Year of Award


Document Type


Degree Type

Master of Science (MS)

Degree Name

Geography (Community and Environmental Planning Option)

Department or School/College


Committee Chair

Dr. David Shively

Commitee Members

Kevin McManigal, Douglas Brinkerhoff, Lisa Eby


Structure-from-motion, photogrammetry, stream assessment and monitoring, remote sensing


University of Montana

Subject Categories

Geographic Information Sciences | Natural Resource Economics | Remote Sensing | Spatial Science | Water Resource Management


Two of the biggest weaknesses in stream restoration and monitoring are: 1) subjective estimation and subsequent comparison of changes in channel form, vegetative cover, and in-stream habitat; and 2) the high costs in terms of financing, human resources, and time necessary to make these estimates. Remote sensing can be used to remedy these weaknesses and save organizations focused on restoration both money and time. However, implementing traditional remote sensing approaches via autonomous aerial systems or light detection and ranging systems is either prohibitively expensive or impossible along small streams with dense vegetation. Hand-held Structure from Motion Multi-view Stereo (SfM-MVS) photogrammetric technology can solve these problems by offering a resource efficient approach for producing 3D Models for a variety of environments. SfM-MVS photogrammetric technology is the result of cutting-edge advances in computer vision algorithms and discipline-specific research in the geosciences. This study found that images taken by GoPro, iPhone, and Digital Single-Lens Reflex cameras were all capable of producing 3D representations of heavily vegetated stream corridors with minimal image post-processing using workflows within Agisoft Metashape™. Analysis within Agisoft Metashape™ produced expected measurements from 3D textured mesh models, digital elevation models, and orthomosaics that were comparable to the physical measurements taken at the time of each survey using an arbitrary latitude, longitude, and elevation classification scheme. The methods described in this study could be applied in future stream restoration and monitoring efforts as a means to complement in person collection and measurement while limiting effort andmoney spent.



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