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UAV-based Tree Height Estimation in Dense Tropical Rainforest Areas in Ecuador and Brazil

    Stefan Reder, Lilli Waßermann, Jan-Peter Mund

GI_Forum 2019, Volume 7, Issue 2, pp. 47-59, 2019/12/11

Journal for Geographic Information Science

doi: 10.1553/giscience2019_02_s47

doi: 10.1553/giscience2019_02_s47


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doi:10.1553/giscience2019_02_s47



doi:10.1553/giscience2019_02_s47

Abstract

The aim of this study was to develop an easily applicable, cost-efficient workflow for tree height estimation in remote, inaccessible rainforest areas in Ecuador and Brazil. Structure from Motion (SfM) was combined with a digital terrain model (DTM) from the Shuttle Radar Topography Mission (SRTM) to complement relief information from photogrammetric point clouds (PPC) which represent the upper canopy layers. Based on ground points extracted from a 3D model, a vertical shift of the model was applied to adjust the ellipsoid level of the PPC. Digital surface models (DSM) of 22 research plots were normalized to canopy height models (CHM) to allow the estimation of relative tree heights in all research plots without using ground control points (GCP). The calculated tree height values indicate the applicability of the proposed workflow even in tropical rainforests with dense canopies. This approach allows the classification of canopy structures for identifying forest succession and other ecological forest monitoring purposes. The results highlight the potential of 3D models for tree height estimation derived from PPCs based on unmanned aerial vehicle (UAV) imagery in rainforest research.

Keywords: unmanned aerial vehicle (UAV), rainforest, canopy height model (CHM), structure from motion (SfM), forest structure