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 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 Determinação da Concentração de Clorofila-a por Sensoriamento Remoto no Reservatório de Chapéu d’Úvas (Mg), Brasil

2021 ◽  
Vol 14 (6) ◽  
pp. 3561
Author(s):  
Larissa Ferreira Serbeto ◽  
George Mendes ◽  
Celso Bandeira de Melo Ribeiro ◽  
Renata De Oliveira Pereira
Keyword(s):  
Remote Sensing ◽  
Water Supply ◽  
Chlorophyll A ◽  
Trophic State ◽  
The Body ◽  
Component Concentration ◽  
Public Water Supply ◽  
Trophic State Index ◽  
Chlorophyll A Concentration ◽  
Sentinel 2

Na atualidade, um grande impacto nos reservatórios de água doce é a eutrofização, que afeta diretamente o tratamento e uso da água para abastecimento público, navegação, fauna e flora aquática e impacto visual. A clorofila-a é um dos indicadores de estado trófico da água e pode ser determinada utilizando sensoriamento remoto. Desta forma, este estudo objetivou determinar a concentração de clorofila-a na barragem de Chapéu d’Uvas em Juiz de Fora (Brasil), um dos principais mananciais de abastecimento público da cidade. Através de um modelo utilizando imagens do satélite Sentinel-2 foi avaliado o comportamento espaço-temporal da concentração do componente, foi correlacionado com dados de pluviosidade, temperatura, evaporação e uso e ocupação do solo em torno da barragem. Também foi aplicado um modelo para determinar o índice de estado trófico, que apresenta o grau de trofia que o corpo hídrico se encontra, classificando Chapéu d’Uvas como estado mesotrófico. Os resultados se mostraram satisfatórios para a espacialização e análise temporal da concentração de clorofila-a, a correlação com os dados de evaporação nos permitiu observar uma compatibilidade direta com a concentração do componente e verificou-se valores de clorofila-a acima da média do reservatório nas regiões de entradas de água pelos riachos e próximos as margens com menos cobertura de vegetação.Determination of Chlorophyll-a Concentration from Remote Sensing in Chapéu d’Úvas Reservoir (State of Minas Gerais, Brazil) A B S T R A C TCurrently, one of the great impacts on the freshwater reservoirs is eutrophication, which directly affects the treatment and use of water for public water supply, navigation, aquatic fauna and flora and visual impact. Chlorophyll-a is one of the water trophic state indicators and it can be determined using remote sensing. Thus, this study aimed to determine chlorophyll-a concentration in Chapéu d’Uvas dam, in Juiz de Fora (Brazil), one of the main water sources of public water supply for the city. From a model that uses Sentinel-2 satellite images, the spatial-temporal behavior of that component concentration was evaluated and correlated with data regarding rainfall, temperature, evaporation, and soil use and occupation around the dam. A model was also applied to determine trophic state index, which presents the body of water trophic state, classifying Chapéu d’Uvas as mesotrophic state. The results were satisfactory regarding spatialization and temporal analysis of chlorophyll-a concentration. The correlation with evaporation data permitted us to observe a direct correspondence with the component concentration. Chlorophyll-a values higher than the reservoir average were found in creek inlets and near the shore with lower vegetal cover.Keywords: eutrophication, Sentinel-2, quality of water, inland waters, trophic state

Estimation Model of Chlorophyll-a Concentration Based on Continuous Wavelet Coefficient

2021 ◽  
Vol 58 (8) ◽  
pp. 0828002
Author(s):  
彭咏石 Peng Yongshi ◽  
陈水森 Chen Shuisen ◽  
陈金月 Chen Jinyue ◽  
赵晶 Zhao Jing ◽  
王重洋 Wang Chongyang ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Wavelet Coefficient ◽  
Continuous Wavelet ◽  
Estimation Model ◽  
Chlorophyll A Concentration

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 Remote sensing estimation of aquatic chlorophyll-a concentration based on Hyperion data in Lake Taihu

2006 ◽  
Vol 18 (4) ◽  
pp. 327-336 ◽  
Author(s):  
WEN Jianguang ◽  
◽  
XIAO Qing ◽  
YANG Yipeng ◽  
LIU Qinhuo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Lake Taihu ◽  
Chlorophyll A Concentration ◽  
Hyperion Data

scholarly journals Analysis Comparison of Algorithms for Determination Concentration of Chlorophyll-a in Traditional and Intensive Milkfish Ponds Using LANDSAT 8 Images

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Nurhadi Bashit ◽  
Abdi Sukmono ◽  
Baskoro Agum Gumelar
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Coastal Area ◽  
Average Concentration ◽  
The Body ◽  
Landsat 8 ◽  
Northern Coast ◽  
Fish Production ◽  
Remote Sensing Technology ◽  
Sensing Technology

Indonesia is an Archipelago Country because the Country of Indonesia consists of many islands stretching from Sabang in the west to the island of Merauke on the east. The Archipelago Country also comes from the old name of the Indonesian Country called Nusantara, because Nusantara is a country that consists of many islands. Indonesia is an Archipelago Country which means it has potential resources in the coastal areas, one of which is found on the northern coast of Java. The coastal area is an important area to be reviewed, one of which is the use of coastal resources by paying attention to the condition of the ecosystem that remains stable. Opportunities for coastal area utilization in the field of fisheries are in the form of fishing activities or fish farming, especially pond cultivation activities. Based on data from the Department of Marine and Fisheries of the Province of Central Java in 2010, pond cultivation is one of the potential resources on the coast. This potential is supported by the government to increase fish production in order to increase the consumption of fish in the community. Therefore, it is necessary to choose the most effective method of pond cultivation between traditional methods and intensive methods to optimize fish production. One indicator of effectiveness between the two methods can be seen from the phytoplankton distribution. Phytoplankton contains chlorophyll-a in the body and is a natural food from fish. Phytoplankton provides important ecological functions for the aquatic life cycle by serving as the basis of food webs in water. Phytoplankton also functions as the main food item in freshwater fish culture and seawater fish cultivation. Therefore, it is necessary to know the chlorophyll-a concentration in the ponds of traditional and intensive methods to determine the concentration chlorophyll-a of the two pond methods. One method used to determine the concentration of chlorophyll-a using remote sensing technology. Remote sensing technology can be used to determine the concentration of chlorophyll-a using the Wouthuyzen, Wibowo, Pentury, Much Jisin Arief and Lestari Laksmi algorithms. The results showed that the Pentury algorithm was relatively better to determine the concentration of chlorophyll-a in shallow waters (ponds). The lowest concentration of chlorophyll-a in traditional ponds is 0.47068 mg/m3, the highest concentration is 1.95017 mg/m3 and the average concentration is 1.12893 mg/m3, while in intensive ponds the lowest concentration is 0.36713 mg/m3, the concentration the highest is 3.17063 mg/m3 and the average concentration is 1.53556 mg/m3.

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.

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