Assessment of the land and sea interaction by using different types of satellite data

Abstract

Seas are crucial for regulating climate conditions and supporting biodiversity, thereby sustaining environment, which is essential for life. Earth observation satellite images provide rich data sources, enabling long-term monitoring in a cost-effective and time-efficient manner. The Sea of Marmara (Türkiye), a semi-enclosed basin, stands out with its unique hydrodynamic and biogeochemical characteristics, having a significant role in the marine ecosystem. As the Sea of Marmara in Türkiye is surrounded by the densely populated provinces, the sea's water quality has increasingly become significant for both scientific scientific and public communities over the years. In the Sea of Marmara, marine mucilage, a viscous organic substance, has been observed in 2021. The presence of thick, different colored mucilage blankets raised public concern due to their potential toxicity and the pathogens, which can accumulate with prolonged mucilage presence. The outbreak of marine mucilage significantly impacted the marine ecosystem. Consequently, the presence of marine mucilage is a one of the indicators of water quality. While remote sensing data was used to identify mucilage-covered areas in the Sea of Marmara in other case studies previously, there is lack of study about determining the areal extents and spectral characteristics of the different colored mucilage types while examining the probable reasons by using remote sensing data and technologies. This study focuses on the mucilage phenomenon and its possible causes, such as increases in Sea Surface Temperature (SST) and changes in Land Use / Land Cover (LU/LC) in coastal cities along the sea. It aims to achieve three main objectives: (1) identifying different types of mucilage, (2) detecting SST trend and anomalies, and (3) observing changes in LU/LC by using different types of satellite data. Mucilage, which varies in type and form, includes three different types detected in İzmit Bay (the Sea of Marmara) using Sentinel-2 and Worldview-3 satellite images. These mucilage types are white mucilage, yellow mucilage, and brown mucilage. White mucilage, characterized by smaller aggregates and a high reflectance spectrum, especially between 600-900 nm, represents dispersed patterns. Yellow mucilage results from aged aggregates, influenced by wind and currents, representing accumulated mucilage. Brown mucilage, distinguished by a high organic matter concentration, represents densely accumulated ageing mucilage. The study leveraged the high spatial resolution of these satellites to analyze the areal extents and characteristics of these mucilage types, with Sentinel-2 providing an overview and Worldview-3 offering detailed information. Spectral analysis using GLCM method and the SVM classification method differentiated these types, revealing that yellow mucilage often surrounds white mucilage, showing dispersed patterns, while brown mucilage, mostly found along coastlines, is more accurately detected with Worldview-3 due to its higher spatial resolution. The ANOVA analysis revealed significant differences (P-value <0.05) among these three mucilage types. The accuracy assessment analysis of the classifications showed the detailed detection capabilities of the high-resolution Worldview-3 (Overall accuracy = 0.93) compared to Sentinel-2 (Overall accuracy = 0.86) for distinguishing mucilage distributions. Continuously monitoring SST and detecting anomalies play a critical role in assessing the water quality of the sea. One probable cause of the mucilage phenomenon is related to the increase in SST. Therefore, investigation of temporal and spatial variations in SST and detection of SST anomalies were conducted. The spatial variations of the Sea of Marmara's SST were examined in detail using Sentinel-3 and Landsat-8 satellite imagery. Sentinel-3's ability to capture the entire area in a single frame provides a significant advantage for recent year monitoring. Validation with Landsat-8 images provided consistent results, highlighting the detection of cold water influx from the Black Sea through the Istanbul Strait. However, the National Oceanic and Atmospheric Administration (NOAA) OISST V2 satellite's coarser resolution limited its effectiveness in distinguishing these spatial SST variations. To assess accuracy, SSTs derived from satellite data were compared against in-situ measurements, which were that were derived from Turkish State Meteorological Service, with RMSE and bias calculated for each dataset, confirming the suitability of all three satellite sources for SST monitoring in the Sea of Marmara. Additionally, a time-series analysis from 1990 to 2021, utilizing the NOAA CDR OISST v02r01 dataset on the GEE platform and applying the STL method, detected SST trend and anomalies, including an increase in SSTs, particularly in 2020, and approximately 2°C variations over 32 years. Anomalies, especially in recent years, were compared with the NOAA OISST V2 anomaly band, highlighting the critical role of STL method in eliminating trend effect from the residual component. Due to the dynamism of the highly urbanized coastal cities along the Sea of Marmara, especially the LU/LC changes between 2018 and 2021 are of great significance. This study evaluates the extent of LU/LC changes in coastal cities along the sea in the periods of 1990-2000, 2000-2006, 2006-2012, 2012-2018, 2018-2021 by using Coordination of Information on the Environment (CORINE) data and the overall inspection period of 1990-2021 by utilizing CORINE-based methodology and Sentinel-2 images. An increase of 95.21% is observed in the artificial surfaces. Water covered areas expanded by 14%, primarily driven by the construction of new surface water collection systems. Agricultural areas and orchards were successfully conserved. There has been a prominent increase of 4% in forest areas. However, there was a decline of 25% in open spaces, and 7% decrease in pastures and complex cultivation patterns. Furthermore, the findings provide a clear evidence of a 1762 ha expansion in the aforementioned cities' area between 1990 and 2021 was due to the construction of land reclamation areas along the Sea of Marmara coast. This research study highlights a practical methodology for monitoring land resources across extensive regions over a prolonged period. In conclusion, this dissertation provides a practical methodology for detecting, monitoring, and paying special attention to the areas that need more urgent mucilage cleaning. Furthermore, the factors that can cause the mucilage phenomenon were researched. A comprehensive SST analysis showed that there is an increasing SST trend between 1990 – 2021. Besides, the temporal LU/LC change in the coastal cities along the sea was also examined in the scope of the land/sea interaction and the increase in artificial surfaces was seen. In this study, the capabilities of different types of satellite data were leveraged to monitor the land and sea interaction, demonstrating its indispensable role of remote sensing data in providing accurate data for environmental sustainability.