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Japanese literature organization and spatiotemporal database system creation for natural disaster analysis

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Bibliographic Details
Title: Japanese literature organization and spatiotemporal database system creation for natural disaster analysis
Authors: Bing Lyu, Xuebin Yue, Lin Meng
Source: Heritage Science, Vol 12, Iss 1, Pp 1-20 (2024)
Publisher Information: SpringerOpen, 2024.
Publication Year: 2024
Collection: LCC:Fine Arts
LCC:Analytical chemistry
Subject Terms: Disaster data organization, Character extraction, Character recognition, Disaster analysis, Disaster spatiotemporal database system, Fine Arts, Analytical chemistry, QD71-142
Description: Abstract Japan is one of the countries with the most frequent natural disasters in the world and is faced with various threats of natural disasters every year, which significantly impact Japan’s social economy and people’s lives. A great deal of information about disasters is preserved in Japanese literature. Interpreting and organizing this information help us to analyze the regularity of disasters and understand the preventive measures of ancient people. This paper aims to organize, analyze and save disaster data by collecting various information about disasters. Then a disaster spatiotemporal database system is constructed by using deep learning, image processing, and database technology. The system consists of two parts, namely, the disaster database and disaster website. The disaster database is the core of the whole system, which saves the disaster data after organizing and summarizing. The database collects disaster information from various sources, including key information such as disaster type, time, location, scale, and scope of impact. The Disaster website is the system’s user interface, providing an interactive platform for users to access and use disaster data easily. The website has many functions, including search, visual display, disaster information query, etc. We also make a detailed analysis of the collected data, aiming to predict the causes and occurrence rules of disasters so as to achieve the target of disaster prediction.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2050-7445
Relation: https://doaj.org/toc/2050-7445
DOI: 10.1186/s40494-024-01132-5
Access URL: https://doaj.org/article/8d68b5f403ab4098b1c3c8933028eaa4
Accession Number: edsdoj.8d68b5f403ab4098b1c3c8933028eaa4
Database: Directory of Open Access Journals
Description
Abstract:Abstract Japan is one of the countries with the most frequent natural disasters in the world and is faced with various threats of natural disasters every year, which significantly impact Japan’s social economy and people’s lives. A great deal of information about disasters is preserved in Japanese literature. Interpreting and organizing this information help us to analyze the regularity of disasters and understand the preventive measures of ancient people. This paper aims to organize, analyze and save disaster data by collecting various information about disasters. Then a disaster spatiotemporal database system is constructed by using deep learning, image processing, and database technology. The system consists of two parts, namely, the disaster database and disaster website. The disaster database is the core of the whole system, which saves the disaster data after organizing and summarizing. The database collects disaster information from various sources, including key information such as disaster type, time, location, scale, and scope of impact. The Disaster website is the system’s user interface, providing an interactive platform for users to access and use disaster data easily. The website has many functions, including search, visual display, disaster information query, etc. We also make a detailed analysis of the collected data, aiming to predict the causes and occurrence rules of disasters so as to achieve the target of disaster prediction.
ISSN:20507445
DOI:10.1186/s40494-024-01132-5