Distribution Of Chlorophyll-a Research Articles

Determining Seasonal Spatial and Temporal Distribution of Chlorophyll-a, and its Concentration in Kuwait and the Arabian Gulf using Satellite and In-situ Data

As an indicator of phytoplankton density in an area, the concentration of chlorophyll-a (Chl-a) is an important reflection of marine water quality. Remote sensing techniques have been developed to measure the near-surface concentration of Chl-a in water by combining spectral bands and in situ data. This algorithm can be applied to sensors of varying spatial, temporal and spectral resolutions. However, in this study, Chl-a level 2 and 3 products of SNPP – VIIRS spectrometer (Equation OC3) from NASA’s OceanColor suite were relied upon to establish the spatial and temporal distribution of Chl-a concentration in the Arabian Gulf (also known as the Persian Gulf) and the territorial waters of the State of Kuwait (located in the north-eastern part of the Arabian Gulf) in 2012-2019. Ground truthing points (n = 192) matched with level 2 products have been used to build and cross-validate an empirical model. The correlation was positive, with r^2 = 0.79 and validation RMSE = ± 0.64 mg/m-3. The derived algorithm was then applied to Chl-a level 3 seasonal products. Additionally, the Chl-a concentration values in Kuwaiti waters were enhanced using the IDW algorithm to increase spatial resolution, given its small size compared to the spatial resolution of level 3 Chl-a products. The model derived from IDW was tested using the Mann Whitney test (Sig = 0.948 p > 0.01). However, the result showed that Chl-a concentration was higher in the Kuwait Bay (average = 2.8 mg/m-3) than in Kuwaiti waters (average = 2.3 mg/m-3), and higher in Kuwaiti waters (average = 2.1 mg/m-3) than in the Arabian Gulf (average = 0.7 mg/m-3). Coasts have higher concentrations than open water. Generally, the Chl-a increases in winter and had a semi-regular cycle during the years of study; this cycle is more regular in the Gulf than in Kuwait.

Response of Upwelling Parameter Before, During, and After Tropical Cyclone (Case Study: Tropical Cyclone Marcus)

Tropical cyclones (TC) can cause damage when they are on the land surface, but on the other hand TC contribute to ocean productivity through upwelling or downwelling when they pass through the ocean. Information of the location and timing of upwelling and downwelling is important for fishing - activities estimation. High chlorophyll-a concentrations and low sea surface temperatures are proxies for upwelling events in the ocean. This study aims to investigate the effects of the TC Marcus on the chlorophyll-a distribution in the Timor Sea using a combination of remotely sensed data from Aqua MODIS chlorophyll-a and ocean-atmosphere reanalysis outputs. The results showed that wind speed, sea surface temperature, salinity, and ocean currents were increased during the TC Marcus event. Spatial analysis reveals that the concentration of chlorophyll-a is high in the waters of the Timor Sea, at coordinates around 12°–13° S and 125°–129° E. High chlorophyll-a concentrations occurred before and after TC Marcus event, according to temporal analysis. The distribution of chlorophyll-a concentrations decreased on March 17–24, 2018, during the occurrence of the TC Marcus in the Timor Sea.

POST-EL-NIÑO WEAKENING OF COASTAL UPWELLING AND ITS ECOLOGICAL IMPACTS IN THE SOUTH-CENTRAL VIET NAM REGION

Upwelling that occurs in the summer offshore of South-Central Viet Nam in the South China Sea (SCS) also known as the East Viet Nam Sea (EVS), is one of the region’s key dynamic processes. The weakening of upwelling phenomena during post-El-Niño events and their ecological responses were studied based on a reanalysis dataset derived from the HYCOM/NCODA system, coupled with a local Finite Element Model (FEM) and observed data. Long-term warming, along with orographic and wind factors, play significant roles in the formation and weakening of upwelling phenomena during normal and post-El-Niño episodes, respectively. The weakening of upwelling during post-El-Niño periods is reflected by: Extreme weakening of wind forcing and Ekman pumping; a northward shift of the cold-saline tongue and current dipole, with a limited eastward extent; dominance of northward circulation in the surface layer and westward circulation in deeper layers; and the formation of a homogeneous surface thermohaline layer of about 50 meters thick, with a thermo-halocline layer at 50-60 meters depth. These abrupt changes strongly influenced the ecological characteristics of the upwelling area. Coral bleaching during the summers of 2010 and 2016, as well as anomalous distributions of chlorophyll-a (Chl-a) in the surface layer in 1998, 2003, 2010, and 2016, were concrete indicators of the ecological responses of Viet Nam's coastal upwelling waters in post-El-Niño years. Detailed intra-seasonal variations of temperature during the summer showed a warming of the waters, leading to coral bleaching and abnormal Chl-a levels during post-El-Niño years. Organisms in this region struggled to adapt to these rapid environmental changes, leading to a potential reduction in living resources.

