Awards & Nominations
ScienceWorks has received the following awards and nominations. Way to go!
Global Nominee
CLaRA
High-Level Project Summary
Landslides are very common in Davao due to our mountainous topography and frequent raining. However, current landslide risk maps and assessments are limited to large-scale earth observations which do not provide localized risk level assessment. To do this, we need to gather near-real-time, regularly-updated, and localized data by maximizing existing affordable technologies and community participation. Introducing CLaRA, which stands for Community-powered Landslide Risk Assessment. CLara is a landslide information and mapping system utilizing citizen science through an app and machine learning.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
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Space Agency Data
NASA's citizen science landslide reporting inspired CLaRA. Unlike the United States, the Philippines do not have a lot of earth observation satellites to gather environmental and geographical data. So, we must empower the local communities to gather landslide warning signs and report landslides, partnered with portable weather stations on the ground.
To provide historical data on average precipitation over Davao City, the team found it necessary to incorporate time-averaged multi-satellite rainfall data from Giovanni. Consequently, CLaRA would also require topographical data of Davao City from Earthdata.
Hackathon Journey
Our team in composed of senior high school STEM teachers in science and math. None of us have any experience in app development, landslide assessment, and machine learning. What we all have, however, is the passion and dedication to make science more accessible and relevant to the general population here in Davao City.
While there is growing general public support in the sciences, more work needs to be done to make the public realize the value of investing in scientific endeavors locally. So, we decided to participate in the local NASA Space Apps Challenge to get a platform where we can start making science with the community.
Our initial plan was to create an app that predicts and visualizes the rise in floodwater level in Davao City over the years to come using predictive algorithm to highlight the harrowing impact of climate change in the long run. However, the team found that we can incorporate our research into landslide prediction instead, since the former causes the latter and we would be hitting two birds with one stone.
The journey was challenging. Since this is our first time joining a hackathon, we quickly realized that communication and collaboration would have been more efficient if we stayed in the same room. We still managed to pull through, however, but it required tremendous effort and patience.
When the team finally pitched and submitted CLaRA to the local competition, we were delighted to see the enthusiasm and interest of our mentors and judges. Their extensive experience and valuable insights in machine learning, app development, earth observation, and on-the-ground experience of collaboration with the government propelled us even further.
The journey to make science work for and with the people of Davao City would not have been possible without the support of the American Spaces DAVAO, our local lead Engr. Jason Occidental, and of course our friends and families in Davao City who keep us motivated.
Now that we have somehow grasped the idea of what we want to do with our project, what lies ahead of us is nothing but exciting times.
References
- CHAPTER 10 - LANDSLIDE HAZARD ASSESSMENT. (1991). OAS.Org. http://www.oas.org/dsd/publications/unit/oea66e/ch10.htm
- Exploring farmersâ intentions to adopt mobile Short Message Service (SMS) for citizen science in agriculture. (2018, August 1). ScienceDirect. https://linkinghub.elsevier.com/retrieve/pii/S0168169916311279
- Landslide Preparedness. (2021). USGS. https://www.usgs.gov/natural-hazards/landslide-hazards/science/landslide-preparedness?qt-science_center_objects=0#qt-science_center_objects
- Pardeshi, S. D. (2013, October 17). Landslide hazard assessment: recent trends and techniques. SpringerPlus. https://springerplus.springeropen.com/articles/10.1186/2193-1801-2-523
- Psomiadis, E. (2020). Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data. MDPI. https://www.mdpi.com/2073-445X/9/5/133
- Vallente, Jefferson Jr & Tan, Kevyn & Estenzo, Therese & Paluya, Russel & Peñamante, Jasper. (2017). Landslide Risk Assessment of Five Selected Barangays in Cagayan de Oro City.
- https://gpm.nasa.gov/landslides/report.html
- Tipping Bucket Rain Gauge
- Arduino Weather Station
- Sapelli.org
Tags
#landslide #citizenscience #machinelearning #philippines #davao #arduino #map
Global Judging
This project has been submitted for consideration during the Judging process.