This document discusses different methods for representing digital terrain, including grids, TINs, quadtrees, and multi-resolution models. Grid DEMs represent terrain as a regular grid of elevation postings. TINs use an irregular network of triangles to connect elevation postings. Quadtrees adapt resolution based on terrain complexity. Multi-resolution models provide multiple levels of detail for large terrain datasets. Each method has advantages like storage efficiency or terrain adaptation and disadvantages like processing costs or irregularity. The best method depends on the application and dataset characteristics.

1. DIGITAL TERRAIN
REPRESENTATIONS
GROUP MEMBERS
Agasha Ochneva, Biniyam
Tilahun
Gülendam Baysal, Roya
Olyazadeh
Muhammad Maimaiti, Shiuli
Pervin
David González Sánchez
Roberto Mediero Martí

2. GENEREAL EXPLANATION OF
DIGITAL TERRAIN
REPRESENTATIONS
A digital terrain model is a topographic
model of the bare earth –terrain relief - that
can be manipulated by computer programs.
The data files contain the spatial elevation
data of the terrain in a digital format

3. DATA SOURCE:
 Ground survey,
 Digitizing contours,
 Digital Photogrammetry,
 Direct image grid DEM,
 LiDAR, RADAR, SONAR;

4. CLASSIFICATION
 The pattern of DTM data could be:
regula
regular irregular
or irregular
r
 Regular: square or rectangular grid
 Irregular: may be based on triangular
network of irregular size, shape and
orientation
 These DIM data could be structured in
different
ways such as grid/raster, quadtree,

5. MOST IMPORTANT
REPRESENTATIONS
TIN
DEM
QUADRATREE
MULTIRESOLUTION

6. Grid DEM
Main description
 DEM: A digital representation of a topographic surface
 They are based on the values of the elevation at the
sampling points- one height per pixel (grid cell)
 The grid representation is the consequence of
sampling elevation values in regular intervals of
latitude and longitude.

7. Grid DEM
Main description
 The result is a matrix whose indices are the
coordinates and values are the elevation value at
each point (raster representation)
 From this sample representation it is possible to
get a representation of the relief

8. Grid DEM
Main description
The steps to build a grid DEM are:
Obtaining the data: Sampling elevation
values in a regular grid pattern; process and
filtered of the acquired data
Model building: Data structures building and
storage
Optimization and visualization of the model

9. SAMPLES

10. SAMPLES

11. ADVANTAGES of GRID
 Regular sample pattern --> Simple data
storage structures and algorithm
 Multisource possibility --> Compatible with
many sources, even satellite, and easy to
combine with imagery
 Allow a high resolution visualization with a
relatively simple process
 It is easy to use to generate other
models, and to deduce from other models

12. DISADVANTAGES of GRID
 Regular sample pattern --> Possibility of
oversampling or
undersampling and redundant data points.
Uniform pixel size. Large amount of storage
memory for large resolutions
 Multisource possibility --> Large mathematical
process to combine them, heavy computation
processes
 For very high resolutions, a too large collection of
points to
render in a short time
 Transformation into/from other models involves a
heavy computational mathematic process

13. TIN
Vector based model
Made up of Irreguarly distributed points
and lines with three dimenion
Vertices are connected with the edges to
form a network of triangles

14. TIN (TRIANGULAR IRREGULAR
NETWORK)
Different methods of Interpolation of TIN:
 Delaunay triangulation
 Distance ordering
 ArcGIS use Delaunay triangulation
 The edge of the TINs forms
continuous non overlapping
triangular facets
Nodes and edge Nodes, edge and facet of TIN

15. TIN (TRIANGULAR IRREGULAR
NETWORK)
Delaunay triangulation
Delaunay triangulation is a proximal method that
satisfies the requirement that a circle drawn through
the three nodes of a triangle will contain no other
node

16. TIN (TRIANGULAR IRREGULAR
NETWORK)
Distance ordering
compute the distance between all pairs
of points
sort from lowest to highest
connect the closest pair of
points until it covers all the points to
form triangulation
this tends to produce many skinny
triangles instead of the preferred "fat"
triangles.

17. TIN (TRIANGULAR IRREGULAR
NETWORK)
Data Structure:
 TIN applied for both regularly and irregularly located
data
 A regular grid network can be formed by interpolation
from a triangular network
 Delaunay triangulation use static data structure
 The input feature used to form the dem remains in
same position

18. TIN (TRIANGULAR IRREGULAR
NETWORK)
Data Structure:
It is possible to create a TIN surface from features,
such as points, line, and polygons that contain
elevation information
Acceptable data size:
10 to 15 million nodes represents the largest size for Win32. The
recommended size is to bound at a few million for the sake of
usability and performance.