Monthly variability of wind-induced upwelling and its impact on chlorophyll-a distribution in the Southern and Northern parts of the Indonesian Archipelago

Monthly variability of wind-induced upwelling and its impact on chlorophyll-a distribution in the Southern and Northern parts of the Indonesian Archipelago

A Study of the Analysis of Chlorophyll-a Phytoplankton in the Tigris Rivers for Some Regions of Iraq by Using GIS Techniques

In this study, the distribution of chlorophyll-a for phytoplankton was monitored using Geographic Information System (GIS) techniques in selected regions of Iraq represented by the three governorates namely: Salah al-Din (Samarra (1), Baghdad (Al-Muthanna Bridge (2), Al-Utaifi (3), Al-Jadiriya(4), Kut (Al-Aziziyah (5), Al-Zubaydah (6), Al-Numaniyah (7), and Al-Muftah (8)) as human agricultural, and industrial activity rose in these locations. These stations, which are located along the Tigris River, were used as sites for collecting samples. The selection procedure was conducted on a monthly basis between February 2022 and January 2023. Chlorophyll-a measurements for phytoplankton throughout the sampling period varied from 3.7 to 2.59 g/L at stations. The two stations (Al-Utaifi and Al-Zubaydah) had similar values for both seasons, and the five stations in the dry season had values of less than 0.23 g/L. While phytoplankton numbers varied from 40.32 104 to 21.16 104cell/L for stations 3 and 5, respectively, they varied from 72.39 104 to 37.7 104cell/L for stations 6 and 8, respectively, throughout the wet season. In all of the stations and classes of phytoplankton, the amount of chlorophyll dye was approximately equal to the overall density of phytoplankton. The area under study’s predictive maps of chlorophyll-a analysis also revealed changes in the concentration of dye in all stations.

From Do-It-Yourself Design to Discovery: A Comprehensive Approach to Hyperspectral Imaging from Drones

This paper presents an innovative, holistic, and comprehensive approach to drone-based imaging spectroscopy based on a small, cost-effective, and lightweight Unmanned Aerial Vehicle (UAV) payload intended for remote sensing applications. The payload comprises a push-broom imaging spectrometer built in-house with readily available Commercial Off-The-Shelf (COTS) components. This approach encompasses the entire process related to drone-based imaging spectroscopy, ranging from payload design, field operation, and data processing to the extraction of scientific data products from the collected data. This work focuses on generating directly georeferenced imaging spectroscopy datacubes using a Do-It-Yourself (DIY) imaging spectrometer, which is based on COTS components and freely available software and methods. The goal is to generate a remote sensing reflectance datacube that is suitable for retrieving chlorophyll-A (Chl-A) distributions as well as other properties of the ocean spectra. Direct georeferencing accuracy is determined by comparing landmarks in the directly georeferenced datacube to their true location. The quality of the remote sensing reflectance datacube is investigated by comparing the Chl-A distribution on various days with in situ measurements and satellite data products.

