Using Machine Learning, Satellite Imagery, and Open Geospatial Data to Identify Aquaculture Sites with High Potential for Production Intensification and Mangrove Restoration in Southeast Asia and Latin America Using Machine Learning, Satellite Imagery, and Open Geospatial Data to Identify Aquaculture Sites with High Potential for Production Intensification and Mangrove Restoration in Southeast Asia and Latin America Mangroves are critical for coastal adaptation to climate change, providing protection from flooding and storm impacts, while also absorbing carbon. Yet shrimp aquaculture has destroyed as much as 38% Trent, et al. (2004) of mangroves globally, resulting in significant biodiversity loss and climate vulnerability. While mangrove loss from aquaculture has slowed in some regions, shrimp ponds continue to produce wastewater that degrades water quality. Efforts to restore these ecosystems remain limited. Conservation International (CI) has piloted a novel Climate Smart Shrimp (CSS) approach that helps shrimp farms to intensify shrimp production on a portion of their ponds in exchange for restoring mangroves on the remainder of their property. The CSS approach could be scaled throughout Asia, but it is too time-consuming and resourceintensive to identify potential farms across hundreds of thousands of hectares of shrimp ponds in Southeast Asia (Boyd, 2018). We propose using machine learning and earth observation data to identify and classify aquaculture farms in Indonesia and the Philippines that use extensive (as opposed to intensive) production methods a critical feature of farms best suited for the CSS approach. Combining this information with open data on sea level rise, flood risk, infrastructure access, and historical mangrove cover will identify the sites with the highest potential will accelerate CIs ability to engage specific farmers, farmer cooperatives, and attract investment to scale CSS. This will provide climate resilience and adaptation benefits by restoring mangroves, protecting coastlines, and improving livelihoods for vulnerable fishing communities hardest hit by climate impacts
|Effective start/end date||2/10/22 → 2/10/23|
- Climate Change AI (CCAI): $145,000.00
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.