1. NR 422: Raster Analysis Jim Graham Spring 2010

2. Continuous vs. Categorized Continuous: –Like photographs –Satellite and aerial photos –Best for analysis Categorized or discrete –Land Cover –Eco-regions –Limited analysis –Careful on precision and accuracy

3. Categorical vs. Continuous

4. “No-Data” or NULL Values Rasters are always rectangular No-Data values are “transparent” and are not used for calculations

5. Geo-Referenced Raster Known Projection and Datum Width and height of a pixel in map units (X1,Y1) Width in Pixels Height in pixels

6. Geo-Referenced Raster Known Projection and Datum (X1,Y1) (X3,Y3)

7. Types of Rasters Digital Elevation Model (DEM) Digital Raster Graphic (Topos) Satellite and Aerial Photos Land Cover & other natural characteristics Cost Distance & other economic Population, taxes, etc. Your own!

8. Digital Raster Graphic

9. Digital Elevation Model (DEM)

10. Hill-shade

11. Contours

12. DEM Cross Section 2000m 1900m 2100m 2200m

13. Slope

14. Calculating Slope DEM Cross Section

15. Aspect – Direction of the slope Slope Aspect (Direction) Angle Rise Run Slope = (Rise/Run) * 100%

16. Aspect

17. Hill-shade

18. Creating a Hillshade Obtain a DEM Crop to Desired Area Create Hillshade Apply color ? To DEM Add DEM over Hillshade with Transparency

19. Screen shots: –Hillshade dialog –Colorizing dems –Transparency

20. Spatial Analyst Extension Make sure “Spatial Analyst” is Checked

21. Tool Bar Right-click in the menu area Select “Spatial Analyst”

23. Hill-shading Azimuth: “Direction” of the sun relative to the ground. 0 is north. Altitude: Angle from the horizon to the sun. North Azimuth Altitude Horizon

25. “Colorize” the DEM

27. Make the Hillshade Transparent

30. Continuous vs. Categorized Continuous: –Like photographs –Satellite and aerial photos –Best for analysis Categorized or discrete –Land Cover –Eco-regions –Limited analysis –Careful on precision and accuracy

31. “GeoReferenced” File Formats GRID: ESRI’s format GeoTIFF: Excellent support MrSID: LizardTech IMG: ERDAS ECW: ERMapper BIL, BIP, BSQ: See header (w/prj) “ASCII” or “GRID ASCII” (w/prj)

32. World Files Contains: –X-dimention Pixel size in map units –Y-axis rotation –X-axis rotation –Y- dimension Pixel size in map units (negative) –X-coordinate of upper-left pixel –Y-coordinate of upper-left pixel Image file contains width and height

33. Not Geo-Referenced BMP PNG GIF JPEG Maybe with a world file and prj file?

34. JPEG Joint Photographic Experts Group Widest used photo format Not for use with vectors JPEG2000 –Completely new format! –Can be georeferenced Edge of Rocky Mountain National Park Boundary with high JPEG compression

35. Tagged Image File Format TIFF Can be georeferenced (GeoTIFF) –Can tell in ArcCatalog or ArcMap TIFF w/world file –Also need Projection and Datum (prj?) Can be compressed –Run-length – Categorical data –LZW – Categorical data –Huffman encoding – Categorical data –JPEG- Continuous data (don’t used on Categorical data!)

36. GRIDS ESRI’s native raster format Pyramids Not an exchange format!

37. ASCII format NCOLS 10 NROWS 9 XLLCORNER 1000 YLLCORNER 1000 CELLSIZE 1 NODATA_VALUE -9 -9 -9 1 1 0 1 0 1 -9 -9 -9 -9 1 1 2 2 2 1 1 -9 -9 1 1 1 2 2 2 2 3 3 Etc. See example

39. Types of Rasters Land Cover: forest, grass, water, roads, urban Digital Elevation Model: DEM Aerial Photos Satellite Photos Scanned: DRG, 24k Topos Derived rasters: lots!

40. Derived Rasters Land Cover from satellite and aerial Topography: Slope, aspect, hillshade Ecoregions Suitable Habitat Flood plains Geological Regions

41. Raster To Vector Satellite & Aerial –Land Cover: roads, forests, etc. –Buildings DEMs –Contours –Peaks & Valleys –Stream Networks –Watersheds

42. Vector To Raster Drawing! Points of interest Roads Water bodies Contours

43. GIS Analysis Analysis Results Raster to Vector Vector to Raster

44. Raster Analysis Topography: Slope, aspect, contours Raster Math Statistics: min, max, mean, std. dev. Distance Density Interpolation Classification Raster / Vector Conversions

45. Raster Math A matrix of pixels 1220233440 1523303139 1522293040 1420282938 1319253237 Columns Rows

46. Spatial Analyist

47. Analysis Environment Spatial Reference (Coordinate System) –Make them the same Extent –Area of interest –All rasters should overlap Cell Size –Largest of all rasters or larger

48. Spatial Analyst: General

49. Spatial Analyst: Extent

50. Spatial Analyst: Cell Size

51. Raster Calculator

52. Raster Math 12 23 129 1310 1311 1513 + = +=11213

53. Common Functions Local: –Arithmatic: +,-,/, *, MOD (Modulo): returns the remainder –Boolean: OR: If either input is true, output is true AND: If both inputs are true, output is true –CON (Conditional)

54. Mathematical Functions Abs (absolute): flips negatives to positive Ceil (ceiling): float to integer next highest integer value (i.e. 1.1 -> 2) Floor: float to integer giving next lowest integer value (i.e. 1.1 -> 1) Int (integer): truncates float to integer

55. Exponents Exp() Exp10() Ln() Log10() Max() Min() Pow() SetNull() Sqrt() Sum()

56. Comparisons <> (Not Equals) == (Equals) < (Less than) <= (Less than or equal to) > (Greater than) >= (Greater than or equal to)

57. Raster Math: Comparisons 12 23 22 32 00 01 > = >=120

58. Raster Math: Boolean AND 00 11 01 01 00 01 AND = =010 “AND” works but the calculator will insert “&”

59. Raster Math: Boolean OR 00 01 11 01 11 01 OR = =011 “OR” works but the calculator will insert “!”

60. Conditional Operator Con(,, ) Given a raster “condition”: –Puts the true value where true and false value where false Example: –Find the elevations in Rocky over 3000 meters –HighElevations=con(RockyDEM>3000,1,0)

61. Elevations over 3000 meters

63. Viewshed Shows which “pixels” can be seen from pre-defined locations

64. View-shed

65. View from Estes Park

66. View from Ridge