Study of Chlorophyl-A Variability in Bone Bay Waters During High Wave Events

Research has been carried out on the distribution of chlorophyll-a in the waters of Bone Bay during high wave events based on the parameters of sea surface temperature, wind speed and ocean currents. The aim of this research is to analyze parameters related to high waves which influence chlorophyll-a concentrations in the waters of Bone Bay. Chlorophyll-a patterns in Bone Bay waters were studied based on Aqua MODIS satellite data for chlorophyll-a data and ECMWF for wind speed, sea surface temperature and ocean current data. The average value was determined using Aqua MODIS and ECMWF satellite data for 10 years from 2011 to 2020. These parameters were analyzed to determine the correlation with chlorophyll-a. The calculation results show that sea surface temperature and wind speed decreased after high waves, while ocean currents and chlorophyll-a increased after high waves in Bone Bay waters. The correlation between chlorophyll-a and wind speed is 0.15, with sea surface temperature -0.44, and with ocean currents -0.26. Spatially, high concentrations of chlorophyll-a are found in the coastal waters of the South Sulawesi region with chlorophyll-a concentrations reaching 0.4-5 mg/m3. Temporally, high chlorophyll-a concentrations occur after high wave events with an average chlorophyll-a concentration of 0.32 mg/m3.

Distribution of methane in the upper water layer of the northern Black Sea: Seasonal and daily trends and seawater-air emissions

We report on methane (CH4) concentration measurements in the northern Black Sea area conducted during 6 cruises with R/V Professor Vodyanitsky from 2017 to 2019. Our work is a multi-season study at a uniform station grid covering an area of 88 × 103 km2 and including three latitudinal transects that comprises both surface and vertical profile water-column measurements. The main goal of the work was to assess the seasonal patterns of vertical CH4 structure in the aerobic water column (upper 100 m) and its emission to the atmosphere.In surface waters, the mean dissolved CH4 concentration ranged from 2.6 nmol L−1 detected in November 2018 to 11.5 nmol L−1 measured in June–July 2018, respectively. Calculated CH4 seawater-air fluxes and saturations were mostly positive (i.e. net flux to atmosphere), and winter fluxes (2.6 μmol m−2 d−1) were higher than summer fluxes (1.6 μmol m−2 d−1) due to the higher wind speed. The integral CH4 flux from the whole study area (88 × 103 km2) ranged from 84 to 235 kM day−1.It was shown that, on average, the methane concentration in the upper layer for deep-water stations where the seabed is located at depths >160 m (σt >16.2) was lower compared to stations at shallow water depths (28–140 m, σt <16.2). The most distinct difference was obtained for the summer season (June–July 2018) and a less significant difference – for spring (April–May 2019) and winter season (November–December 2018). During these seasons the water column was also considerably less saturated in CH4 compared to the entire monitoring period. We observed subsurface maxima, which were generally located at the base of the thermocline and exceeded 100 nmol L−1 at some stations. Exceptions were observed in October 2019 (cruise 110), when vertical CH4 distributions were characterized by two-peaks at ∼20 and ∼50 m depth. The strong influence of the thermohaline structure on the water column CH4 distribution has also been shown in studies of daily dynamics of CH4 vertical profiles in the shallow water region. Despite the high variability of CH4 concentrations, significant similarities in vertical distributions of CH4 and chlorophyll-a for which sub-surface maxima coincided at some stations, are shown. Extremely high concentrations of CH4 (up to 351 nmol L−1) in the near-bottom water layer were revealed during all seasons at the station near the Dnieper paleo-channel at the northwestern edge of the study area. This enrichment is assumed to be caused by methane emissions from gas seeps densely located in this region.

Characteristics and Distribution of Chemical-Biological Parameters in The Seawaters of Eastern Java Sea

The Java Sea is influenced by the west and east monsoons, which have an impact on hydrodynamic processes and chemical-biological water quality. Chemical-biological parameters play an important role in the food chain cycle that occurs in these waters. The quality of the eastern Java Sea waters is still limited by chemical-biological parameters, so the characteristics and distribution of these waters can be comprehensively known. chemical-biological. This study aimed to analyze the characteristics and distribution of nitrate, phosphate, oxygen, chlorophyll-A, and NPP parameters in the eastern Java Sea waters. This study used secondary data with daily temporal resolution from January to December 2020. Spatial analysis uses the climatological averaging method for 6 months as a statistical representative of the west monsoon and east monsoon. For each parameter, a vertical analysis was conducted to compare parameter values between the coastal waters of Tuban, Java Sea, and Banjarmasin Waters. Correlation analysis between parameters was conducted using the Pearson correlation method. Nitrate, phosphate, oxygen, chlorophyll-A, and NPP concentrations have temporal and spatial variability. Monsoon factors in Indonesia have a strong influence on the variability of nitrate, phosphate, oxygen, chlorophyll- A, and NPP concentrations. During the east monsoon, the concentration of chemical-biological parameters decreases, while in the west monsoon, the concentration increases and reaches its highest value. Generally, high concentrations occur in the northern and southern parts of the study site, around the coastal areas of Java and Kalimantan. Key Word: Chemical-Biological Parameters, Java Sea, Tuban Waters

