Daniele Settembre;Davide De Santis;Giovanni Schiavon;Fabio Del Frate
{"title":"Methane Column Estimation Using PRISMA Hyperspectral Data and Comparison With Other Earth Observation Products","authors":"Daniele Settembre;Davide De Santis;Giovanni Schiavon;Fabio Del Frate","doi":"10.1109/LGRS.2025.3539870","DOIUrl":null,"url":null,"abstract":"Our work investigates the potential of high-resolution hyperspectral satellite data for detecting atmospheric methane concentrations. We employ the matched filter with Albedo correction and reweiGhted L1 sparsity Code (MAG1C) algorithm, which integrates a sparsity prior, a matched filter, and albedo correction techniques. For the analysis, we utilize hyperspectral data from the PRISMA mission, leveraging its high spatial resolution to potentially enable more accurate localization of point emission sources. Comparing the methane column estimation resulting from our work with corresponding products provided by both the Sentinel-5P and GHGsat missions, a good agreement was found. In particular, a bias of 5 ppb with respect to the methane abundance estimated from GHGsat was reached.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10884721","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10884721/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Our work investigates the potential of high-resolution hyperspectral satellite data for detecting atmospheric methane concentrations. We employ the matched filter with Albedo correction and reweiGhted L1 sparsity Code (MAG1C) algorithm, which integrates a sparsity prior, a matched filter, and albedo correction techniques. For the analysis, we utilize hyperspectral data from the PRISMA mission, leveraging its high spatial resolution to potentially enable more accurate localization of point emission sources. Comparing the methane column estimation resulting from our work with corresponding products provided by both the Sentinel-5P and GHGsat missions, a good agreement was found. In particular, a bias of 5 ppb with respect to the methane abundance estimated from GHGsat was reached.