scholarly journals CHLOROPHYLL ESTIMATION OF LAKE WATER AND COASTAL WATER USING LANDSAT-8 AND SENTINEL-2A SATELLITE

2019 ◽  
Vol XLII-3/W7 ◽  
pp. 77-82 ◽  
Author(s):  
S. Yadav ◽  
Y. Yamashiki ◽  
J. Susaki ◽  
Y. Yamashita ◽  
K. Ishikawa
Keyword(s):  
Chlorophyll A ◽  
Coastal Water ◽  
Lake Water ◽  
Satellite Images ◽  
Lake Biwa ◽  
Measurement Data ◽  
Landsat 8 ◽  
Chlorophyll A Concentration ◽  
Wakasa Bay ◽  
Sentinel 2A

<p><strong>Abstract.</strong> Chlorophyll-a is an optically active compound (OAC) commonly used as a proxy for phytoplankton biomass in an aquatic environment. Retrieving the concentration of chlorophyll-a remains a challenge due to the presence of several OAC particularly in water bodies which are in proximity to the land-based activities. In this study, an effort has been made to estimate the chlorophyll-a concentration of both the freshwater Lake Biwa and the coastal water of Wakasa Bay in Japan. A spectral decomposition algorithm was used to determine the chlorophyll-a using the satellite images. The algorithm was applied to the satellite images from two different sensors namely Landsat-8/OLI and Sentinel-2A/MSI. The satellite-derived chlorophyll-a concentration for the lake and coastal water from two different sensors were compared to assess the performance of both the sensors. The accuracy of the chlorophyll-a results derived from the images was evaluated with the in-situ measurement data of the chlorophyll-a for the Lake Biwa and the coastal water of Wakasa Bay. Both satellite sensors appear to give the best results for the coastal water (R<sup>2</sup>&amp;thinsp;&amp;gt;&amp;thinsp;0.80) with an RMSE &amp;lt;&amp;thinsp;0.3&amp;thinsp;&amp;mu;g/L. However, slight underestimation of chlorophyll-a noted for the Landsat-8 image with an increase in chlorophyll-a concentration. For the lake water, Sentinel-2A results were relatively better (R<sup>2</sup>&amp;thinsp;&amp;gt;&amp;thinsp;0.70) than Landsat-8, with an RMSE of &amp;lt;&amp;thinsp;1.0&amp;thinsp;&amp;mu;g/L. The obtained results will be useful to evaluate the primary productivity of both freshwater and coastal water body.</p>

scholarly journals Retrieval and Evaluation of Chlorophyll-a Concentration in Reservoirs with Main Water Supply Function in Beijing, China, Based on Landsat Satellite Images

2021 ◽  
Vol 18 (9) ◽  
pp. 4419
Author(s):  
Yuequn Lai ◽  
Jing Zhang ◽  
Yongyu Song ◽  
Zhaoning Gong
Keyword(s):  
Remote Sensing ◽  
Water Supply ◽  
Chlorophyll A ◽  
Phosphorus Concentration ◽  
Landsat 8 ◽  
Supply Function ◽  
Estimation Model ◽  
Nitrogen And Phosphorus ◽  
Chlorophyll A Concentration ◽  
Guanting Reservoir

Remote sensing retrieval is an important technology for studying water eutrophication. In this study, Guanting Reservoir with the main water supply function of Beijing was selected as the research object. Based on the measured data in 2016, 2017, and 2019, and Landsat-8 remote sensing images, the concentration and distribution of chlorophyll-a in the Guanting Reservoir were inversed. We analyzed the changes in chlorophyll-a concentration of the reservoir in Beijing and the reasons and effects. Although the concentration of chlorophyll-a in the Guanting Reservoir decreased gradually, it may still increase. The amount and stability of water storage, chlorophyll-a concentration of the supply water, and nitrogen and phosphorus concentration change are important factors affecting the chlorophyll-a concentration of the reservoir. We also found a strong correlation between the pixel values of adjacent reservoirs in the same image, so the chlorophyll-a estimation model can be applied to each other.

scholarly journals Remote sensing of the chlorophyll-a based on OLI/Landsat-8 and MSI/Sentinel-2A (Barra Bonita reservoir, Brazil)

2018 ◽  
Vol 90 (2 suppl 1) ◽  
pp. 1987-2000 ◽  
Author(s):  
FERNANDA WATANABE ◽  
ENNER ALCÂNTARA ◽  
THANAN RODRIGUES ◽  
LUIZ ROTTA ◽  
NARIANE BERNARDO ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Landsat 8 ◽  
Sentinel 2A

scholarly journals Comparing of Landsat 8 and Sentinel 2A using Water Extraction Indexes over Volta River

2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Clement Kwang ◽  
Edward Matthew Osei Jnr ◽  
Adwoa Sarpong Amoah
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Unsupervised Classification ◽  
Water Bodies ◽  
Water Extraction ◽  
Landsat 8 ◽  
Sensing Data ◽  
Optimal Classifier ◽  
Sentinel 2A

