Land Reclamation in the Mississippi River Delta

Driven by the need to expand urban/industrial complexes, and/or mitigate anticipated environmental impacts (e.g., tropical storms), many coastal countries have long implemented large-scale land reclamation initiatives. Some areas, like coastal Louisiana, USA, have relied heavily on restoration activities (i.e., beneficial use of dredged material) to counter extensive long-term wetland loss. Despite these prolonged engagements, the quantifiable benefits of these activities have lacked comprehensive documentation. Therefore, this study leveraged remote sensing data and advanced machine learning techniques to enhance the classification and evaluation of restoration efficacy within the wetlands adjacent to the Mississippi River’s Southwest Pass (SWP). By utilizing air- and space-borne imagery, land and water data were extracted and used to compare land cover changes during two distinct restoration periods (1978 to 2008 and 2008 to 2020) to historical trends. The classification methods employed achieved an overall accuracy of 85% with a Cohen’s kappa value of 0.82, demonstrating substantial agreement beyond random chance. To further assess the success of the SWP reclamation efforts in a global context, broad-based land cover data were generated using biennial air- and space-borne imagery. Results show that restoration activities along SWP have resulted in a significant recovery of degraded wetlands, accounting for approximately a 30 km2 increase in land area, ranking among the most successful land reclamation projects in the world. The findings from this study highlight beneficial use of dredged material as a critical component in large-scale, recurring restoration activities aimed at mitigating degradation in coastal landscapes. The integration of remote sensing and machine learning methodologies provides a robust framework for monitoring and evaluating restoration projects, offering valuable insights into the optimization of ecosystem services. Overall, the research advocates for a holistic approach to coastal restoration, emphasizing the need for continuous innovation and adaptation in restoration practices to address the dynamic challenges faced by coastal ecosystems globally.

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Publication Details

Journal
Remote Sensing
Published
2025-03-01
DOI
https://doi.org/10.3390/rs17050878
Citations
2
Primary Topic
American Environmental and Regional History
Type
article
Field-Weighted Citation Impact
4.84
Controls
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article

Land Reclamation in the Mississippi River Delta

Christina Saltus, Glenn Suir, Jeffrey Corbino
2 citations
Remote Sensing
American Environmental and Regional History
4.84
article

Land Reclamation in the Mississippi River Delta

Christina Saltus, Glenn Suir, Jeffrey Corbino
article en
2 citations

Abstract

Driven by the need to expand urban/industrial complexes, and/or mitigate anticipated environmental impacts (e.g., tropical storms), many coastal countries have long implemented large-scale land reclamation initiatives. Some areas, like coastal Louisiana, USA, have relied heavily on restoration activities (i.e., beneficial use of dredged material) to counter extensive long-term wetland loss. Despite these prolonged engagements, the quantifiable benefits of these activities have lacked comprehensive documentation. Therefore, this study leveraged remote sensing data and advanced machine learning techniques to enhance the classification and evaluation of restoration efficacy within the wetlands adjacent to the Mississippi River’s Southwest Pass (SWP). By utilizing air- and space-borne imagery, land and water data were extracted and used to compare land cover changes during two distinct restoration periods (1978 to 2008 and 2008 to 2020) to historical trends. The classification methods employed achieved an overall accuracy of 85% with a Cohen’s kappa value of 0.82, demonstrating substantial agreement beyond random chance. To further assess the success of the SWP reclamation efforts in a global context, broad-based land cover data were generated using biennial air- and space-borne imagery. Results show that restoration activities along SWP have resulted in a significant recovery of degraded wetlands, accounting for approximately a 30 km2 increase in land area, ranking among the most successful land reclamation projects in the world. The findings from this study highlight beneficial use of dredged material as a critical component in large-scale, recurring restoration activities aimed at mitigating degradation in coastal landscapes. The integration of remote sensing and machine learning methodologies provides a robust framework for monitoring and evaluating restoration projects, offering valuable insights into the optimization of ecosystem services. Overall, the research advocates for a holistic approach to coastal restoration, emphasizing the need for continuous innovation and adaptation in restoration practices to address the dynamic challenges faced by coastal ecosystems globally.

Remote SensingVol. 17(5)
United States Army Corps of Engineers (US), GDA (United States) (US), Environmental Technologies (United States) (US)
Openalex Percentile: Top 7%
American Environmental and Regional History
4.84
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