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GEOG5060 GIS & Environment

School of Geography FACULTY OF ENVIRONMENT. GEOG5060 GIS & Environment. Dr Steve Carver Email: S.J.Carver@leeds.ac.uk. Lecture 6: Terrain modelling - applications. Outline: introduction access modelling landscape evaluation. Introduction. Many applications of terrain models

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GEOG5060 GIS & Environment

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  1. School of Geography FACULTY OF ENVIRONMENT GEOG5060 GIS & Environment Dr Steve Carver Email: S.J.Carver@leeds.ac.uk

  2. Lecture 6: Terrain modelling - applications Outline: introduction access modelling landscape evaluation

  3. Introduction • Many applications of terrain models • visualisation covered already: • hillshading and orthographic views • animation and photorealism • others: • access modelling • visibility analysis and landscape evaluation • hazard mapping • hydrological modelling

  4. Access modelling • Terrain is a vital element for realistic access models • flat, boundless plains of Weberian industrial location analysis just don’t exist! • need to take terrain-based costs into account • Slope as push/pull factor • Barrier features • additional layer in GIS access models

  5. Distance models • Isotropic distance models • don’t take cost factors into account • e.g. eucdistance in GRID or buffer in Arc/Info • Anisotropic distance models • take cost factors into account • e.g. costdistance in GRID

  6. Example distance model output Buffer zones Distance surface Anisotropic surface Residuals

  7. Routing models • Cost or “friction” surfaces can be used to calculate shortest path between two points • Euclidean model takes only distance into account • result is straight line or “as the crow flies” • anisotropic model takes cost or friction surface into account • may be positive (push) or negative (pull) • uses “cost” of traversing a cell in a particular direction to identify least accumulative cost route • result is unlikely to be a straight line

  8. Example routing output Crianlarich-Benmore circular walk Minimum distance/time surface Check-points Actual route Predicted route

  9. Case study: modelling remoteness • Off-road accessibility is function of: • distance from nearest road • slope relative to direction of travel • ground conditions (trafficability) • barrier features (rivers, lakes, cliffs, etc.) • Combine within anisotropic access model as cost or friction surfaces

  10. Question...What other cost factors might we include in a model of off-road accessibility?

  11. Remoteness model • Combined model integrating: • Dijkstra’s Shortest Path Algorithm • calculate shortest path from origin to any destination based on relative costs of movement through set of cells between origin and destination • Naismith’s Rule (1892) • “an hour for every three miles on the map, with an additional hour for every 2,000 feet of ascent” • -10 minutes/300 m descent for slopes 5°>12°; +10 minutes/300 m descent for slopes >12°

  12. Model implementation • Implemented as C++ routine • using inputs from Arc/Info GRID • can be platform/software independent • Single or multiple origin models • Incorporates geographical factors • distance matrix modified according to cost/push factors by adding/subtracting time penalties to represent effects of ground cover, trails, etc. • effects of barriers (rivers, lakes and cliffs) represented by cells with null values

  13. Results • Naismith's/Dijkstra's model used to model relative remoteness of Cairngorms area under different scenarios • with and without mountain-bike access along trails • before and after proposed ski funicular • Arc/Info alternative COSTPATH • calculates the least-accumulative-cost distance over cost surface from source cell(s) accounting for surface distance and horizontal/vertical cost factors.

  14. “What if?” modelling of Mountain bike restrictions Mar Lodge estate With mountain bike use along track from Linn of Dee Without mountain bike use along track from Linn of Dee

  15. Effects of the Ski Funicular With parking restrictions at the Day Lodge and along access road Without parking restrictions at the Day Lodge or along access road

  16. Landscape evaluation “Scenery is a natural resource... [to determine which landscapes are of high quality and deserve attention by resource managers, it is essential...] to attempt the evaluation of scenic resources in some objective and quantitative fashion”(Linton, 1968, p.219)

  17. Conflicting views “Beauty cannot be described: therefore it cannot be defined... measured... [or] made the basis of a science” (Kates, 1967, p.22) “It’s about time that environmentalists supported their arguments... [about landscape aesthetics] with numbers” (Leopold, 1969, p.41)

  18. Components of landscape • Biophysical • terrain (relief, variability, geomorphology, etc.) • water inc. snow & ice (presence, type, quality) • flora and fauna (variety, condition, etc.) • Socio-psychological • land use inc. urban (type, extent, modification) • transport (accessibility, intrusion) • other human features (powerlines, dams, etc.) • cultural (presence, type) • people (numbers, activities, behaviour, etc.) • mystery

  19. The role of GIS in landscape studies • Descriptive • INVENTORY - map presence/absence • EVALUATIVE - map quality / suitability • PREDICTIVE - model impacts of proposed action • RECOMMEDATORY - map preventative measures • SYNTHESIS - integrate the above • Combined • mix elements of descriptive and preference approaches • multi-criteria (landscape) evaluation

  20. What’s in a view? • What can be seen from where is a key component of landscape analysis • depends strongly on terrain variables • can be quantified using visibility analysis • what, how much and what quality?

