Learn how to help protect the environment with informed site selection analytics and data-driven methane tracking and reporting.
2022 Proceedings
HSE Sensing and Analytics
, GIS Focal Point, Enel Green Power
, GIS Specialist, Enel Green Power Spa
, Enel Green Power Spa
, Staff Data Manager, bp
Session Type: User Presentations
Session Level: All Attendees
Esri Products: ArcGIS Enterprise, ArcGIS Pro
Presentation 1 Title: Enel GIS Tool for Environmental Analysis in Renewable Project Assessment
Presentation 1 Speaker 1: Veronica Campagnoni
Presentation 1 Speaker 2: Jyoti Rohodia
Presentation 1 Speaker 3: Grazia Pannarale
Presentation 1 Abstract:
GIS has been a driving force in promoting digitalization at Enel. Given our efforts to build a sustainable future, our business requires us to assess potential Renewable sites such that our work doesn't impact our environment & biodiversity. Hence, we developed a semi-automatic GIS enabled Environmental Analysis tool internally to help us carry out the constraint analysis in the efficient manner. The tool is aimed at establishing a standardized quantitative & qualitative approach to carry out spatial risk analysis pertaining to the environmental key performance factors using ArcGIS Geoprocessing tools. It supports our Environment, Archaeology & Biodiversity function in conducting the analysis faster & accurately at the preliminary stage of project development, to identify and assess impact of any existing environmental, social, ecological, archaeological sensitivities associated pertaining to the project area of influence. It would also help in avoiding time losses due to several iterations during the design and pre-planning phase of a project. Thus, saving in time and cost. Lastly, the outputs generated would be restored on Enterprise portal creating a powerful GIS repository.
Presentation 2 Title: Using Hyperspectral Imagery for the Identification and Quantification of Methane
Presentation 2 Speaker 1: Kevin Goldsmith
Presentation 2 Abstract:
Methane is a powerful greenhouse gas that is emitted from a variety of anthropogenic activities and natural processes. Over the years, several hyperspectral sensors (TROPOMI, PRISMA, and GHGSat) with spectral channels in the 400-2500nm spectral range and spatial resolution between 0.03-7km have been used to detect and quantify small to large scale methane. This study evaluates the potential of PRISMA hyperspectral dataset for methane mapping. We applied a data-driven matched-filter approach with albedo correction in the 2300nm spectral region to detect methane plume at a 30m spatial resolution and retrieve its concentration in parts per million per meter (ppmXm). For each detected plume, we calculated its emission flux. The performance of our plume detection is demonstrated using the knowledge of a gas well blowout reported at Eagle Ford shale near Victoria, Texas. A comparative analysis was also performed using the state-of-the-arts detection results of real plume at various methane hotspot regions. Our study reports the advantage of PRISMA for methane detection and suggest that our methane detection approach will be possible with additional satellite sensors like EnMAP.
