QUEÑARIS

Problem

Arequipa, Peru's second-largest city, faces critical water scarcity: queñua forests that retain water have been degraded, and traditional reforestation is slow and hard to scale.

Solution

A decision-support platform for large-scale reforestation: drone orthomosaics and NASA vegetation and moisture indices (NDVI, EVI, NDMI and others from Earthdata and MODIS products) feed an AI analysis that picks the best planting areas; seedlings are strengthened with native microorganisms; a web platform lets communities plan campaigns and monitor forest health over time.

Demo moment

Not described in the sources.

Why it stood out

• organizer statedWon the award for the greatest potential for local impact.Source ↗
• organizer statedNames one city, one ecosystem (queñua forests) and one causal chain (forest loss → water scarcity).Source ↗
• team statedQuantifies the local stake: spring flow dropping from 14 L/s to zero within days threatens water for households, agriculture, energy and mining.Source ↗
• team statedJoins three scales — satellite indices, drone orthomosaics and field biology — into one planting decision, with seedlings already prepared for a first field campaign.Source ↗
• curator inferenceMoved from the BloomWatch phenology brief to a local restoration intervention, trading challenge literalism for concrete local stakes — what the Local Impact award rewards.

Lessons for your next hackathon

• Name the place, the ecosystem and the causal chain; Local Impact is decided by specificity.
• Bring field reality into the submission (a named site, seedlings ready); it turns a platform into a plan.
• LATAM precedent: a team from Peru won a global award with a local problem.