digital terrain modelling · digital terrain modelling ayman f. habib 3 terminology • dem...

Digital Terrain Modelling Ayman F. Habib1

Digital Terrain Modelling

Chapter 1: Introduction


Digital Terrain Modelling• Definition:

– A statistical representation of the continuous surface of the ground by a large number of selected points with known X, Y, and Z co-ordinates in an arbitrary co-ordinate field.

– Provide the means for representing the continuous surface in a digital form using a finite amount of storage.

– Provide the means for representing the earth’s surface in the computer.

• Terminology:– Digital Terrain Model (DTM).– Digital Elevation Model (DEM).– Digital Height Model (DHM).– Digital Ground Model (DGM).– Digital Terrain Elevation Data (DTED).– Digital Surface Model (DSM).


Terminology

• DEM (Digital Elevation Model): – Generally refers to a regular array of elevations

(squares or hexagon).– The term is in widespread use in the USA.

• DHM (Digital Height Model):– Similar as DEM but less commonly used.– The term originated in Germany.

• DGM (Digital Ground Model):– More emphasis on the digital model of the

solid/continuous surface of the earth.– The term in is general use in the UK.


Terminology

• DTM (Digital Terrain Model):– More complex concept involving elevations and other

GIS features (e.g., rivers, ridges, break lines, etc.).– It encompasses terrain relief, planimetric, and derived

data (slope, aspect, visibility, etc.).• DTED (Digital Terrain Elevation Data):

– Term used by the US National Geospatial-Intelligence Agency (NGA).

• Formerly known as the National Imaging and Mapping Agency (NIMA).

• Formerly known as the Defense Mapping Agency (DMA).– Usually refers to girded/regular arrays.


Terminology

• DSM (Digital Surface Model):– The previous terms usually refer to bare terrain models.– DSM refers to digital models including features above

the surface of the earth (e.g., buildings).– Very important for ortho-photo generation.


DTM Application Domains

• Civil Engineering:– Cut-and-fill problems for road design.– Site planning.– Volumetric calculations in building dams and reservoirs.

• Earth Sciences:– Drainage basin network development and delineation.– Hydrological run-off modelling.– Geo-morphological simulation and classification.– Geological mapping.– Generating slope and aspect maps.


Cut and Fill Applications


Volumetric Calculations


Transportation - Highway Expansion


Power Line Mapping


DTM Application Domains

• Planning and Resource Management:– This is a major grouping of diverse fields including remote

sensing, agriculture, soil science, meteorology, climatology, environmental and urban planning, and forestry, whose central focus is the management of natural resources.

– Site location.– Support of image classification in remote sensing by DTM

derivatives.– Geometric and radiometric correction of remote sensing images.– Soil erosion potential models.– Crop suitability studies.– Wind flow and pollution dispersion models.


DTM Application Domains• Surveying and Photogrammetry:

– They are important sources for DTM generation.– DTMs are useful for various surveying and photogrammetric

activities:• Ortho-photo production,• Data quality assessment, and • Topographic mapping.

• Military Applications:– Consumers and producers (e.g., NGA).– End objectives are very specialised and demanding.– Inter-visibility analysis for battlefield management.– 3-dimensional display for weapons guidance systems and flight

simulation.– Radar line-of-sight analyses.


Perspective Image Versus Ortho-photo

Perspective Projection Orthogonal Projection


Perspective Image Versus Ortho-photo

• Perspective Projection • Orthogonal Projection


Elements of Digital Terrain Modelling

• Tasks involved in DTM production and use.


DTM Generation

• Sampling of original terrain data, and formation of relations among the diverse observations (model construction). This could be done through:– Photogrammetric data capture (including aerial photography and

digital satellite imagery). [Passive Sensor]– RADAR: RAdio Detection And Ranging. [Active Sensor]

• Radio wave portion of the electromagnetic spectrum.– LIDAR: LIght Detection And Ranging. [Active Sensor]

• Ultraviolet, visible and infrared region of the electromagnetic spectrum.

– Digitized contours.– Ground surveying


Passive Sensors (e.g., Optical Imagery)

A

a

Sensor


Active Sensors (e.g., LIDAR & RADAR)

Sensor

A

Emitted Wave

a

Reflected Wave


Active and Passive Sensors


DTM Generation / Photogrammetry

ADS 40

RC 30

DMCTM

Data acquisition systems


Object Point (A)

Conjugate Points

• The relative relationship between the two camera stations has to be known.

a a´



DTM Generation / LIDAR

ALS 40


Visible & LIDAR Range Imagery


Visible & LIDAR Intensity Imagery


DTM Generation / Digitized Contours

• Contours in analog maps can be:– Manually digitized,– Semi-automatically or automatically extracted after

raster scanning.

