1. 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)

5. 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 9 123 456 789

6. Typical Slope Calculation b = (z 3 + 2z 6 + z 9 - z 1 - 2z 4 - z 7 ) / 8D c = (z 1 + 2z 2 + z 3 - z 7 - 2z 8 - z 9 ) / 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 (b 2 + c 2 ) 123 456 789

7. 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

8. Slope Definitions (cont.)

9. 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 123 456 789

10. Terrain Analysis Indices (e.g., TPI/BPI, rugosity) 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)

11. Dawn Wright Emily Lundblad*, Emily Larkin^, Ron Rinehart Dept. of Geosciences, Oregon State University Josh Murphy, Lori Cary-Kothera, Kyle Draganov NOAA Coastal Services Center Benthic Terrain Modeler GIS Training for Marine Resource Management Monterey, CA Photo by

12. Maps courtesy of National Park of American Samoa

13. Artwork by Jayne Doucette, Woods Hole Oceanographic Institution

14. By former OrSt grad student Emily Larkin

15. 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

16. OrSt & USF Earliest Multibeam Surveys By OrSt grad student Emily Lundblad

17. Completed by NOAA CRED By OrSt grad student Kyle Hogrefe

18. Benthic Habitat Pilot Area, DMWR

19. Fagatele Bay National Marine Sanctuary, 2001 bathy

20. 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)

21. Algorithm compares each cell’s elevation to the mean elevation of the surrounding cells in an annulus or ring. bpi = 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

22. (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

23. 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

24. BPI Zone and Structure Classification Flowchart Emily Lundblad, OrSt M.S. Thesis

25. Structure Classification Decision Tree Emily Lundblad, OrSt M.S. Thesis

27. Fish Abundance & BPI Courtesy of Pat Iampietro, CSU-MB, ESRI UC 2003

28. 2005 HURL Sub & ROV surveys Ka‘imikai-o-Kanaloa Pisces IV or V RCV-150

29. 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 on elevations of 8 neighbors 3D view of grid on the leftCenter pts of 9 cells connected To make 8 triangles Portions of 8 triangles overlapping center cell used for surface area

30. Emily Lundblad, OrSt M.S. Thesis

31. Fine BPI + + Broad BPI Slope Step One Step TwoStep Three Bathymetry Benthic Terrain Step Four Classification Dictionary BTM Methodology

32. Classification Wizard

33. Help Pages

34. Standardization Over Multiple Areas

35. Classification Dictionary

38. 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

39. Animated Terrain Flyovers Dr. K, OSU and Aileen Buckley, ESRI

40. Our Tools Portal … dusk.geo.orst.edu/djl/samoa/tools.html Image courtesy of FBNMS

42. 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

43. 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., 2006. A benthic terrain classification scheme for American Samoa, Marine Geodesy, 26(2). 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.

44. Gateway to the Literature Wright, D.J. and Heyman, W.D., 2008. Marine and coastal GIS for geomorphology, habitat mapping, and marine reserves, Marine Geodesy, 31(4): 1-8. 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.