We find patterns on Earth, from space.

Marple trains AI models to detect objects and patterns in satellite and aerial data, and turns them into meaningful maps and figures. The result: faster, cheaper and better-founded decisions on climate, agriculture and cities.

Field boundaries detected by FieldFinder on a satellite image
FieldFinderPrecise field boundaries – for any type of field, anywhere in the world.Learn more ›
Map of detected cotton fields
CoCuRADetects cotton fields – and predicts which are grown to organic standards.Learn more ›
WARM map showing water quality along the Guadalquivir river near Córdoba
WARM Reveals water stress – based on water quantity, quality and temperature. Learn more ›
Vehicles detected by CCEM in an aerial image of Hamburg
CCEMLocates and classifies vehicles in cities to assess traffic and parking space.Learn more ›
Micro urban heat islands marked in red on a satellite image of Hamburg
MUHIDFinds the hotspots that overheat cities – for interventions with maximum impact.Learn more ›
DykeMap heat map of a monitored dyke line along a coast
DykeMap Maps dykes, levees and flood walls, and monitors every section from space. Learn more ›

Who we work with

European Space Agency Federal Ministry for Digital and Transport Global Standards (GOTS) International Labour Organization
Daniel Lanz

Working on climate, agriculture or cities?

Tell us what you want to see from space, and we’ll show you what the data can do.

Daniel Lanz

Email Daniel+49 (0)2207 9610 551