Monitoring coastal water quality using trios ramses hyperspectral reflectance data

The coastal area is very strategic as the center of national economic activity. Coastal areas that have strategic value from the potential of aquatic resources and environmental services, among others, are located on the northern coast of the Java Sea, one of which is Muaragembong. The Muaragembong...

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Main Authors: Adawiah Syifa W., Supriatna, Massita M.M.
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:BIO Web of Conferences
Online Access:https://www.bio-conferences.org/articles/bioconf/pdf/2024/08/bioconf_srcm2024_01009.pdf
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author Adawiah Syifa W.
Supriatna
Massita M.M.
author_facet Adawiah Syifa W.
Supriatna
Massita M.M.
author_sort Adawiah Syifa W.
collection DOAJ
description The coastal area is very strategic as the center of national economic activity. Coastal areas that have strategic value from the potential of aquatic resources and environmental services, among others, are located on the northern coast of the Java Sea, one of which is Muaragembong. The Muaragembong coast in general has a problem of decreasing water quality. One of the water quality parameters that is often used to measure conditions in the field is Total Suspended Solid (TSS). Monitoring the concentration of TSS in a waters can be done through an approach, namely the development of an empirical model using remote sensing data. In addition to satellite imagery data, remote sensing data can also be performed by measuring the spectral reflection of an aquatic object using a tool called a radiometer. This study aims to build an empirical model using TRIO RAMSES data which is simulated into a combination of wavelengths from the Sentinel 2 and Landsat 8 bands to be able to estimate TSS concentrations in waters.The results showed that Reflectance Remote Sensing (Rrs) from TRIOS RAMSES data which was simulated into the wavelength range of Sentinel 2A image data was able to build an empirical model using multivariate band combinations. The results obtained on Sentinel 2 imagery show an R2 value of 0.68 and RMSE 113.04 mg/L.
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spelling doaj.art-c817179e53ff4db0a4c9fdd8964fd6332024-01-26T09:39:22ZengEDP SciencesBIO Web of Conferences2117-44582024-01-01890100910.1051/bioconf/20248901009bioconf_srcm2024_01009Monitoring coastal water quality using trios ramses hyperspectral reflectance dataAdawiah Syifa W.0Supriatna1Massita M.M.2Deputy for Development Policy-BRINFaculty of Mathematics and Natural Sciences, University of IndonesiaFaculty of Mathematics and Natural Sciences, University of IndonesiaThe coastal area is very strategic as the center of national economic activity. Coastal areas that have strategic value from the potential of aquatic resources and environmental services, among others, are located on the northern coast of the Java Sea, one of which is Muaragembong. The Muaragembong coast in general has a problem of decreasing water quality. One of the water quality parameters that is often used to measure conditions in the field is Total Suspended Solid (TSS). Monitoring the concentration of TSS in a waters can be done through an approach, namely the development of an empirical model using remote sensing data. In addition to satellite imagery data, remote sensing data can also be performed by measuring the spectral reflection of an aquatic object using a tool called a radiometer. This study aims to build an empirical model using TRIO RAMSES data which is simulated into a combination of wavelengths from the Sentinel 2 and Landsat 8 bands to be able to estimate TSS concentrations in waters.The results showed that Reflectance Remote Sensing (Rrs) from TRIOS RAMSES data which was simulated into the wavelength range of Sentinel 2A image data was able to build an empirical model using multivariate band combinations. The results obtained on Sentinel 2 imagery show an R2 value of 0.68 and RMSE 113.04 mg/L.https://www.bio-conferences.org/articles/bioconf/pdf/2024/08/bioconf_srcm2024_01009.pdf
spellingShingle Adawiah Syifa W.
Supriatna
Massita M.M.
Monitoring coastal water quality using trios ramses hyperspectral reflectance data
BIO Web of Conferences
title Monitoring coastal water quality using trios ramses hyperspectral reflectance data
title_full Monitoring coastal water quality using trios ramses hyperspectral reflectance data
title_fullStr Monitoring coastal water quality using trios ramses hyperspectral reflectance data
title_full_unstemmed Monitoring coastal water quality using trios ramses hyperspectral reflectance data
title_short Monitoring coastal water quality using trios ramses hyperspectral reflectance data
title_sort monitoring coastal water quality using trios ramses hyperspectral reflectance data
url https://www.bio-conferences.org/articles/bioconf/pdf/2024/08/bioconf_srcm2024_01009.pdf
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