The Interaction of Chlorophyll-a and Total Suspended Matter along the Western Semarang Bay, Indonesia, Based on Measurement and Retrieval of Sentinel 3

The Kendal Regency area is one of the areas on the northern coast of Central Java that has been experiencing rapid industrial development. The high human activity in this area will impact the quality of water in these surrounding areas and affect the fertility of the waters. The concentrations of chlorophyll-a (Chl-a) and total suspended matter (TSM) are major water quality parameters that can be retrieved using remotely sensed data. The retrieval satellite of the 3 OLCI chosen in this study has a 300 m spatial resolution. This study aimed to see the distribution and effect of total suspended matter (TSM) on chlorophyll-a based on measurement and retrieval of Sentinel 3 imagery using the linear regression method. The results show the chlorophyll-a distribution and the value from retrieval satellite are higher and occur over larger surface area compared to chlorophyll-a measurements. The linear regression model of chlorophyll-a by retrieval satellite imagery and measurement is y = 0.65x + 4.65 with R2 = 0.54. The presence of high amounts of suspended solids in the waters causes disturbances in the reflectance values, which are recorded by the retrieval of satellite. The model regression chlorophyll-a with TSM accuracy from retrieval satellite results in the equation y = -0.0416x + 5.14 (R2 = 0.45, p = 0.05, n = 13). The determination (R2) coefficient value is 0.445, which means that suspended solids have a 44.5% effect on chlorophyll-a and 55.5% is influenced by other factors and not examined in this study. The results show that TSM has an influence on the accuracy of chlorophyll-a and retrieval satellite recording can be disrupted if waters have high turbidity.

[1]  R. Setiawan,et al.  Phytoplankton Chlorophyll-a Biomass and the Relationship with Water Quality in Barrang Caddi, Spermonde, Indonesia , 2022, Ecological Engineering & Environmental Technology.

[2]  P. V. Nagamani,et al.  Assessment of chlorophyll-a retrieval algorithms over Kakinada and Yanam turbid coastal waters along east coast of India using Sentinel-3A OLCI and Sentinel-2A MSI sensors , 2021, Remote Sensing Applications: Society and Environment.

[3]  Sri Yulina Wulandari,et al.  Sebaran Spasial dan Temporal Klorofil-a di Perairan Teluk Semarang , 2021, Indonesian Journal of Oceanography.

[4]  K. Topouzelis,et al.  Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data , 2021 .

[5]  R. Setiawan,et al.  Estimation of Chlorophyll a Phytoplankton in the Coastal Waters of Semarang and Jepara for Monitoring the Eutrophication Process using MODIS-Aqua Imagery and Conventional Methods , 2021 .

[6]  Luca Brocca,et al.  River Flow Monitoring by Sentinel-3 OLCI and MODIS: Comparison and Combination , 2020, Remote. Sens..

[7]  Jun Chen,et al.  An Improved Model for Chlorophyll-a Concentration Retrieval in Coastal Waters Based on UAV-Borne Hyperspectral Imagery: A Case Study in Qingdao, China , 2020, Water.

[8]  A. Newton,et al.  The Globalization of Cultural Eutrophication in the Coastal Ocean: Causes and Consequences , 2020, Frontiers in Marine Science.

[9]  C. Brockmann,et al.  Inorganic suspended matter as an indicator of terrestrial influence in Baltic Sea coastal areas — Algorithm development and validation, and ecological relevance , 2020 .

[10]  D. Swain,et al.  Estimation of Chlorophyll-a in Northern Coastal Bay of Bengal Using Landsat-8 OLI and Sentinel-2 MSI Sensors , 2019, Front. Mar. Sci..

[11]  A. Melesse,et al.  Satellite Estimation of Chlorophyll-a Using Moderate Resolution Imaging Spectroradiometer (MODIS) Sensor in Shallow Coastal Water Bodies: Validation and Improvement , 2019, Water.

[12]  Fernanda Sayuri Yoshino Watanabe,et al.  High performance of chlorophyll- a prediction algorithms based on simulated OLCI Sentinel-3A bands in cyanobacteria-dominated inland waters , 2018, Advances in Space Research.

[13]  L. Maslukah,et al.  Chlorophyll-a Distribution and Its Relation with Current Pattern in Northern Waters of Central Java , 2018, Omni-Akuatika.

[14]  Muslim,et al.  Effect of ENSO on the variability of SST and Chlorophyll-a in Java Sea , 2018 .

[15]  S. Subiyanto.  Remote Sensing and Water Quality Indicators in the West Flood Canal Semarang City: Spatio-temporal Structures of Lansat-8 Derived Chlorophyll-a and Total Suspended Solids , 2017 .

[16]  Tiit Kutser,et al.  Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument imagery in the Baltic Sea , 2017, Remote. Sens..

[17]  Xinyan Fan,et al.  Retrieval of Chlorophyll-a and Total Suspended Solids Using Iterative Stepwise Elimination Partial Least Squares (ISE-PLS) Regression Based on Field Hyperspectral Measurements in Irrigation Ponds in Higashihiroshima, Japan , 2017, Remote. Sens..

[18]  André B. Couto,et al.  Which ocean colour algorithm for MERIS in North West European waters , 2017 .

[19]  T. Sidabutar.  The abundance of phytoplankton and its relationship to the N/P ratio in Jakarta Bay, Indonesia , 2016 .

[20]  Andrea Taramelli,et al.  Total Suspended Matter (TSM) and Maximum Signal Depth (Z90_max) for Monitoring the Evolution of Sediment Resuspension Process in Shallow Coastal Environments , 2015 .

[21]  H. Paerl,et al.  Evolving Paradigms and Challenges in Estuarine and Coastal Eutrophication Dynamics in a Culturally and Climatically Stressed World , 2014, Estuaries and Coasts.

[22]  V. Siregar,et al.  PRIMARY PRODUCTIVITY OF JAKARTA BAY IN A CHANGING ENVIRONMENT: ANTHROPOGENIC AND CLIMATE CHANGE IMPACTS , 2013 .

[23]  R. Doerffer,et al.  The MERIS Case 2 water algorithm , 2007 .

[24]  Timothy R. Parsons,et al.  A manual of chemical and biological methods for seawater analysis , 1984 .

[25]  H. Effendi,et al.  The Horizontal Distribution Clorophyll-a Fitoplankton as Indicator of the Tropic State in Waters of Meulaboh Bay , West Aceh ) , 2022 .