Response of the phytoplankton size fractions along environmental gradients from an oxygen minimum zone in the central Mexican Pacific

The marine phytoplankton community responds to latitudinal, longitudinal (coast to ocean), and vertical environmental gradients, an important subject in Oxygen minimum zones (OMZ). The phytoplankton structure and the effect of environmental gradients along the central Mexican Pacific, an area within an OMZ, were studied, especially the importance of size fractions and taxonomic groups. A combination of various methods and protocols, such as microscopic analysis, flow cytometer, and pigment analysis, were followed in this study. Oceanographic conditions included thermal gradients along the study area and unreported evidence of a weak upwelling in the southern zone (Acapulco). Vertical distribution of chlorophyll a showed subsurface maxima (SCM, 15-45 m depth) in all stations, and deeper chlorophyll-a maxima (DCM, 85-95 m depth) in more oceanic stations. Chain-forming diatoms dominated in the northern zone stations. Prochlorococcus, Synechococcus, and picoeukaryotes abundances ranged between 0.01 to 21.7 cells×104 mL-1, although most samples showed the highest contribution to biomass (47.95 μg C L-1) by picoeukaryotes. Expected tendencies of Prochlorococcus distribution were observed: highest densities coincided with the DCM and divinyl chlorophyll-a distribution at oceanic stations. Fucoxanthin had the highest concentrations, whereas fucoxanthin and zeaxanthin concentrations were higher at SCM depths. We documented the co-dominance of the pico- and microplankton: picoplankton was important at the DCM, related to oligotrophic and more stratified water column, whereas microplankton prevailed in coastal stations, with mixed water column, high nutrient concentrations, and diatoms as the dominant group. Picoeukaryotes abundances were related to the concentration of prasinoxanthin, which suggests an important mamiellophyte component not previously revealed.

Predicting the temporal-spatial distribution of chlorophyll-a in the Yellow River estuary using explainable machine learning

The water quality in estuaries is influenced by both physical and biochemical processes, making it difficult to identify and quantify the main controlling factors of chlorophyll-a (Chl-a) concentration. This study introduces an interpretable machine learning approach to identify and quantify the dominant control factors determining Chl-a concentration in the Yellow River Estuary (YRE). The model utilizes in situ data and MODIS data in the Yellow River Estuary, incorporating five key variables: salinity, water depth, turbidity, dissolved inorganic nitrogen (DIN), and soluble reactive phosphorus (SRP). Three types of inputs are used to predict Chl-a, including physical, biogeochemical, and physical-biogeochemical factors. The model further uses feature importance ranking and partial dependence plot to identify and quantify key control factors. The results reveal that (1) Chl-a variation is influenced by multiple factors, especially salinity and turbidity; (2) Chl-a concentration is inhibited when salinity is below 26, turbidity is lower than 16 NTU and above 30 NTU, DIN is lower than 0.314 mg/L and SRP is below 0.01 mg/L; (3) riverine inputs change turbidity and salinity in the Yellow River Estuary and Laizhou Bay, in response to temporal-spatial distributions of phytoplankton. This research can provide a valuable reference for water quality management in the Yellow River Estuary.

Study of upwelling and mixing process in the Somali coastal region using satellite and numerical model observations: A Lagrangian approach

