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Kyle Hogrefe continuedArc Hydro, Arc MarineArc Hydro, Arc Marine
marinecoastalgis.net/kyle08marinecoastalgis.net/kyle08
Terrestrial
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Terrain Analysis• Slope (Landslide susceptibility)
• Aspect (Solar insolation, vegetation)
• Catchment or dispersal area (Runoff volume, soil drainage)
• Flow path (Distance of water flow to point)
• Profiles, fence diagrams• Viewshed (visibility)• Indices (e.g., TPI/BPI, rugosity)
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Slope and Aspect• measured from an elevation or bathymetry
raster – compare elevations of points in a 3x3 neighborhood
– slope and aspect at one point estimated from its elevation and that of surrounding 8 points
• number points row by row, from top left from 1 to 9
1 2 3
4 5 6
7 8 9
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Typical Slope Calculation• b = (z3 + 2z6 + z9 - z1 - 2z4 - z7) / 8D
• c = (z1 + 2z2 + z3 - z7 - 2z8 - z9) / 8D– b denotes slope in the x direction
– c denotes slope in the y direction
– D is the spacing of points (30 m)
• find the slope that fits best to the 9 elevations
• minimizes the total of squared differences between point elevation and the fitted slope
• weighting four closer neighbors higher
• tan (slope) = sqrt (b2 + c2)
1 2 3
4 5 6
7 8 9
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Slope Definitions
• Slope defined as an angle• … or rise over horizontal run• … or rise over actual run• various methods
– important to know how your favorite GIS calculates slope
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Slope Definitions (cont.)
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Aspect
• tan (aspect) = b/c– b denotes slope in the x direction
– c denotes slope in the y direction
• Angle between vertical and direction of steepest slope
• Measured clockwise• add 180 to aspect if c is positive, 360 to
aspect if c is negative and b is positive
1 2 3
4 5 6
7 8 9
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Dawn Wright
Emily Lundblad*, Emily Larkin^, Ron RinehartDept. of Geosciences, Oregon State University
Josh Murphy, Lori Cary-Kothera, Kyle DraganovNOAA Coastal Services Center
Benthic Terrain Modeler
GIS Training for Marine Resource Management
Monterey, June 13, 2005Photo by
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Maps courtesy of National Park of American Samoa
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Artwork by Jayne Doucette, Woods Hole Oceanographic Institution
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By former OrSt grad student Emily Larkin
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FBNMS: Some Major Issues• Natural & human impacts
– Crown-of-thorns invasion, hurricanes, bleaching– Illegal fishing, sewage outfall
Photos courtesy of NOAA National Marine Sanctuary System
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OrSt & USFEarliest Multibeam Surveys
By OrSt grad student Emily Lundblad
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Completed by NOAA CRED
By OrSt grad student Kyle Hogrefe
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Benthic Habitat Pilot Area, DMWR
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Fagatele Bay National Marine Sanctuary, 2001 bathy
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Bathymetric Position Index(from TPI, Jones et al., 2000; Weiss, 2001; Iampietro & Kvitek, 2002)
Measure of where a point is in the overall land- or “seascape”Compares elevation of cell to mean elevation of neighborhood
(after Weiss 2001)
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Algorithm compares each cell’s elevation to the mean elevation of the surrounding cells in an annulus or ring.
bpi<scalefactor> = int((bathy - focalmean(bathy, annulus, irad, orad)) + .5)
Bathymetric Position Index
-3m-
|---2---| |---------4-------|
resolution = 3 m
irad = 2 cells (6 m)
orad = 4 cells (12 m)
scalefactor = resolution * orad = 36 m
• Negative bpi = depression
• Positive bpi = crest
• Zero bpi = constant slope or flat
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(1) Crests
(2) Depressions
A surficial characteristic of the seafloor based on a bathymetric position index value range at a broad scale & slope values.
