Chlorophyll-A Concentrations Estimation from Aqua-Modis and Viirs-NPP Satellite Sensors in South Java Sea Waters (original) (raw)
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A study on chlorophyll-a concentration on Cambodia water in the Gulf of Thailand was conducted using the Visible Infrared Imaging Radiometer Suite (VIIRS) to produce an estimation of global chlorophyll-a concentration. Field data was obtained from R/V Koyo-maru cruise No 49/2514 in 26 stations on November 2014 using calibration and validation. The study yielded results of a mean concentration of 1.467 mg/m 3 , minimum concentration of 0.503 mg/m3 and maximum concentration of 55.663 mg/m 3 . The relationship between field data and satellite data is Y = 1.721x + 0.291, where Y is field chlorophyll-a concentration and x is concentration from VIIRS product. The coefficient of determination (R 2 ) is 0.245 which is lower than expected whereas RMSE from validation is 0.275 which is acceptable enough.
Journal of Geomatics
Study has been carried out to monitor the phytoplankton biomass in Bay of Bengal (BoB) and Arabian Sea (AS) using Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua satellite data. Cloud masking, geometric corrections and subsets generations were performed to retrieve chlorophyll images from MODIS-Aqua data during the periods January - December for the years 2007 and 2008. The two regions (BoB & AS) have been divided into four subsets; subset-1 (Northern Bay of Bengal), subset-2 (Southern Bay of Bengal), subset-3 (Northern Arabian Sea) and subset-4 (Southern Arabian Sea). The results were analyzed and confirmed that chlorophyll concentration mean range was high (0.97-1.89 mg m-3) in northern Arabian Sea during the months of July for both years 2007 and 2008 and low concentration range (0.12-0.35 mg m-3) was obtained during April month for both years in southern Bay of Bengal. This study found to be important as information about the chlorophyll concentration in the Northern ...
2021
The primary productivity of an aquatic system like the Arabian Sea is broadly determined by the concentration of Chlorophyll-a (Chl-a/Ca) pigment. The present study is essaying to validate the Chl-a data set retrieved from the prominent ocean color sensors (OC3M - MODIS, OC-OCM2, and OC3V-VIIRS) with sea truth data, collected from 204 stations for a three year period (2015–2017). The in-situ concentrations of Chl-a depict the geographic region under the mesotrophic and eutrophic spans with a mean of 1.36 mg m-3 ((0.1 > Ca>1.0 mg m-3). The ratio of CaOCM2/CaIn-situ was 0.97 ± 0.27 mg m-3 (n = 199), but the ratios were higher with CaVIIRS/CaIn-situ is 1.75 ± 0.79 mg m-3 (n = 170) and CaMODIS/CaIn-situ is 2.53 ± 1.42 mg m-3 (n = 158). The coefficient of determination proclaims a moderate significant relationship for MODIS (R2 = 0.36; p
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The size and distribution of Phytoplankton populations are indicators of the ecological status of a water body. The chlorophyll-a (Chl-a) concentration is estimated as a proxy for the distribution of phytoplankton biomass. Remote sensing is the only practical method for the synoptic assessment of Chl-a at large spatial and temporal scales. Long-term records of ocean color data from the MODIS Aqua Sensor have proven inadequate to assess Chl-a due to the lack of a robust ocean color algorithm. Chl-a estimation in shallow and coastal water bodies has been a challenge and existing operational algorithms are only suitable for deeper water bodies. In this study, the Ocean Color 3M (OC3M) derived Chl-a concentrations were compared with observed data to assess the performance of the OC3M algorithm. Subsequently, a regression analysis between in situ Chl-a and remote sensing reflectance was performed to obtain a green-red band algorithm for coastal (case 2) water. The OC3M algorithm yielded ...
