Pysically Based Data Fusion Between Airborne Lidar and Hyperspectral Data: Geometric and Radiometric Synergies

摘要

Combining airborne LiDAR (ALS) and hyperspectral data refers to utilize the LiDAR based Digital Elevation Model (DEM) and the spectral information of the hyperspectral imaging (HSI) sensor. The separation of both discretized data entities leads to a substantial loss of information and does not exhaust the full capabilities of the contrasting sensors. A physically based in-flight fusion of HSI and ALS sensor characteristics is presented. Based on their respective intensity information overlaps, ray tracing and radiative transfer procedures utilize geometric and radiometric synergies. In a first step a rigorous parametric co-alignment procedure is realized using an automated and adjustable tie point detection algorithm. It ensures sub-pixel co-alignment of the contrasting sensors. In a second step we present a rigorous illumination correction of HSI data based on the radiometric cross-calibrated return intensity information of ALS data. This radiometric fusion corrects cloud and cast shadowing effects, across track illumination, partly anisotropy effects and illumination changes over time for the entire HSI wavelength domain. The presented fundamental fusion of the passive and active sensor characteristics is aimed at improving and developing the complete, sensor inherent data density to ensure highest spectral and geometric information content for a variety of applications.