Title: Slajd 1
1Warsaw University of Technology
APPLICATION OF COMPUTATIONAL INTELLIGENCE
ALGORITHMS IN TOPOLOGY PRESERVING PROCESS OF
DTM SIMPLIFICATION
Robert Olszewski
2Assumption data
- Generalisation of the digital terrain model is
an important issue for supplying geographic
information systems with data, - The main idea of generalisation of the DTM
should be the preservation of its structure (the
morphological skeleton), - Simple algorithms of the DTM generalisation
allow for relatively low reduction of the
structure complexity
3The aim of the research
- Development of the concept of the multiscale
(hierarchical) representation of the terrain
relief, - The concept of multirepresentation digital
terrain model is a logical supplement of the idea
of multirepresentation (MRDB) topographic
database and allows to perform common analyses of
all topographic components.
Hierarchical DTM with monoscales representations
of the model at an arbitrary, user-defined level
of generalisation
4Spatial data generalisation
- Distinction
- model generalisation (analysis-oriented),
- cartographic generalisation (display-oriented)
- Distinction
- DLM (to supply geographic information systems),
- DCM (to supply maps production systems)
5Digital Terrain Model - DTM
- Generalisation of the DTM is based on one of the
methods (Weibel, 1992) - global filtration,
- local filtration (usually multi-stage),
- heuristic approach.
Generalisation of the DTM (TIN) is understood as
model generalisation and not as generalisation of
contour lines
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7The idea of DTM generalisation
- combination of two approaches (local weighted
filtration structure lines extraction), - multi iteration approach,
- determination of the skeleton of the terrain,
- dichotomic classification of source data (mass
points vs. structural points), - differential weighting for mass and structural
points, - multiscale (hierarchical) TIN model (with
monoscale representations), - topology preservation...
8The idea of DTM generalisation
- combination of two approaches (local weighted
filtration structure lines extraction), - multi iteration approach,
- determination of the skeleton of the terrain,
- dichotomic classification of source data (mass
points vs. structural points), - differential weighting for mass and structural
points, - multiscale (hierarchical) TIN model (with
monoscale representations), - topology preservation...
9Tatra Mountains
10The idea of DTM generalisation
- combination of two approaches (local weighted
filtration structure lines extraction), - multi iteration approach,
- determination of the skeleton of the terrain,
- dichotomic classification of source data (mass
points vs. structural points), - differential weighting for mass and structural
points, - multiscale (hierarchical) TIN model building
(with monoscale representations), - topology preservation...
11Topology preservation
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13Spatial data mining and model generalisation
- Nowadays, the algorithmic approach may be
considered as the dominating tendency in the
field of spatial data generalisation, but - Results of utilisation of computational
intelligence and cognitive modelling are also
very promising ... - On the contrary to classical expert systems,
well known since the eighties of the 20th
century, which utilise IF-THEN deterministic
rules, the essence of this approach is connected
with the use of machine learning (ML) processes
(Meng, 1998).
14Inference systems
15The idea of DTM generalisation
- combination of two approaches (local weighted
filtration structure lines extraction), - multi iteration approach,
- determination of the skeleton of the terrain,
- dichotomic classification of source data (mass
points vs. structural points), - differential weighting for mass and structural
points, - multiscale (hierarchical) TIN model (with
monoscale representations), - topology preservation...
16Weighted local filtration
- In the process of generalisation points are
eliminated basing on local evaluation of several
criteria - vertical significance (mass points structural
points), - horizontal significance (density) (mass points
structural points), - the weight of a structural line (structural
points only), - the local sinusoity of a structural line
(structural points only).
Selection of significance of particular factors
is fully parameterised, what allows arbitrary
assigning of weighting coefficients.
17DTM generalisation
TIN generalisation
18Implementation
2D (MapInfo)
193D (ArcGIS)
20Hierarchical model
21Levels of TIN
topology preservation
22Inference engines
-
- Engines already implemented
- CRISP,
- FUZZY,
- NEURO
-
- Engines to be implemented
- classification and regression trees,
- boosted trees,
- random forest,
- MARS (Multivariate Adaptive Regression Splines),
- SVM (Support Vector Machines)
23Conclusions
- The basic feature of generalisation of the
terrain model should be the preservation of its
structure (the morphological skeleton) - topology
preservation, - Utilisation of local weighted filtration
algorithms allow for - representative selection of points from the
source model, - the construction of the multiscale
(hierarchical) TIN model with a monoscale
representation at an arbitrary, user-defined
level of generalisation, - topology preservation..