Application of Google Earth Engine to Monitor Greenhouse Gases: A Review
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...
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MDPI AG
2025-01-01
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| author | Damar David Wilson Gebrekidan Worku Tefera Ram L. Ray |
| author_facet | Damar David Wilson Gebrekidan Worku Tefera Ram L. Ray |
| author_sort | Damar David Wilson |
| collection | DOAJ |
| description | 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’s 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’s 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 (CO<sub>2</sub>), methane (CH<sub>4</sub>), and nitrous oxide/nitrogen dioxide (N<sub>2</sub>O/NO<sub>2</sub>) 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’s role in pinpointing emission hotspots, as demonstrated in studies monitoring uptakes. By providing insights into GEE’s capabilities for precise monitoring and mapping of GHGs, this review aims to advance environmental research and decision-making processes in mitigating climate change. |
| format | Article |
| id | doaj-art-4a12bc5edd9c49e1831f32be531665db |
| institution | Kabale University |
| issn | 2306-5729 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-4a12bc5edd9c49e1831f32be531665db2025-01-24T13:28:33ZengMDPI AGData2306-57292025-01-01101810.3390/data10010008Application of Google Earth Engine to Monitor Greenhouse Gases: A ReviewDamar David Wilson0Gebrekidan Worku Tefera1Ram L. Ray2College of Agriculture Food and Natural Resources, Prairie View A&M University, Prairie View, TX 77446, USACollege of Agriculture Food and Natural Resources, Prairie View A&M University, Prairie View, TX 77446, USACollege of Agriculture Food and Natural Resources, Prairie View A&M University, Prairie View, TX 77446, USAGoogle 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’s 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’s 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 (CO<sub>2</sub>), methane (CH<sub>4</sub>), and nitrous oxide/nitrogen dioxide (N<sub>2</sub>O/NO<sub>2</sub>) 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’s role in pinpointing emission hotspots, as demonstrated in studies monitoring uptakes. By providing insights into GEE’s capabilities for precise monitoring and mapping of GHGs, this review aims to advance environmental research and decision-making processes in mitigating climate change.https://www.mdpi.com/2306-5729/10/1/8greenhouse gasGoogle Earth Enginemachine learningartificial intelligencegeographic information systemCDA |
| spellingShingle | Damar David Wilson Gebrekidan Worku Tefera Ram L. Ray Application of Google Earth Engine to Monitor Greenhouse Gases: A Review Data greenhouse gas Google Earth Engine machine learning artificial intelligence geographic information system CDA |
| title | Application of Google Earth Engine to Monitor Greenhouse Gases: A Review |
| title_full | Application of Google Earth Engine to Monitor Greenhouse Gases: A Review |
| title_fullStr | Application of Google Earth Engine to Monitor Greenhouse Gases: A Review |
| title_full_unstemmed | Application of Google Earth Engine to Monitor Greenhouse Gases: A Review |
| title_short | Application of Google Earth Engine to Monitor Greenhouse Gases: A Review |
| title_sort | application of google earth engine to monitor greenhouse gases a review |
| topic | greenhouse gas Google Earth Engine machine learning artificial intelligence geographic information system CDA |
| url | https://www.mdpi.com/2306-5729/10/1/8 |
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