Improving bird population models using airborne remote sensing

This work was undertaken to devise a technique to measure the height of cro ps in farmland fields through remote sensing. Crop height is a useful spati al variable which, when measured by ground-based manual survey, has proven to be an important predictor of bird species population. An airborne scanni ng laser system capable of measuring topography to a height accuracy of bet ter than 10 cm was used to acquire height data over a region of farmland ne ar Oxford, UK. A scanning laser wa's pulsed from an aircraft at the ground, measuring the time between transmission and receipt of the last significan t return signal. Differential Geographical Positioning System (GPS) and onb oard attitude sensors were combined with these delay times to construct a s et of spot heights through the region. Crop height was also measured from t he ground. Pulses were returned from mainly within the crop, rather than pr edominantly the canopy or ground, so an algorithm to measure the variation of the returned height, after detrending the heights for topography, was de veloped. A simple relationship was found between the mean crop height and t he standard deviation of detrended return heights within a field. This rela tionship could be used to derive crop height from Light Detection and Rangi ng (LiDAR) data with an accuracy better than 10 cm.