Home

Welcome to the APRIL wiki!

Description

Analysis of Coastal Risk Perception in Occitanie (A.P.Ri.L: Analyse de la Perception des Risques Littoraux en Occitanie)

Coastal areas are facing increasing risks due to climate change, including rising sea levels, coastal erosion, and extreme weather events such as storms and flooding. Understanding how various stakeholders—such as local communities, policy makers, businesses, and environmental organizations—perceive these risks is crucial for informed decision-making and effective coastal management strategies. The A.P.Ri.L. (Analyse de la Perception des Risques Littoraux en Occitanie) project seeks to fill this gap by conducting a detailed analysis of coastal risk perception in the Occitanie region, located in southern France, which has a significant and vulnerable coastline.

The APRIL project aims to collect a representative corpus of textual data from diverse web-based sources, including news articles, government reports, blog posts, social media, and scientific literature. This data collection is intended to capture a wide range of perspectives on coastal risks—such as erosion, flooding, and habitat loss—within the region. By gathering this data, the project aspires to develop a comprehensive understanding of the concerns, priorities, and awareness levels of different stakeholder groups.

Using advanced Natural Language Processing (NLP) techniques, the project will analyze the collected data to identify key themes, concerns, and the emotional tone of discourse around coastal risks. For instance, it will evaluate whether stakeholders view coastal risks as urgent or manageable, what measures they believe are necessary, and how they perceive the role of government or private actors in managing these risks. By structuring and analyzing this information, the project will provide valuable insights into the perceptions of coastal risks at both local and regional levels.

The goal of the APRIL project is not just to create a static snapshot of risk perception but to offer an evolving analysis that can inform adaptive coastal management policies. Insights derived from the project will help guide local authorities in designing and implementing policies that reflect the needs and concerns of the population. Furthermore, this project contributes to greater public awareness of coastal risks by highlighting areas where perception might differ from scientific risk assessments, thus helping to bridge the gap between science, policy, and public understanding.

As part of its methodology, the APRIL project emphasizes the ethical use of data, ensuring that the sources of information are transparent and respect data privacy regulations. Data collected from public sources will be handled with strict adherence to ethical guidelines to avoid infringing on the privacy of individuals or violating the terms of service of websites.

Ultimately, by combining web scraping, data analysis, and stakeholder engagement, the APRIL project provides a robust framework for understanding coastal risk perception in Occitanie. The findings will be crucial for informing both short-term interventions, such as emergency preparedness, and long-term strategies, such as coastal zone management and land-use planning, aimed at reducing vulnerability to coastal risks.

Objectives

• Develop a program that generates a sufficiently comprehensive corpus based on input parameters provided by the users.
• Develop a program that allows filtering (selection and extraction), tagging, and visualizing the corpus according to various criteria.

Success Criteria

• Recall rate (number of documents found compared to the number of existing documents) → Issue of unknown information on existing content.
• Number of documents by location? (minimum of 50 for at least 70% of the locations).
• Number of documents by keywords? (minimum of 1, less critical than the previous one).

Authors

• thibaut-dst: Spearheaded the design, system architecture, NLP feature development, frontend and UI/UX design.

• l-gou: Led the project, NLP features, managed documentation, and handled testing efforts.

• theoP17: Worked on frontend development and conducted research on available options and best practices.

• antoinebtb: Focused on backend development and API integration.

• pharaoph09: Contributed to backend development and wrote documentation.