Assessment of biological and physic chemical water quality parameters using Landsat 8 time series

2018 ◽  
Author(s):  
Gordana Jakovljevic ◽  
Miro Govedarica ◽  
Flor Álvarez Taboada
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Landsat 8 ◽  
Chemical Water

scholarly journals Detecting spatiotemporal variability in the physicochemical properties of water in the Lower Mearim using remote sensing data

2020 ◽  
Vol 42 ◽  
pp. e32
Author(s):  
George Colares Silva Filho ◽  
Juliana Martins dos Santos ◽  
Paulo Cesar Mendes Villis ◽  
Ingrid Santos Gonçalves ◽  
Isael Coelho Correia ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Physicochemical Properties ◽  
Monitoring Program ◽  
Remote Sensing Data ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Spatiotemporal Variability ◽  
Landsat 8 ◽  
Solids Content

Natural or anthropogenic chemical compounds of different origins often accumulate in estuarine regions. These compounds may alter the water quality. Therefore, It is important to constantly monitor the quality of estuarine regions. A combination of remote sensing and traditional sampling can lead to a better monitoring program for water quality parameters. The objective of this work is to assess the spatiotemporal variability of the physicochemical properties of water in the lower region of the Mearim River and estimate water quality parameters via remote sensing. Samples were collected at 16 points, from Baixo Arari to the mouth of the watershed, using a multiparameter meter and Landsat 8 satellite images. The physicochemical parameters of the water had high salinity levels, between 2.30 and 20.10 parts per trillion; a high total dissolved solids content, between 2.77 and 19.70 g/L; and minimum dissolved oxygen values. Estimating the physicochemical properties of the water via remote sensing proved feasible, particularly in the dry season when there is less cloud cover.

Water quality in two catchment areas: a case study of Crocodile (West) and Berg Catchment areas

2014 ◽  
Vol 9 (4) ◽  
pp. 526-533
Author(s):  
S. A. Akinseye ◽  
J. T. Harmse
Keyword(s):  
Water Quality ◽  
Catchment Area ◽  
Pearson Correlation ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Western Cape ◽  
Catchment Areas ◽  
Domestic Use ◽  
Physical And Chemical ◽  
Chemical Water

This study focuses on the different physical and chemical water quality parameters of two catchment areas centring on the extent of water pollution in the two basins. Data containing physical and chemical water quality parameters for the Crocodile (West) Catchment area (Gauteng) and the Berg Catchment area (Western Cape) at reconnaissance level of detail were collected from the Department of Water Affairs (DWA) over a period of 5 years, 2007–2011. The relevant data were screened and sorted using the SPSS Software Version 2.0. The data were subjected to ANOVA statistics to search for significant variations in the water quality parameters of concern across the study period in each of the catchment area. The physical and chemical analyses were carried out to determine whether the water quality falls within the total water quality range as prescribed by DWA and WHO for domestic use. Pearson correlation analyses were used to determine the relationship between physical and chemical water quality parameters and the rainfall data over the study period.

scholarly journals Monitoring water quality parameters of Lake Koronia by means of long time-series multispectral satellite images

2017 ◽  
Vol 52 (2) ◽  
pp. 176-188
Author(s):  
Triantafyllia-Maria Perivolioti ◽  
Antonios Mouratidis ◽  
Dimitra Bobori ◽  
Georgia Doxani ◽  
Dimitrios Terzopoulos
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Satellite Images ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Long Time Series ◽  
Multispectral Satellite Images ◽  
Long Time

scholarly journals ESTIMATION OF WATER QUALITY IN A RESERVOIR FROM SENTINEL-2 MSI AND LANDSAT-8 OLI SENSORS

2020 ◽  
Vol V-3-2020 ◽  
pp. 401-408
Author(s):  
F. M. C. Pizani ◽  
P. Maillard ◽  
A. F. F. Ferreira ◽  
C. C. de Amorim
Keyword(s):  
Water Quality ◽  
Multiple Regression ◽  
Regression Models ◽  
Quality Parameters ◽  
Optically Active ◽  
Water Quality Parameters ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Multiple Regression Models ◽  
Sentinel 2

