Identifikasi dan Pemetaan Konsentrasi Salinitas dan Suhu Permukaan Laut di Pesisir Kabupaten Probolinggo dengan Data Citra Satelit Landsat-8

The coastal area of ​​Probolinggo City is flowed by six rivers, namely the Kedunggaleng River, Umbul River, Banger River, Legundi River, Kasbah River and Pancur River. With an average flow length reaching 3.80 km. The river flows throughout the year from the south to the north according to the slope of the coastal area of ​​Probolinggo City. These activities can result in interactions between fresh water and sea water. This interaction influences the distribution pattern of salinity and sea surface temperature in the Probolinggo Coastal waters. Salinity and sea surface temperature are one of the biggest factors causing corrosion in the sea which can damage building structures around the sea. Based on this background, research is needed to monitor the distribution of salinity and sea surface temperature values ​​for 2020 to 2024 on the Probolinggo Coast using Landsat-8 satellite imagery. In this research, direct sample collection and measurement were used, for measuring salinity values ​​a Refractometer was used for sea surface temperature using an Infrared Thermometer. After data collection, regression and ANOVA tests were carried out on the data with the aim of finding out whether there were differences in in-situ data with sensor data from Landsat-8 satellite imagery. The results of the algorithm modeling were obtained, the algorithm model for processing image salinity was the Band_3 wavelength with the Logarithmic equation with y = 10.534ln(x) + 58.369 and the degree of determination value R^2 = 0.2499. Meanwhile, for sea surface temperature, the Exponential equation is y = 25.637e^3.1286x and the degree of determination R^2 = 0.0847. The analysis results from the ANOVA test for the H1 salinity value are accepted, meaning there is a significant difference between the in situ salinity value and the Landsat-8 satellite image salinity value from 2020 to 2024. Meanwhile, for the H1 sea surface temperature, it is accepted, meaning there is a significant difference between in situ SST and Satellite image SST from 2020 to 2024.

Authors

Institutions

Publication Details

Journal
Reslaj Religion Education Social Laa Roiba Journal
Published
2024-12-02
DOI
https://doi.org/10.47467/reslaj.v6i12.4793
Primary Topic
Marine and Coastal Ecosystems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifikasi dan Pemetaan Konsentrasi Salinitas dan Suhu Permukaan Laut di Pesisir Kabupaten Probolinggo dengan Data Citra Satelit Landsat-8

Indra Yoganata, Siti Zainab
Reslaj Religion Education Social Laa Roiba Journal
Marine and Coastal Ecosystems
article

Identifikasi dan Pemetaan Konsentrasi Salinitas dan Suhu Permukaan Laut di Pesisir Kabupaten Probolinggo dengan Data Citra Satelit Landsat-8

Indra Yoganata, Siti Zainab
article en

Abstract

The coastal area of ​​Probolinggo City is flowed by six rivers, namely the Kedunggaleng River, Umbul River, Banger River, Legundi River, Kasbah River and Pancur River. With an average flow length reaching 3.80 km. The river flows throughout the year from the south to the north according to the slope of the coastal area of ​​Probolinggo City. These activities can result in interactions between fresh water and sea water. This interaction influences the distribution pattern of salinity and sea surface temperature in the Probolinggo Coastal waters. Salinity and sea surface temperature are one of the biggest factors causing corrosion in the sea which can damage building structures around the sea. Based on this background, research is needed to monitor the distribution of salinity and sea surface temperature values ​​for 2020 to 2024 on the Probolinggo Coast using Landsat-8 satellite imagery. In this research, direct sample collection and measurement were used, for measuring salinity values ​​a Refractometer was used for sea surface temperature using an Infrared Thermometer. After data collection, regression and ANOVA tests were carried out on the data with the aim of finding out whether there were differences in in-situ data with sensor data from Landsat-8 satellite imagery. The results of the algorithm modeling were obtained, the algorithm model for processing image salinity was the Band_3 wavelength with the Logarithmic equation with y = 10.534ln(x) + 58.369 and the degree of determination value R^2 = 0.2499. Meanwhile, for sea surface temperature, the Exponential equation is y = 25.637e^3.1286x and the degree of determination R^2 = 0.0847. The analysis results from the ANOVA test for the H1 salinity value are accepted, meaning there is a significant difference between the in situ salinity value and the Landsat-8 satellite image salinity value from 2020 to 2024. Meanwhile, for the H1 sea surface temperature, it is accepted, meaning there is a significant difference between in situ SST and Satellite image SST from 2020 to 2024.

Reslaj Religion Education Social Laa Roiba JournalVol. 6(12)
University of Pembangunan Nasional Veteran Jawa Timur (ID)
Life below water
Openalex Percentile: Top 78%
Marine and Coastal Ecosystems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.