{"title":"利用 GeoAI 和 ChatGPT 研究埃及东南海岸红海的沿海水质动态","authors":"","doi":"10.1016/j.jafrearsci.2024.105409","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":14874,"journal":{"name":"Journal of African Earth Sciences","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Coastal water quality dynamics of the Red Sea, southeast coast of Egypt using GeoAI and ChatGPT\",\"authors\":\"\",\"doi\":\"10.1016/j.jafrearsci.2024.105409\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":14874,\"journal\":{\"name\":\"Journal of African Earth Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of African Earth Sciences\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1464343X24002425\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of African Earth Sciences","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1464343X24002425","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
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.
期刊介绍:
The Journal of African Earth Sciences sees itself as the prime geological journal for all aspects of the Earth Sciences about the African plate. Papers dealing with peripheral areas are welcome if they demonstrate a tight link with Africa.
The Journal publishes high quality, peer-reviewed scientific papers. It is devoted primarily to research papers but short communications relating to new developments of broad interest, reviews and book reviews will also be considered. Papers must have international appeal and should present work of more regional than local significance and dealing with well identified and justified scientific questions. Specialised technical papers, analytical or exploration reports must be avoided. Papers on applied geology should preferably be linked to such core disciplines and must be addressed to a more general geoscientific audience.