IESS — International Energy and Sustainability SummitAYSC 2026
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Climate Data & AIAYSC26-DA-007

Forest Guard: Ecology Tracking & Reforestation Blueprint System

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AI-powered platform that detects deforestation at the species level across Kenya's forests and generates data-driven reforestation blueprint

Problem

Deforestation monitoring in Kenya typically reports loss in broad regional or hectare terms, which hides what's actually happening on the ground. Conservationists, forestry officers, and policymakers can't tell which of Kenya's native tree species are being hit hardest, or whether the cause is legal logging, illegal logging, disease, or fire. Without that granularity, KEFRI (Kenya Forestry Research Institute) data and satellite alerts stay siloed, and reforestation efforts end up generic rather than targeted at the species and regions most at risk. Cutting hotspots often go unflagged until damage is severe.The result is slower response times, reforestation plans that don't match local ecology, and a harder time proving conservation impact to funders or regulators. To quantify impact, the system currently tracks 12 native Kenyan tree species with the following population loss trends (based on aggregated KEFRI and satellite data): African Mahogany (Khaya anthotheca): 34% loss (5-year trend) East African Sandalwood (Osyris lanceolata): 41% loss (5-year trend) African Cherry (Prunus africana): 28% loss (5-year trend) Meru Oak (Vitex keniensis): 47% loss (5-year trend) African Olive (Olea europaea ssp. cuspidata): 19% loss (5-year trend) Podo (Podocarpus falcatus): 33% loss (5-year trend) Mukau (Melia volkensii): 22% loss (5-year trend) The percentages represent estimated declines in mature individual counts within key forest blocks over the last five years.

Solution

Solution description ForestGuard EcoBlueprint is a web platform that tracks deforestation down to the species level and turns that data into actionable reforestation plans. It follows 12 native Kenyan tree species using KEFRI species codes, conservation status, and habitat data, breaking down loss by cause (legal logging, illegal logging, disease, fire) so users see not just how much forest is disappearing, but which species and why. The core is an interactive ecology map built with Leaflet, offering three views: Region Colors, Habitat Colors, and Cutting Hotspots. The Cutting Hotspots view surfaces 18 active logging/disease/fire events filterable by cause for near-real-time situational awareness. This view updates every 6 hours via a scheduled sync from Sentinel-2 satellite imagery (10m resolution) and KEFRI field report APIs, with event validation triggered by the Gemini AI integration to confirm ground conditions. The map also includes a polygon-based Education Mode with expandable species cards and visual loss-breakdown bars, making the data accessible to non-specialists. Species are rendered with custom CAD-style geometric tree icons (rounded, conical, umbrella) for instant visual identification. On the analysis side, the Reforestation Blueprint module generates species-specific planting recommendations paired with projected carbon sequestration, so replanting efforts target the right species in the right regions rather than generic afforestation. A KEFRI webhook API lets the Institute push live forest data directly into the system, and the Gemini AI integration analyzes satellite or field photos to help verify ground conditions. Analytics and reporting tools round it out with species loss tables, cause-breakdown charts, and regional comparisons for funders, researchers, and policymakers. https://github.com/MuchiriTimothyGitau/ForestGuard-EcoBlueprint/tree/master Built with React 19, Vite, Leaflet, and Recharts on the frontend and Python/FastAPI on the backend, the system is designed to plug directly into KEFRI and Kenya Forest Service data pipelines.

Team Emit IQ
TG
Timothy Gitau Muchiri · Lead
JW
Joanlynn Wambere
CN
Collins Njuguna