Lidar Remote Sensing for Forestry and Terrestrial Applications

Abstract

Remote sensing has facilitated extraordinary advances in modeling, mapping,<br><br>and the understanding of ecosystems. Applications of remote sensing involve<br><br>either images from passive optical systems, such as Aerial Photography and<br><br>the Landsat Thematic Mapper, or, active Radar sensors such as RADARSAT.<br><br>These types of remote sensors have proven to be satisfactory for many forest<br><br>applications, such as mapping and classifying land cover into specific classes<br><br>and, in some biomes, estimating aboveground biomass and Leaf Area Index<br><br>(LAI). However, conventional sensors have significant limitations for<br><br>ecological and forest applications. The sensitivity and accuracy of these<br><br>devices have repeatedly been shown to fall with increasing aboveground<br><br>biomass and LAI. They are also limited in their ability to represent the spatial<br><br>patterns. They produce only two-dimensional (x & y) images, which cannot<br><br>fully represent the three dimensional structure of the forest canopy. Ecologists<br><br>have long understood that the presence of specific organisms and the overall<br><br>richness of wildlife communities can be highly dependent on the threedimensional<br><br>spatial pattern of vegetation. Individual bird species, in particular,<br><br>are often associated with specific three dimensional features in riparian<br><br>forests. Additionally, aspects of forests, such as productivity, may be related to<br><br>forest canopy structure. Lidar (light detecting and ranging) is an alternative<br><br>remote sensing technology that promises to both increase the accuracy of<br><br>biophysical measurements and extend spatial analysis into the third dimension<br><br>(z). Lidar sensors directly measure the three-dimensional distribution of forest<br><br>canopies as well as sub-canopy topography, therefore providing high<br><br>resolution topographic maps and highly accurate estimates of tree height cover, and canopy structure. In addition, lidar has been shown to accurately<br><br>estimate LAI and aboveground biomass, even in those high biomass<br><br>ecosystems, where passive optical and active radar sensors typically fail to do<br><br>so. Estimation of forest structural attributes, such as LAI, is an important step<br><br>in identifying the amount of water use in forest areas.