Eco-index
Open-access geospatial products and AI-trained remote detection models that help identify native vegetation, ecosystem reconstruction priorities, and catchment-scale biodiversity opportunities across Aotearoa New Zealand.
Biodiversity planning needs defensible spatial data, but teams often have to piece together disconnected GIS layers, ecological assumptions, and manual interpretation before deciding where restoration effort should go.
Eco-index combines GIS layers, browser-based mapping, and AI-trained remote detection models using satellite and aerial imagery to surface native forest cover, regeneration signals, ecosystem reconstruction opportunities, and cost layers.
Eco-index products and code are now open access, giving councils, researchers, restoration groups, and land managers practical tools for understanding vegetation, ecosystem potential, and catchment-scale priorities.
Python
PyTorchComputer VisionGISSatellite Imagery