- Lidar Demonstrates Feature Discrimination
Scientists use remote-sensing techniques to characterize landform variation, to evaluate the health of vegetation and to measure the temperature of the oceans. But while in the visible to the infrared offers valuable information, the ambient light can limit its capabilities. Moreover, long-wavelength emissions depend on the temperature of the source, which further complicates interpretation. Now researchers at Los Alamos National Laboratory in Los Alamos, N.M., have demonstrated a multispectral lidar imaging system that uses long-wave infrared light from a CO2 laser to avoid these limitations.
Researchers are investigating the potential of CO2 lidar imaging. The red square in the scene represents the field of view of the system at more than 4 km. The system offers range data and sufficient spectral information to classify features in the target region.
In the system, acousto-optic modulators from Isomet Corp. of Springfield, Va., tune 5-kHz pulsed CO2 laser heads from Synrad Inc. of Mukilteo, Wash., to sweep through 44 wavelengths between 9.6 and 10.6 µm, providing complete spectral capture at 113 Hz. A scanning mirror moves the 350-µrad-divergence beam in 350-µrad steps.
A 30-cm Cassegrain telescope collects the return signal, which passes through an 8- to 12-µm bandpass filter at 77 K. An HgCdTe detector cooled to 35 K detects this signal, and another HgCdTe detector monitors the output pulse to offer a reference that the researchers use to remove pulse-to-pulse variations from the signal. Besides spectral data, the return signal also offers range information, with an accuracy of about 1.5 m.
Allowing for mirror settling and data acquisition, the system acquires a 16 × 16-pixel scene in approximately nine minutes. The acquired data set can be thought of as a mosaic of 44 individual 16 × 16-pixel spectral reflectance maps.
Natural and artificial features
To prove the utility of the method, the researchers imaged a scene at a range of 4.1 km. Because one of the CO2 laser lines is on a water-absorption line, the obtained reflectance values represent the concentration of water vapor in the beam's path. But by discarding that line and using scene averaging to minimize the atmospheric effects at other wavelengths, the researchers obtained detailed spectral data. They classified the 1.3 × 1.3-m pixels into four spectral profiles, corresponding to grassy vegetation, to trees and to two types of rock.
They also have investigated the ranging capability of the lidar system. Given a scene of overlapping hills, the system provided details about the ranges to three distinct hills and measured the variation in range caused by tree height.
Bernard R. Foy, a member of the team, said that the researchers are currently characterizing scenes that include artificial features, such as buildings and vehicles. A future application, he said, may be mapping forest canopies, because the system can determine both the shape of the canopy and the species of trees. Other systems may employ matched spectral filters to enable the rapid and accurate classification of a variety of surface features.
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