Farrell, S.L., Collier, B.A., Skow, K.L., Long, A.M., Campomizzi A.J., Morrison, M.L., Hays K.B. and Wilkins R.N. 2013. Using LiDAR-derived vegetation metrics for high-resolution, species distribution models for conservation planning. Ecosphere. 4(3):42.

            The use of coarse grain methods is very common in the species distribution modeling. Because species distribution is influenced by local habitat conditions, these models may result inaccurate. Light Detection and Ranging (LiDAR) allows to obtain high resolution and precise of surface or vegetation structure. The authors evaluated if the use of estimates of vegetation height and canopy cover derived from LiDAR, would provide more accurate high-resolution models than standard remotely sensed. Farrell et al., modeled the distribution of two federally endangered: golden-checked warbler and black-capped vireo, combining LiDAR and standart remotely sensed data. Their results show that, while models that included LiDAR derived vegetation height and canopy cover resulted competitive for both species, models without LiDAR data had notable lower weight. Thus, they prove that LiDAR can provide ecological important high resolution information that enhances the performance of the prediction models.