Week 19 GEOG2750 – Earth Observation and GIS of the Physical Environment

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Lecture 16Terrain modelling:

the basics

•Outline– introduction– DEMs and DTMs – derived variables– example applications

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Adding the third dimension

• In high relief areas variables such as altitude, aspect and slope strongly influence both human and physical environments– a 3D data model is therefore essential– use a Digital Terrain Model (DTM)– derive information on:

height (altitude), aspect and slope (gradient) watersheds (catchments) solar radiation and hill shading cut and fill calculations etc.

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DEMs and DTMs

• Some definitions…– DEM (Digital Elevation Model)

set of regularly or irregularly spaced height valuesno other information

– DTM (Digital Terrain Model)set of regularly or irregularly spaced height valuesbut, with other information about terrain surface ridge lines, spot heights, troughs, coast/shore lines,

drainage lines, faults, peaks, pits, passes, etc.

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UK DEM data sources

• Ordnance Survey:– Landform Panorama

source scale: 1:50,000 resolution: 50mvertical accuracy: ±3m

– Landform Profile source scale: 1:10,000 resolution: 10mvertical accuracy: ±0.3m

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Comparison

Landform Panorama Landform Profile

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LIDAR data (LIght Detection And Ranging)

Horizontal resolution: 2mVertical accuracy: ± 2cm

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Modelling building and topological structures

• Two main approaches:– Digital Elevation Models (DEMs) based on

data sampled on a regular grid (lattice)– Triangular Irregular Networks (TINs) based on

irregular sampled data and Delaunay triangulation

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DEMs and TINs

DEM with sample points TIN based on same sample points

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Advantages/disadvantages• DEMs:

– accept data direct from digital altitude matrices– must be resampled if irregular data used– may miss complex topographic features– may include redundant data in low relief areas– less complex and CPU intensive

• TINs:– accept randomly sampled data without resampling– accept linear features such as contours and breaklines (ridges and

troughs)– accept point features (spot heights and peaks)– vary density of sample points according to terrain complexity

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Task

• Make you own TIN from a piece of paper

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Derived variables

• Primary use of DTMs is calculation of three main terrain variables: – height

altitude above datum

– aspectdirection area of terrain is facing

– slope gradient or angle of terrain

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Question

• What might slope and aspect maps be used for?

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Calculating slope

• Inclination of the land surface measured in degrees or percent – 3 x 3 cell filter– find best fit tilted plane that minimises squared

difference in height for each cell– determine slope of centre (target) cell

Slope = b2 + c2

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z = a + bx + cy

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Calculating aspect

• Direction the land surface is facing measured in degrees or nominal classes (N, S, E, W, NE, SE, NW, SW, etc.)– use 3 x 3 filter and best fit tilted plane– determine aspect for target cell

Aspect = tan-1 c / b

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Other derived variables

• Many other variables describing terrain features/characteristics– hillshading– profile and plan curvature– feature extraction– etc.

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Examplesheight

slopeaspect

hillshading

plan curvature

Feature Feature extractionextraction

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Question

• What other important variables can be derived from DEMs?

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Problems with DEMs

• Issues worth considering when creating/using DTMs– quality of data used to generate DEM– interpolation technique– give rise to errors in surface such as:

sloping lakes and rivers flowing uphill local minimastepped appearanceetc.

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Example applications

• Visualisation– terrain and other 3D surfaces

• Visibility analysis– intervisibility matrices and viewsheds

• Hydrological modelling– catchment modelling and flow models

• Engineering– cut & fill, profiles, etc.

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Terrain visualisation

• Analytical hillshading• Orthographic views

– any azimuth, altitude, view distance/point– surface drapes (point, line and area data)

• Animated ‘fly-through’• What if? modelling

– photorealism– photomontage– CAD

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Examples of hillshading and orthographic projection

Hillshading

DEM

Orthographic projection

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Example surface drape

DEM

Rainfall

Draped image

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Example animated fly-through

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Photorealism

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Photo-realism “what if?” visualisation

Visualisation 1: before felling

Visualisation 2: clear-cut

Visualisation 3: strip felling

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Wind farm – photomontage

before

wire-frame model

after

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Conclusions

• Need for third dimensional GIS– especially in environmental applications– new data models/structures– new opportunities for analysis

• Basic uses and derived variables• Application areas

– visualisation– visibility analysis– etc.

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Practical

• Using DEMs for hillslope geomorphology• Task: Derive key variables from DEM and

relate to slope profiles• Data: The following datasets are provided

for the Hohe Tauern Alps, Austria…– 25m resolution DEM– 10m interval contour data (derived from 25m

resolution DEM)

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Practical

• Steps:1. Display DEM in ArcMap or GRID 2. Derive slope and aspect variables using slope

and aspect functions in GRID3. Derive valley cross and long profiles using the

identity tool in ArcMap4. Plot altitude, slope and aspect against distance

along profile in Excel5. Relate to physical form

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Learning outcomes

• Familiarity with TIN/DEM construction in Arc/Info

• Experience with deriving surface variables

• Experience with displaying surfaces in Arcplot

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Useful web links

• View global DEMs– http://www.ngdc.noaa.gov/mgg/image/images.html#relief

• DEM derived operations– http://www.powerdata.com.au/derive.htm

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After reading week…

• Terrain modelling: applications– Access modelling– Landscape evaluation– Hazard mapping

• Practical: Visibility assessment