scholarly journals SPATIAL-TEMPORAL DISTRIBUTION OF CHLOROPHYLL-A IN SOUTHERN PART OF THE MAKASSAR STRAIT

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Wasir Samad Daming ◽  
Muhammad Anshar Amran ◽  
Amir Hamzah Muhiddin ◽  
Rahmadi Tambaru
Keyword(s):  
Chlorophyll A ◽  
Satellite Data ◽  
Chlorophyll Concentration ◽  
Temporal Distribution ◽  
Fishing Ground ◽  
Landsat 8 ◽  
Trade Winds ◽  
Chl A ◽  
June July ◽  
Potential Area

Surface chlorophyll-a (Chl-a) distribution have been analyzed with seasonal variation during southeast monsoon in southern part of Makassar Strait and Flores Sea. Satellite data of Landsat-8 is applied to this study to formulate the distribution of chlorophyll concentration during monsoonal wind period. The distribution of chlorophyll concentration was normally peaked condition in August during southeast monsoon. Satellite data showed that a slowdown in the rise of the distribution of chlorophyll in September with a lower concentration than normal is likely due to a weakening the strength of southeast trade winds during June – July – August 2016. Further analysis shows that the southern part of the Makassar strait is likely occurrence of upwelling characterized by increase in surface chlorophyll concentrations were identified as the potential area of fishing ground.

scholarly journals Spatiotemporal Variability of Surface Phytoplankton Carbon and Carbon-to-Chlorophyll a Ratio in the South China Sea Based on Satellite Data

2020 ◽  
Vol 13 (1) ◽  
pp. 30
Author(s):  
Wenlong Xu ◽  
Guifen Wang ◽  
Long Jiang ◽  
Xuhua Cheng ◽  
Wen Zhou ◽  
...  
Keyword(s):  
South China Sea ◽  
Chlorophyll A ◽  
South China ◽  
Satellite Data ◽  
Phytoplankton Biomass ◽  
The South China Sea ◽  
Spatiotemporal Variability ◽  
The South ◽  
Chl A ◽  
China Sea

The spatiotemporal variability of phytoplankton biomass has been widely studied because of its importance in biogeochemical cycles. Chlorophyll a (Chl-a)—an essential pigment present in photoautotrophic organisms—is widely used as an indicator for oceanic phytoplankton biomass because it could be easily measured with calibrated optical sensors. However, the intracellular Chl-a content varies with light, nutrient levels, and temperature and could misrepresent phytoplankton biomass. In this study, we estimated the concentration of phytoplankton carbon—a more suitable indicator for phytoplankton biomass—using a regionally adjusted bio-optical algorithm with satellite data in the South China Sea (SCS). Phytoplankton carbon and the carbon-to-Chl-a ratio (θ) exhibited considerable variability spatially and seasonally. Generally, phytoplankton carbon in the northern SCS was higher than that in the western and central parts. The regional monthly mean phytoplankton carbon in the northern SCS showed a prominent peak during December and January. A similar pattern was shown in the central part of SCS, but its peak was weaker. Besides the winter peak, the western part of SCS had a secondary maximum of phytoplankton carbon during summer. θ exhibited significant seasonal variability in the northern SCS, but a relatively weak seasonal change in the western and central parts. θ had a peak in September and a trough in January in the northern and central parts of SCS, whereas in the western SCS the minimum and maximum θ was found in August and during October–April of the following year, respectively. Overall, θ ranged from 26.06 to 123.99 in the SCS, which implies that the carbon content could vary up to four times given a specific Chl-a value. The variations in θ were found to be related to changing phytoplankton community composition, as well as dynamic phytoplankton physiological activities in response to environmental influences; which also exhibit much spatial differences in the SCS. Our results imply that the spatiotemporal variability of θ should be considered, rather than simply used a single value when converting Chl-a to phytoplankton carbon biomass in the SCS, especially, when verifying the simulation results of biogeochemical models.

scholarly journals Chlorophyll-a Variability during Upwelling Events in the South-Eastern Baltic Sea and in the Curonian Lagoon from Satellite Observations

