1. Intro. To GIS Post Midterm Review March 25 th, 2013

2. Vector vs. Raster CharacteristicVectorRaster Data StructureUsually complexUsually simple Storage Requirements Small for most datasets Large for most data Coordinate Conversion SimpleMay be slow and require resampling Analysis Preferred for network analysis Easy for continuous data, combining layers Positional Precision Limited only by positional measurements (scale) Floor set by cell size

3. Vector Data Vector data represented by coordinates – Points have X and Y coordinate pairs – Lines (arcs) connect two or more points – Polygons are a series of connected lines

4. Raster Data Many cells make up a raster grid/image Size of cells can vary Each cell has a value Think of a digital photograph… – Pixels = cells

5. Cont’d Question 4 and Question 5: Page 132 Question 6 ??? Com’on

6. REVIEW: Scale?

7. Datums Reference surfaces used for mapping – Tied to a specific ellipsoid – Based on many precise measurements – Both horizontal (e.g. ellipsoid) and vertical (Geoid) datums Common US horizontal (2D) datums: – North American Datum (NAD) 1927 or 1983 – World Geodetic System of 1984 – U.S. DOD (used worldwide)

8. Earth Shape: Sphere and Ellipsoid

9. Earth Models and Datums

10. Horizontal Datums: Ellipsoids Bulge at the equator Flattened at the poles A theoretical surface which fits the Earth best (globally/regionally) – Semi-major axis – Semi-minor axis Flattening a b

11. Ellipsoid vs. Geoid Ellipsoids are idealized (mathematical) models Geoids are more complex and representative (of the Earth surface) Different ellipsoids work better in certain parts of the world – In North America, usually WGS 1984 or GRS 80

12. Types of Projections Planar (Azimuthal) Cylindrical (Mercator) Conical

14. Review: Transverse Mercator (TM) Central Meridian Central Meridian changes with the specific region for which the projection is done

15. Isopleth/Contour Map

16. Question 14 Based on USGS standards, a 1:24,000 map scale has 24ft horizontal accuracy

17. Earth Observing (EO)/Infrared (IR) Remote Sensing Systems Space borne – CORONA – IKONOS / Geoeye (high spatial res.) – Quickbird / WorldView (high spatial res.) – Landsat/ SPOT (medium spatial res.) – MODIS/VIIRS/AVHRR (low spatial res.) Airborne (UAV) – AVIRIS – Predator – Global Hawk

18. Scale and Generalization Yellow generalization for smaller scale maps

19. 03_19_Figure Spatial Resolution

20. 03_03_Figure Need at least 4 satellites to find X, Y, Z, and error in receiver’s clock (Time) Need at least 4 satellites to find X, Y, Z, and error in receiver’s clock (Time)

21. DGPS Site x+30, y+60 x+5, y-3 True coordinates = x+0, y+0 Correction = x-5, y+3 DGPS correction = x+(30-5) and y+(60+3) True coordinates = x+25, y+63 x-5, y+3 DGPS Receiver Receiver Differential GPS (DGPS) Realtime (RTK)

22. Sources of Errors When Positioning with GPS Standard Positioning Service (SPS ): Civilian Users SourceAmount of Error  Satellite clocks:0.5 to 1 meter  Orbital errors (ephemeris):< 1 meter  Ionosphere:5.0 to 10.0 meters  Troposphere:0.5 to 1 meter  Receiver noise:0.3 to 1.5 meters  Multipath:0.6 to 1.0 meters  Selective Availability (SA)Does not exist any more  User error:Up to a kilometer or more Errors are cumulative and increased by DOP. Note that the numbers are not current (absolute). However, you can get a feel for which errors are more significant than the other (relative).

23. The satellites broadcast two types of data, Almanac and Ephemeris. Almanac data is coarse orbital parameters for all SVs. Each SV broadcasts Almanac data for ALL SVs (Satellite Vehicles). This Almanac data is not very precise and is considered valid for up to several months. Ephemeris data by comparison is very precise orbital and clock correction for each SV and is necessary for precise positioning. EACH SV broadcasts ONLY its own Ephemeris data. This data is only considered valid for about 30 minutes. The Ephemeris data is broadcast by each SV every 30 seconds. When the GPS is initially turned on after being off for more than 30 minutes, it "looks" for SVs based on where it is based on the almanac and current time. With this information, appropriate SVs can be selected for initial search. When the GPS receiver initially locks onto a SV, the Garmin display then shows "hollow" signal strength bars. At this time, the Ephemeris data has yet to be completely collected. Once the ephemeris data is collected from EACH SV in turn, the associated signal strength bar will turn "solid" black and then the data from that SV is considered valid for navigation. If power is cycled on a GPS unit, and when turned back on, the Ephemeris data is less than 30 minutes old, lock-on will be very quick since the GPS does not have to collect new Ephemeris data. Difference between Almanac and Ephemeris