Abstract. The low operational cost of using freely available remote sensing data is a strong incentive for water agencies to complement their field campaigns and produce spatially distributed maps of some water quality parameters. The objective of this study is to compare the performance of Sentinel-2 MSI and Landsat-8 OLI sensors to produce multiple regression models of water quality parameters in a hydroelectric reservoir in Brazil. Physical-chemistry water quality parameters were measured in loco using sensors and also analysed in laboratory from water samples collected simultaneously. The date of sampling corresponded to the almost simultaneous overflight of Sentinel-2B and Landsat-8 satellites which provided a means to perform a fair comparison of the two sensors. Four optically active parameters were considered: chlorophyll-a, Secchi disk depth, turbidity and temperature (the latter using Landsat-8 TIR sensor). Other six optically non-active parameters were also considered. The multiple regression models used the spectral reflectance bands from both sensors (separately) as predictors. The reflectance values were based on averaging kernels of 30 m and 90 m. Stepwise variable selection combined with a priori knowledge based on other studies were used to optimize the choice of predictors. With the exception of temperature, the other optically active parameters yielded strong regression models from both the Sentinel and Landsat sensors, all with r2 > 0.75. The models for the optically non-active parameters produced less striking results with r2 as low as 0.03 (temperature) and as high or better than > 0.8 (pH and Dissolved oxygen).

scholarly journals Epilithic Diatom Abundance Study in the Batang Kuranji River in Padang City, West Sumatra

2020 ◽  
Vol 4 (2) ◽  
pp. 39
Author(s):  
Mida Yulia Murni
Keyword(s):  
Water Quality ◽  
Quality Parameters ◽  
Inorganic Materials ◽  
Water Quality Parameters ◽  
Dominant Group ◽  
West Sumatra ◽  
Almost All ◽  
Physical And Chemical ◽  
Epilithic Diatom ◽  
Chemical Water

A study about abundant of epilithic diatom was conducted on 2017 in Kuranji River. The objective of this study was to clarify species and abundant of epilithic diatom in Batang Kuranji River. Samples were collected in 3 stations by purposive sampling and brushing method. The results showed that totally 82 species in 22 genera had been found. The total abundant of epilithic diatom was 15139,26 individual/cm2. The highest abundance of epilithic diatom was found in station I (Batu Busuak) and the lowest in station III (Sawah Liek). Synedra sp and Fragillaria sp were dominant group of diatoms which are found in almost all sites. Some physical and chemical water quality parameters were showed that Batang Kuranji River were polluted slightly by organic and inorganic materials.

Determination of water quality parameters in the Tan Rai exploiting area (Lam Dong province) using Sentinel-2 msi and Landsat 8 data

2020 ◽  
Vol 61 (2) ◽  
pp. 126-134
Author(s):  
Nghia Viet Nguyen ◽  
Hung Le Trinh ◽  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Secchi Depth ◽  
Great Influence ◽  
Surface Water Quality ◽  
Mining Area ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Landsat 8 ◽  
Optical Remote Sensing

Despite high profits, the mining process often leads to negative effects on the quality of groundwater around the mining site. Due to the close relationship between the concentration of water quality parameters and spectral reflectance values of surface watẻ, optical remote sensing image has been used effectively in the world in assessing and monitoring surface water quality. This paper presents the results of determining some surface water quality parameters in the Tan Rai bauxite mining area (Lam Dong province) such as turbidity, water-transparency (Secchi depth), and surface temperature from Sentinel-2A and Landsat 8 images taken on January 29, 2019. The results obtained in this study show that the mining process has a great influence on the surface water quality in Tan Rai (Lam Dong), reflected in all three water quality parameters such as turbidity, Secchi depth, and water temperature.

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