To What Extent Can UAV Photogrammetry Replicate UAV LiDAR to Determine Forest Structure? A Test in Two Contrasting Tropical Forests

Iain M. Mcnicol, Edward T. A. Mitchard, Chiara Aquino, Andrew Burt, Harry Carstairs, Creck Dassi, Anaick Modinga Dikongo, Mathias I. Disney

Research output: Contribution to journalArticlepeer-review

Abstract

Tropical forests are complex multi-layered systems, with the height and three-dimensional (3D) structure of trees influencing the carbon and biodiversity they contain. Fine-resolution 3D data on forest structure can be collected reliably with Light Detection and Ranging (LiDAR) sensors mounted on aircraft or Unoccupied Aerial Vehicles (UAVs), however, they remain expensive to collect and process. Structure-from-Motion (SfM) Digital Aerial Photogrammetry (SfM-DAP), which relies on photographs taken of the same area from multiple angles, is a lower-cost alternative to LiDAR for generating 3D data on forest structure. Here, we evaluate how SfM-DAP compares to LiDAR data acquired concurrently using a fixed-wing UAV, over two contrasting tropical forests in Gabon and Peru. We show that SfM-DAP data cannot be used in isolation to measure key aspects of forest structure, including canopy height (%Bias: 40%–50%), fractional cover, and gap fraction, due to difficulties measuring ground elevation, even under low tree cover. However, we find even in complex forests, SfM-DAP is an effective means of measuring top-of-canopy structure, including surface heterogeneity, and is capable of producing similar measurements of vertical structure as LiDAR. Thus, in areas where ground height is known, SfM-DAP is an effective method for measuring important aspects of forest structure, including canopy height, and gaps, however, without ground data, SfM-DAP is of more limited utility. Our results support the growing evidence base pointing to photogrammetry as a viable complement, or alternative, to LiDAR, capable of providing much needed information to support the mapping and monitoring of biomass and biodiversity.
Original languageEnglish
Article numbere2021JG006586
JournalJournal of Geophysical Research: Biogeosciences
Volume126
Issue number12
Early online date12 Dec 2021
DOIs
Publication statusPublished - 20 Dec 2021

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