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

Abstract

Purpose of Review Three-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 Findings Extensive 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. Summary Herein, 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 areabased 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. Keywords Digital aerial photogrammetry. Image-matching. Airborne laser scanning. Forest inventory update. Digital stereo imagery. Forest structure. Image based point clouds This article is part of the Topical Collection on Remote Sensing

Structure from Motion Photogrammetry in Forestry: a Review

“…However, photogrammetric data can be combined with pre-existing ground data, derived from light detection and ranging data (LiDAR) for example. This data synergy has been thoroughly discussed by Goodbody et al [11], indicating the potential for cost-efficient forest inventory updates. Similarly, Kangas et al [6] suggest an equal value of photogrammetric and ALS data in forest management planning, given that a ALS ground information is available from previous campaigns.…”

Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities

“…2020, 12, 1046 2 of 35 used [4]. Forest ecosystems are very dynamic, being extremely important to the acquisition of accurate and up-to-date data [5]. The regular acquisition of data could be very expensive, depending on which remote sensing platform is being used [6].…”

Individual Tree Detection in a Eucalyptus Plantation Using Unmanned Aerial Vehicle (UAV)-LiDAR

“…UAV-LiDAR allows the production of LiDAR data at a fraction of the cost of airplane LiDAR [48]. However, with UAV, it is possible to reach difficult-to-approach areas such as narrow valleys and to acquire higher resolution point clouds [20,48,49]. For these reasons, the weight of laser scanners was reduced to meet the carrying capacity of UAVs [50].…”

“…It has been proven to be adequate for both ABA and ITD approaches [19]. A synergy can be achieved by combining LiDAR data and SfM [20]. However, when they are compared alone, SfM may provide poor definition of the mid-and under-story when the crowns overlap [21].…”