2020 ◽  
Vol 12 (21) ◽  
pp. 3661
Author(s):  
Toma Dabuleviciene ◽  
Diana Vaiciute ◽  
Igor E. Kozlov
Keyword(s):  
Baltic Sea ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Coastal Upwelling ◽  
Curonian Lagoon ◽  
The Baltic Sea ◽  
Chl A ◽  
Resolution Imaging ◽  
The Baltic ◽  
Eastern Baltic

Based on the analysis of multispectral satellite data, this work demonstrates the influence of coastal upwelling on the variability of chlorophyll-a (Chl-a) concentration in the south-eastern Baltic (SEB) Sea and in the Curonian Lagoon. The analysis of sea surface temperature (SST) data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua/Terra satellites, together with Chl-a maps from Medium Resolution Imaging Spectrometer (MERIS) onboard Envisat, shows a significant decrease of up to 40–50% in Chl-a concentration in the upwelling zone. This results from the offshore Ekman transport of more productive surface waters, which are replaced by cold and less-productive waters from deeper layers. Due to an active interaction between the Baltic Sea and the Curonian Lagoon which are connected through the Klaipeda Strait, coastal upwelling in the SEB also influences the hydrobiological conditions of the adjacent lagoon. During upwelling inflows, SST drops by approximately 2–8 °C, while Chl-a concentration becomes 2–4 times lower than in pre-upwelling conditions. The joint analysis of remotely sensed Chl-a and SST data reveals that the upwelling-driven reduction in Chl-a concentration leads to the temporary improvement of water quality in terms of Chl-a in the coastal zone and in the hyper-eutrophic Curonian Lagoon. This study demonstrates the benefits of multi-spectral satellite data for upscaling coastal processes and monitoring the environmental status of the Baltic Sea and its largest estuarine lagoon.

scholarly journals Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir

2017 ◽  
Vol 49 (5) ◽  
pp. 1608-1617 ◽  
Author(s):  
Matias Bonansea ◽  
Claudia Rodriguez ◽  
Lucio Pinotti
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Landsat Imagery ◽  
Quality Parameters ◽  
Landsat 8 ◽  
Chlorophyll A Concentration ◽  
Chl A ◽  
Sensing Applications ◽  
Wide Range ◽  
Quality Assessments

Abstract Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 = 0.88). Using observed versus predicted Chl-a values the model was validated (R2 = 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.

scholarly journals Bromocarbons in the tropical coastal and open ocean atmosphere during the 2009 Prime Expedition Scientific Cruise (PESC-09)

2014 ◽  
Vol 14 (15) ◽  
pp. 8137-8148 ◽  
Author(s):  
M. S. Mohd Nadzir ◽  
S. M. Phang ◽  
M. R. Abas ◽  
N. Abdul Rahman ◽  
A. Abu Samah ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Statistical Tests ◽  
Open Ocean ◽  
Common Source ◽  
Sampling Point ◽  
Coastal Regions ◽  
Chl A ◽  
June July ◽  
Strait Of Malacca

Abstract. Atmospheric concentrations of very short-lived species (VSLS) bromocarbons, including CHBr3, CH2Br2, CHCl2Br, CHClBr2, and CH2BrCl, were measured in the Strait of Malacca and the South China and Sulu–Sulawesi seas during a two-month research cruise in June–July 2009. The highest bromocarbon concentrations were found in the Strait of Malacca, with smaller enhancements in coastal regions of northern Borneo. CHBr3 was the most abundant bromocarbon, ranging from 5.2 pmol mol−1 in the Strait of Malacca to 0.94 pmol mol−1 over the open ocean. Other bromocarbons showed lower concentrations, in the range of 0.8–1.3 pmol mol−1 for CH2Br2, 0.1–0.5 pmol mol−1 for CHCl2Br, and 0.1–0.4 pmol mol−1 for CHClBr2. There was no significant correlation between bromocarbons and in situ chlorophyll a, but positive correlations with both MODIS and SeaWiFS satellite chlorophyll a. Together, the short-lived bromocarbons contribute an average of 8.9 pmol mol−1 (range 5.2–21.4 pmol mol−1) to tropospheric bromine loading, which is similar to that found in previous studies from global sampling networks (Montzka et al., 2011). Statistical tests showed strong Spearman correlations between brominated compounds, suggesting a common source. Log–log plots of CHBr3/CH2Br2 versus CHBr2Cl/CH2Br2 show that both chemical reactions and dilution into the background atmosphere contribute to the composition of these halocarbons at each sampling point. We have used the correlation to make a crude estimate of the regional emissions of CHBr3 and to derive a value of 32 Gg yr−1 for the Southeast (SE) Asian region (10° N–20° S, 90–150° E). Finally, we note that satellite-derived chlorophyll a (chl a) products do not always agree well with in situ measurements, particularly in coastal regions of high turbidity, meaning that satellite chl a may not always be a good proxy for marine productivity.

