A mathematical method usually employed in economics for studying income inequality has been applied to the study of tree-size variation using lidar data. Researchers from the University of Eastern Finland have identified and analyzed indicators for expressing size differences among neighboring trees and developed methods to obtain these indicators — which measure characteristics such as stem density — using lidar technology. In this method, forests were scanned with a laser on board a plane that penetrated the canopy and provided information about the entire vertical profile. Laser scans were obtained throughout entire forest areas to create high-resolution maps of changes within small forest areas, and detect characteristics that field-plot sampling cannot. The study, which was the basis of Rubén Valbuena’s doctoral thesis (doi: 10.14214/df.205), used indicators based on the Lorenz curve, such as the Gini coefficient, to create maps of several study areas in Finland and Spain. Similarly to the way a society can be evaluated not just for being rich but also for being egalitarian, a forest can be evaluated for its structural complexity — variations in tree size, for example — in addition to commonly measured properties such as biomass and growth. The researchers said that maps created using the lidar technology could allow identification of various structural properties of forests, evaluate different types of forest management regimes and monitor compliance of forestry practices with legal restrictions to logging in a more cost-effective and environmentally friendly way. Valbuena's doctoral thesis was carried out in collaboration with the European Forest Institute, Technical University of Madrid and Natural Resources Institute of Finland. Funding was provided by the Finnish Forest Service via the Foundation for European Forest Research. Most recently the work was published in Ecological Indicators (doi: doi:10.1016/j.ecolind.2015.08.001).