LiDAR / RSD Validation, Classification & Campaign Assurance

ProfEC Ventus provides validation and classification of Remote Sensing Devices within its DAkkS-accredited ISO/IEC 17025 testing scope, together with campaign verification, data-quality assessment and integration into wind resource measurement programmes.

Remote sensing can provide highly valuable wind data, but its value depends on how well the device, deployment, verification and data quality are managed.

ProfEC Ventus supports developers, IPPs, consultants and project owners with independent technical assurance for LiDAR and SoDAR measurement campaigns.

Our support can include:

• pre-deployment verification and campaign preparation

• review of device configuration and measurement strategy

• installation and commissioning support

• comparison with reference measurements where required

• data availability and quality assessment

• identification of measurement gaps, anomalies and environmental influences

• integration of remote sensing data with met mast measurements

• suitability assessment for Wind Resource Assessment and Energy Yield Assessment

• technical documentation supporting project review and bankability

The objective is to help project teams use remote sensing data with greater confidence and understand clearly how the measurement basis supports subsequent engineering, investment and financing decisions.

For developers and IPPs, this provides stronger control over campaign quality and reduces uncertainty before the data enters the resource assessment process. For consultants, investors and lenders, it provides an independent technical basis for assessing the reliability and suitability of the remote sensing dataset.

ProfEC Ventus combines remote sensing expertise with accredited measurement, calibration, WRA and EYA capabilities, allowing the measurement campaign to be assessed within the wider project-development chain.

We welcome discussions with organisations using or planning LiDAR and SoDAR campaigns where independent verification, data-quality assessment or integration with conventional measurements can strengthen the project basis.