The document discusses a presentation on the use of GRASS GIS for terrain visualization in the Rocky Mountains, focusing on the Sky View Factor (SVF) as a technique for modeling visibility using digital elevation models. It covers implementations, parameters, performance case studies, and applications, particularly in the context of datasets from Colorado and New Mexico. Various slides detail the effectiveness of visualizations based on the number of directions and data set size, including specific examples and results from case studies.

1. GRASS GIS: Striking Terrain Visualizations in the Rockies
An r.skyview tour: Ft. Collins, CO to Las Cruces, NM
Robert S. Dzur
rdzur@bhinc.com
GRASS GIS: Striking Terrain Visualizations in the Rockies Slide # 1
September 19-20, 2018
Hilton Denver Inverness, Denver, Colorado

2. Overview
Sky View Factor (SVF)
Definition / Background01
GRASS GIS Implementation
GRASS GIS in general; r.skyview extension
by Anna Petrasova, NCSU OSGeoREL
02
Applications - Outlook
Visualization on other LiDAR datasets;
potential use cases
04
Parameter Testing & Performance
Case study analysis of four (4) 3.75-minute
USGS Quarter Quadrangles
03
Overview Slide # 2
0°
45°315°

3. Sky view factor | n. A model of terrain visualization that uses an input
digital elevation model (DEM) to calculate the degree to which each
grid cell location is visible to the sky. [3]
The resulting calculations are used to shade and simulate multi-
directional diffuse illumination over the surface model. [2]
Sky View Factor (SVF)
Sky View Factor (SVF)
[1] B. Stular, Z. Kokalj, K. Ostir and L. Nuninger, "Visualization of lidar-derived
relief models for detection of archaeological features," Journal of
Archaeological Science, vol. 39, pp. 3354-3360, 2012.
[2] K. Zakšek, K. Oštir and Z. Kokalj, "Sky-View Factor as a Relief
Visualization Technique," Remote Sensing, vol. 3, pp. 398-415, 2011.
[3] Z. Kokalj, K. Zaksek and K. Ostir, "Application of sky-view factor for the
visualisation of historic landscape features in lidar-derived relief models,"
Antiquity, p. 263–273, March 2011.
[4] P. J. Kennelly and A. J. Stewart, "A Uniform Sky Illumination Model to
Enhance Shading of Terrain and Urban Areas," Cartography and
Geographic Information Science, vol. 33, no. 1, pp. 21-36, January 2006.
Horsetooth Reservoir SW
3Slide #

4. Number of Directions:
Visualization: At least 8 directions and more than 32 search directions
bring no noticeable improvement. [2]
Maximum Search Radius:
Visualization: Consider the objective of the visualization & the size of
the objects of interest - between between 10 and 30 pixels good for
general purpose - greater than 50 pixels adds significant
computational expense. [2]
Data Set Size & Spatial Resolution:
Visualization: size of the dataset is currently the limiting factor [2]
SVF Considerations
SVF Considerations
Fort Collins NW
4Slide #

5. GRASS GIS: Open Source environment
GRASS GIS: Open Source environment Slide # 5
Map Display
2D / 3D
View
Integrate
Bash / Python
Script
#!
r.out.gdal
v.out.ogr
Export
r.* - Raster
v.* - Vector
i.* - Imagery
g.* - General
db.* - Database
t.* - Time
ps.* - Map
Analyze
r.in.gdal
r.in.lidar
v,in.lidar
Import
grassmac.wikidot.com
grass.osgeo.org
www.osgeo.org

6. GRASS GIS Implementation: r.skyview
GRASS GIS Implementation: r.skyview Slide # 6
https://grass.osgeo.org/grass74/manuals/addons/r.skyview.html https://grass.osgeo.org/grass74/manuals/r.horizon.html

7. Number of Directions:
Test: How do the visualizations vary between 8 & 32 direction -
incremented by 4?
Maximum Search Radius:
Test: What is the trade off in time running the visualizations with an
unconstrained horizon versus a maximum distance of 10 pixels (px)?
Data Set Size & Spatial Resolution:
Test: How do these factors vary on datasets comprised of a USGS 3.75
minute quarter quadrangle (QQ ~ 15 square miles) with varying
resolution QL2 LiDAR based DEMs and DSMs?
Colorado - 0.75 m (2.46 ft) resolution
New Mexico - 2.0 ft (0.61 m) resolution
Parameters & Performance
Parameters & Performance
Santa Fe SE
7Slide #