• Drawback:– Inherit exiting errors in the available maps.– Not accurate.– Dense data along the contour lines and hardly any data

across the contour lines.


DTM Generation / Digitized Contours


DTM Generation / Ground Surveying

• Characteristics:– Most accurate technique.– Time consuming.– Very expensive.

• Usually restricted to specific projects involving small areas.


DTM Generation / Ground Surveying


DTM Manipulation

• Modification and refinement of DTMs, and derivation of intermediate models.

• This might include:– Editing: correcting errors and updating DTMs.– Filtering: smoothing, enhancing, compression, and

resampling.– Merging and joining DTMs: combining DTMs from

several sources (possibly at different epochs).– Converting DTM from one data structure to another:

for example: TIN to grid conversion.


DTM Interpretation

• DTM analysis and information extraction.– The value of DTMs depends on the derived knowledge

and information regarding terrain and its attributes.

• General geomorphometry:– Generate slope and its dual derivatives of the gradient

and aspect.

• Specific geomorphometry:– Analytically portrays terrain features and attributes in

relation to the surface hydrology.


DTM Visualization

• Graphical rendering of DTMs and derived information.

• Very important for perceptual understanding and appreciation of DTMS.

• Visualization addresses two objectives:– Interactive visualization for exploring, calibration and

refinement applications.– Static visualization for basic communication of results.

• Visualization tools include 3-D modeling, realistic scene rendering and animation.


DTM Applications• Development of appropriate application models for specific disciplines.• Within the scope of this course, these are typical applications of DTMs:

– Given (X,Y) estimate/find Z.– Given an array of (X,Y,Z) points, fit a surface to estimate Z.– Given an array of (X,Y,Z) points at fixed interval, interpolate Z at selected

(X,Y).– Generation of profiles.– Contour line estimation.– Determine line-of-sight.– Earthwork calculations.– Slope.– Aspect.– Image rectification for ortho-photo generation.


Data Models in DTM• A surface model should:

– Accurately represent the surface. – Be suitable for efficient data collection.– Minimise data storage requirements. – Maximise data handling efficiency. – Be suitable for surface analysis.

• Representation Alternatives:– Contour lines.– Raster DTM/DEM.– Triangular Irregular Networks (TIN).


Contour Lines• Contour Line: locus of points with constant elevation.

– Dense information along the contour line.– Hardly any information across the contour line.

H H

V

V

U

UG

G

P

C1

C2

C3

C4

1

2

3

45

6

7

8


Raster Versus TIN Representations

• Raster DEM:– Elevation data are available at equally spaced grid

points.

• TIN:– Elevation data are available at irregular points that are

connected by triangle legs.– The TIN is generated in such a way that the summation

of the lengths of the triangle legs is minimum.


Area of Interest


Raster DEM


Raster DEM

494640.00 494680.00 494720.00

4251820.00

4251840.00

4251860.00

4251880.00

4251900.00

4251920.00

4251940.00

4251960.00

4251980.00

4252000.00


Lattice Versus Categorical Interpretation

Lattice Categorical


Grid Size & Surface Representation

• Sampling interval will affect:– Amount of details captured (accuracy).– Amount of storage (redundancy, efficiency).

• Optimum sampling interval depends on the nature of the terrain.


Raster DEM• Advantages:

– Simple data structures (similar to a digital image).– Capability of applying most of array processing

techniques.

• Disadvantages:– Difficult to integrate break lines.– Large space requirement for data storage.– Reconstructing the surface requires the need for solving

large equation systems.


Raster DEM

• Advantages: – Already have grid DEM with no further processing.– Is suitable for trend surfaces.

• Disadvantages:– Inefficient sampling.– The highest or lowest points on the landscape are rarely

sampled.


TIN• Each Vertex must have the following information

(attributes):– Height.– Connectivity information (how are the vertices

connected to each other to form the TIN).– Surface normal (perpendicular to the tangent at the

surface).• For vertices along break lines, we need to have two surface

normals.

• You can force the triangle legs to coincide with the break lines.


TIN


TIN Generation• Objective:

– Define a network of triangles through the reference points.

• Criterion:– The summation of the lengths of the triangle legs is

minimum.

• Some techniques:– Delauny Triangulation.– Radial sweep algorithm.


TIN Generation

• Three points form a triangle if the circle which passes through them contains no other point


TIN

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