995, p.
.omatic
. Ph.D,
Farhad Samadzadegan
A ROBUST AUTOMATIC DIGITAL TERRAIN MODELLING METHOD
BASED ON FUZZY LOGIC
Farhad SAMADZADEGAN', Mehdi REZAEIAN®, Michael HAHN"
"University of Tehran, IRAN
Faculty of Engineering, Department of Surveying Engineering
Paradeyes @kanoon.net
^ University of Applied Sciences, Stuttgart, GERMANY
m.hahn.fbv Q fht-stutteart.de
Working Group III/2
KEY WORDS: Fuzzy Logic, Fuzzy Reasoning, Fuzzy Inference System, DTM, Matching, Robust Estimation, Finite
Elements
ABSTRACT
Most of the proposed methods for automatic DTM reconstruction are based on parametric estimation processes with
very little capabilities for reasoning and decision making. Human operators which measure DTMs solve interpretation
related problems while they carry out the geometric measurements. When working with terrain often decisions have to
be made which are of imprecise nature. For those problems fuzzy logic is a perfect basis to design a fuzzy inference
process.
In this paper we start to develop a fuzzy system for DTM acquisition. Fuzzy logic can be blended with proven concepts
and modules of DTM generation and therefore may supplement rather than substitute classical procedures for DTM
reconstruction. In a first step we design and implement algorithms for fuzzy feature detection and fuzzy matching in
image space. The transfer from image space to object space is then carried out by classical spatial intersection combined
with robust finite element modelling for the reconstruction of the terrain surface. Experiments with a Iranian test site are
carried out and show the applicability of the procedure. In the next step of future work imprecise hypothetical
information extracted from image space will be combined in a fuzzy manner with surface modelling to complete the
fuzzy inference system.
1 INTRODUCTION
Itis more than ten years ago that success in image matching has initiated the development of numerous concepts and
routines for automatic acquisition of Digital Terrain Models (DTMs). First experiments with those routines have
indicated that the automatic procedures promise high accuracy of the reconstructed surface. Today, DTM modules are
mostly included in the software packages of digital photogrammetric systems and are widely applied in production. By
listening to critical voices it has to be noticed that neither commercial nor academic DTM modules are doing the job in
such a way that production highly benefits from automatically acquired DTMs. Many reports state that there is a fairly
high demand for interactive DTM editing and post processing in standard applications.
A closer look to these methods shows that in general DTM collection procedures are based on parametric estimation
processes combined with some robustification to eliminate errors. Obviously this classical concepts can not solve DTM
data collection properly. There is, for example, no procedure in such processes which may help to find out whether
measured points are on the terrain or on top of some topographic or manmade objects. Thus a lack of reasoning about
possible causalities has to be noticed in these approaches.
To cope with unsatisfactory DTM quality other sensors like laser scanners and radar are taken into account. The
discrimination between first and last response of the reflected laser signal contributes to a simplification of the
Interpretation related aspects of DTM acquisition. But this does not mean that the basic interpretation problem is solved
or bypassed with range measurement scanners.
Instead of working with complementary data sources like range data and images more sophisticated algorithms may be
developed which is basically the background of the presented work. In the following we propose a method which
employs established concepts of hierarchical feature based matching and robust finite element modelling and introduce
International Archives of Photogrammetry and Remote Sensing. Vol, XXXIII, Part B3. Amsterdam 2000. 799
