At QZ Solutions, we transform Earth Observation and in-situ data into meaningful, actionable information.
We develop data-driven models and analytical frameworks that extract key information from satellite and in-situ observations. By combining hyperspectral, multispectral, and radar data with laboratory-validated ground measurements, we ensure both scientific reliability and practical usability.
Our models support real-world decision-making in agriculture and encironmental management.
We specialize in translating complex satellite and field data into quantitative indicators that reflect real-world conditions. Our modelling portfolio covers a broad range of applications, including:
Our analytical framework combines machine learning, data fusion, and geospatial analysis to ensure consistency and reliability across spatial and temporal scales.
We integrate multispectral and hyperspectral satellite imagery with in-situ and laboratory measurements, building models that deliver precise, validated, and scalable insights for real-world applications.
We design custom analytical pipelines — from feasibility studies to operational monitoring systems.
Our approach supports data harmonization, multi-sensor integration, and the generation of indicators that describe crop growth, soil condition, and environmental dynamics.
Our technical expertise includes:
Through this approach, we ensure that every dataset and model we deliver meets both scientific excellence and operational usability, bridging the gap between Earth Observation data and decision-making in agriculture and environmental management.
Interested in launching a new project or train a model. Contact us to assist you.
