ASAAN

Manila | Measuring the Value of Earth Observations

Project Anitun Tabu: Localized Risk Assessment of Tropical Cyclones

High-Level Project Summary

Project Anitun Tabu is a website that disseminates weather data conditions readings, analysis, illustration, and predictions intended to inform and prepare the community for the potential casualties caused by tropical cyclones and their aftermath. Utilizing topographic maps with satellite data on enhancing the analysis of tropical cyclones and their aftermath minimizes the casualties and devastation on a large scale as the community will be provided with information on what are the high-risk areas, the expected fatality, and the emergency response teams nearby.

Link to Project "Demo"

https://docs.google.com/presentation/d/1NyerrpoqSTfu5scU-1-bimxICJlqcxZmOW-glxR4zRQ/edit?usp=sharing

Link to Final Project

https://github.com/Inferior-Programmer/anitun-tabu-app

Detailed Project Description

Project Anitun Tabu is a web app that analyzes and publicizes comprehensible weather data conditions, illustrations, predictions, and aftermath regarding tropical cyclones to notify the community which areas are the most exposed to hazards.

The web app gathers relevant datasets that include satellite imagery, socioeconomic data, and weather forecasting models to generate map models of communities at risk. This generated map contains information that can help local government units to prepare and be alert via SMS alert or email for them to look up the web app and disseminate information to their communities. Evacuation Centers and Emergency Facilities are also mapped in the web app with associated road paths as a guide for the community in case disaster strikes.

The system of the web app is divided into two; the Storm Profiling and Risk Reduction Tool. The web app fetches Global Forecast System (GFS) data from National Oceanic and Atmospheric Administration (NOAA) that includes accumulated precipitation, wind speed, and storm track. For real-time wind data, Global Wind Atlas Dataset is used. For localized data, this data is augmented with the forecast system of the Philippine Atmospheric, Geophysical, and Astronomical Administration (PAGASA). Real-time Infrared and Heavy Rain Potential satellite imagery of the typhoon are obtained from Japan Meteorological Agency (JMA) and Japan Aerospace Exploration Agency (JAXA). All these data are utilized for the Risk Reduction Tool in determining communities at risk.

The Risk Reduction Tool has 6 components: Flooding, Storm Surge, Strong Winds, Landslide, and Emergency Facilities. All of the components use the base map from Leaftlet and the topographic map from Global Wind Atlas.

In Flooding, animated quiver plots are used to model rain runoff using rain prediction models from the GFS Model with a topographic map. The direction of quiver flow and speed represents the rain runoff flow and volume. It will also utilize the infrared and high rainfall potential datasets from satellite Himawari-8 in storm profiling. River system Map and low-lying area map together with quiver plots determine which communities will be affected through Population Count data from SEDAC.

Storm surge also uses animated quiver plots together with the coastal region from SEDAC and topographic map. To determine wave height, wind model data from GFS is used. Through population count and fishery industry from the Department of Agriculture and SEDAC on coastal areas, the communities affected can be determined.

For strong winds, animated quiver plots are also utilized to represent wind speed and direction models from the GFS Model and topographic mapping. Integrating these models with a local mapping of agricultural land from the DA and SEDAC will establish which agricultural regions will be affected.

As for landslides, color overlay will be used to represent areas at risk using landslide hazard data from SEDAC and rainfall amount data overlay.

Lastly, in Evacuation Centers and Emergency Facilities, datasets of existing evacuation centers and emergency facilities from the Department of Interior and Local Government (DILG) are integrated. Then the base map will generate a relevant mapping of available centers and facilities by map plotting in case of disastrous events.

Located near the western edge of the Pacific Ocean, the Philippines is in the direct path of seasonal typhoons. According to the Internal Displacement Monitoring Centre, 4.4 million Filipinos were affected by internal disaster displacement, alone.This places the country as the second-most affected due to extreme weather conditions casualties. This depicts the demand for further data analysis and circulation regarding extreme weather conditions, such as tropical cyclones, to enhance the disaster risk management and response in order to lessen the socioeconomic casualties.

The Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA) is operating on the geostationary weather satellite. HIMAWARI-8, to provide and utilize satellite imagery in weather monitoring and forecasting. They disseminate daily weather updates to the public via scheduled news broadcasting. However, due to insufficient weather stations, the advisories on every city are generalized, disregarding the concept of how topography affects the climate condition in several areas.

Topographic maps are essential in enhancing the analysis of tropical cyclones as the maps portray the contrasting features in every area in a three-dimensional landscape, reducing the probability of generalized weather data and advisories on high-risk areas that may lead to a huge loss in the interactive natural and socioeconomic factors.

The coding language used by the team is Python. For the web app, Plotly Dash is used as the framework, and Bootstrap as the front-end. To host and deploy the web app, Heroku is utilized and finally Google Collab for processing large datasets.

Space Agency Data

The Socioeconomic Data and Applications Center (SeDAC) of the National Aeronautics and Space Administration provides many of the datasets used in the project.

The Himawari-8 of Japan Meteorological Agency (JMA) and Japan Aerospace Exploration Agency (JAXA) had various datasets that were greatly relevant to the project. Specifically, the image datasets of infrared bands and high rainfall potential bands were heavily used in the implementation of storm profiling.

The Global Forecast System (GFS) of the National Oceanic and Atmospheric Administration (NOAA) is a global numerical weather prediction model. Its datasets are freely available to anyone who is interested, however it requires a significant amount of post-processing to be more understandable for common people. These datasets inspired the storm tracking prediction model of Project Anitun Tabu and will pose great significance once this feature is made functionable and public.

Meanwhile, the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAG-ASA) provides local weather forecasts and data. This would be used together with the international satellite data gathered through the aforementioned reliable resources to further the validity of the data output, plotting, and mapping of the web app.

Following this, the agricultural mapping feature of the project was inspired by the possible datasets to be acquired from the Department of Agriculture. The collection of the agricultural locations would be used in plotting the map of agricultural regions to pinpoint the agricultural areas at risk in case of possible natural hazards.

Finally, the wind direction and the magnitude datasets of the Global Wind Atlas that is currently managed in partnership by World Bank Group, the Energy Sector Management Assistance Program, Vortex, the Technological University of Denmark Wind Energy Department. The raw data from the datasets were processed and integrated to the base map in order to produce a quiver map to visualize the direction and magnitude of wind.

Hackathon Journey

We, as a team, experienced a variety of emotions while undertaking the challenges that came in this event. A fair amount of stress went in this, of course. However, we still had fun and thoroughly appreciated and learned more about the processes and the amount of hard work, patience, and crucial research required to create a presentable project that vies for scientific and humanitarian innovation.

Our team was motivated by the fact that this is one of the areas that we are knowledgeable about. Furthermore, all of us have our own share of horrible experiences with disastrous floods due to the typhoons that came in recent years. With that being said, this is us doing our part in helping our community, and hopefully, our whole country by researching and creating the things that interest us the most.

Our perspective towards developing the project was oriented towards developing a means or a platform that would minimize the disastrous effects of tropical cyclones, specifically on high-risk communities.

(src: https://www.sciencedirect.com/science/article/pii/S2225603221000278)

The above table presents data on the number of damaged houses, the number of damaged infrastructures in the Philippine Peso, and the amount of damaged agriculture in Philippine Peso caused by the strongest tropical cyclones to hit the Philippines in the year 2020. Through examining this table, it is visibly evident that tropical cyclones heavily affect the country’s agricultural sector and even civilians.

We were able to formulate a solution through rigorous brainstorming and data-gathering. By skimming through various datasets available in NASA and other partners, we came up with using these datasets to do localized risk assessment of tropical cyclones. Some of the datasets we used were images from Himawari-8, SeDAC datasets on population and hazards, and other satellite datasets. Also, we decided that the project will utilize local data of agricultural and fishery locations in order to make local citizens aware of the possible risks of incoming tropical cyclones.

As we go through this journey, we thank the Almighty God for His guidance and protection while developing this project. Nothing would have been started if not for His grace amidst these trying times. We would also like to thank our beloved family for caring and encouraging us whenever we would get in a slump or feel down. Your words of encouragement and support give us the push we so much needed when we thought that we could no longer move forward. Lastly, We deeply appreciate each and every one of those that had been there for us may it be openly or silently, thank you.