During the summer monsoon, the Somali region undergoes a significant upwelling phenomenon that enhances plankton productivity, thereby benefiting fisheries. Wind and coastal dynamics initially drive this upwelling, but eventually, eddy flows influence it. Our study explores the interplay between ocean currents, eddies, and chlorophyll-a concentrations using the backward Finite-Size Lyapunov Exponents (bFSLEs) technique. We also delve into the specific role of Ekman transport in distributing chlorophyll-a across the region. The Great Whirl (GW), an anticyclonic eddy, predominantly causes strong downwelling, interrupting the summer monsoon upwelling along the Somali coast longitudinally. Despite the GW's significant impact on moving upwelled water offshore, the influence of downwelling diminishes northward. As a result, the northern Somali coast, especially around 9°N and 10°N, showcases the most extensive offshore upwelling, reaching as far as 55°E. Our findings highlight a robust connection between chlorophyll-a levels and oceanic dynamics, influenced by both currents and eddies, as evidenced by bFSLEs, and by cross-shore Ekman transport, particularly within chlorophyll-a concentrations ranging from 0.2 to 0.6 mg m−3. The data suggests that Ekman transport-induced upwelling primarily drives coastal phytoplankton biomass. Furthermore, bFSLEs analysis underlines the supportive role of ocean currents and eddies in the offshore distribution of chlorophyll-a, especially near the coast. Further examination of lagged correlations reveals a temporal lag between peak concentrations of chlorophyll-a and Ekman transport; the lag increases offshore and is at least 9 days near the coast.

Long‐Term Trends in the Distribution of Ocean Chlorophyll

AbstractThe concentration of chlorophyll‐a (CHL) is an important proxy for autotrophic biomass and primary production in the ocean. Quantifying trends and variability in CHL are essential to understanding how marine ecosystems are affected by climate change. Previous analyses have focused on assessing trends in CHL mean, but little is known about observed changes in CHL extremes and variance. Here we apply a quantile regression model to detect trends in CHL distribution over the period of 1997–2022 for several quantiles. We find that the magnitude of trends in upper quantiles of global CHL (&gt;90th) are larger than those in lower quantiles (≤50th) and in the mean, suggesting a growing asymmetry in CHL distribution. On a regional scale, trends in different quantiles are statistically significant at high latitude, equatorial, and oligotrophic regions. Assessing changes in CHL distribution has potential to yield a more comprehensive understanding of climate change impacts on CHL.

Analysis of Chlorophyll-a Variability in the Eastern Indonesian Waters Using Sentinel-3 OLCI from 2020-2021

The Eastern Indonesian waters are significant in influencing the global climate system and oceanic connectivity. However, the Indonesian Through Flow (ITF) facilitates the movement of waters from the Pacific Ocean to the Indian Ocean. This flow vertically mixes water masses in the Eastern regions, leading to the concentration of phytoplankton. In addition, the distribution of phytoplankton, indicative of chlorophyll-a concentration, is influenced by upwelling and downwelling phenomena. Chlorophyll-a, responsible for capturing carbon and producing oxygen in marine ecosystems, is important in regulating climate change. Moreover, oceanographic conditions play a significant role in the dispersion of chlorophyll-a concentration. Therefore, this study adopted ocean colour remote sensing technology to assess chlorophyll-a distribution. Monthly ocean colour data was collected by the multi-temporal Sentinel-3 Ocean and Land Colour Instrument (OLCI). The analysis output included chlorophyll-a concentration associated with currents and the El Nino Southern Oscillation (ENSO). Data processing using the Case-2 Regional Coast Colour (C2RCC) processor resulted in an average chlorophyll-a concentration in the Eastern Indonesian waters ranging from 0.16 to 0.52. The results showed higher chlorophyll-a levels during the southeast monsoon (July to September) and lower levels during the northwest monsoon (January to March).

Vertical and Horizontal Variability of Chlorophyll-a and Its Relationship with Environmental Parameters in the Waters of Sangihe and Talaud Islands, North Sulawesi, Indonesia

