Spatiotemporal Change of Chl-a Concentration in Jakarta Bay using Sentinel-2 Multispectral Imageries

Abstract

Abstract Jakarta Bay is the estuary of 13 rivers that flows through Jakarta Metropolitan areas. Consequently, nutrients and pollutants accumulate in Jakarta Bay and lead to eutrophication. Therefore, monitoring the water quality of Jakarta Bay is essential to support integrated river coastal management. Chlorophyll a (Chl-a) concentration is one of the essential parameters in describing water environment conditions. For large and dynamic areas, Chl-a concentration distribution monitoring requires multi-temporal remote sensing data. This study examines remote sensing data and methods combined with on-site measurement to get more accurate and effective Chl-a spatiotemporal analysis approaches. We estimate Chl-a concentration of Jakarta Bay during 2016-2021 using selected Sentinel-2A and Sentinel-2B images. We conducted an atmospheric correction using a C2RCC (Case 2 Regional Coast Colour) processor and obtained Chl-a concentration from the embedded Neural Network model. The results showed that the model could retrieve Chl-a concentration with an R2 of 0.79 and the root mean square error of 31.75 mg/m3. Time-series results reveal an increase of maximum Chl-a concentration during 2016-2021. Our remotely sensed estimation results well-captured the change of temporal and spatial of Chl- a concentration in the Jakarta Bay. It provides the public and policymakers valuable information to support integrated river coastal sustainable management of Jakarta Metropolitan