Challenge background
The Philippines is an archipelago surrounded by vast seas and oceans. With the availability of aquatic resources, the country leverages these for socioeconomic growth by establishing fisheries and engaging in various fishing activities. In 2018, the Philippines was ranked 8th among the top fish-producing countries in the world (FAO, 2020). However, as of 2020, there has been a decrease in volume of production by 0.33% and production value by 2.90% compared to 2019 (Philippine Fisheries Profile, 2020).
Project timeline
- 1
Week 1
Collection of satellite imagery, fishery sites and inventory, socioeconomic data
- 2
Week 2
Data preprocessing
- 3
Week 3
Mapping satellite images using various image analysis and remote sensing techniques
- 4
Week 4
Mapping satellite images using various image analysis and remote sensing techniques
- 5
Week 5
Relating mapped fisheries with socioeconomic data to develop resource allocation recommendations
- 6
Week 6
Relating mapped fisheries with socioeconomic data to develop resource allocation recommendations
- 7
Week 7
Model and web app deployment
- 8
Week 8
Presentation and project wrap up
What you'll learn
Collect satellite images and extract relevant features, Prototype an ML model to for site identification Prototype an ML model to devise recommendations on allocating fisheries and resources, Curated project-based resource for computer vision and image processing for impact application