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Estimation of Individual Tree Metrics Using Structure-From-Motion Photogrammetry

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Estimation of Individual Tree Metrics Using Structure-From-Motion Photogrammetry Estimation of Individual Tree Metrics using Structure-from-Motion Photogrammetry A thesis submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geography Jordan M. Miller Department of Geography University of Canterbury 2015 Abstract The deficiencies of traditional dendrometry mean improvements in methods of tree mensuration are necessary in order to obtain accurate tree metrics for applications such as resource appraisal, and biophysical and ecological modelling. This thesis tests the potential of SfM-MVS (Structure-from- Motion with Multi-View Stereo-photogrammetry) using the software package PhotoScan Professional, for accurately determining linear (2D) and volumetric (3D) tree metrics. SfM is a remote sensing technique, in which the 3D position of objects is calculated from a series of photographs, resulting in a 3D point cloud model. Unlike other photogrammetric techniques, SfM requires no control points or camera calibration. The MVS component of model reconstruction generates a mesh surface based on the structure of the SfM point cloud. The study was divided into two research components, for which two different groups of study trees were used: 1) 30 small, potted ‘nursery’ trees (mean height 2.98 m), for which exact measurements could be made and field settings could be modified, and; 2) 35 mature ‘landscape’ trees (mean height 8.6 m) located in parks and reserves in urban areas around the South Island, New Zealand, for which field settings could not be modified. The first component of research tested the ability of SfM-MVS to reconstruct spatially-accurate 3D models from which 2D (height, crown spread, crown depth, stem diameter) and 3D (volume) tree metrics could be estimated. Each of the 30 nursery trees was photographed and measured with traditional dendrometry to obtain ground truth values with which to evaluate against SfM-MVS estimates. The trees were destructively sampled by way of xylometry, in order to obtain true volume values. The RMSE for SfM-MVS estimates of linear tree metrics ranged between 2.6% and 20.7%, and between 12.3% and 47.5% for volumetric tree metrics. Tree stems were reconstructed very well though slender stems and branches were reconstructed poorly. The second component of research tested the ability of SfM-MVS to reconstruct spatially-accurate 3D models from which height and DBH could be estimated. Each of the 35 landscape trees, which varied in height and species, were photographed, and ground truth values were obtained to evaluate against SfM-MVS estimates. As well as this, each photoset was thinned to find the minimum number of images required to achieve total image alignment in PhotoScan and produce an SfM point cloud (minimum photoset), from which 2D metrics could be estimated. The height and DBH were estimated by SfM-MVS from the complete photosets with RMSE of 6.2% and 5.6% respectively. The height and DBH were estimated from the minimum photosets with RMSE of 9.3% and 7.4% respectively. The minimum number of images required to achieve total alignment was between 20 and 50. There does not appear to be a correlation between the minimum number of images required for alignment and the error in the estimates of height or DBH (R2=0.001 and 0.09 respectively). Tree height does not appear to affect the minimum number of images required for image alignment (R2=0.08). I External parameters, which include things such as the position of the tree relative to its surroundings, the background scene and the ambient lighting, appear to be the primary determinants of model success. The results show that SfM-MVS is capable of producing estimates of 3D and 2D metrics with accuracy at least equal to that of laser scanning and potentially much more accurate than allometric models and traditional dendrometry techniques. SfM-MVS provides a low-cost alternative to remote sensing technologies currently used such as terrestrial laser scanning, and as no specialised equipment is required it is able to be used by people with little expertise or training. Future research is required for exploring the suitability of SfM-MVS for specific applications requiring accurate dendrometry. II Table of Contents Chapter One: Introduction ........................................................................................................... 1 1.1 Background ................................................................................................................................... 1 1.2 Current Methods for Traditional Dendrometry ............................................................................ 1 1.3 The Need for Accurate Tree Mensuration .................................................................................... 4 Chapter Two: Remote Sensing in Forestry ..................................................................................... 7 2.1 Laser Scanning ............................................................................................................................... 7 2.1.1 Remote Sensing in Forestry - Aerial Laser Scanning .............................................................. 8 2.1.2 Remote Sensing in Forestry - Terrestrial Laser Scanning ....................................................... 9 2.2 Optical Dendrometry and Photogrammetry ............................................................................... 11 2.2.1 Remote Sensing in Forestry - Stereo-photogrammetry ....................................................... 13 2.3 Remote Sensing in Forestry - Structure from Motion and Multi-View Stereo ........................... 14 2.3.1 The SfM-MVS Workflow ....................................................................................................... 15 2.3.2 Aerial SfM-MVS .................................................................................................................... 16 2.3.3 Terrestrial SfM-MVS ............................................................................................................. 17 2.4 Summary ..................................................................................................................................... 18 2.5 Research Questions ..................................................................................................................... 18 Chapter Three: SfM-MVS Estimation of Tree Metrics................................................................... 20 3.1 Introduction ................................................................................................................................ 20 3.1.1 Research Aim ....................................................................................................................... 20 3.2 Method ........................................................................................................................................ 21 3.2.1 Overall Approach ................................................................................................................. 21 3.2.2 Study Area ............................................................................................................................ 21 3.2.3 Image Acquisition ................................................................................................................. 23 3.2.4 Ground Truth Mensuration .................................................................................................. 23 3.2.5 Model Reconstruction in PhotoScan.................................................................................... 25 3.2.6 Model Spatial Scale .............................................................................................................. 28 3.2.7 Linear Measurement in PhotoScan ...................................................................................... 28 3.2.8 Volume Measurement of Nursery Trees ............................................................................. 28 3.2.9 Volume Measurement in PhotoScan ................................................................................... 31 3.2.10 Statistical Analysis .............................................................................................................. 32 3.3 Results ......................................................................................................................................... 32 III 3.3.1 Volume ................................................................................................................................. 33 3.3.2 Height and Crown ................................................................................................................ 34 3.3.3 Stem Diameter ..................................................................................................................... 37 3.4 Discussion .................................................................................................................................... 39 3.4.1 SfM-MVS Volume Estimation ............................................................................................... 40 3.4.2 SfM-MVS Volume Estimation – Results in the context of previous research ...................... 40 3.4.2.1 Results in the context of previous research - Allometric Stem Taper Models ................. 40 3.4.2.2 Results in the context of previous research - Terrestrial Photogrammetry ..................... 41 3.4.2.4 Results in the context of previous research - Terrestrial Laser Scanning ......................... 42 3.4.3 SfM-MVS Linear Estimation ................................................................................................
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