High-Level Project Summary
When catastrophes strike in rural areas, particularly severe or long-lasting disasters such as landslides, the community in a rural area is unprepared for something they don't know what is coming since they don't have any clue on what will happen in the future. CallApps is an application that alerts rural communities on the possibility that a landslide could occur. This application also informs the local communities and governments on what areas are prone to an unforeseen landslide. It is important for us to help those people who are in rural communities as they are our primary source of food as agriculture is their primary and often only source of income.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
Space Agency Data
Our App, CallApps, uses Landslide Points and Landslide Susceptibility that can be found in gpm.nasa.gov/landslides. This project uses of Geographic Information System (GIS) as it provides NASA landslide data that is already in GIS format. We use this data to make a machine learning that could predict the coordinates of the next possible landslide. As we, NS Elite, are survivors of the landslide caused by the Typhoon Sendong, we make sure that everyone is prepared for the worst scenario.
Hackathon Journey
The Space Apps experience so much fun and also we, as a team, learned so much more than we have before this Hackathon. We learned how to interpret and analyze data, make a machine learning and designed an application. Our team chooses this challenge because as we already said that we experienced being a victim of landslide and we don't want other people experience the worst.
Our team resolve setbacks and challenges by teamwork, brainstorming and voting which idea has the best.
We would like to thank Sir Archie Velasco for giving us this opportunity to have this Hackathon. And also to our best mentor, Dr. Doroja for mentoring us and giving insights that give us more ideas to our prototype.
References
Articles:
https://agricultureandfoodsecurity.biomedcentral.com/articles/10.1186/s40066-017-0116-6
NASA Data:
https://gpm.nasa.gov/landslides/
Research Papers:
Landslide Points:Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., & Lerner-Lam, A. (2010). A global landslide catalog for hazard applications: method, results, and limitations. Natural Hazards, 52(3), 561–575. doi:10.1007/s11069-009-9401-4.
Landslide Susceptibility:Stanley, T., and D. B. Kirschbaum (2017), A heuristic approach to global landslide susceptibility mapping, Nat. Hazards, 1–20, doi:10.1007/s11069-017-2757-y. Link to article: http://link.springer.com/article/10.1007%2Fs11069-017-2757-y
Tools:
Canvas:https://www.canva.com
Figma:https://www.figma.com
Github: https://github.com
Google Drive:https://drive.google.com
Google Maps:https://www.google.com.ph/maps
Youtube:https://www.youtube.com
Tags
#world #soil #information #ml #landslide