4.5 Review

Digital Aerial Photogrammetry for Updating Area-Based Forest Inventories: A Review of Opportunities, Challenges, and Future Directions

Journal

CURRENT FORESTRY REPORTS
Volume 5, Issue 2, Pages 55-75

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/s40725-019-00087-2

Keywords

Digital aerial photogrammetry; Image-matching; Airborne laser scanning; Forest inventory update; Digital stereo imagery; Forest structure; Image based point clouds

Categories

Funding

  1. AWARE (Assessment of Wood Attributes using Remote sEnsing) Natural Sciences and Engineering Research Council of Canada Collaborative Research and Development grant
  2. Canadian Wood Fibre Centre of the Canadian Forest Service

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Purpose of ReviewThree-dimensional (3D) data on forest structure have transformed the level of detail and accuracy of forest information. While these 3D data have primarily been derived from airborne laser scanning (ALS), there has been growing interest in the use of 3D data derived from digital aerial photogrammetry (DAP) and image-matching algorithms. In particular, research and operational forestry communities are interested in using DAP data to update existing ALS-derived enhanced forest inventories. Although DAP depends on accurate terrain information provided by ALS to normalize digital surface models to heights above ground, in an inventory update scenario, DAP data currently have cost advantages over repeat ALS acquisitions.Recent FindingsExtensive research across a broad range of forest types has demonstrated that DAP data can provide comparable accuracies to ALS for estimating inventory attributes such as volume, basal area, and height when used in an area-based approach with co-located ground plot information.SummaryHerein, we review research relevant to the use of DAP for updating area-based forest inventories in subsequent inventory cycles, highlighting issues and opportunities for DAP data in this context. We examine the use of DAP for area-based forest inventory applications, comparing data inputs, algorithms, and outcomes across numerous studies and forest environments. Lastly, we outline outstanding research gaps that require further inquiry including benchmarking of acquisition parameters and image-matching algorithms.

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