8. Number of Directions
Number of Directions
Tortugas Mountain SE
8
12
16
20
24
28
32
8 12 16 20 24 28 32
ndir
count
Seven (7) SVF / test
1 2 3 4 5 6 7
8Slide #

9. Test
Test Number of Directions (140) / Input
0
45
90
135
180
225
270
315
azimuth
azimuth
ndir = 8
0
30
60
90
120
150
180
210
240
270
300
330
azimuth
azimuth
ndir = 12
0.0
22.5
45.0
67.5
90.0
112.5
135.0
157.5
180.0
202.5
225.0
247.5
270.0
292.5
315.0
337.5
azimuth
azimuth
ndir = 16
0
18
36
54
72
90
108
126
144
162
180
198
216
234
252
270
288
306
324
342
azimuth
azimuth
ndir = 20
0
15
30
45
60
75
90
105
120
135
150
165
180
195
210
225
240
255
270
285
300
315
330
345
azimuth
azimuth
ndir = 24
0.00 12.86
25.72
38.58
51.44
64.30
77.16
90.02
102.88
115.74
128.60
141.46
154.32
167.18180.04192.90
205.76
218.62
231.48
244.34
257.20
270.06
282.92
295.78
308.64
321.50
334.36
347.22
azimuth
azimuth
ndir = 28
0.00 11.25
22.50
33.75
45.00
56.25
67.50
78.75
90.00
101.25
112.50
123.75
135.00
146.25
157.50
168.75180.00191.25
202.50
213.75
225.00
236.25
247.50
258.75
270.00
281.25
292.50
303.75
315.00
326.25
337.50
348.75
azimuth
azimuth
ndir = 32
45° 30° 22.5°
15°
18°
12.86° 11.25°
9Slide #

10. Colorado Test Case Slide # 10
1800
2000
2200
0 2000 4000
transect distance (meters)
elevation(meters)
Horsetooth Reservoir SW
1500
1525
1550
1575
1600
0 2000 4000
transect distance (meters)
elevation(meters)
Fort Collins NW
40:37:30N
105:07:30W
Illumination
Fort Collins NW 3.75 Minute Quarter Quadrangle Sky View Factor − ndir=8 maxdist=
0 1
miles0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
40:30N
105:15W
Illumination
Horsetooth Reservoir SW 3.75 Minute Quarter Quadrangle Sky View Factor − ndir=8 maxdist=
0 1
miles0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Colorado Test Case Terrain Profiles, GSD = 0.75 m, cells = ~68 Million
Range = 43.5 m (142.7 ft); V.E. = 15.6
Range = 435.9 m (1430.1 ft); V.E. = 2.8

11. New Mexico Test Case Slide # 11
35:37:30N
105:52:30W
Illumination
Santa Fe SE 3.75 Minute Quarter Quadrangle Sky View Factor − ndir=8 maxdist=
0 1
miles0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
32:15N
106:37:30W
Illumination
Tortugas Mountain SE 3.75 Minute Quarter Quadrangle Sky View Factor − ndir=8 maxdist=20
0 1
miles0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95
7000
7500
8000
8500
0 5000 10000 15000
transect distance (feet)
elevation(feet)
Santa Fe SE
4200
4400
4600
4800
0 5000 10000 15000 20000
transect distance (feet)
elevation(feet)
Tortugas Mountain SE
New Mexico Test Case Terrain Profiles, GSD = 2 ft, cells = ~110 Million
Range = 1383.8 ft (421.7 m) ; V.E. = 3.6
Range = 472.5 ft (144 m) ; V.E. = 6.2

12. Horsetooth Reservoir SW, Colorado
40:30N
105:15W
Elevation (meters)
Horsetooth Reservoir SW 3.75 Minute Quarter Quadrangle LiDAR DEM − 0.75 m x=7281 y=9469 cells=68943789
0 1
miles1650 1700 1750 1800 1850 1900 1950 2000 2050 2100 2150 2200
Traditional Terrain & Sky View Factor Visualization
40:30N
105:15W
Illumination
Horsetooth Reservoir SW 3.75 Minute Quarter Quadrangle Shaded Relief − altitude=45 azimuth=315
0 1
miles0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
40:30N
105:15W
Illumination
Horsetooth Reservoir SW 3.75 Minute Quarter Quadrangle Sky View Factor − ndir=8 maxdist=
0 1
miles0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
40:30N
105:15W
Slope (degrees)
Horsetooth Reservoir SW 3.75 Minute Quarter Quadrangle Slope
0 1
miles10 20 30 40 50 60 70 80
Horsetooth Reservoir SW, Colorado Slide # 12
40:30N
105:15W
Horsetooth Reservoir SW 3.75 Minute Quarter Quadrangle Sky View Factor Color − ndir=8 maxdist=
0 1
miles
Shaded ReliefDigital Elevation Model Slope Shading Sky View Factor Sky View Factor Color
Pseudo Color Table Single Point Illumination
Directional Diffuse
Illumination
Directional Diffuse
Illumination
+
Pseudo Color Table
Vertical Illumination