Remote sensing data are most often used in water bodies’ extraction studies and the type of remote sensing data used also play a crucial role on the accuracy of the extracted water features. The performance of the proposed water indexes among the various satellite images is not well documented in literature. The proposed water indexes were initially developed with a particular type of data and with advancement and introduction of new satellite images especially Landsat 8 and Sentinel, therefore the need to test the level of performance of these water indexes as new image datasets emerged. Landsat 8 and Sentinel 2A image of part Volta River was used. The water indexes were performed and then ISODATA unsupervised classification was done. The overall accuracy and kappa coefficient values range from 98.0% to 99.8% and 0.94 to 0.98 respectively. Most of water bodies enhancement indexes work better on Sentinel 2A than on Landsat 8. Among the Landsat based water bodies enhancement ISODATA unsupervised classification, the modified normalized water difference index (MNDWI) and normalized water difference index (NDWI) were the best classifier while for Sentinel 2A, the MNDWI and the automatic water extraction index (AWEI_nsh) were the optimal classifier. The least performed classifier for both Landsat 8 and Sentinel 2A was the automatic water extraction index (AWEI_sh). The modified normalized water difference index (MNDWI) has proved to be the universal water bodies enhancement index because of its performance on both the Landsat 8 and Sentinel 2A image.

scholarly journals Detection and Analysis of the Causes of Intensive Harmful Algal Bloom in Kamchatka Based on Satellite Data

2021 ◽  
Vol 9 (10) ◽  
pp. 1092
Author(s):  
Valery Bondur ◽  
Viktor Zamshin ◽  
Olga Chvertkova ◽  
Ekaterina Matrosova ◽  
Vasilisa Khodaeva
Keyword(s):  
Chlorophyll A ◽  
Suspended Matter ◽  
Algal Bloom ◽  
Harmful Algal Bloom ◽  
Simulated Data ◽  
Region Of Interest ◽  
Chlorophyll A Concentration ◽  
Ocean Level ◽  
Radar Satellite ◽  
Sentinel 2A

In this paper, the causes of the anomalous harmful algal bloom which occurred in the fall of 2020 in Kamchatka have been detected and analyzed using a long-term time series of heterogeneous satellite and simulated data with respect to the sea surface height (HYCOM) and temperature (NOAA OISST), chlorophyll-a concentration (MODIS Ocean Color SMI), slick parameters (SENTINEL-1A/B), and suspended matter characteristics (SENTINEL-2A/B, C2RCC algorithm). It has been found that the harmful algal bloom was preceded by temperature anomalies (reaching 6 °C, exceeding the climatic norm by more than three standard deviation intervals) and intensive ocean level variability followed by the generation of vortices, mixing water masses and providing nutrients to the upper photic layer. The harmful algal bloom itself was manifested in an increase in the concentration of chlorophyll-a, its average monthly value for October 2020 (bloom peak) approached 15 mg/m3, exceeding the climatic norm almost four-fold for the region of interest (Avacha Gulf). The zones of accumulation of a large amount of biogenic surfactant films registered in radar satellite imagery correlate well with the local regions of the highest chlorophyll-a concentration. The harmful bloom was influenced by river runoff, which intensively brought mineral and biogenic suspensions into the marine environment (the concentration of total suspended matter within the plume of the Nalycheva River reached 10 mg/m3 and more in 2020), expanding food resources for microalgae.

scholarly journals OPTMIZATION OF BIO-OPTICAL MODEL PARAMETERS FOR TURBID LAKE WATER QUALITY ESTIMATION USING LANDSAT 8 AND WASI-2D

2020 ◽  
Vol XLII-3/W11 ◽  
pp. 67-72
Author(s):  
A. Manuel ◽  
A. C. Blanco ◽  
A. M. Tamondong ◽  
R. Jalbuena ◽  
O. Cabrera ◽  
...  
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
The Philippines ◽  
Quality Data ◽  
Model Parameters ◽  
Landsat 8 ◽  
Water Quality Data ◽  
Chlorophyll A Concentration ◽  
In Situ Data

Abstract. Laguna Lake, the Philippines’ largest freshwater lake, has always been historically, economically, and ecologically significant to the people living near it. However, as it lies at the center of urban development in Metro Manila, it suffers from water quality degradation. Water quality sampling by current field methods is not enough to assess the spatial and temporal variations of water quality in the lake. Regular water quality monitoring is advised, and remote sensing addresses the need for a synchronized and frequent observation and provides an efficient way to obtain bio-optical water quality parameters. Optimization of bio-optical models is done as local parameters change regionally and seasonally, thus requiring calibration. Field spectral measurements and in-situ water quality data taken during simultaneous satellite overpass were used to calibrate the bio-optical modelling tool WASI-2D to get estimates of chlorophyll-a concentration from the corresponding Landsat-8 images. The initial output values for chlorophyll-a concentration, which ranges from 10–40 μg/L, has an RMSE of up to 10 μg/L when compared with in situ data. Further refinements in the initial and constant parameters of the model resulted in an improved chlorophyll-a concentration retrieval from the Landsat-8 images. The outputs provided a chlorophyll-a concentration range from 5–12 μg/L, well within the usual range of measured values in the lake, with an RMSE of 2.28 μg/L compared to in situ data.

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.

Estimation of chlorophyll‐a concentration and trophic states in Nalban Lake of East Kolkata Wetland, India from Landsat 8 OLI data

2017 ◽  
Vol 25 (1) ◽  
pp. 75-87 ◽  
Author(s):  
Pulak Priti Patra ◽  
Sourabh Kumar Dubey ◽  
Raman Kumar Trivedi ◽  
Sanjeev Kumar Sahu ◽  
Sangram Keshari Rout
Keyword(s):  
Chlorophyll A ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Chlorophyll A Concentration ◽  
East Kolkata Wetland

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 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.

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