The chlorophyll-a is an important biological parameter that could act as a proxy to indicate the abundance of phytoplankton and the primary productivity of an aquatic ecosystem. This paper investigates the vertical and horizontal variability of chlorophyll-a in the waters of Sangihe and Talaud Islands, Indonesia, and its correlation with water environmental parameters. In this study, the distribution of chlorophyll-a, temperature, salinity, and nutrients (NO3 and PO4) from the surface to a depth of 200 m (photic zone) was measured at 29 research stations. The results showed that the distribution of chlorophyll-a in the waters of the Sangihe-Talaud Islands was varied vertically and horizontally. The waters around the Sangihe Islands generally exhibited a higher chlorophyll-a distribution and shallower Deep Chlorophyll Maxima compared to the water around the Talaud Islands. The concentration of chlorophyll-a varied between 0.0017 and 1.2155 mg.m-3, with most of the water column in Sangihe-Talaud considered oligotrophic, although some stations or depths were mesotrophic or slightly eutrophic. The maximum chlorophyll-a concentration was found in the sub-surface layer at depths between 46 and 101 m. The low N:P ratio (&lt;16) and N:Si ratio (&lt;1) indicate that the water columns of Sangihe-Talaud, up to a depth of 200m, were N-limited. Based on the GAM analysis, chlorophyll-a concentration in Sangihe-Talaud waters was primarily regulated by temperature, salinity, and the N:P ratio, with weak influence from phosphate and the N:Si ratio. The analysis also suggests that primary productivity in Sangihe-Talaud is sensitive to temperature changes, indicating its vulnerability to future warming events.

Vertical distribution patterns of chlorophyll-a during autumn in a coastal environment inside the Gulf of California

An evaluation of the vertical distribution of chlorophyll-a (Chl-a) levels, as an indicator of phytoplankton biomass, has strong repercussions in any marine ecosystem since it allows evaluating its productive potential and the amount of matter that is available for the higher trophic levels of the pelagic food web. This short communication aims to report the vertical distribution patterns of Chl-a levels and some selected hydrographic parameters during autumn in the Bay of La Paz, the biggest and deepest coastal environment inside the Gulf of California, a site also recognized for its high biodiversity. Two oceanographic research cruises were carried out during November 2014 and 2016. A CTD probe configured with dissolved oxygen and active fluorescence sensors, all pre-calibrated by the manufacturer, was used to acquire high-resolution data along the water column. The results showed two distribution patterns of Chl-a: 1) deep peaks (&gt;60 m depth, with concentrations &gt;6 mg m-3) associated with the bottom at nearshore stations, and 2) maximum concentration peaks associated with the thermocline/pycnocline with concentrations up to 7.40 mg m-3 observed at deep stations. A multivariate statistical analysis confirmed the role played by some physical variables in the distribution patterns described. The results shown in this study complement the previous research and fill in the existing gaps for the transition periods between the warm and the cold.

Using a Combination of High-Frequency Coastal Radar Dataset and Satellite Imagery to Study the Patterns Involved in the Coastal Countercurrent Events in the Gulf of Cadiz

This study exploits the combination of High-Frequency Coastal Radar (HFR) information with satellite-derived observations to characterize the patterns involved in the coastal countercurrents (CCCs) events in the Gulf of Cadiz (GoC), which is situated in the SW of the Iberian Peninsula. The westward alongshore currents are observed throughout the year, but the main drivers necessary to develop this flow and its extension in both parts of the basin are not fully clear. In order to identify the main physical processes (both local and remote) that induce the development of these countercurrents and to evaluate the connection of the circulation patterns between the eastern and the western part of the GoC, we make use of several data sources available for the region. First of all, a land-based system of HFR antennas located at four different sites of the GoC provides the velocity field of the surface circulation of the basin. To achieve a significant characterization of the CCCs in the Gulf, the dataset analyzed is processed by means of a series of operations, including the Empirical Orthogonal Functions (EOFs) analysis used to identify spatial and temporal variability of the flow, a low-pass filter used to isolate the sub-inertial signal of the current and temporal interpolation to fill in the missing values. Secondly, given the known importance of the zonal component of the local winds combined with the variations in the mean pressure at sea level over the Western Mediterranean during these events, time series of meteorological data are processed and correlated with the current velocity series via a statistical analysis. Finally, sea surface temperature fields and chlorophyll-a distribution patterns are used as tracers to obtain information on the extension of the countercurrents where HFR data are missing in four cases studied during the year 2017. The conducted analysis revealed the consistent occurrence of westward coastal currents throughout the year, driven in the most intense cases by a combination of the zonal component of the local wind and atmospheric pressure fluctuations over the Western Mediterranean Sea. During those events, CCCs reached the Portuguese side of the Gulf and facilitated the advection of biological material and warmer waters.

