Simulating Space Lidar Waveforms From Smaller-Footprint Airborne Laser Scanner Data for Vegetation Observation

A possible step in dimensioning future space-based full-waveform lidar sensors is to predict space signals from commercial airborne laser scanner data. This method has proved able to simulate passive satellite sensors with precise accounting of the scene heterogeneity effects. In this letter, we use the DELiS code (n-Dimensional Estimation of Lidar Signals) to numerically evaluate a simple, efficient aggregation method for combining airborne lidar measurements (submeter footprints) into space lidar signals (decametric footprints). Two main sources of error are studied: the heterogeneity of the scene combined with an insufficient coverage by the airborne scanner, and the multiple scattering of the laser pulse in vegetation. It is found that for three different types of vegetation (corn, orchard, rainforest), and in three usual scanning configurations, the satellite signal can be derived with good precision. However, multiple scattering in the vegetation is shown to induce errors of up to 30% of the total backscattered signal depending on the wavelength.