Chloris Geospatial

Chloris Geospatial, founded in 2020 and headquartered in San Francisco, California, is a forest carbon intelligence company that uses satellite imagery, machine learning, and established forest ecology models to provide science-based above-ground biomass (AGB) measurements and forest carbon stock tracking for voluntary carbon markets, corporate net-zero commitments, and conservation finance applications.

The company's core platform processes multi-spectral satellite imagery from Sentinel-2, Landsat, and commercial high-resolution sources through proprietary ML models trained on ground-truth forest inventory data from hundreds of field plots globally. These models estimate above-ground biomass density (tonnes of carbon per hectare) at 30-meter and 10-meter spatial resolution — fine enough to distinguish individual forest patches and attribute carbon stocks to specific parcels. Temporal repeat observations enable annual change detection that identifies deforestation events, forest degradation from selective logging, and carbon accumulation from reforestation, providing the additionality and permanence evidence required for carbon credit certification.

Chloris serves carbon project developers, forest landowners, conservation organizations (REDD+ programs), and corporate buyers seeking independently verified carbon removal and avoided deforestation credits. The platform addresses the persistent credibility problem in voluntary carbon markets — many existing forest carbon projects rely on low-resolution proxy methods that overestimate baseline emissions and underestimate leakage — by providing satellite-derived ground truth that reduces quantification uncertainty to below 15% at the project level.

Chloris raised $8.5M in Series A financing in 2025, led by climate-focused VCs, to scale its ML model coverage globally and expand analytical products. The company competes with SilviaTerra (now NCX), Pachama, and South Pole in the forest carbon measurement and verification market, differentiating through spatial resolution, scientific methodology transparency, and direct carbon registry integration.