scholarly journals ESTIMASI PRODUKTIVITAS PRIMER PERAIRAN BERDASARKAN KONSENTRASI KLOROFIL-A YANG DIEKSTRAK DARI CITRA SATELIT LANDSAT-8 DI PERAIRAN KEPULAUAN KARIMUN JAWA

2017 ◽  
Vol 14 (1) ◽  
Author(s):  
Mulkan Nuzapril ◽  
Setyo Budi Susilo ◽  
James Parlindungan Panjaitan
Keyword(s):  
Chlorophyll A ◽  
Attenuation Coefficient ◽  
Primary Productivity ◽  
Chlorophyll Concentration ◽  
Euphotic Zone ◽  
Landsat 8 ◽  
Secchi Disk ◽  
Estimation Model ◽  
Chlorophyll A Concentration ◽  
Average Value

Sea primary productivity is an important factor in monitoring the quality of sea waters due to his role in the carbon cycle and the food chain for heterotrophic organisms. Estimation of sea primary productivity may be suspected through the values of chlorophyll-a concentration, but surface chlorophyll-a concentration was only able to explain 30% of the primary productivity of the sea. This research aims to build primary productivity estimation model based on chlorophyll-a concentration value of a surface layer of depth until depth compensation. Primary productivity model of relationships with chlorophyll concentration were extracted from Landsat-8 imagery then it could be used to calculated of sea primary productivity. The determination of the depth classification were done by measuring the attenuation coefficient values using the luxmeter underwater datalogger 2000 and secchi disk. The attenuation coefficient values by the luxmeter underwater, ranges between of 0.13-0.21 m-1 and secchi disk ranged, of 0.12 – 0.21 m-1. The penetration of light that through into the water column where  primary productivity is still in progress or where the depth of compensation ranged from 28.75 – 30.67 m. The simple linier regression model between average value of chlorophyll- concentration in all euphotic zone with sea primary productivity has high correlation, it greater than of surface chlorophyll-a concentration (R2 = 0.65). Model validation of sea primary productivity has high accuracy with the RMSD value of 0.09 and satellite-derived sea primary productivity were not significantly different. The satellite derived of chlorophyll-a could be calculated into sea primary productivity.Abstrak Produktivitas primer perairan merupakan faktor penting dalam pemantauan kualitas perairan laut karena berperan dalam siklus karbon dan rantai makanan bagi organisme heterotrof. Estimasi produktivitas primer perairan dapat diduga melalui nilai konsentrasi klorofil-a, namun konsentrasi klorofil-a permukaan laut hanya mampu menjelaskan 30% produktivitas primer laut. Penelitian ini bertujuan untuk membangun model estimasi produktivitas primer berdasarkan nilai konsentrasi klorofil-a dari lapisan kedalaman permukaan sampai kedalaman kompensasi. Model hubungan produktivitas primer dengan konsentrasi klorofil-a yang diekstrak dari citra satelit Landsat-8 kemudian dapat digunakan untuk mengestimasi produktivitas primer satelit. Penentuan klasifikasi kedalaman dilakukan dengan mengukur nilai koefisien atenuasi menggunakan luxmeter underwater datalogger 2000  dan secchi disk. Nilai koefisien atenuasi dengan menggunakan luxmeter underwater berkisar antara 0,13 -0,21m-1 dan secchi disk berkisar antara 0,12 – 0,21 m-1. Penetrasi cahaya yang masuk ke kolom perairan dimana produksi primer masih berlangsung atau kedalaman kompensasi berkisar antara 28,75 – 30,67 m. Model regresi linier sederhana antara konsentrasi klorofil-a rata-rata seluruh zona eufotik dengan produktivitas primer perairan memiliki korelasi yang lebih tinggi dibandingkan konsentrasi klorofil-a permukaan dengan R2= 0,65. Validasi model produktivitas primer memiliki keakuratan yang tinggi dengan RMSD sebesar 0,09 dan produktivitas primer satelit secara signifikan tidak berbeda nyata dengan produktivitas primer data insitu. Sehingga  nilai konsentrasi klorofil-a satelit dapat ditransformasi menjadi produktivitas primer satelit.

