ids-drr-assam-risk-model

Intelligent Data Solution - Disaster Risk Reduction is a system to assist flood management in the state of Assam through data-driven ways. The repository contains codes to extract relevant datasets and the modelling approach used to calculate Risk Scores for each revenue circle in Assam.

https://github.com/civicdatalab/ids-drr-assam-risk-model

Science Score: 26.0%

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    Low similarity (11.3%) to scientific vocabulary

Keywords

data-engineering data-science disaster-management flood-mapping gis remote-sensing

Scientific Fields

Artificial Intelligence and Machine Learning Computer Science - 40% confidence
Last synced: 4 months ago · JSON representation

Repository

Intelligent Data Solution - Disaster Risk Reduction is a system to assist flood management in the state of Assam through data-driven ways. The repository contains codes to extract relevant datasets and the modelling approach used to calculate Risk Scores for each revenue circle in Assam.

Basic Info
  • Host: GitHub
  • Owner: CivicDataLab
  • License: agpl-3.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 839 MB
Statistics
  • Stars: 1
  • Watchers: 3
  • Forks: 0
  • Open Issues: 5
  • Releases: 0
Topics
data-engineering data-science disaster-management flood-mapping gis remote-sensing
Created about 3 years ago · Last pushed 5 months ago
Metadata Files
Readme License Citation

README.md

Intelligent Data Solution for Disaster Risk Reduction (IDS-DRR)

Previously IDEA-FRM

In Assam, the most visible risk is flooding. As per a study by the Ministry of Home Affairs, Government of India, the state ranks 2nd in the flood risk index. Assam State Disaster Management Authority (ASDMA) has initiated the process of disaster risk reduction (DRR). ASDMA has aligned with recommendations in SFDRR through multiple ways like preparing Disaster Risk Reduction (DRR) Roadmap for Assam, capturing daily flood damage data through Flood Response Information Management System (FRIMS), maintaining a web GIS portal and more.

Data that could enable more effective disaster-risk response and management is scattered or siloed across different agencies, at different scales and formats, making it difficult for decision-makers and relevant stakeholders to make data-informed decisions. The availability of good quality, machine-readable, and interoperable data is crucial for effective climate action and disaster response. However, in India, this data is fragmented and siloed, scattered across different agencies, making it difficult for decision-makers to make data-informed decisions in a timely manner.

We have developed a data model for combining climate, losses & damages, procurement and demographic data for effective flood mitigation strategies in Assam state. Our solution leverages advanced data science techniques to derive insights for decision makers and make it into a user-friendly, interactive open-access tool.

With IDS-DRR, we are keen to build on the IDEA-FRM project by building data pipelines so that datasets are updated automatically and thus data-driven governance can be installed.

The project report for details can be accessed here: Link

Directory Tree:

  1. Sources: Contains all data sources along with the scripts used to obtain data from these sources.
  2. RiskScoreModel: Contains codes for calculating the Comprehensive risk score and factor scores for Flood Hazard, Vulnerability, Exposure and Government Response.
  3. NYU-Capstone-Research : MS Data Science students from the New York University selected IDS-DRR for their capstone project. This folder contains the paper they have written and the codes.
  4. Archive: Codes and documents beyond the scope of project.

License:

All content in this repository is licensed under GNU-AGPL

If you want to contribute to the data sources, research or have any doubts with the data, please contact us at info@civicdatalab.in

Owner

  • Name: CivicDataLab
  • Login: CivicDataLab
  • Kind: organization
  • Email: info@civicdatalab.in
  • Location: India

Harnessing Data, Tech, Design and Social Science to strengthen the course of Civic Engagements in India.

GitHub Events

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