Methane Column Estimation Using PRISMA Hyperspectral Data and Comparison With Other Earth Observation Products

被引:0
|
作者
Settembre, Daniele [1 ]
De Santis, Davide [1 ]
Schiavon, Giovanni [1 ]
Del Frate, Fabio [1 ]
机构
[1] Tor Vergata Univ Rome, Civil Engn & Comp Sci Engn Dept, I-00133 Rome, Italy
关键词
GHGSat; hyperspectral data; landfill; matched filter with Albedo correction and reweiGhted L1 sparsity code (MAG1C); methane emissions; petrochemical plants; PRISMA; TROPOspheric Monitoring Instrument (TROPOMI); CLIMATE;
D O I
10.1109/LGRS.2025.3539870
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
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.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] EXPLORING METHANE COLUMN ESTIMATION FROM PRISMA DATA
    Settembre, Daniele
    De Santis, Davide
    Del Frate, Fabio
    IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024, 2024, : 3700 - 3703
  • [2] Leonardo spaceborne infrared payloads for Earth observation: SLSTRs for Copernicus Sentinel 3 and PRISMA hyperspectral camera for PRISMA satellite
    Coppo, Peter
    Brandani, Fabio
    Faraci, Marco
    Sarti, Francesco
    Dami, Michele
    Chiarantini, Leandro
    Ponticelli, Beatrice
    Giunti, Lorenzo
    Fossati, Enrico
    Cosi, Massimo
    APPLIED OPTICS, 2020, 59 (23) : 6888 - 6901
  • [3] Reducing the Influence of Soil Moisture on the Estimation of Clay from Hyperspectral Data: A Case Study Using Simulated PRISMA Data
    Castaldi, Fabio
    Palombo, Angelo
    Pascucci, Simone
    Pignatti, Stefano
    Santini, Federico
    Casa, Raffaele
    REMOTE SENSING, 2015, 7 (11) : 15561 - 15582
  • [4] Joint Use of in-Scene Background Radiance Estimation and Optimal Estimation Methods for Quantifying Methane Emissions Using PRISMA Hyperspectral Satellite Data: Application to the Korpezhe Industrial Site
    Nesme, Nicolas
    Marion, Rodolphe
    Lezeaux, Olivier
    Doz, Stephanie
    Camy-Peyret, Claude
    Foucher, Pierre-Yves
    REMOTE SENSING, 2021, 13 (24)
  • [5] SCIENTIFIC RESEARCH AND APPLICATIONS DEVELOPMENT BASED ON EXPLOITATION OF PRISMA DATA IN THE FRAMEWORK OF ASI - ISRO EARTH OBSERVATION WORKING GROUP HYPERSPECTRAL ACTIVITY
    Tapete, Deodato
    Jaiswal, Rajeev Kumar
    Licciardi, Giorgio
    Sacco, Patrizia
    Gupta, Praveen Kumar
    Raju, Pokkuluri Venkat
    Raj, Babu Govindha
    Sahadevan, Anand S.
    Ahmad, Touseef
    Lyngdoh, Rosly Boy
    Kumar, Vinay
    Agrawal, Shefali
    Choudhary, Karun Kumar
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 1648 - 1651
  • [6] A generalized approach to the vicarious calibration of multiple Earth observation sensors using hyperspectral data
    Teillet, PM
    Fedosejevs, G
    Gauthier, RP
    O'Neill, NT
    Thome, KJ
    Biggar, SF
    Ripley, H
    Meygret, A
    REMOTE SENSING OF ENVIRONMENT, 2001, 77 (03) : 304 - 327
  • [7] Assessment and estimation of coal dust impact on vegetation using VIs difference model and PRISMA hyperspectral data in mining sites
    Kayet, Narayan
    Pathak, Khanindra
    Singh, Chandra Prakash
    Chaturvedi, Rajiv Kumar
    Brahmandam, Anjanikumar SV.
    Mandal, Chinmoy
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2024, 367
  • [8] SCIA PROJECT: DEVELOPMENT OF ALGORITHMS FOR GENERATING PRODUCTS RELATED TO CRYOSPHERE BY EXPLOITING PRISMA HYPERSPECTRAL DATA
    De Gregorio, L.
    Callegari, M.
    Colombo, R.
    Cremonese, E.
    Di Mauro, Biagio
    Garzonio, R.
    Giardino, C.
    Marin, C.
    Matta, E.
    Notarnicola, C.
    Pepe, M.
    Ravasio, C.
    Montuori, A.
    Licciardi, G.
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 1641 - 1643
  • [9] Using PRISMA Hyperspectral Data for Land Cover Classification with Artificial Intelligence Support
    Delogu, Gabriele
    Caputi, Eros
    Perretta, Miriam
    Ripa, Maria Nicolina
    Boccia, Lorenzo
    SUSTAINABILITY, 2023, 15 (18)
  • [10] Estimation of Mining Subsidence in Talcher Region using Time Series Earth Observation Data
    Behera, A.
    Rawat, K. S.
    Singh, S. K.
    JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA, 2024, 100 (08) : 1140 - 1148