13. Fort Collins NW, Colorado
40:37:30N
105:07:30W
Elevation (meters)
Fort Collins NW 3.75 Minute Quarter Quadrangle LiDAR DEM − 0.75 m x=7262 y=9459 cells=68691258
0 1
miles1505 1510 1515 1520 1525 1530 1535 1540 1545 1550 1555 1560
Traditional Terrain & Sky View Factor Visualization
40:37:30N
105:07:30W
Illumination
Fort Collins NW 3.75 Minute Quarter Quadrangle Shaded Relief − altitude=45 azimuth=315
0 1
miles0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
40:37:30N
105:07:30W
Illumination
Fort Collins NW 3.75 Minute Quarter Quadrangle Sky View Factor − ndir=8 maxdist=
0 1
miles0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
40:37:30N
105:07:30W
Slope (degrees)
Fort Collins NW 3.75 Minute Quarter Quadrangle Slope
0 1
miles0 10 20 30 40 50 60 70 80 90
Fort Collins NW, Colorado Slide # 13
40:37:30N
105:07:30W
Fort Collins NW 3.75 Minute Quarter Quadrangle Sky View Factor Color − ndir=8 maxdist=
0 1
miles
Shaded ReliefDigital Elevation Model Slope Shading Sky View Factor Sky View Factor Color
Pseudo Color Table Single Point Illumination
Directional Diffuse
Illumination
Directional Diffuse
Illumination
+
Pseudo Color Table
Vertical Illumination

14. Santa Fe SE, New Mexico
35:37:30N
105:52:30W
Elevation (feet)
Santa Fe SE 3.75 Minute Quarter Quadrangle LiDAR DEM − 2.0 usft x=9404 y=11488 cells=108033152
0 1
miles7000 7200 7400 7600 7800 8000 8200 8400 8600 8800 9000
Traditional Terrain & Sky View Factor Visualization
35:37:30N
105:52:30W
Illumination
Santa Fe SE 3.75 Minute Quarter Quadrangle Shaded Relief − altitude=45 azimuth=315
0 1
miles0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
35:37:30N
105:52:30W
Illumination
Santa Fe SE 3.75 Minute Quarter Quadrangle Sky View Factor − ndir=8 maxdist=
0 1
miles0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
35:37:30N
105:52:30W
Slope (degrees)
Santa Fe SE 3.75 Minute Quarter Quadrangle Slope
0 1
miles0 10 20 30 40 50 60 70 80 90
Santa Fe SE, New Mexico Slide # 14
35:37:30N
105:52:30W
Santa Fe SE 3.75 Minute Quarter Quadrangle Sky View Factor Color − ndir=8 maxdist=
0 1
miles
Shaded ReliefDigital Elevation Model Slope Shading Sky View Factor Sky View Factor Color
Pseudo Color Table Single Point Illumination
Directional Diffuse
Illumination
Directional Diffuse
Illumination
+
Pseudo Color Table
Vertical Illumination

15. Tortugas Mountain SE, New Mexico
32:15N
106:37:30W
Elevation (feet)
Tortugas Mountain SE 3.75 Minute Quarter Quadrangle LiDAR DEM − 2.0 usft x=9781 y=11486 cells=112344566
0 1
miles4200 4300 4400 4500 4600 4700 4800 4900
Traditional Terrain & Sky View Factor Visualization
32:15N
106:37:30W
Illumination
Tortugas Mountain SE 3.75 Minute Quarter Quadrangle Shaded Relief − altitude=45 azimuth=315
0 1
miles0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
32:15N
106:37:30W
Illumination
Tortugas Mountain SE 3.75 Minute Quarter Quadrangle Sky View Factor − ndir=8 maxdist=20
0 1
miles0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95
32:15N
106:37:30W
Slope (degrees)
Tortugas Mountain SE 3.75 Minute Quarter Quadrangle Slope
0 1
miles10 20 30 40 50 60 70 80 90
Tortugas Mountain SE, New Mexico Slide # 15
32:15N
106:37:30W
Tortugas Mountain SE 3.75 Minute Quarter Quadrangle Sky View Factor Color − ndir=8 maxdist=20
0 1
miles
Shaded ReliefDigital Elevation Model Slope Shading Sky View Factor Sky View Factor Color
Pseudo Color Table Single Point Illumination
Directional Diffuse
Illumination
Directional Diffuse
Illumination
+
Pseudo Color Table
Vertical Illumination

