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Ali, Mahmoud El Nokrashy 
ACCURACY ANALYSIS FOR NEW CLOSE-RANGE 
PHOTOGRAMMETRIC SYSTEMS 
Dr. Mahmoud El-Nokrashy O. ALI Dr. Mohamed Ashraf ELIWA 
Prof. of Photogrammetry, Civil Eng. Associate Prof. of Geodesy, Civil Eng 
Al Azhar University, Cairo, Egypt Minia University, Minia, Egypt. 
m_ali@starnet.com.eg 
Dr. Ahmed Abd-Elreheem MOHAMMED Eng. Abbas Mohammed ABBAS 
Associate Prof. of Photogrammetry, Civil Eng. Lecturer Assistant, Civil Eng. 
Assuit University, Assuit, Egypt Minia University, Minia, Egypt. 
Working Group V/1 
KEY WORDS: Close Range Photogrammetry, Accuracy Evaluation, Mobile Mapping System. 
ABSTRACT 
Mobile mapping system is a close range photogrammetric system proved to be useful in many GIS applications. 
Whenever an area needs to be surveyed, a van equipped with all the necessary instruments and sensors travels into that 
area and takes a series of images of the objects and collects other information related to each images. The data is 
displayed on the workstation monitor. Through the interaction, the operator can measure all of the objects that appear in 
multiple images and subsequently calculate and store 3D data in GIS database. 
Due to financial limitation it was impossible to have a mobile system. But using simple technique it was possible to 
investigate many factors, which could affect the accuracy and performance of such system. So, this study was done 
using professional non-metric 35mm camera. Image coordinates were measured using stereo-comparator and the data 
was processed on a personal computer using bundle with self-calibration aerial triangulation program. The description 
of the tests which have been carried out as well as the results and their analysis are presented. 
1- INTRODUCTION 
In 1989, the Center for Mapping of the Ohio State University established a major research program that focuses on the 
development of Mobile Mapping Systems (MMS). These devices capture a comprehensive set of land-related data from 
airplanes, cars, or trains. Spatial positions and attributes of objects are extracted automatically on the mobile platform or 
during post-processing, and are immediately transferred to a multi-media geographic database (Novak, 1995). 
The University of Calgary and GEOFIT INC., a high-tech company in Laval, Quebec, Canada have Jointly developed 
the same system The system named VISAT, stands for Video-Inertial-SATellite and integrates inertial and GPS 
technology with a cluster of CCD cameras (El-Sheimy, 1996 & Li , 1996). 
The main objective of this research is to study some of the factors affecting the accuracy of any close range 
photogrammetric system such as the mobile mapping. The study area was a road 12mx100m at Assuit University 
campus. Professional non-metric (Voigatlander) 35 mm camera, mounted on a tripod, has a bubble for adjusting the 
horizontalty and has a handle with graduation for rotating was employed with black and white film as a data acquisition 
system. Natural points were selected as control and check points. Their coordinates were estimated using field survey 
techniques. Fig.1 illustrates the study area and the positions of camera stations and the object points (both control & 
check points.) 
Image coordinates were measured four times using a stereocomparator and the average was used for data processing. 
The accuracy of the measurements can be assumed 2 or 3 microns. A Bundle adjustment with Self-Calibration (BSC) 
program developed and written by Novak from Ohio State University was utilized for photogrammetric triangulation. 
Bundle adjustment is an analytical method used to compute accurate object space coordinates of points from their 
photographic coordinates. Basically, a bundle is created by each exposure of a camera. The perspective center and the 
points in the image define this bundle in a local image coordinate system. The bundle solution tries to shift and rotate 
these bundles of light-rays so that they fit to some given control points. Additionally constraints can be included such as 
distances measured between object points or perspective centers, to further stabilize the solution (Novak 1991). Bundle 
adjustment can also be extended to calibrate the cameras and solve for additional parameters to model distortions of the 
images. These parameters, as well as, an open interior orientation, help to fit the bundles to the object control in a better 
way. 
  
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B5. Amsterdam 2000. 17