> BRIDGES

> DAMS

> EARTHQUAKE COMPLETENESS MAP

> FAULT DIAGNOSIS OF SATELLITE
SUBSYSTEM

> HYDROLOGICAL / METEOROLOGICAL
DATA VALIDATION

> NEAR SURFACE AIR TEMPERATURE

> RAIL SHIPMENT ROUTING
AND RAILROAD ASSET MANAGEMENT

> ROOF OF THE MONTREAL
OLYMPIC STADIUM

> SATELLITE CONSTELLATION
MANAGEMENT

> SNOW DEPTH MEASUREMENT

> SNOW-WATER EQUIVALENCY

> SOIL MOISTURE AND ROUGHNESS
ESTIMATION VIA REMOTE SENSING

> TRAFFIC COUNT ESTIMATION
AND MONITORING


SNOW-WATER EQUIVALENCY

GlobVision developed a method that uses artificial intelligence techniques to estimate the snow-water equivalency in areas where no ground stations exist.

Comparing the results obtained through GlobVision’s intelligent-based analysis of remotely sensed data with existing mathematical models paved the way for the estimation of surface parameters critical to many applications using only remote sensing.

Such an approach offers clear advantages, such as, reduced cost, timely information and increased coverage from the data available. The latter two advantages are critical to applications such as climate modelling, drought monitoring and prediction, as well as water resources management, flood prediction and irrigation schemes, among others.