16. Animation - Horsetooth Reservoir SW - USNG 13T DE 8286 Slide # 16
Animation - Number of Directions 8-32 ; DEM (maxdist={}) ; DEM (10px) ; First Return DSM (10px) ; Last Return DSM (10px)

17. Animation - Fort Collins NW - USNG 13T DE 9291 Slide # 17
Animation - Number of Directions 8-32 ; DEM (maxdist={}) ; DEM (10px) ; First Return DSM (10px) ; Last Return DSM (10px)

18. Animation - Santa Fe SE - USNG 13S DV 1747 Slide # 18
Animation - Number of Directions 8-32 ; DEM (maxdist={}) ; DEM (10px) ; First Return DSM (10px) ; Last Return DSM (10px)

19. Animation - Tortugas Mountain SE - 13S CR 4274 Slide # 19
Animation - Number of Directions 8-32 ; DEM (maxdist={}) ; DEM (10px) ; First Return DSM (10px) ; Last Return DSM (10px)

20. Santa_Fe_SE Tortugas_Mountain_SE
Fort_Collins_NW Horsetooth_Reservoir_SW
8 12 16 20 24 28 32 8 12 16 20 24 28 32
10
20
30
40
50
10
20
30
40
50
ndir
minutes
input DEM First Last
maxdist= 10 px
Santa_Fe_SE Tortugas_Mountain_SE
Fort_Collins_NW Horsetooth_Reservoir_SW
8 12 16 20 24 28 32 8 12 16 20 24 28 32
4
8
12
16
4
8
12
16
ndir
hours
input DEM
maxdist= {}
Performance Slide # 20
Performance - resolution and horizon settings more significant time impact than surface type. 3.5 GHz 6-Core Intel / 64GB RAM

21. Source Input:
Additional point cloud datasets from Mobil LiDAR and
Photogrammetry may offer unique application opportunities.
Applications & Outlook
Applications & Outlook
DSM:
Offers visualization for additional features of interest (e.g.
infrastructure, archeological, planning, energy).
Guard rail
Edge of pavement
Delineator
Car CDOT I-70 West
21Slide #

22. Number of Directions (ndir):
DEM in the test case, changes appear minimal after 12 directions.
DSM in the test case, influence of directionality at lower number of
directions with elevated features represented by cross or star like
elements — a characteristic which is reduced with an increased number
of directions.
GRASS Default recommendation of 16 appears reasonable, depending
upon 1) feature application in question, 2) dataset size and 3) user
requirements for speed (as influenced by size, ndir & maxdistance).
Maximum Distance / Search Radius (maxdistance):
Unconstrained search exhibits influence of major terrain features and
may mask minor or subtle terrain features + high computational cost.
10 px search highlights localized terrain features with significant detail
in fine scale features such as drainage + faster processing speeds.
Findings
Findings
Horsetooth Reservoir SW
22Slide #

23. Software
GRASS Development Team, 2018. Geographic Resources Analysis
Support System (GRASS) Software, Version 7.4. Open Source Geospatial
Foundation. https://grass.osgeo.org
Michael Barton, PhD. - GRASS Macintosh Binaries http://grassmac.wikidot.com/
Anna Petrasova, NCSU - GRASS r.skyview https://github.com/petrasovaa
Data
US Geological Survey - The National Map - https://nationalmap.gov/3DEP/
• Brittany Roche, Cartographer
Santa Fe County GIS - https://www.santafecountynm.gov/growth_management/gis
• Erle Wright, GISP, GIS Manager
Dona Ana County Flood Commission - https://donaanacounty.org/flood
• John Gwynne, P.E., CFM, Director
Colorado Department of Transportation - https://www.codot.gov/
•Roberto Avila, Ph.D., GIS Applications & Data Services Unit Manager
Acknowledgments
Acknowledgments
Fort Collins NW
23Slide #