scholarly journals RELATIONSHIP BETWEEN CHLOROPHYLL-A AND SEA SURFACE TEMPERATUR WITH Sardinella lemuru CATCHING IN BALI STRAIT

2021 ◽  
Vol 15 (1) ◽  
pp. 12
Author(s):  
Niken Gustantia ◽  
Takahiro Osawa ◽  
I Gusti Bagus Sila Dharma ◽  
Wayan Sandi Adnyana
Keyword(s):  
Chlorophyll A ◽  
Sea Surface ◽  
Fishing Ground ◽  
Fish Production ◽  
Resource Potential ◽  
Chl A ◽  
Remote Sensing Technique ◽  
Fish Resources ◽  
Fish Catch ◽  
Total Fish

The Bali Strait is one of Indonesia's territorial waters that have high natural resource potential. The area is only about 2,500 km2 but has a high potential fishing ground. The Bali Strait has unique and dynamic waters that can cause fluctuations in fish production amount each year. The largest type of fish caught in the Bali Strait is lemuru (Sardinella lemuru), a fish found only in the Bali Strait. This fish plays a significant role in the economy of fishers in the Bali Strait. Each year the catch of lemuru has fluctuated, making fishing locations challenging to predict. Sea Surface Temperature (SST) and Chlorophyll-a (Chl-a) are oceanographic parameters that can affect the resources of the ocean. Oceanographic phenomena, such as upwelling, can also influence the condition of fish resources. Therefore, understanding the relationships between these factors is essential in practical fisheries management. Observation of oceanographic factors is very hard with the field observation due to time and cost limitations. The remote sensing technique is an efficient method to determine SST distributions and Chl-a concentrations using satellite imagery. This study analyzes SST and Chl-a concentration in the Bali Strait using the Global Change Observation Mission(GCOM-C) satellite and determines the correlation between Chl-a and SST with a total fish catch(lemuru) during 2019. The results showed the maximum average Chl-a concentration observed on August 1.62 mg/m3 and the lowest concentration observed on January 0.45 mg/m3, the maximum SST on March was 28.12° C, and on August (Dry season) with 22.40° C. The SST variable's influence provides a negative correlation (R = -0.209) with changes in lemuru catch, while the Chl-a parameter has a positive correlation (R = 0.375) with changes in the catch. The pattern of relationship between Chl-a with fish catching had a good relationship than the SST in 2019.Keywords: Bali Strait; Sardinella lemuru; SST; Chl-a.

scholarly journals ESTIMATING AND MAPPING CHLOROPHYLL-A CONCENTRATION OF PHEWA LAKE OF KASKI DISTRICT USING LANDSAT IMAGERY

2019 ◽  
Vol IV-5/W2 ◽  
pp. 127-132
Author(s):  
N. Wagle ◽  
R. Pote ◽  
R. Shahi ◽  
S. Lamsal ◽  
S. Thapa ◽  
...  
Keyword(s):  
Regression Model ◽  
Chlorophyll A ◽  
Algal Blooms ◽  
Landsat Imagery ◽  
Measurement Data ◽  
Landsat 8 ◽  
Chl A ◽  
Gis Techniques ◽  
The One