  21. Visibility analysis • Use of DTM to calculate “viewshed” of particular point • where can point X be seen from on surface Y? • what part of surface Y can be seen from point X? • Multiple point viewsheds combined to calculate viewshed of line and area features • where and part of feature X be seen on surface Y? • what part of surface Y can be seen from which point on feature X?

  22. Calculating viewsheds • Uses line of sight from observer point to terrain surface to calculate intervisibility matrix: • visible parts of terrain surface • non-visible areas (i.e. ‘dead’ areas) • Use of observation point and terrain offsets • e.g. height of person or observation tower • e.g. height of wind turbine or other feature

  23. not visible visible Calculating an inter-visibility matrix Offset a Offset b v nv v nv v nv without offset b with offset b

  24. Example viewsheds

  25. Uses of visibility analysis • Many different uses… • visual impact analysis • landscape evaluation • siting of observation towers and cellular communications masts • modelling coverage of cellular communications • military applications • virtual GIS

  26. Wind farm impact assessment

  27. Landscape evaluation of Scotland Litton’s 1968 scenic assessment DEM Intervisibility matrix (After Miller)

  28. Landscape evaluation of Britain

  29. Cell phone coverage, Vodafone

  30. PFS FILE • 100km x 100km • 50m resolution • one cell DEF File • Location X & Y • Height • Power • Mechanical Downtilt • Antenna Type • Orientation Coverage Estimation Algorithm Terrain Database Clutter Database Algorithm Terrain database Clutter database GEOG5060 - GIS and Environment

  31. Predicted Field Strength (PFS) files

  32. PFS PFS PFS PFS PFS PFS Coverage databases VGis Coverage Databases Database Update • Live Databases • Planned Databases

  33. Predicted digital coverage

  34. Military applications

  35. Virtual GIS

  36. Hazard mapping • Certain types of hazard are either created or controlled by terrain • avalanches and landslides • floods and mudflows • lahars, lava and pyroclastic flows • Knowledge of terrain is essential in creating hazard maps

  37. Example: avalanche hazard mapping • Model for predicting avalanche potential based on DEM data • assessment of the terrain • slope • aspect (relative to wind direction) • snow accumulation • prevailing weather (precipitation, temperature and wind)

  38. Question…What kind of model is most appropriate?Model parameters are required?

  39. Snow avalanche likelihood based on assessment of terrain and snow accumulation. Red indicates that a destructive avalanche is almost certain to occur within a 30 year period. Green indicates that it is almost certain that no avalanche will occur. Example predictive avalanche map

  40. Conclusions • Many uses for DEMs in environmental applications of GIS • key variable determining accessibility • important landscape variable • controlling factor in “gravity” hazards including flooding, avalanches, landslides, etc.

  41. Workshop • Visibility analysis • Questions to consider: • What uses are there for visibility analysis? • What are the key issues/problems associated with the technique?

  42. Practical • Visibility and impact assessment • Task: Calculate viewshed and visual impact of wind farm • Data: The following datasets are provided… • Digital elevation model (50m resolution 1:50,000 OS Panorama data) • Contour data (1:50,000 OS Panorama data) • ITE land cover map (25m resolution) • Roads (1:250,000 Meridian data) • Population density (200m resolution) • Wind farm turbine location(s)

  43. Practical • Steps: • Calculate viewshed of wind turbines using both 1 and 16 turbines assuming a turbine height of 30m • Estimate the relative impact of the turbines

  44. Practical • Familiarity with the VISIBILITY command in Arc/Info • Experience with developing impact assessments based on environmental variables

  45. Next week… • Hydrological modelling 1: catchment models • Basics of hydrology • Creating hydrologically correct DEMs • Modelling catchment variables • Workshop: Catchment modelling in GRID • Practical: Catchment modelling

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