{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T15:43:43Z","timestamp":1781883823357,"version":"3.54.5"},"reference-count":78,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,1,11]],"date-time":"2025-01-11T00:00:00Z","timestamp":1736553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"United States Department of Agriculture (USDA), National Institute of Food and Agriculture","award":["NR237442XXXXC023"],"award-info":[{"award-number":["NR237442XXXXC023"]}]},{"name":"Natural Resource Conservation Service (NRCS)","award":["NR237442XXXXC023"],"award-info":[{"award-number":["NR237442XXXXC023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Google Earth Engine (GEE) is a cloud-based platform revolutionizing geospatial analysis by providing access to vast satellite datasets and computational capabilities for monitoring environmental and societal issues. It incorporates machine learning (ML) techniques and algorithms as part of its tools for analyzing and processing large geospatial data. This review explores the diverse applications of GEE in monitoring and mitigating greenhouse gas emissions and uptakes. GEE is a cloud-based platform built on Google\u2019s infrastructure for analyzing and visualizing large-scale geospatial datasets. It offers large datasets for monitoring greenhouse gas (GHG) emissions and understanding their environmental impact. By leveraging GEE\u2019s capabilities, researchers have developed tools and algorithms to analyze remotely sensed data and accurately quantify GHG emissions and uptakes. This review examines progress and trends in GEE applications, focusing on monitoring carbon dioxide (CO2), methane (CH4), and nitrous oxide\/nitrogen dioxide (N2O\/NO2) emissions. It discusses the integration of GEE with different machine learning methods and the challenges and opportunities in optimizing algorithms and ensuring data interoperability. Furthermore, it highlights GEE\u2019s role in pinpointing emission hotspots, as demonstrated in studies monitoring uptakes. By providing insights into GEE\u2019s capabilities for precise monitoring and mapping of GHGs, this review aims to advance environmental research and decision-making processes in mitigating climate change.<\/jats:p>","DOI":"10.3390\/data10010008","type":"journal-article","created":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T09:49:17Z","timestamp":1736761757000},"page":"8","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Application of Google Earth Engine to Monitor Greenhouse Gases: A Review"],"prefix":"10.3390","volume":"10","author":[{"given":"Damar David","family":"Wilson","sequence":"first","affiliation":[{"name":"College of Agriculture Food and Natural Resources, Prairie View A&M University, Prairie View, TX 77446, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gebrekidan Worku","family":"Tefera","sequence":"additional","affiliation":[{"name":"College of Agriculture Food and Natural Resources, Prairie View A&M University, Prairie View, TX 77446, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7833-9253","authenticated-orcid":false,"given":"Ram L.","family":"Ray","sequence":"additional","affiliation":[{"name":"College of Agriculture Food and Natural Resources, Prairie View A&M University, Prairie View, TX 77446, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,11]]},"reference":[{"key":"ref_1","first-page":"100907","article-title":"What Is Going on within Google Earth Engine? 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