Cloud-based satellite remote sensing for enhancing seagrass monitoring and ecosystem management

Abstract

We examined the feasibility of monitoring interannual and intra-annual changes in seagrass extent in Tampa Bay, Florida between 1987 and 2023 using remote sensing with the Landsat 5, Landsat 7, Landsat 8, and Sentinel-2 satellite sensor series. This study filled gaps and extended the time series developed for the period 1990–2021 by Lizcano-Sandoval et al. (2022). Seagrass extent was evaluated for six Tampa Bay segments: Hillsborough Bay (HB), Old Tampa Bay (OTB), Middle Tampa Bay (MTB), Lower Tampa Bay (LTB), Boca Ciega Bay (BCB), Manatee River + Terra Ceia Bay (MRTC). Results were compared with reference data from the biennial mapping program conducted by the Southwest Florida Water Management District (SWFWMD). Overall, seagrass showed long-term increases in extent in Tampa Bay. The highest increasing rates over 1987–2023 were observed in HB (+5.7 % yr⁻¹) and OTB (+3.5 % yr⁻¹). Smaller increases were observed in BCB (0.9 % yr⁻¹). However, in HB and MRTC seagrass extent showed decreases in particular years between 2015 and 2023 (34 % and 11 %, respectively), and in OTB between 2017 and 2023 (41 %). Intra-annual changes in seagrass extent were observed during 2021–2023. Intra-annual coefficient of variation was estimated to be as low as 3 % in BCB and as high as 60 % in HB. Seagrass extent estimated by remote sensing was highly correlated with the reference data (r > 0.74), except in the MRTC segment (r = -0.29). A Google Earth Engine app was developed to allow public access to the temporal and spatial changes of seagrass extent and distribution in Tampa Bay. The results showed that seagrass extent assessments to complement existing field and airborne seagrass monitoring programs are feasible at low cost with public satellite imagery in the cloud.