The contribution of the scientific research for a less vulnerable and more resilient community: the Val d'Agri (Southern Italy) case

The increasingly intensive use of natural resources with consequent environmental impacts has generated numerous social conflicts over the years, for whose solution it is necessary to build up an innovative territorial governance model based on sustainable and resilience thinking. At the international level, the problems associated with oil and gas extraction activities have been tackled by recognizing scientific research as a strategic role aimed at guaranteeing a more in-depth knowledge of environmental issues, the creation of collaboration networks between the various stakeholders and the whole usability of environmental data. This article presents the commitment made by the National Research Council of Italy – Institute of Methodologies for Environmental Analysis – CNR-IMAA to make the Val d'Agri community, an area affected by mining activities, less vulnerable and more resilient. Through the combined use of different scientific research methodologies, a multidisciplinary approach was developed which contributed to increasing the overall knowledge of the environmental problems of Val d'Agri as well as providing concrete indications for the development of more effective territorial management tools. Other activities, complementary to those of research, were aimed at ensuring correct and detailed environmental data information and communication and a broaden participation and involvement of citizens

Mt. Etna Paroxysms of February–April 2021 Monitored and Quantified through a Multi-Platform Satellite Observing System

On 16 February 2021, an eruptive paroxysm took place at Mt. Etna (Sicily, Italy), after continuous Strombolian activity recorded at summit craters, which intensified in December 2020. This was the first of 17 short, but violent, eruptive events occurring during February–April 2021, mostly at a time interval of about 2–3 days between each other. The paroxysms produced lava fountains (up to 1000 m high), huge tephra columns (up to 10–11 km above sea level), lava and pyroclastic flows, expanding 2–4 km towards East and South. The last event, which was characterised by about 3 days of almost continuous eruptive activity (30 March–1 April), generated the most lasting lava fountain (8–9 h). During some paroxysms, volcanic ash led to the temporary closure of the Vincenzo Bellini Catania International Airport. Heavy ash falls then affected the areas surrounding the volcano, in some cases reaching zones located hundreds of kilometres away from the eruptive vent. In this study, we investigate the Mt. Etna paroxysms mentioned above through a multi-platform satellite system. Results retrieved from Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Spinning Enhanced Visible and Infrared Imager (SEVIRI), starting from outputs of the Robust Satellite Techniques for Volcanoes (RSTVOLC), indicate that the 17th paroxysm (31 March–1 April) was the most powerful, with values of radiative power estimated around 14 GW. Moreover, by the analysis of SEVIRI data, we found that the 5th and 17th paroxysms were the most energetic. The Multispectral Instrument (MSI) and the Operational Land Imager (OLI), providing shortwave infrared (SWIR) data at 20/30 m spatial resolution, enabled an accurate localisation of active vents and the mapping of the areas inundated by lava flows. In addition, according to the Normalized Hotspot Indices (NHI) tool, the 1st and 3rd paroxysm (18 and 28 February) generated the largest thermal anomaly at Mt. Etna after June 2013, when Landsat-8 OLI data became available. Despite the impact of clouds/plumes, pixel saturation, and other factors (e.g., satellite viewing geometry) on thermal anomaly identification, the used multi-sensor approach allowed us to retrieve quantitative information about the 17 paroxysms occurring at Mt. Etna. This approach could support scientists in better interpreting changes in thermal activity, which could lead to future and more dangerous eruptions

On the Potential of the RST-FLARE Algorithm for Gas Flaring Characterization from Space

An effective characterization of gas flaring is hampered by the lack of systematic, complete and reliable data on its magnitude and spatial distribution. In the last years, a few satellite methods have been developed to provide independent information on gas flaring activity at global, national and local scale. Among these, a MODIS-based method, aimed at the computation of gas flared volumes by an Italian plant, was proposed. In this work, a more general version of this approach, named RST-FLARE, has been developed to provide reliable information on flaring sites localization and gas emitted volumes over a long time period for the Niger Delta region, one of the top five gas flaring areas in the world. Achieved results showed a good level of accuracy, in terms of flaring sites localization (95% of spatial match) and volume estimates (mean bias between in 16% and 20%, at annual scale and 2–9% in the long period) when compared to independent data, provided both by other satellite techniques and national/international organizations. Outcomes of this work seem to indicate that RST-FLARE can be used to provide, at different geographic scales, quite accurate data on gas flaring, suitable for monitoring purposes for governments and local authorities

A Tailored Approach for the Global Gas Flaring Investigation by Means of Daytime Satellite Imagery