Estimation of chlorophyll-a concentration from satellite ocean color data in upper Gulf of Thailand
Proceedings of SPIE, 2006
The high nutrient concentrations coming from non-point and point pollution have been linked to algae blooms, especially in hydroelectric plant reservoirs, due to higher residence time compared to rivers. The monitoring of algae is important to prevent risk of contamination by toxins in reservoirs used for drinking water supply. In this context, a physical model-based approach was adopted to retrieve chlorophyll-a (chl a) concentration, a photosynthetic pigment found in all phytoplankton species. We assumed that a semi-analytical algorithm parameterized to a eutrophic reservoir could also be applied to other eutrophic reservoirs, at least the specific inherent optical properties (SIOPs) are not similar. The parameterization was carried out based on Ocean and Land Color Instrument (OLCI) bands aboard Sentinel-3 spacecraft. In our study, the semi-analytical approach showed good performance in retrieving chl a content, with a normalized root mean square error (NRMSE) of 18.7%. The findings encourage the use of a unique semi-analytical algorithm in a reservoir cascade, where the impoundments present similar bio-optical status. The good performance of the algorithm indicates that this approach is rather useful in predicting trophic status in reservoirs.
2019
In-situ data of chlorophyll-a concentrations (Chl-a) and sea surface temperature (SST) of the Gujarat region for the period, 2002-2009 were obtained from Indian National Centre for Ocean Information Services (INCOIS), Hyderabad. Out of nearly 100 sampling points, 22 and 67 points qualified for comparison with the satellite measurements of Chl-a and SST, respectively. Chl-a concentrations were estimated from the MODIS satellite data (4 km resolution) with the existing global ocean color algorithms, namely, OC2V4, OC4V4, and OC3M. The SST was calculated with the help of bands 31 and 32 using MODIS-Aqua sensor long wave SST algorithm and European Centre for Medium-Range Weather Forecasts (ECMWF) assimilation SST retrieval model (split window method). The satellite images were processed using global Sea WiFS Data Analysis System (SeaDAS) software v.7.3.1. Chl-a retrieved from OC3M algorithm had high coefficient of determination (R2=0.74) and less root mean square error (RMSE=1.24) as co...
Forum Geografi/Forum geografi, 2024
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 chlorophylla concentration. Therefore, this study adopted ocean colour remote sensing technology to assess chlorophylla 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).
IEEE Geoscience and Remote Sensing Letters, 2000
We present here the results of calibrating and validating a three-band model and, its special case, a two-band model, which use MEdium Resolution Imaging Spectrometer (MERIS) reflectances in the red and near-infrared spectral regions for estimating chlorophyll-a (chl-a) concentration in inland, estuarine, and coastal turbid productive waters. During four data collection campaigns in 2008 and one campaign in 2009 in the Taganrog Bay and the Azov Sea, Russia, water samples were collected, and concentrations of chl-a and total suspended solids were measured in the laboratory. The data collected in 2008 were used for model calibration, and the data collected in 2009 were used for model validation. The models were applied to MERIS images acquired within two days from the date of in situ data collection. Two different atmospheric correction procedures were considered for processing the MERIS images. The results illustrate the high potential of the models to estimate chl-a concentration in turbid productive (Case II) waters in real time from satellite data, which will be of immense value to scientists, natural resource managers, and decision makers involved in managing the inland and coastal aquatic ecosystems.
Remote Sensing, 2019
In this study, a low-altitude remote sensing (LARS) observation system was employed to observe a rapidly changing coastal environment-owed to the regular opening of the sluice gate of the Saemangeum seawall-off the west coast of South Korea. The LARS system uses an unmanned aerial vehicle (UAV), a multispectral camera, a global navigation satellite system (GNSS), and an inertial measurement unit (IMU) module to acquire geometry information. The UAV system can observe the coastal sea surface in two dimensions with high temporal (1 s−1) and spatial (20 cm) resolutions, which can compensate for the coarse spatial resolution of in-situ measurements and the low temporal resolution of satellite observations. Sky radiance, sea surface radiance, and irradiance were obtained using a multispectral camera attached to the LARS system, and the remote sensing reflectance (Rrs) was accordingly calculated. In addition, the hyperspectral radiometer and in-situ chlorophyll-a concentration (CHL) measu...