurrence and the OLI/L8-9 and MSI/S2 images available for the selected site), aggregated by years and months (i.e, annually- and monthly-based persistence) provide useful information about the time in which the site has been active, allowing to label the GF as a continuous/routine or intermittent hot source.
All data included in the two Apps refer to the GF sites detected in 2023.
Contact: mariapia.faruolo @ cnr.it
When using the data please credit the product generation to the CNR-IMAA, 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.
Page updated
Google Sites
Report abuse