Improving bird population models using airborne remote sensing

This work was undertaken to devise a technique to measure the height of crops in farmland fields through remote sensing. Crop height is a useful spatial variable which, when measured by ground-based manual survey, has proven to be an important predictor of bird species population. An airborne scanning laser system capable of measuring topography to a height accuracy of better than 10 cm was used to acquire height data over a region of farmland near Oxford, UK. A scanning laser wa's pulsed from an aircraft at the ground, measuring the time between transmission and receipt of the last significant return signal. Differential Geographical Positioning System (GPS) and onboard attitude sensors were combined with these delay times to construct a set of spot heights through the region. Crop height was also measured from the ground. Pulses were returned from mainly within the crop, rather than predominantly the canopy or ground, so an algorithm to measure the variation of the returned height, after detrending the heights for topography, was developed. A simple relationship was found between the mean crop height and the standard deviation of detrended return heights within a field. This relationship could be used to derive crop height from Light Detection and Ranging (LiDAR) data with an accuracy better than 10 cm.