Swatantran, A., Dubayah, R., Goetz, S., Hofton, M., Betts, M.G., Sun, M., Simard, M., and Holmes, R. 2012. Mapping migratory bird prevalence using remote sensing data fusion. PLoS ONE 7(1): e28922. doi:10.1371/journal.pone.0028922

            While environmental and climatic variables influence wildlife habitats, it is the structure of the vegetation one of the most important factors that influence habitat use in birds. Thus, vegetation structure characteristics of sites regularly used by birds may be indicators of habitat quality. Recent advances in remote sensing allow measuring those characteristics. In this study, the authors evaluated the capacity of predicting multi-year (prevalence) detections of 8 species of birds, using (multi-sensor fusion) three types of remote sensing data: LiDAR, Radar and multispectral. Among the results are: fusion improved the predictive power of Radar (25%), Landsat (15%), and LiDAR (4%). Thus, multi-sensor fusion was more accurate explaining variations in prevalence than any sensor alone. Therefore, multi-sensor fusion is an approach to improve habitat mapping.