Coastal water quality dynamics of the Red Sea, southeast coast of Egypt using GeoAI and ChatGPT

The Red Sea coastal environment of Halayeb and Shalateen area is renowned for its abundant marine flora and fauna. It also holds significant economic and cultural importance for local communities. However, this region is currently confronted with various challenges, including climate change and habitat destruction. To effectively address and mitigate these issues, advanced technologies that offer a holistic understanding of the area's environmental conditions are required. This paper applies the integration of Geospatial Artificial Intelligence (GeoAI) and ChatGPT to study the Red Sea Coastal water quality dynamics of Halayeb and Shalateen Area. Landsat imagery and Copernicus Marine Service were used to retrieve area boundaries and monitor the physicochemical characteristics of the coastal water respectively. ChatGPT was utilized to generate Python code that facilitates the creation of optimal distribution maps for each physical and chemical property criterion. The Python codes were incorporated into the Python program within the ArcGIS 10.7.1 and executed to generate the desired maps representing the dynamics of physical and chemical properties. It was found an observed fluctuation in chemical properties next to the coastline around the mouth of two main wadies; Wadi Hudain, and Wadi Da'eb. The degree of stability increased away from the coast toward the deep water. That proved the effect of the runoff on the seawater, as the runoff plays an essential role in the water state, especially in such semi-closed water bodies like the Red Sea where the flashfloods are the main source that can enrich water with sediment and nutrients. The state of seawater in terms of physical properties was not characterized by a specific pattern. The distribution of physical parameters in the Red Sea is influenced by factors such as regional climate variations , monsoonal winds, and local topography. This paper serves as a stepping stone for future research endeavors, exploring the full potential of this integrated approach. It can be concluded that the fusion of GeoAI and ChatGPT technologies has the potential to revolutionize our approach to studying and managing the coastal environment.

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Publication Details

Journal
Journal of African Earth Sciences
Published
2024-08-30
DOI
https://doi.org/10.1016/j.jafrearsci.2024.105409
Citations
5
Primary Topic
Coastal and Marine Management
Type
article
Field-Weighted Citation Impact
3.55

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article

Coastal water quality dynamics of the Red Sea, southeast coast of Egypt using GeoAI and ChatGPT

Ahmed El-Zeiny, Mohamed Alkhuzamy Aziz, Doaa M. Naguib, Fayrouz M. Hassan
5 citations
Journal of African Earth Sciences
Coastal and Marine Management
3.55
article

Coastal water quality dynamics of the Red Sea, southeast coast of Egypt using GeoAI and ChatGPT

Ahmed El-Zeiny, Mohamed Alkhuzamy Aziz, Doaa M. Naguib, Fayrouz M. Hassan
article en
5 citations

Abstract

The Red Sea coastal environment of Halayeb and Shalateen area is renowned for its abundant marine flora and fauna. It also holds significant economic and cultural importance for local communities. However, this region is currently confronted with various challenges, including climate change and habitat destruction. To effectively address and mitigate these issues, advanced technologies that offer a holistic understanding of the area's environmental conditions are required. This paper applies the integration of Geospatial Artificial Intelligence (GeoAI) and ChatGPT to study the Red Sea Coastal water quality dynamics of Halayeb and Shalateen Area. Landsat imagery and Copernicus Marine Service were used to retrieve area boundaries and monitor the physicochemical characteristics of the coastal water respectively. ChatGPT was utilized to generate Python code that facilitates the creation of optimal distribution maps for each physical and chemical property criterion. The Python codes were incorporated into the Python program within the ArcGIS 10.7.1 and executed to generate the desired maps representing the dynamics of physical and chemical properties. It was found an observed fluctuation in chemical properties next to the coastline around the mouth of two main wadies; Wadi Hudain, and Wadi Da'eb. The degree of stability increased away from the coast toward the deep water. That proved the effect of the runoff on the seawater, as the runoff plays an essential role in the water state, especially in such semi-closed water bodies like the Red Sea where the flashfloods are the main source that can enrich water with sediment and nutrients. The state of seawater in terms of physical properties was not characterized by a specific pattern. The distribution of physical parameters in the Red Sea is influenced by factors such as regional climate variations , monsoonal winds, and local topography. This paper serves as a stepping stone for future research endeavors, exploring the full potential of this integrated approach. It can be concluded that the fusion of GeoAI and ChatGPT technologies has the potential to revolutionize our approach to studying and managing the coastal environment.

Journal of African Earth SciencesVol. 219
National Authority for Remote Sensing and Space Sciences (EG), Ain Shams University (EG), Fayoum University (EG)
U.S. Geological Survey
Life below water
Openalex Percentile: Top 8%
Coastal and Marine Management
3.55
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