Loss of Relict Oak Forests along Coastal Louisiana: A Multiyear Analysis Using Google Earth Engine
Coastal forests along the southeastern Gulf of Mexico are known to be diminishing at an alarming rate. The live-oak dominant chenier forests of southeast Louisiana are amongst those exhibiting the steepest declines. The remnant stands have experienced numerous hurricanes and intense storm events in...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Forests |
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| Online Access: | https://www.mdpi.com/1999-4907/13/7/1132 |
| _version_ | 1797406308881661952 |
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| author | Paurava Thakore Parusha Raut Joydeep Bhattacharjee |
| author_facet | Paurava Thakore Parusha Raut Joydeep Bhattacharjee |
| author_sort | Paurava Thakore |
| collection | DOAJ |
| description | Coastal forests along the southeastern Gulf of Mexico are known to be diminishing at an alarming rate. The live-oak dominant chenier forests of southeast Louisiana are amongst those exhibiting the steepest declines. The remnant stands have experienced numerous hurricanes and intense storm events in recent years, calling into question the current status and immediate future of this imperiled natural resource. Despite their noted ecological and physiographic importance, there is a lack within national geographic data repositories of accurate representations of forest loss and wetland extent for this region. Supervised machine learning algorithms in the Google Earth Engine were used to classify and process high-resolution National Agricultural Image Product (NAIP) datasets to create accurate (>90%) tree cover maps of the Louisiana Chenier Plains in Cameron and Vermilion Parishes. Data from three different years (2003, 2007, and 2019) were used to map 2302 km<sup>2</sup> along the southwestern coast of Louisiana. According to the analyses, there was a 35.73% loss of forest cover in this region between 2003 and 2019. A majority of the land-use change was from tree cover to saltmarsh, with losses in pastoral land also documented. We found variable rates of loss with respect to elevation. Forest cover losses corresponded strongly to rises in mean sea level. These findings deliver a baseline understanding of the rate of forest loss in this region, highlighting the reduction and potentially the eventual extirpation of this imperiled ecosystem. |
| first_indexed | 2024-03-09T03:24:31Z |
| format | Article |
| id | doaj.art-77e19469a0c642798394ed8c9d079a26 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-09T03:24:31Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-77e19469a0c642798394ed8c9d079a262023-12-03T15:04:22ZengMDPI AGForests1999-49072022-07-01137113210.3390/f13071132Loss of Relict Oak Forests along Coastal Louisiana: A Multiyear Analysis Using Google Earth EnginePaurava Thakore0Parusha Raut1Joydeep Bhattacharjee2Plant Ecology Lab, Department of Biology, University of Louisiana at Monroe, 700 University Avenue, Monroe, LA 71209, USADepartment of Computer Science, University of Louisiana at Monroe, 700 University Avenue, Monroe, LA 71209, USAPlant Ecology Lab, Department of Biology, University of Louisiana at Monroe, 700 University Avenue, Monroe, LA 71209, USACoastal forests along the southeastern Gulf of Mexico are known to be diminishing at an alarming rate. The live-oak dominant chenier forests of southeast Louisiana are amongst those exhibiting the steepest declines. The remnant stands have experienced numerous hurricanes and intense storm events in recent years, calling into question the current status and immediate future of this imperiled natural resource. Despite their noted ecological and physiographic importance, there is a lack within national geographic data repositories of accurate representations of forest loss and wetland extent for this region. Supervised machine learning algorithms in the Google Earth Engine were used to classify and process high-resolution National Agricultural Image Product (NAIP) datasets to create accurate (>90%) tree cover maps of the Louisiana Chenier Plains in Cameron and Vermilion Parishes. Data from three different years (2003, 2007, and 2019) were used to map 2302 km<sup>2</sup> along the southwestern coast of Louisiana. According to the analyses, there was a 35.73% loss of forest cover in this region between 2003 and 2019. A majority of the land-use change was from tree cover to saltmarsh, with losses in pastoral land also documented. We found variable rates of loss with respect to elevation. Forest cover losses corresponded strongly to rises in mean sea level. These findings deliver a baseline understanding of the rate of forest loss in this region, highlighting the reduction and potentially the eventual extirpation of this imperiled ecosystem.https://www.mdpi.com/1999-4907/13/7/1132Google Earth Enginevegetation declinecoastal forestsNAIPforest losslive oak |
| spellingShingle | Paurava Thakore Parusha Raut Joydeep Bhattacharjee Loss of Relict Oak Forests along Coastal Louisiana: A Multiyear Analysis Using Google Earth Engine Forests Google Earth Engine vegetation decline coastal forests NAIP forest loss live oak |
| title | Loss of Relict Oak Forests along Coastal Louisiana: A Multiyear Analysis Using Google Earth Engine |
| title_full | Loss of Relict Oak Forests along Coastal Louisiana: A Multiyear Analysis Using Google Earth Engine |
| title_fullStr | Loss of Relict Oak Forests along Coastal Louisiana: A Multiyear Analysis Using Google Earth Engine |
| title_full_unstemmed | Loss of Relict Oak Forests along Coastal Louisiana: A Multiyear Analysis Using Google Earth Engine |
| title_short | Loss of Relict Oak Forests along Coastal Louisiana: A Multiyear Analysis Using Google Earth Engine |
| title_sort | loss of relict oak forests along coastal louisiana a multiyear analysis using google earth engine |
| topic | Google Earth Engine vegetation decline coastal forests NAIP forest loss live oak |
| url | https://www.mdpi.com/1999-4907/13/7/1132 |
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