19. ADVANTAGES of TIN:
 The position of input feature remain
unchanged
 Fewer points needed for the same accuracy
 Less dik space is needed
 TIN preserves all the precision of input data
 Preisely located feature on a surface
 resolution adapts to terrain
 Typically used for high precision modeling of
smaller areas

20. DISADVANTAGES of TIN:
 Usually TIN expects units to be in feet or
meters, not decimal degrees
 Delaunay Triangulation is not valid when
triangulation constructed using angular
coordinate from the geographic coordinate
system.
 More expensive to build and process
 less widely available than the raster surface
model
 TIN is seems to be less efficient than processing
raster data.

21. MULTI-RESOLUTION
 It provides an abstraction for representing, manipulating, and
visualizing large volumes of spatial data at multiple levels of
detail and accuracy (LOD).
 vertex removal, edge collapse, and triangle collapse.
 It shows topographic features: peak, pit, ridge
channel, pass, valley, concave or convex area.
MULTI-RESOLUTION

22. ALGORITHMS
They have been improved and by using least square
adjustment they can add or remove details by
changing resolution.

23. ALGORITHMS
 B-Spline algorithm
 Multi-TIN
 Regular Triangle Mesh
 Simplification

24. ADVANTAGES DISADVANTAGES
- Easy analysis of - This method is so
topographic parameters at complicated and using
different resolutions. different algorithms in
different level and
- This model can be used for sometimes least square
huge data with level of adjustment for unique
detail (LOD) in online form. answer
- There is no technique for
- It may remove noise and simplification and multi-
errors in the input data and resolution modeling of
tetrahedral meshes.
- Maintainance of the
topology of the isolines of
the TIN at full resolution at - Irregularities caused by
differents LODs. real small scale landforms
in the landscape.

25. USAGE AND APPLICATION
Multi-Resolution method can be fundamental for applications
involving geometric navigation and computations on the mesh.
For example: contour line extraction, drainage network
computation, path planning, etc.

26. SAMPLES

27. QUADTREE
 Quadtree is a grid-based
structure and has variable
resolution.
 A quadtree have tree data
structure in which each
internal node has
exactly four children.

28. STEPS

29. TYPES
 The restricted quadtree for regularly-
sampled surface data
 PMR quadtree for irregularly-sampled data.

30. RQT QUADTREE
RQT is like decomposition of quadtree which
employs only shared vertices.

31. PMR QUADTREE
Uses probabilistic splitting rule

32. SAMPLES

33. ADVANTAGES of QUADTREE
 Need less storage space
 Compact representation of the terrain
 Fast LOD triangulation and rendering, and are
easier to implement as well.

34. DISADVANTAGES of QUADTREE
 Not very efficient structure to represent grid
DTM data, continuous surface, and
unclassified imagery data.
 Difficult to modify any changes to the pattern
of the data, requires recalculation of the
quadtree.

35. SAMPLES

36. FINAL COMPARISON
DEM TIN MR QT
Regular Sample
Pattern √ √ X √ X √ X
Data Storage X √ √ √
Multisource
Possibility √ √ √ √
Visualisation √ √ √ √
Conversion √ √ √ X
Speed of
Performance X √ √ √
Level of Details
(LOD) X √ √ √

37. RESOURSES:
Book and Research Paper Resources
 Emanuele Danovaro, Leila De Floriani, Enrico Puppo1, and Hanan Samet, Out-of-core Multi-resolution
Terrain Modeling, Department of Computer and Information Science University of Genoa - Via
Dodecaneso, 35, 16146 Genoa, Italy
 Zhi Wanga, Qingquan Lia, Besheng Yanga, Multi Resolution Representation of Digital Terrain Models
with topographical features presentation, State Key Laboratory for Information Engineering in
Surveying, Mapping and Remote Sensing, Wuhan University,
 Emanuele Danovaro, Leila De Floriani, Paola Magillo, Mohammed Mostefa Memoudi,Enrico
Puppo, MorphologyDriven Simplification and Multiresolution Modeling of Terrains, Dipartimento di
Informatica e Scienze dell’Informazione Universit `a di Genva
 Jan Rasmus SULEBAK and Øyvind HJELLE,2003, Multiresolution Spline Models and Their
Applications in Geomorphology, SINTEF Applied Mathematics, P.O. Box 124, Blindern, N-0314
Oslo, Norway
 HÉLIO PEDRINI, 2001, Multi-Resolution Terrain Modeling based on Triangulated Irregular
Networks, Revista Brasileira de Geociências 31(2):117-122, 2001
 Leila De Floriani , Paola Magillo, Regular and Irregular MultiResolution Terrain Models: a Comparison
Dept. of Computer Science University of Genova
Web Resources
http://www.etsimo.uniovi.es http://www.etsimo.uniovi.es
http://www.gtbi.net http://en.wikipedia.org
http://www.technion.ac.il http://www.wiley.com
http://eprints.utm.my http://www.earsel.org

38. Obrigado por sua atenção!
Gracias por su atención!
Thank you for your attention!
Þakka þér fyrir athygli þína!
Gràcies per la seva atenció!