Abstract
The study area encompasses the largest remedial effort ever undertaken in oil-contaminated mangrove habitats (∼1000 ha) and includes planting of ∼2 million mangrove seedlings to initiate the restoration process. To establish a reference point for both the initial planting and long-term monitoring, and to investigate the longer-term effects of numerous oil spills, mangrove distribution (with minor quantities of nipa palm) was determined using 0.1 and 0.5 m resolution imagery from 2013 and from 2020, supported by numerous ground surveys and low-altitude overflights. A review of pre-spill mangrove location and elimination of pipeline and road corridors determined that 829 ha of former mangrove habitat was suitable for restorative planting.After testing each method, existing vegetation was classified using a supervised object-based classification method (Support Vector Machine) and mean shift segmentation, trained with ten manually classified plots of 1 ha and validated against seven additional plots. Initial classification errors occurred due to false positives caused by surface algae, which were manually removed. The accuracy assessment to determine overall mangrove cover (ha) and ability to encounter mangroves at a specific location within randomly selected 0.785 m2 circles increased to ≥95% within validation plots. In contrast to losses found in other areas of the Niger Delta, vegetation increased in the core area of study (15.6 ha–40.2 ha) but represented only 4.8% of the total 829 ha to be planted. To the west, a 10% vegetation gain was found; to the east where oil theft activities were common, there was a 16% loss. A comparison to a West Africa 20-m data set shows comparative values within 5%, with notable differences when reviewed in detail. Monitoring of the area as it is replanted is expected to continue to 2027 and will use these results as a comparison. This study serves as guidance for analysis and monitoring of future mangrove restorations in the Niger Delta.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Remote Sensing Applications: Society and Environment
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.