Perhaps no other aspect of remote sensing carries with it true life-changing possibilities than precision agriculture. High-value crops can be planted, cared-for, and harvested with the help of spectral data that leads to better decision-making. This in turn means spectacular crop yields and healthier foods...especially in parts of the world where agricultural success is a life-saving or life-enriching necessity. Irrigation levels, pesticide and fertilizer effectiveness, and the telltale signs of invasive and hard-to-detect diseases can be spotted using hyperspectral image sensors. The key is to recognize these signs early and often, which is why continual airborne monitoring allows for trend analysis throughout the season.
From UAVs and aircraft as well as tractors and other mobile machinery, researchers can determine stress levels and overall plant vitality using hyperspectral image sensors at the VNIR (400-1000nm) and SWIR (900-2500nm) spectral ranges. These sensors operate in a line-scanning fashion, requiring movement to occur as the sensor builds a data-rich image cube containing all the spatial and spectral information within the field of view. GPS and LiDAR, plus the post-processing task of orthorectification, stamp the image data precisely. The end result is high-quality data that farmers and agriculturalists can use to make smart decisions.
Headwall's sensors feature aberration-correction for precise image data from edge to edge. This wide field of view is particularly beneficial for the new breed of small, lightweight UAVs that require flight-path optimization. The wider the field of view, the fewer passes over a plot of land the UAV (or aircraft) needs to make.
Headwall supplements its sensors with the industry's best airborne hyperspectral software package called Hyperspec III. The package includes all the tools necessary to set up the sensor for airborne operation, and tie that operation in with GPS and LiDAR data streams. The software also will monitor and manage more than one sensor at a time, permitting a single pass using a VNIR and a separate SWIR sensor for example.