RETRACTED ARTICLE: Coastal atmospheric characteristics and research and study travel resource planning based on geographic information system

• Published in: Arabian journal of geosciences Vol. 14; no. 12
• Main Author: Dong, Yuan
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 2021; Springer Nature B.V
• Subjects: Atmospheric conditions; Atmospheric diffusion; Atmospheric models; Coastal zone; Data acquisition; Diffusion; Earth and Environmental Science; Earth Sciences; Environment and Low Carbon Transportation; Geographic information systems; Geographical information systems; Geography; Information systems; Original Paper; Pollutants; Pollution; Remote sensing; Storage; Technology; Tourism; Training; Research trip; Geographic information system; Atmospheric characteristics; Polluted meteorology; Coastal area
• ISSN: 1866-7511; 1866-7538
• DOI: 10.1007/s12517-021-07414-7

With the continuous development of science and technology, remote sensing technology has also developed relatively perfect. Combining remote sensing science and computer technology, and then applying some geography knowledge in it, can form a practical system—Geographic Information System. The storage function of this system is very convenient and fast, and it can also analyze the characteristics and attributes of geographic space in real time. At present, its application range has been very extensive. This research is mainly aimed at planning the atmospheric conditions and tourism resources in coastal areas, and has carried out some research in combination with related requirements. We want to use existing technology to simulate atmospheric diffusion and establish related models, and visualize the results, so that we can intuitively see the range and concentration of pollutants after diffusion. To realize these functions, we need to carry out a lot of research work in combination with the characteristics of pollution and the law of diffusion and related knowledge of geography. This model can also realize the exchange of data, which can greatly reduce the possibility of errors. At the same time, the model automatically classifies and weights the acquired data, and judges the air condition level based on the total score obtained. At the end of the experiment, we put forward relevant research strategies for some regional training methods, hoping to improve people's will and take practical measures to ensure the smooth development of research activities. At the same time, we have also conducted a large number of experiments and speeches to promote our research content.