Cecil

Data marketplace

40+ datasets. One agreement.

Browse our marketplace with 40+ commercial and open datasets under a standardized agreement.

Plant Biomass

Aboveground biomass stock and change at 10–30 m resolution — annual global coverage from 2000.

Chloris · Sylvera · Planet · UMD

Biodiversity Integrity

IUCN Red List, Key Biodiversity Areas, and Protected Areas alongside Biodiversity Intactness Index and Forest Landscape Integrity at 300 m–10 km — for TNFD disclosures and SBTN targets.

IBAT · IUCN · WDPA · NHM · WCS

Land Use & Cover

Global and US LULC in 9–17 class schemas at 3–30 m. Impact Observatory, JRC forest layers, USGS NLCD, and SBTN Natural Lands across multiple epochs.

Impact Observatory · JRC · WRI · USGS

Soil Moisture

Surface soil moisture at 20 m–1 km sub-monthly, plus Planet Soil Water Content — essential for drought monitoring and agricultural risk assessment.

Lobelia Earth · Planet

Asset Locations

Global Major Mines, industrial asset footprints, and administrative boundaries for supply chain due diligence, TNFD reporting, and spatial risk screening.

PlanetSapling · geoBoundaries

Risk

Climate hazard diagnostics covering coastal floods, fluvial floods, cyclones, and wildfire at 1–11 km resolution from 1980 to 2080 — for TCFD and physical risk disclosure.

Emmi

View all datasets →

Cecil SDK

From discovery to analysis in minutes

Develop secure, resilient, and highly scalable workflows with the Cecil SDK.

CLI, Python, and agentic interfaces Streamline the process to acquire and analyze datasets from industry-leading data providers.
Mapping & visualization integrations Compatible with QGIS, Leaflet, Kepler.gl, and any visualization tools.

            
            cecil_demo.ipynb
            ×
          
          Python 3.11
        
import cecil

client = cecil.Client()

# Subscribe to a dataset

sub = client.create_subscription(

  aoi_id=my_aoi_id,

  dataset_id="87251e55-8685-4a45-bf3a-52bfa3829b44"

)

# Load directly as xarray Dataset

ds = client.load_xarray(sub.id)
          
<xarray.Dataset>
Dimensions:  (time: 24, y: 4096, x: 4096)
Variables:
  * time   (time) datetime64[ns] 2023-01 ... 2023-12
  * agb    (time, y, x) float32 dask.array
Attributes:
    dataset_id:  87251e55-8685-4a45-bf3a-52bfa3829b44
    crs:         EPSG:4326

Built for how data teams actually work

Cecil provides compatibility and seamless integration with your existing tools and workflows.

Curated by scientists

Cecil draws on foundational scientific principles to identify and describe data in an objective, transparent, and rigorous way.

Consistent, analysis-ready formats

Every dataset arrives pre-normalised to consistent coordinate systems and schemas. No custom parsers, no cleaning, no guessing about projections.

Works with your stack

Compatible with CLI, Python SDK, agentic interfaces, QGIS, Leaflet, and any geospatial tools.

Developers

Get your API key and start building

Develop secure, resilient, and highly scalable workflows with the Cecil SDK.

Get API key →

Enterprise

Need a guided onboarding?

Talk to us about custom datasets, volume-based pricing, or integration services for your team.

Contact sales →

Spatial data,ready for analysis