Abstract
Wetland ecosystems are being modified and threatened due to anthropogenic activities and climate change, hence the urgent need for wetland restoration. Wetland rehabilitation is important in the reversal of these dire conditions, and this can be pursued through restoring damaged wetland ecosystems and recovering wetland vegetation. Wetland biophysical properties such as leaf area index (LAI) are important indicators of vegetation productivity and stress. Therefore, the study sought to test the potential of Sentinel-2 multispectral instrument (MSI) derived standard bands, traditional vegetation indices and red-edge derived vegetation indices in estimating wetland vegetation LAI across natural and rehabilitated wetlands. Traditional field surveys were carried out for LAI measurement of wetland vegetation using the LAI-2200 Plant Canopy Analyser. Partial Least Squares Regression (PLSR) algorithms were used to compare the estimation strength of models derived from all Sentinel-2 MSI bands, conventional vegetation indices and red-edge derived vegetation indices. Leave-one-out cross-validation (LOOCV) was completed on a selected measured dataset to evaluate the performance and accuracy of the estimation models. The optimal models for estimating wetland vegetation LAI were produced based on red-edge bands centred between the 705–783 nm as well as the 865 nm (Band 8a) of the electromagnetic spectrum. The results showed that vegetation indices derived from red-edge bands performed better at estimating LAI for both wetlands with a root mean square error of prediction (RMSE) of 0.32 m2/m2 and R2 of 0.61 for the natural wetland, and RMSE of 0.51 m2/m2 and R2 of 0.75 for the rehabilitated wetland. The optimal model for predicting LAI across natural and rehabilitated wetlands was attained based on red-edge bands centred at 705 nm (Band 5), 740 nm (Band 6), 783 nm (Band 7) as well as 865 nm (Band 8a) yielding a RMSE of 0.51 m2/m2 and R2 of 0.54. Overall, the results underscore the importance of remotely sensed derived data and vegetation indices in the optimal characterisation of wetland vegetation productivity which can be utilized in the monitoring and management of wetland ecosystems.
Highlights
Wetlands are important ecosystems and play a significant role in regulating the health of the environment [1,2]
The leaf area index (LAI) measurements represent a variable distribution across the two types of wetlands, and a wide range of LAI measurements was recorded for the rehabilitated wetland (Figure 3)
The current study sought to investigate the ability of Sentinel-2 multispectral instrument (MSI) derived data and vegetation indices to estimate wetland vegetation LAI under different management regimes
Summary
Wetlands are important ecosystems and play a significant role in regulating the health of the environment [1,2]. Wetlands are responsible for maintaining environmental quality, micro-climate stabilisation, flood control, water infiltration and biodiversity support [1,3,4,5]. They provide an interface for terrestrial and wetland species interaction [2,6]. Hopkins et al [9], state that wetland degradation or loss could increase the net global carbon dioxide in the atmosphere, by up to 6% per year This challenge is compounded by the fact that currently there is a dearth of comprehensive frameworks and objective criteria for monitoring the health of these wetlands. Recent studies on wetland restoration have highlighted the importance of restoring degraded wetlands and the importance of monitoring and maintaining these wetlands [10,11,12]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