(3) Flats
(4) Slopes
if (B-BPI >= 100) out_zones = 1
else if (B-BPI > -100 and B-BPI < 100 and slope <= gentle) out_zones = 3
Broadscale Zones from BPI
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1. Narrow depression 8. Open slopes
2. Local depression on flat 9. Local crest in depression
3. Lateral midslope depression 10. Local crest on flat
4. Depression on crest 11. Lateral midslope crest
5. Broad depression with an open bottom 12. Narrow crest
6. Broad flat 13. Steep slope
7. Shelf
A surficial characteristic of the seafloor based on a BPI value range at a combined fine scale & broad scale, slope & depth
Finescale Structures from BPI
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BPI Zone and
Structure
Classification
Flowchart
Emily Lundblad, OrSt M.S. Thesis
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Structure Classification Decision Tree
Emily Lundblad, OrSt M.S. Thesis
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Emily Lundblad, OrSt M.S. Thesis
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Fish Abundance & BPI
Courtesy of Pat Iampietro, CSU-MB, ESRI UC 2003
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2005 HURL Sub & ROV surveys
Ka‘imikai-o-Kanaloa Pisces IV or V
RCV-150
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Rugosity• Measure of how rough or bumpy a surface is, how convoluted and complex• Ratio of surface area to planar area
Graphics courtesy of Jeff Jenness, Jenness Enterprises, and Pat Iampietro, CSU-MB
Surface area based onelevations of 8 neighbors
3D view of grid on the left Center pts of 9 cells connectedTo make 8 triangles
Portions of 8 triangles overlapping center cellused for surface area
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Emily Lundblad, OrSt M.S. Thesis
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Fine BPI+
+Broad BPI
Slope
Step One Step Two Step Three
Bathymetry
BenthicTerrain
Step Four
ClassificationDictionary
BTM Methodology
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Classification Wizard
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Help Pages
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Standardization Over Multiple Areas
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Classification Dictionary
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Classification Dictionary
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Classification Dictionary
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Use of Terrain Analysis Tools
• Look at version # (e.g., v. 1.0, and all that that implies!)
• Careful study of your own data– BPI scale factors– Fledermaus Viz and Profile Control helped in
conjunction
• Customized classification schemes• ArcGIS 9.x w/ latest Service Pack?• > 2.0 GHz processor, > 1 Gb disk space
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Animated Terrain Flyovers
Dr. K, OSU and Aileen Buckley, ESRIDr. K, OSU and Aileen Buckley, ESRI
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Our Tools Portal …dusk.geo.orst.edu/djl/samoa/tools.html
Image courtesy of FBNMS
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Other Resources• GEO 580 web site - links• GIS@OSU, “Data & Software”
– www.geo.oregonstate.edu/ucgis/datasoft.html
• Wilson and Gallant (ed.), Terrain Analysis• ESRI Virtual Campus library
– campus.esri.com/campus/library
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Gateway to the Literature• Guisan, A., Weiss, S.B., Weiss, A.D., 1999. GLM versus CCA spatial
modeling of plant species distribution. Plant Ecology, 143: 107-122.• Jenness, J. 2003. Grid Surface Areas: Surface Area and Ratios from
Elevation Grids [Electronic manual]. Jenness Enterprises: ArcView® Extensions. http://www.jennessent.com/arcview/arcview_extensions.htm
• Jones, K., Bruce, et al., 2000. Assessing landscape conditions relative to water resources in the western United States: A strategic approach, Environmental Monitoring and Assessment, 64: 227-245.
• Lundblad, E., Wright, D.J., Miller, J., Larkin, E.M., Rinehart, R., Battista, T., Anderson, S.M., Naar, D.F., and Donahue, B.T., A benthic terrain classification scheme for American Samoa, Marine Geodesy, 26(2), 2006. http://dusk.geo.orst.edu/mgd2006_preprint.pdf
• Rinehart, R., D. Wright, E. Lundblad, E. Larkin, J. Murphy, and L. Cary-Kothera, 2004. ArcGIS 8.x Benthic Habitat Extension: Analysis in American Samoa. In Proceedings of the 24th Annual ESRI User Conference. San Diego, CA, August 9-13. Paper 1433. http://dusk.geo.orst.edu/esri04/p1433_ron.html
• Weiss, Andy, 2001. Topographic Positions and Landforms Analysis (Conference Poster). ESRI International User Conference. San Diego, CA, July 9-13.
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Gateway to the LiteratureWright, D.J. and Heyman, W.D., 2008, Marine and coastal GIS for
geomorphology, habitat mapping, and marine reserves, Marine Geodesy, 31(4): 1-8, 2009.
Sappington, J.M., Longshore, K.M., Thompson. D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis: A case study using bighorn sheep in the Mojave Desert. J. of Wildlife Management, 71(5): 1419-1427.
Dunn, D.C. and Halpin, P.N., 2009, Rugosity-based regional modeling of hard-bottom habitat. Marine Ecology Progress Series, 377: 1-11. doi:10.3354/meps07839
Borruso, G., 2008. Network density estimation: A GIS approach for analysing point patterns in a network space. Transactions in GIS, 12(3): 377-402.