PERFORMANCE ANALYSIS OF DISTRIBUTED ORTHO GENERATION USING ERDAS 
ORTHO ACCELERATOR (LOA) 
Yasemin Kuzu-Sinram 
ERDAS, Inc. 5051 Peachtree Comers Circle, Norcross, Georgia 30092-2500 - yasemin.sinram@erdas.com 
Commission IV, WG IV/3 
KEY WORDS: Distributed, Automation, Processing, Digital, Orthorectification, Performance 
ABSTRACT: 
The demand for digital ortho imagery is rapidly increasing with the growth of Internet and GIS applications. Orthophotos are a 
valuable source of information for government agencies, engineers, planners, land managers and individuals. Orthophotos are 
required to be updated periodically and the delivery times are decreasing rapidly. The size and the number of the images increase 
with the demand for more detailed and accurate imagery. Since ortho rectification projects are becoming very data heavy, ortho 
production is a bottleneck for photogrammetric shops due to huge processing times which is often too high for single processor 
architectures.In this paper we are examining the benefits of the ERDAS Ortho Accelerator by analyzing the performance of the 
distributed processing. In this experiment, we have chosen large orthorectification jobs to show the time savings of distributed 
processing. Distributed orthorectification processing performance metrics are analyzed with respect to the number of processing 
nodes applied. The results are also compared to stand-alone processing performance. This paper shows distributed processing is 
necessary with large photogrammetric projects as processing time can decrease significantly with the number of nodes used. 
1. INTRODUCTION 
Adoption rates of distributed processing in the photogrammetry 
industry have not been universal. Photogrammetric processing 
is largely workstation-based. With the advances in computer 
and network hardware, current inexpensive computer systems 
can handle larger amounts of data and computer prices are 
getting relatively cheaper. In order to generate orthos in reduced 
delivery times demanded by the market, photogrammetric 
workflows can use automated procedures such as distributed 
computing. Distributed computing can be defined as the ability 
to divide large processing jobs into smaller tasks and running 
them on multiple processors or multiple machines. Distributed 
processing harnesses the processing power of several CPU 
nodes to increase throughput. It results in greater throughput 
and frees up operators to perform other tasks. Also, purchasing 
nodes instead of softcopy workstations will result in cost 
savings. 
ERDAS Ortho Accelerator (LOA) is developed under a 
strategic development agreement between Leica Geosystems 
Geospatial Imaging (now ERDAS) and GeoCue Corporation 
(formerly NIIRS10). LOA was developed to speed up the rate 
with which digital orthophotos are produced. LOA integrates 
ERDAS photogrammetric processing components into the 
GeoCue geospatial process management framework to create a 
very efficient, enterprise-enabled orthophoto production 
environment. LOA is an extension (CuePac) to GeoCue. A 
CuePac is a collection of GeoCue menus, checklist and 
auxiliary programs that implement a “canned” set of workflows. 
GeoCue is not workstation centric. The command dispatch 
system allows distributing ortho jobs to remote nodes. With 
orthorectification and mosaicking capabilities, ERDAS Ortho 
Accelerator takes advantage of the distributed and scheduled 
workflow processing capabilities as well as process 
management tools provided by GeoCue. 
LOA provides below solutions to several market problems 
which exist in orthophoto production processes: 
• Orthorectification jobs are distributed to individual 
machines (ortho nodes). 
• Dispatched tasks can be run on a machine other than 
the one on which it was launched 
• Orthorectification and mosaicing jobs can be 
scheduled to run at user defined times 
• Multi user access to the same project from any 
workstation in the network. 
• Accurate and real-time monitoring of scheduled tasks. 
• Each manipulation of the data is incrementally saved 
via transaction processing against the database. 
• The system is protected from unauthorized access to 
data 
• User-defined metadata can be associated with the 
imagery 
LOA consists of 3 modules which are: Project Importer, Ortho 
CuePac and Mosaic CuePac. LOA is built on LPS and ERDAS 
mosaicing components. 
Project Importer enables introducing a photogrammetric 
project into the GeoCue managed workflow. LOA supports LPS 
block files, BAE SOCET SET® projects, INPHO MATCH-AT 
projects and Intergraph Z/I Imaging® and ImageStation® 
Automatic Triangulation (ISAT) projects. When a 
photogrammetric project is imported, graphical objects are 
created in GeoCue with geographically correct footprints and 
locations in the Map View. Also, metadata is attached to each 
entity that includes fields such as interior and exterior 
orientation, image size, camera information and so fort. 
Ortho CuePac is an enterprise ortho production system that is