Assessing the Accuracy of High Resolution Digital Surface Models Computed by PhotoScan® and MicMac® in Sub-Optimal Survey Conditions

Marion Jaud,Réjanne Le Bivic,Nicolas Le Dantec,Philippe Grandjean,Sophie Passot,Christophe Delacourt

doi:10.3390/rs8060465

Abstract

For monitoring purposes and in the context of geomorphological research, Unmanned Aerial Vehicles (UAV) appear to be a promising solution to provide multi-temporal Digital Surface Models (DSMs) and orthophotographs. There are a variety of photogrammetric software tools available for UAV-based data. The objective of this study is to investigate the level of accuracy that can be achieved using two of these software tools: Agisoft PhotoScan® Pro and an open-source alternative, IGN© MicMac®, in sub-optimal survey conditions (rugged terrain, with a large variety of morphological features covering a range of roughness sizes, poor GPS reception). A set of UAV images has been taken by a hexacopter drone above the Rivière des Remparts, a river on Reunion Island. This site was chosen for its challenging survey conditions: the topography of the study area (i) involved constraints on the flight plan; (ii) implied errors on some GPS measurements; (iii) prevented an optimal distribution of the Ground Control Points (GCPs) and; (iv) was very complex to reconstruct. Several image processing tests are performed with different scenarios in order to analyze the sensitivity of each software package to different parameters (image quality, numbers of GCPs, etc.). When computing the horizontal and vertical errors within a control region on a set of ground reference targets, both methods provide rather similar results. A precision up to 3–4 cm is achievable with these software packages. The DSM quality is also assessed over the entire study area comparing PhotoScan DSM and MicMac DSM with a Terrestrial Laser Scanner (TLS) point cloud. PhotoScan and MicMac DSM are also compared at the scale of particular features. Both software packages provide satisfying results: PhotoScan is more straightforward to use but its source code is not open; MicMac is recommended for experimented users as it is more flexible.

Highlights

Remote sensing techniques combined with data from Unmanned Aerial Vehicles (UAVs) can provide imagery with very high spatial and temporal resolution and covering areas of a few Remote Sens. 2016, 8, 465; doi:10.3390/rs8060465 www.mdpi.com/journal/remotesensingRemote Sens. 2016, 8, 465 hundred meters
They claim that the best distribution of Ground Control Points (GCPs) is an even distribution throughout the focus area with a spacing of 1/5 to 1/10 of the UAV flying height, and that GCPs should be closer in steeper terrain
Before processing data with MicMac based on the different scenarios, the MicMac module for UAV

Summary

Introduction

Remote sensing techniques combined with data from Unmanned Aerial Vehicles (UAVs) can provide imagery with very high spatial and temporal resolution and covering areas of a few Remote Sens. 2016, 8, 465; doi:10.3390/rs8060465 www.mdpi.com/journal/remotesensingRemote Sens. 2016, 8, 465 hundred meters. Many recent studies deal with performance assessment of methods and software solutions for georeferenced point clouds or Digital Surface Models (DSMs) production; see [10], for instance, for a literature review on this issue. Harwin and Lucieer [13] notice that the number and the distribution of the Ground Control Points (GCPs) have a major impact on the accuracy, on the area with topographic relief. They claim that the best distribution of GCPs is an even distribution throughout the focus area with a spacing of 1/5 to 1/10 of the UAV flying height, and that GCPs should be closer in steeper terrain.

Objectives

Results

Conclusion