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Use of Naturally Available Reference Targets to Calibrate Airborne Laser Scanning Intensity Data
AbstractWe have studied the possibility of calibrating airborne laser scanning (ALS) intensity data, using land targets typically available in urban areas. For this purpose, a test area around Espoonlahti Harbor, Espoo, Finland, for which a long time series of ALS campaigns is available, was selected. Different target samples (beach sand, concrete, asphalt, different types of gravel) were collected and measured in the laboratory. Using tarps, which have certain backscattering properties, the natural samples were calibrated and studied, taking into account the atmospheric effect, incidence angle and flying height. Using data from different flights and altitudes, a time series for the natural samples was generated. Studying the stability of the samples, we could obtain information on the most ideal types of natural targets for ALS radiometric calibration. Using the selected natural samples as reference, the ALS points of typical land targets were calibrated again and examined. Results showed the need for more accurate ground reference data, before using natural samples in ALS intensity data calibration. Also, the NIR camera-based field system was used for collecting ground reference data. This system proved to be a good means for collecting in situ reference data, especially for targets with inhomogeneous surface reflection properties.
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Vain, A.; Kaasalainen, S.; Pyysalo, U.; Krooks, A.; Litkey, P. Use of Naturally Available Reference Targets to Calibrate Airborne Laser Scanning Intensity Data. Sensors 2009, 9, 2780-2796.View more citation formats
Vain A, Kaasalainen S, Pyysalo U, Krooks A, Litkey P. Use of Naturally Available Reference Targets to Calibrate Airborne Laser Scanning Intensity Data. Sensors. 2009; 9(4):2780-2796.Chicago/Turabian Style
Vain, Ants; Kaasalainen, Sanna; Pyysalo, Ulla; Krooks, Anssi; Litkey, Paula. 2009. "Use of Naturally Available Reference Targets to Calibrate Airborne Laser Scanning Intensity Data." Sensors 9, no. 4: 2780-2796.