The Daytime Approach for gas Flaring Investigation (DAFI), running in Google Earth Engine (GEE) environment, exploits a Normalized Hotspot Index (NHI), analyzing near-infrared and short-wave infrared radiances, to detect worldwide high-temperature gas flaring sites (GFs). Daytime Landsat 8—Operational Land Imager (OLI) observations, of 2013–2021, represents the employed dataset. A temporal persistence criterion is applied to a gas flaring customized NHI product to select the GFs. It assures the 99% detection accuracy of more intense and stable GFs, with a very low false positive rate. As a result, the first daytime database and map of GF sites, operating during the last 9 years at global scale, has been generated. For each site, geographical metadata, frequency of occurrence and time persistence levels, at both monthly and annual scale, may be examined, through the specific developed GEE App. The present database will complement/integrate existing gas flaring maps. The joint use of global scale daytime and nighttime GFs inventories, in fact, will allow for tracking gas flaring dynamics in a timely manner. Moreover, it enables a better evaluation of GF emissions into the atmosphere. Finally, the next DAFI implementation on Landsat 9 and Sentinel 2 data will further improve our capabilities in identifying, mapping, monitoring and characterizing the GFs

A Tailored Approach for the Global Gas Flaring Investigation by Means of Daytime Satellite Imagery

The Daytime Approach for gas Flaring Investigation (DAFI), running in Google Earth Engine (GEE) environment, exploits a Normalized Hotspot Index (NHI), analyzing near-infrared and short-wave infrared radiances, to detect worldwide high-temperature gas flaring sites (GFs). Daytime Landsat 8—Operational Land Imager (OLI) observations, of 2013–2021, represents the employed dataset. A temporal persistence criterion is applied to a gas flaring customized NHI product to select the GFs. It assures the 99% detection accuracy of more intense and stable GFs, with a very low false positive rate. As a result, the first daytime database and map of GF sites, operating during the last 9 years at global scale, has been generated. For each site, geographical metadata, frequency of occurrence and time persistence levels, at both monthly and annual scale, may be examined, through the specific developed GEE App. The present database will complement/integrate existing gas flaring maps. The joint use of global scale daytime and nighttime GFs inventories, in fact, will allow for tracking gas flaring dynamics in a timely manner. Moreover, it enables a better evaluation of GF emissions into the atmosphere. Finally, the next DAFI implementation on Landsat 9 and Sentinel 2 data will further improve our capabilities in identifying, mapping, monitoring and characterizing the GFs

Multi-Temporal Satellite Investigation of gas Flaring in Iraq and Iran: The DAFI Porting on Collection 2 Landsat 8/9 and Sentinel 2A/B

The synergic use of satellite data at moderate spatial resolution (i.e., 20–30 m) from the new Collection 2 (C2) Landsat-8/9 (L8/9) Operational Land Imager (OLI) and Sentinel-2 (S2) Multispectral Instrument (MSI) provides a new perspective in the remote sensing applications for gas flaring (GF) identification and monitoring, thanks to a significant improvement in the revisiting time (up to ~3 days). In this study, the daytime approach for gas flaring investigation (DAFI), recently developed for identifying, mapping and monitoring GF sites on a global scale using the L8 infrared radiances, has been ported on a virtual constellation (VC) (formed by C2 L8/9 + S2) to assess its capability in understanding the GF characteristics in the space-time domain. The findings achieved for the regions of Iraq and Iran, ranked at the second and third level among the top 10 gas flaring countries in 2022, demonstrate the reliability of the developed system, with improved levels of accuracy and sensitivity (+52%). As an outcome of this study, a more realistic picture of GF sites and their behavior is achieved. A new step aimed at quantifying the GFs radiative power (RP) has been added in the original DAFI configuration. The preliminary analysis of the daily OLI- and MSI-based RP, provided for all the sites by means of a modified RP formulation, revealed their good matching. An agreement of 90% and 70% between the annual RPs computed in Iraq and Iran and both their gas-flared volumes and carbon dioxide emissions were also recorded. Being that gas flaring is one of the main sources of greenhouse gases (GHG) worldwide, the RP products may concur to infer globally the GHGs GF emissions at finer spatial scales. For the presented achievements, DAFI can be seen as a powerful satellite tool able to automatically assess the gas flaring dimension on a global scale

The VIIRS-Based RST-FLARE Configuration: The Val d’Agri Oil Center Gas Flaring Investigation in Between 2015–2019

The RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive power. The Val d’Agri Oil Center (COVA) is a gas and oil pre-treatment plant operating for about two decades within an anthropized area of Basilicata region (southern Italy) where it represents a significant potential source of social and environmental impacts. RST-FLARE, developed to study and monitor the gas flaring activity of this site by means of MODIS (Moderate Resolution Imaging Spectroradiometer) data, has exported VIIRS (Visible Infrared Imaging Radiometer Suite) records by exploiting the improved spatial and spectral properties offered by this sensor. In this paper, the VIIRS-based configuration of RST-FLARE is presented and its application on the recent (2015-2019) gas flaring activity at COVA is analyzed and discussed. Its performance in gas flaring characterization is in good agreement with VIIRS Nightfire outputs to which RST-FLARE seems to provide some add-ons. The great consistency of radiant heat estimates computed with both RST-FLARE developed configurations allows proposing a multi-sensor RST-FLARE strategy for a more accurate multi-year analysis of gas flaring

On the potential of the RST-FLARE algorithm for gas flaring characterization from space

An effective characterization of gas flaring is hampered by the lack of systematic, complete and reliable data on its magnitude and spatial distribution. In the last years, a few satellite methods have been developed to provide independent information on gas flaring activity at global, national and local scale. Among these, a MODIS-based method, aimed at the computation of gas flared volumes by an Italian plant, was proposed. In this work, a more general version of this approach, named RST-FLARE, has been developed to provide reliable information on flaring sites localization and gas emitted volumes over a long time period for the Niger Delta region, one of the top five gas flaring areas in the world. Achieved results showed a good level of accuracy, in terms of flaring sites localization (95% of spatial match) and volume estimates (mean bias between in 16% and 20%, at annual scale and 2–9% in the long period) when compared to independent data, provided both by other satellite techniques and national/international organizations. Outcomes of this work seem to indicate that RST-FLARE can be used to provide, at different geographic scales, quite accurate data on gas flaring, suitable for monitoring purposes for governments and local authorities

Analyzing the December 2013 Metaponto Plain (Southern Italy) Flood Event by Integrating Optical Sensors Satellite Data

Timely and continuous information about flood dynamics are fundamental to ensure an effective implementation of the relief and rescue operations. Satellite data provided by optical sensors onboard meteorological satellites could have great potential in this framework, offering an adequate trade-off between spatial and temporal resolution. The latest would benefit from the integration of observations coming from different satellite systems, also helping to increase the probability of finding cloud free images over the investigated region. The Robust Satellite Techniques for detecting flooded areas (RST-FLOOD) is a sensor-independent multi-temporal approach aimed at detecting flooded areas which has already been applied with good results on different polar orbiting optical sensors. In this work, it has been implemented on both the 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) and the 375 m Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS). The flooding event affecting the Basilicata and Puglia regions (southern Italy) in December 2013 has been selected as a test case. The achieved results confirm the RST-FLOOD potential in reliably detecting, in case of small basins, flooded areas regardless of the sensor used. Flooded areas have indeed been detected with similar performance by the two sensors, allowing for their continuous and near-real time monitoring

On the Potential of RST-FLOOD on Visible Infrared Imaging Radiometer Suite Data for Flooded Areas Detection

Timely and continuous information about flood spatiotemporal evolution are fundamental to ensure an effective implementation of the relief and rescue operations in case of inundation events. In this framework, satellite remote sensing may provide a valuable contribution provided that robust data analysis methods are implemented and suitable data, in terms of spatial, spectral and temporal resolutions, are employed. In this paper, the Robust Satellite Techniques (RST) approach, a satellite-based differential approach, already applied at detecting flooded areas (and therefore christened RST-FLOOD) with good results on different polar orbiting optical sensors (i.e., Advanced Very High Resolution Radiometer – AVHRR – and Moderate Resolution Imaging Spectroradiometer – MODIS), has been fully implemented on time series of Suomi National Polar-orbiting Partnership (Suomi-NPP-SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data. The flooding event affecting the Metaponto Plain in Basilicata and Puglia regions (southern Italy) in December 2013 was selected as a case study and investigated by analysing five years (only December month) of VIIRS Imagery bands at 375 m spatial resolution. The achieved results clearly indicate the potential of the proposed approach, especially when compared with a satellite-based high resolution map of flooded area, as well as with the official flood hazard map of the area and the outputs of a recent published VIIRS-based method. Both flood extent and dynamics have been recognized with good reliability during the investigated period, with only a residual 11.5% of possible false positives over an inundated area extent of about 73 km2. In addition, a flooded area of about 18 km2 was found outside the hazard map, suggesting it requires updating to better manage flood risk and prevent future damages. Finally, the achieved results indicate that medium-resolution optical data, if analysed with robust methodologies like RST-FLOOD, can be suitable for detecting and monitoring floods also in case of small hydrological basins