Geospatial analysis for prediction of potential fishing zones in the Banggai Waters using hydroacoustic data and satellite remote sensing

Banggai waters are a strategic area rich in fish resources and a source of livelihood for most of the local population. Mapping fish stocks is important to ensure the sustainability of fishing in the area. One of them uses hydroacoustic data and satellite imagery to provide more comprehensive results on fish stocks and more accurate predictions of potential fishing zones. This study will spatially estimate fish density in Banggai waters using hydroacoustic data and investigate the distribution of chlorophyll-a and sea surface temperature using Himawari-8 imagery. Hydroacoustic data processing will produce target strength (TS) and volume backscatter strength (Sv) values to determine the value and distribution of fish density. Meanwhile, ZPPI results are obtained from the overlay of chlorophyll-a and sea surface temperature. From the results of mapping the potential fishing zone, the high category has the highest percentage of 43%, low 28% and medium 29%. The ZPPI point distribution map then shows the concentration of ZPPI points in the southern Banggai waters. The fish density distribution map shows that the spatial distribution tends to be around the coast of Banggai Peninsula, dominated by small and very small fish categories. Correlation of fish density point distribution with ZPPI results and oceanographic parameters has a positive influence on fish density from GAM modelling.

Analysis of Chlorophyll-A Distribution And Sea Surface Temperature for Estimation of Skipjack Fishing Grounds (Katsuwonus Pelamis) Based on Different Seasons in South Buton Waters

The success of fishing activities is certainly greatly influenced by the conditions of the Fishing Ground (FG). Therefore, information about potential fishing areas is needed by fishermen in fishing activities. Chlorophyll-a is the primary productivity in water. The development of aquatic chlorophyll is influenced by Sea Surface Temperature (SST). The purpose of this study was to analyze the distribution of chlorophyll-a and sea surface temperature (SST) for estimating fish fishing areas based on different seasons in South Buton Waters. This type of research is exploratory research. This study used remote sensing method. The direct interview method with respondents aims to validate data (fishermen) from remote sensing processing. The study used Aqua Modis satellite imagery data to derive parameter values of chlorophyll-a and sea surface temperature. The results of the analysis of the distribution of chlorophyll-a in South Buton waters are the highest with chlorophyll-a concentrations ranging from 0.3-3.0 mg / m³ spread in the waters of Sampolawa and Batauga Districts with surface temperatures ranging from 26 °C and 33 °C. Eastern and Transitional Season II have high levels of chlorophyll-a concentration. This season will be a potential skipjack fishing area in South Buton Waters.

Decision tree ensemble with Bayesian optimization to predict the spatial dynamics of chlorophyll-a concentration: A case study in Bay of Bengal

An accurate prediction of the spatial distribution of phytoplankton biomass, as represented by Chlorophyll-a (CHL-a) concentrations, is important for assessing ecological conditions in the marine environment. This study developed a hyperparameter-optimized decision tree-based machine learning (ML) models to predict the geographical distribution of marine phytoplankton CHL-a in the Bay of Bengal. To predict CHL-a over a large spatial extent, satellite-derived remotely sensed data of ocean color features (CHL-a, colored dissolved organic matter, photosynthetically active radiation, particulate organic carbon) and climatic factors (nighttime sea surface temperature, surface absorbed longwave radiation, sea level pressure) from 2003 to 2022 are used to train and test the models. Results obtained from this study have shown the highest concentrations of CHL-a occurred near the Bay's coastal belts and river estuaries. Analysis revealed that aside from photosynthetically active radiation, organic components exhibited a stronger positive relationship with CHL-a than climatic features, which are correlated negatively. Results showed the chosen decision tree methods to all possess higher R2 and lower root mean square error (RMSE) errors. Furthermore, XGBoost outperforms all other models in predicting the geographic distribution of CHL-a. To assess the model efficacy on seasonal basis, a best performing XGBoost model was validated in the Bay of Bengal region which has shown a good performance in predicting the spatial distribution of Chl-a as well as the pixel values during the summer, winter and monsoon seasons. This study provides the best ML model to researchers for predicting CHL-a in the Bay of Bengal. Further it helps to improve our knowledge of CHL-a spatial dynamics and assist in monitoring marine resources in the Bay of Bengal. It worth noting that the water quality in the Indian Ocean is very dynamic in nature, therefore, additional efforts are needed to test the efficacy of this study model over different seasons and spatial gradients.