A web application that assesses economic and humanitarian impact i.e. how much resources could potentially be lost when a flood happens in a city, and how that city gauges to resolve the losses by its allocated budget for such disaster as well as how that city fares with its other neighboring cities.
It is important because this can be a critical juncture when making decisions on allocating budget on flood-disaster risk management. Since this is available to the public, anyone could evaluate how much resources could potentially be lost when flood-disaster happens, and analyze how a city is prepared in combatting losses.
A user can interact with the application such as using sliders on different flood levels to observe possible losses.
Our team hopes to achieve that this project should be accessible for educational purposes as well as for local government units to replicate or even modify. Most importantly on replicating or reproducing the project, the team extensively believes that local government units could use this in making critical decisions when it comes to budget allocation for flood-disaster preparedness.
The team was inspired to choose this challenge because we believe this project plays a vital role in making decisions for government officials so that they can make necessary actions to prepare for budget allocation, improve flood-disaster protocols, and upgrade evacuation centers.
Our approach was to collect and gather population, population density, workforce, income, budget for flood-disaster data particularly on National Capital Region (NCR), the seat of power and commerce of the Philippines. The team also utilized NASA's Categories API to get flood alerts. The team used flood hazard maps data from LiPAD (LiDAR Portal for Archiving and Distribution), which is the country's primary data access and distribution center of the LiDAR technology developed by the Department of Science and Technology. The team used Python for data cleaning, manipulation and JavaScript for web development.
Problems encountered were learning QGIS, developing the map, and mostly finding sufficient and latest data. Achievements were to have a working prototype in a span of 12 hours, as well as discovering the data that the team crucially needs.
The team used NASA's Categories API to get alerts about floods.
LiPAD (https://lipad.dream.upd.edu.ph/): Flood hazard maps
Philippine Statistics Authority (https://drive.google.com/drive/folders/1T7nLSisZwwJrzwWz9MSSIsmnteSlBIeX?usp=sharing): ncr_age_pop_2018.csv, FIES_2018_Final_Report.pdf
PhilGIS (http://philgis.org/vector-and-raster-datasets-cities-and-capitals): Administrative bounds of Metro Manila