Jen-Jer Jaw
CONTROL SURFACE IN AERIAL TRIANGULATION
Jen-Jer JAW
Department of Civil Engineering, National Taiwan University,
Taipei, Taiwan, Republic of China
Jejaw G ce.ntu.edu.tw
Working Group III/2
KEY WORDS: Control Surface, Tie Surface, Laser Range Finder, INSAR
ABSTRACT
With the increased availability of surface-related sensors, the collection of surface information becomes easier and more
straightforward than ever before. Thus, the integration of surface information into the photogrammetric workflow, the
task which has been long time interesting as well as challenging, is gaining focus again within the photogrammetric
community. In this paper, the author proposes a model in which the surface information is integrated into the aerial
triangulation workflow by hypothesizing plane observations in the object space, the estimated object points via photo
measurements (or matching) together with the adjusted surface points would provide a better point group describing the
surface. Apart from releasing aerial triangulation from the necessity of identifying control points in the object space, the
proposed algorithms require no special structure of surface points and involve no interpolation process. The proposed
system is proven workable having data collection in the photogrammetric laboratory.
1 INTRODUCTION
More and more surface related sensors, such as airborne laser range finder, INSAR (INterferometric Synthetic Aperture
Radar) with tightly integrated on-board GPS/INS system became commercially available during the last decade. By that,
the booming research and applications mainly in generating elevation information for the area of interest and scene
analyses, especially for the buildings in residential areas have been, among others, promising an era of sensors in which
the collection of surface information becomes easier and more straightforward than ever before. Besides, due to the
state-of-the-art of the sensor integration technique [Schwarz, 1995], the accuracy of the analyzed surfaces via airborne
laser scanning system proves competitive with the scenario where a well-controlled data set and careful measurements
by the operator are the necessities for the accuracy typical in traditional photogrammetric production line. Thus, how
would photogrammetrists consider this newly available technique and its seemingly favorable data set apart from the
aforementioned interests? One of the attractive thoughts follows: Can aerial triangulation by taking photo measurements
benefit from this sensor dominant era and do a better job for the task of the surface reconstruction and how? These
questions led the author into this study.
This very same idea and attempt had been carried out a decade ago at the Technical University of Munich, Germany,
conducted by Ebner [Ebner/Strunz,1988][Ebner et al., 1991][Ebner/Ohlhof, 1994] even when the laser range data did
not yet come to applications. Their algorithms focused mainly on the satisfaction of accuracy for the middle and small
scale photogrammetry by minimizing the differences between the heights of the object-to-be-solved and the interpolated
heights (bilinear interpolation) via the surrounding surface points, DEMs (Digital Elevation Models) in their case, as
constraints. In this study, without interpolation on the surface points and requiring no special structure of the surface
points, the author explo its different algorithms by hypothesizing planes (also called *control surface" in this paper) and
assessing the uncertainties via checking the fitting planes with local surface points; the minimization takes distances
along the surface normal as the target function when formulating the surface constraint.
The rest of this paper consists of the following: Section two introduces the surface constraint with formulating its
mathematical as well as stochastic model. The integration of surface constraint into aerial triangulation, the least
squares solution and the extended model by employing "tie surface" are explained in section three. Section four
demonstrates the experimental test in the photogrammetric laboratory together with the accuracy (root mean square
error) report and the analyses. Section five concludes this study by giving some observations of this research from this
author's perspective.
444 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000.
