How long does it take to get results from an agent?
Most assessments are completed within minutes to hours, compared to weeks with traditional consulting approaches. Complex reports typically deliver within 3 hours.
Can agents handle multiple methodologies?
Yes, our agents are trained on VM0047, REDD+, Gold Standard, Isometric, and other major frameworks.
How do AI agents work with my project data?
Our agents analyze your uploaded files (GeoJSON, shapefiles) using our proprietary AI models and guide you through methodology selection, eligibility screening, and report generation via natural conversation
What data sources do your data products use?
Kanop's models combine multiple satellite data sources to produce accurate biomass, canopy height, and forest cover estimates.
Optical imagery: Sentinel-2 (10-20m resolution, from 2015) and Landsat-8/9 (30m resolution, from 2013) provide spectral reflectance data linked to vegetation density and structure.
SAR (Synthetic Aperture Radar): Sentinel-1 (C-band) and PALSAR-2 (L-band) capture structural information about vegetation regardless of cloud cover or lighting conditions, making them essential for consistent monitoring in tropical regions.
Elevation data: The SRTM digital elevation model provides topographic context (slope, aspect, elevation) that informs biomass predictions.
Training data: Our deep learning models are trained on 125 million hectares of LiDAR reference data, including 42 million hectares from 754 airborne LiDAR campaigns and 83 million hectares from NASA's GEDI spaceborne LiDAR mission, spanning 76 countries.
Field measurements (optional): When available, user-provided plot-level measurements can be used to recalibrate model outputs through a Gaussian Process Regression approach, improving local accuracy.
Is there an API to access the platform?
Yes, our API connects your sites and projects directly to our advanced analytics platform. Moreover, built with security at its core, our API ensures that your data remains safe. If you're interested, let us know.
