@article{LatifiHeurich2019,
  author    = {Latifi, Hooman and Heurich, Marco},
  title     = {Multi-scale remote sensing-assisted forest inventory: a glimpse of the state-of-the-art and future prospects},
  series = {Remote Sensing},
  volume    = {11},
  journal   = {Remote Sensing},
  number    = {11},
  issn      = {2072-4292},
  doi       = {10.3390/rs11111260},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197358},
  year      = {2019},
  abstract  = {Advances in remote inventory and analysis of forest resources during the last decade have reached a level to be now considered as a crucial complement, if not a surrogate, to the long-existing field-based methods. This is mostly reflected in not only the use of multiple-band new active and passive remote sensing data for forest inventory, but also in the methodic and algorithmic developments and/or adoptions that aim at maximizing the predictive or calibration performances, thereby minimizing both random and systematic errors, in particular for multi-scale spatial domains. With this in mind, this editorial note wraps up the recently-published Remote Sensing special issue "Remote Sensing-Based Forest Inventories from Landscape to Global Scale", which hosted a set of state-of-the-art experiments on remotely sensed inventory of forest resources conducted by a number of prominent researchers worldwide.},
  language  = {en}
}