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LiDAR Upgrade

Hyperspectral Imaging and LiDAR:
Complementary Tools

Hyperspectral imaging and Light Detection and Ranging (LiDAR) are very complementary. Hyperspectral imaging can remotely detect conditions such as crop disease, water deficits, or plant stress or vigor, while LiDAR measures distances with extreme precision using pulses of laser light. When combined with accurate positioning data from a global positioning system and inertial measurement unit (GPS/IMU), LiDAR data can be used to produce an extremely accurate digital elevation model (DEM) of terrain.

LiDAR Tools software comes with each LiDAR-equipped payload package from Headwall. These systems, such as the Nano HP VNIR or Co-Aligned HP VNIR-SWIR sensor, are mounted to a compatible UAV platform, providing flight-ready operation, and representing the gold standard for lightweight, remote sensing airborne platforms. And adding LiDAR contributes less than a kilogram to the payload! Buy it as part of a new system or ask us about upgrade packages for your compatible UAV/drone.

The combination of hyperspectral imaging and LiDAR is especially powerful because the entire dataset can be acquired simultaneously, maximizing efficiency by minimizing flight time. Requirements for overlap of adjacent flight paths are also significantly less than those for photogrammetry. The DEM file that the LiDAR Tools software provides is utilized in the process of orthorectification of the hyperspectral imaging data.

Headwall integrates multiple sensor modalities and provides the tools necessary for the most efficient and productive workflow for data capture and exploitation. Customers benefit from our expertise and our robust and proven platforms, whether imaging payload systems added to a UAV or an entire integrated solution including imaging and positioning packages and the UAV itself.

Part Number for LiDAR Upgrade for Nano HP VNIR: 1005A-10810, Part Number for LiDAR Upgrade for Co-Aligned HP VNIR-SWIR: 1005A-10527

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For more information download the product data sheets: