Spatiotemporal Variation in Mangrove Chlorophyll Concentration using Remote Sensing Technique

Introduction/Purpose

Mangrove ecosystems play a crucial role in coastal environments, serving as a vital habitat for various species and providing numerous ecosystem services. Understanding their dynamics and health is imperative for informed conservation and management efforts (Kuenzer et al., 2011). In this study, we utilized Landsat imagery to monitor changes in mangrove cover over a 28-year period (1992-2020) and established a statistical relationship between remotely sensed vegetation indices and ground-based chlorophyll measurements to estimate chlorophyll concentration in Al Khor, Qatar.

Methods

Mangrove cover assessment was performed using Normalized Difference Vegetation Index (NDVI) to extract mangrove cover from Landsat images acquired in 1992, 2002, 2013, and 2020. To estimate chlorophyll concentration through remote sensing, we compared Landsat 8 bands and broadband indices with ground-based chlorophyll measurements. Ground measurements were obtained using both an optical method (chlorophyll meter) and a chemical method (acetone extraction).

Results

Mangrove extraction results indicated a steady increase in mangrove area over the years: 1992 (0.338 ha), 2002 (255.008 ha), 2013 (429.120 ha), and 2020 (642.956 ha). Statistical analysis revealed that the Simple Ratio Index demonstrated the highest correlation with chlorophyll concentration measured through the chemical method (R2=0.5292, p value = 0.0048). Further validation using Leave-One-Out-Cross-Validation (LOOCV) yielded a high coefficient of determination (R2=0.785) and a low Root Mean Square Error (RMSE = 3.332 × 10-8 microgram/cm2). These results confirm that the chemical method exhibited a robust relationship with Landsat 8 vegetation indices, making it a superior choice for chlorophyll estimation.

Discussion

Our findings highlight the effectiveness of Landsat imagery for monitoring mangrove cover dynamics over the study period. The linear increase in mangrove area signifies the importance of ongoing conservation efforts in Al Khor. The superior performance of the chemical method in establishing a statistical relationship with Landsat-derived vegetation indices underscores its reliability in estimating chlorophyll concentration. This methodology can be further extended tocreate spatial maps of chlorophyll concentration, aiding in the assessment of ecosystem health and assisting conservation and management initiatives in the region.

Conclusion

This study showcases the potential of Landsat imagery for assessing mangrove cover changes and estimating chlorophyll concentration in coastal environments. The findings emphasize the critical importance of monitoring and conserving mangrove ecosystems, especially in the context of climate change and habitat loss. By combining remote sensing techniques with ground-based measurements, we have established a robust methodology for estimating chlorophyll concentration, which can be applied in broader ecological studies and management strategies in Al Khor and similar coastal regions.