International Journal of Applied Earth Observations and Geoinformation (Dec 2023)
Detection of large-scale Spartina alterniflora removal in coastal wetlands based on Sentinel-2 and Landsat 8 imagery on Google Earth Engine
Abstract
The invasion of Spartina alterniflora has posed significant threats to the ecosystem health and biodiversity in coastal wetlands in China. In recent years, China has enacted large-scale S. alterniflora removal projects. Accurate monitoring of the S. alterniflora removal dynamics is crucial for evaluating the effectiveness of the removal projects and coastal wetland management. In this study, we presented a novel method for automatic and rapid detection of S. alterniflora removal events and removal timing at large scale based on time series Sentinel-2 and Landsat 8 imagery on Google Earth Engine. The method first detected and reconstructed the tidal-inundation-related Normalized Difference Vegetation Index (NDVI) using a newly proposed Tide Gap Filling algorithm, aiming to alleviate the impact of tidal inundation on S. alterniflora removal detection; then, the potential removal period were extracted based on the reconstructed NDVI time series; finally, the removal event and the corresponding removal timing were identified and mapped within the potential removal period by considering the phenological characteristics of the undisturbed S. alterniflora. We took the Shandong Province in northern coastal China and Fujian Province in southern coastal China as our study areas, where large-scale S. alterniflora removal projects were carried out in 2021 and 2022, respectively. Accuracy assessment based on field surveys and high-spatial-resolution PlanetScope imagery showed that the method achieved good accuracies for removal detection, with overall accuracies of 88.89 % for Shandong and 81.33 % for Fujian, respectively. The mean absolute error day (MAED) between the detected removal timing and the reference removal timing was 6.77 days in Shandong and 13.75 days in Fujian. Both provinces have successfully implemented the S. alterniflora removal projects. In Shandong, 82.32 % (7,243.94 ha) of S. alterniflora were removed during July to December in 2021; in Fujian, 88.81 % (6,649.21 ha) of S. alterniflora were removed during July to December in 2022. We expect that the method has great potential to be applied at national scale to provide baseline data for coastal wetland restoration and management.