Abstract. Water is a major component in the living ecosystem. As water quality is degrading due to human intervention, continuous monitoring is necessary. One of the indicators is Chlorophyll-a (Chl-a) which indicates algal blooms which are often driven by eutrophication phenomena in freshwater. Lakes should be monitored for Chl-a because Chla-a is related to eutrophication phenomena which are an enrichment of water by nutrients salt. When the environment becomes enriched with nutrients the excessive growth can lead to the death of fish. In this study, the Remote Sensing (RS) and Geographic Information System (GIS) techniques were utilized to determine Chl-a concentration of Phewa Lake of Kaski district. We used Landsat 8 satellite imagery for estimation and mapping of the Chl-a concentration. In-situ measurements from different sample points were taken and used to form a regression model for Chl-a and its concentration over the water body was calculated. The preceding year’s (2016) in situ measurement data of Chl-a concentration at a specific location were assessed with the one evaluated from the regression model thus produced for the succeeding year (2017) using Root Mean Square Error (RMSE) technique. As a result, we concluded that the estimation and mapping of Chl-a of a lake in Nepal can be done with the help of RS and GIS techniques.

scholarly journals An Optimal Two Bands Ratio Model to Monitor Chlorophyll-a in Urban Lake Using Landsat 8 Data

2020 ◽  
Vol 143 ◽  
pp. 02003
Author(s):  
Qi Chen ◽  
Mutao Huang ◽  
Kaiyuan Bai ◽  
Xiaojuan Li
Keyword(s):  
Chlorophyll A ◽  
Environmental Issue ◽  
Inland Waters ◽  
Landsat 8 ◽  
Ratio Model ◽  
Landsat 8 Oli ◽  
Band Ratio ◽  
Chl A ◽  
Quality Indexes

Chlorophyll-a (Chl-a) estimation in inland waters is an essential environmental issue. This study aimed to identify a band ratio model for Chl-a simulation using Landsat 8 OLI data and in situ Chl-a measuring in Lake Donghu. The band B1and B2, respectively at the wavelength of 443 nm and 483 nm, in the band ratio model [B1/B2] performed best in Chl-a estimation with the R2 of 0.6215. K-means cluster analysis based on water quality indexes (Chl-a, pH, DO, TN, TP, COD, Turbidity) was conducted to further improve the accuracy of inversion model. The MAPE of the optimal [B1/B2] algorithm has decreased by 4.81% and 39.87% respectively for 17 December 2017 (R2=0.7669, N=42) and 26 March 2018 (R2=0.9156, N=45).

scholarly journals Estimation of chlorophyll-a concentration using Landsat 8 in the Cassaffousth reservoir

2019 ◽  
Vol 19 (7) ◽  
pp. 2021-2027 ◽  
Author(s):  
María Micaela Ledesma ◽  
Matías Bonansea ◽  
Claudia Rosa Ledesma ◽  
Claudia Rodríguez ◽  
Joel Carreño ◽  
...  
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Field Data ◽  
Warning System ◽  
Landsat 8 ◽  
Chl A ◽  
Physico Chemical ◽  
Regression Techniques ◽  
Remote Sensing Techniques

Abstract The physico-chemical and biological composition of a reservoir's effluents directly influences water quality. The values of variables such as high values of concentrations of chlorophyll-a (Chl-a) are indicators of pollution. The objective of this work was to monitor the trophic status and water quality of the Cassaffousth reservoir (Córdoba, Argentina) through the development of statistical models based on field data and satellite information. During 2016 and 2017, samples were taken bimonthly. Seven sampling sites were selected and physico-chemical and biological parameters were assessed. By using regression techniques, Landsat 8 information was related with field data to construct and validate a statistical model to determine the distribution of Chl-a in the reservoir (R2 = 0.87). The generated algorithm was used to generate maps which contained information about the dynamics of Chl-a in the entire reservoir. Remote sensing techniques can be used to expand the knowledge of the dynamics of the Cassaffousth reservoir. Moreover, these techniques can be used as baselines for the development of an early warning system for this and other reservoirs in the region.

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