Intensity normalization and automatic gain control correction of airborne LiDAR data for classifying a rangeland ecosystem

Airborne LiDAR not only records elevation but also the intensity, or the amplitude, of the returning light beam. LiDAR intensity information can be useful for many applications, including landcover classification. Intensity is directly associated with the reflectance of the target surface and can be influenced by factors such as flying altitude and sensor settings. LiDAR intensity data must be calibrated before use and this is especially important for multi-temporal studies where differing flight conditions can cause more variations. Some sensors such as the Leica ALS50 Phase II also records automatic gain control (AGC), which controls the gain of the LiDAR signal, allowing information from low-reflectance surfaces. We demonstrate a post-processing method for calibrating intensity using airborne LiDAR data collected over a sage-steppe ecosystem in southeastern Idaho, USA. Range normalization with respect to the sensor-to-object distance is performed by using smoothed best estimated trajectory information collected at an interval of every second. Optimal parameters for calibrating AGC data are determined by collecting spectral reference data at the time of overflights, in test areas with homogenous backscatter properties. Intensity calibration results are compared with vendor corrected intensity data, and used to perform landcover classification using the Random Forests method. We also test this intensity calibration approach using a separate multi-temporal LiDAR data set collected by the same sensor.