REFINED SATELLITE IMAGE ORIENTATION IN THE FREE OPEN-SOURCE PHOTOGRAMMETRIC TOOLS APERO/MICMAC

E Rupnik,Y Klinger,M Pierrot Deseilligny,A Delorme

doi:10.5194/isprsannals-iii-1-83-2016

E Rupnik, Y Klinger + Show 2 more

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https://doi.org/10.5194/isprsannals-iii-1-83-2016

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Abstract

This publication presents the RPC-based bundle adjustment implemented in the freeware open-source photogrammetric tool Apero/MicMac. The bundle adjustment model is based on some polynomial correction functions, enriched with a physical constraint that introduces the notion of a global sensor rotation into the model. The devised algorithms are evaluated against two datasets consisting of two stereo and a triplet pair of the Pleiades images. Two sets of correction functions and a number of GCPs configurations are examined. The obtained geo-referencing accuracy falls below the size of 1GSD.

Highlights

The value of high-resolution optical satellite imaging in earth sciences is indisputable
The satellite optical sensors offer a variety of ground sample distances (GSD) and frequent revisit times are advantageous for cost-effective land-cover classification (Schindler, 2012), country/world-wide digital surface model (DSM) creation, orthophoto generation (d‘Angelo, 2013) or even updating of the city building models/cadastral maps (Guerin et al, 2014)
The mean reprojection error in the range of 3 pixels, and the significant differences on check points (CPs) suggest that both the relative and absolute orientations are apt for refinement

Summary

Introduction

The value of high-resolution optical satellite imaging in earth sciences is indisputable. Among the most common applications are the mapping of natural hazards, monitoring the effects of the climate change, as well as large-scale land classification and surveying. Quantification of the ground displacements caused by Earthquakes with e.g. SPOT-2 (Puymbroeck et al, 2000), SPOT-5 (Binet and Bollinger, 2005; Vallage et al, 2015), Quickbird-II (Rosu et al, 2015) has proven to give supixel accuracy result. The satellite optical sensors offer a variety of ground sample distances (GSD) and frequent revisit times are advantageous for cost-effective land-cover classification (Schindler, 2012), country/world-wide digital surface model (DSM) creation, orthophoto generation (d‘Angelo, 2013) or even updating of the city building models/cadastral maps (Guerin et al, 2014)

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