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Open AccessArticle

Semi-Automated Delineation of Stands in an Even-Age Dominated Forest: A LiDAR-GEOBIA Two-Stage Evaluation Strategy

1
Department of Natural Resources and Society, College of Natural Resources, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844, USA
2
Forestry Sciences Laboratory, Rocky Mountain Research Station, Forest Service, U.S. Department of Agriculture, 1221 South Main St., Moscow, ID 83843, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(10), 1622; https://doi.org/10.3390/rs10101622
Received: 25 August 2018 / Revised: 26 September 2018 / Accepted: 9 October 2018 / Published: 12 October 2018
(This article belongs to the Special Issue Advances in Remote Sensing of Forest Structure and Applications)
Regional scale maps of homogeneous forest stands are valued by forest managers and are of interest for landscape and ecological modelling. Research focused on stand delineation has substantially increased in the last decade thanks to the development of Geographic Object Based Image Analysis (GEOBIA). Nevertheless, studies focused on even-age dominated forests are still few and the proposed approaches are often heuristic, local, or lacking objective evaluation protocols. In this study, we present a two-stage evaluation strategy combining both unsupervised and supervised evaluation methods for semi-automatic delineation of forest stands at regional scales using Light Detection and Ranging (LiDAR) raster summary metrics. The methodology is demonstrated on two contiguous LiDAR datasets covering more than 54,000 ha in central Idaho, where clearcuts were a common harvesting method during the twentieth century. Results show good delineation of even-aged forests and demonstrate the ability of LiDAR to discriminate stands harvested more than 50 years ago, that are generally challenging to discriminate with optical data. The two-stage strategy reduces the reference data required within the supervised evaluation and increases the scope of a reliable semi-automatic delineation to larger areas. This is an objective and straightforward approach that could potentially be replicated and adapted to address other study needs. View Full-Text
Keywords: GEOBIA; LiDAR; forest stand delineation; even-aged; supervised evaluation; unsupervised evaluation GEOBIA; LiDAR; forest stand delineation; even-aged; supervised evaluation; unsupervised evaluation
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MDPI and ACS Style

Sanchez-Lopez, N.; Boschetti, L.; Hudak, A.T. Semi-Automated Delineation of Stands in an Even-Age Dominated Forest: A LiDAR-GEOBIA Two-Stage Evaluation Strategy. Remote Sens. 2018, 10, 1622.

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