Remote sensing Technology (MODIS) for Extraction Sea surface Salinity Season Variation: Red Sea Saudi Arabia

Sea Surface Salinity model has been applied for high-intensity, short-duration SSS estimation, classification and mapping of SSS from MODIS Satellite data, which are in turn useful for fish potential zone mapping and forecasting, marine management, and improved contingency planning provided that more detailed geophysical studies are concurrently implemented. The outputs of this study are also important for early warning when it is foreseen that unfavorable changes in oceanographic conditions that can affect fish catch may happen. MODIS data demonstrates the ability of signature value in quantifying and predicting the relationships between these parameters, and will so help track the changes in these parameters from time to time for early warning in case of any non-desirable foreseen changes in any or all of these parameters. This type of model also helps for accurate monitoring of large coverage areas at low cost and within short periods of time. Such model furthermore allows prediction of the total fish catch in the different seasons, thus contributing to fish industry management and marketing. This research recommends use of the generated SSS map for mass scale fish harvesting in short time from large areas. The SSS map was carried out off the Yanbu and Jeddah cost of Red sea, Saudi Arabia as there was sufficient In-situ SSS data for accuracy assessment. The Roˆ was computed as 0.92 and the higher SSS have coincided very well with the higher SSS value, meaning the tool is ready for use for extraction salinity and chlorophyll.

Publication Details

Journal
مجلة کلیة الآداب القاهرة
Published
2024-10-01
DOI
https://doi.org/10.70216/2682-485x.1680
Primary Topic
Advanced Computational Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Remote sensing Technology (MODIS) for Extraction Sea surface Salinity Season Variation: Red Sea Saudi Arabia

مجلة کلیة الآداب القاهرة
Advanced Computational Techniques and Applications
article

Remote sensing Technology (MODIS) for Extraction Sea surface Salinity Season Variation: Red Sea Saudi Arabia

article en

Abstract

Sea Surface Salinity model has been applied for high-intensity, short-duration SSS estimation, classification and mapping of SSS from MODIS Satellite data, which are in turn useful for fish potential zone mapping and forecasting, marine management, and improved contingency planning provided that more detailed geophysical studies are concurrently implemented. The outputs of this study are also important for early warning when it is foreseen that unfavorable changes in oceanographic conditions that can affect fish catch may happen. MODIS data demonstrates the ability of signature value in quantifying and predicting the relationships between these parameters, and will so help track the changes in these parameters from time to time for early warning in case of any non-desirable foreseen changes in any or all of these parameters. This type of model also helps for accurate monitoring of large coverage areas at low cost and within short periods of time. Such model furthermore allows prediction of the total fish catch in the different seasons, thus contributing to fish industry management and marketing. This research recommends use of the generated SSS map for mass scale fish harvesting in short time from large areas. The SSS map was carried out off the Yanbu and Jeddah cost of Red sea, Saudi Arabia as there was sufficient In-situ SSS data for accuracy assessment. The Roˆ was computed as 0.92 and the higher SSS have coincided very well with the higher SSS value, meaning the tool is ready for use for extraction salinity and chlorophyll.

مجلة کلیة الآداب القاهرةVol. 84(4)
Life below water
Openalex Percentile: Top 73%
Advanced Computational Techniques and Applications
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.

Remote sensing Technology (MODIS) for Extraction Sea surface Salinity Season Variation: Red Sea Saudi Arabia · مجلة کلیة الآداب القاهرة (2024) | TGRS Research Map | TGRS