24. N S W E Poor Satellite Geometry

25. Spectral Resolution

26. REVIEW: Spectral Resolution Reflectance (%) Electromagnetic Spectrum

28. Transformation types: Affine The affine transformation function is: x’ = Ax + By + C y’ = Dx + Ey + F where x and y are coordinates of the input layer and x’ and y’ are the transformed coordinates. The C and F parameters control shift in origin (translation) A, B, D, E control scale and rotation their values are determined by comparing the location of source and destination control points. Scales, skews, rotates, and translates 6 unknowns( A,B,C,D,E,F) so a minimum of three “displacement links” required Little benefit from more than 18-30 links The most common choice

29. Vector Data and Topology Topology – The arrangement for how point, line, and polygon features share geometry – Or knowledge about relative spatial positioning Two types of vector models exist in a GIS – Geo-relational Vector Model Arc Coverage (has topology) >>> format: binay Shape files (no topology) >>>> format: *.shp, *.shx, *dbf, etc. – Object-based Vector Model Includes classes and geodatabases >>> format: *.mdb

30. Organizing Attribute Data Flat Files Hierarchical Relational (databases) Object-oriented (database)

31. Relational ( What is commonly used in GIS ) – Various tables (databases) are “linked” through unique identifiers Organizing Attribute Data

32. Non-spatial Data Or Attributes (for a vector dataset) Record Field (Attribute)--- It could be either numeric or text) The Shape Field/Object ID tells about the type of vector feature (point/polygon/line)… It is where the coordinates are also stored (you do not see them here)

33. add our one second error to the third receiver… XX …circle from 3rd satellite cannot intersect where other two do purple dots are intersections of 2 satellites define area of solutions …receivers calculate best solution (add or subtract time from each satellite) With Only Three Satellites Visible to the receiver

34. position determined from multiple pseudo-range measurements 4 satellites…three (X, Y, Z) dimensions and time when clock offsets are determined, the receiver position is known Fourth Satellite

35. Q 33 and 34 Page 30 1 degree longitude: 111km * cos (phi)=81.2 km Page 31

36. State Plane

37. 02_11_Figure UTM Coordinate System

38. 02_11_Figure Datum and UTM NAD83: (North American Datum) produced in 1983 Q38 – Page 38 Q39 – Blocking of signal due to the trees/branches, etc.

39. Q 42

40. Radiometric Resolution

41. 03_21_Figure Radiometric Resolution

42. 03_21_Figure Jpeg Vs. Tiss Jpeg is a lossy format Jpeg does not inherently carry geo-coordinates

43. Spectral Resolution

44. Q 48 Land cover: nominal Temperature: interval Building numbers: ordinal/nominal Population: ratio Check your email for further discription

45. Query: Select by Attributes Or Structured Query Language (SQL) Enter criteria for one or more fields – Numeric values =,,<> – Nominal values = ‘text’ Change criteria or narrow results based on additional criteria

46. REVIEW: Joins and Relates Many datasets are available in tabular format – Excel (.xls,.xlsx), comma-spaced values (.csv), text Tables can be imported to ArcMap and linked points, lines, or polygons using a common ID

47. REVIEW: Joining Tables Tables downloaded as text or CSV may need to be opened and saved as Excel files first First row of table should contain short headers with no special characters (or spaces, ideally) Table must have an ID that matches geography

48. REVIEW: One-to-one A one-to-one relationship means that each record in one table has only one matching record in another table

49. REVIEW: Many-to-one Many-to-one means multiple records in the table match to one record in another table

50. REVIEW: Joining Tables Right-click the spatial data which will have the table joined to it, click Joins and Relates, then Join… Choose the table and the common ID fields

51. REVIEW: Spatial Join Join can be performed using spatial location to summarize/select data from another layer “Join data from another layer based on spatial location” option in the Join dialog box Choose another layer to join, then – Summarize numeric attributes OR – Give the attributes of the closest feature

52. REVIEW: Relating Tables Relates are used when tables have a one-to- many or many-to-many relationship Attributes are not appended to the table, but selecting a record in one table will select all related records in another table Right-click layer, choose Joins and Relates, then Relate…

53. Q 53-54 Page 73 Use the formula to find out the specification (dpi) for the scanner? dpi: Dot per inch Q54: ???

54. Topology Concepts – Adjacency – Enclosure – Connectivity Terms to be defined – Node – Arc – Polygon

55. Non-spatial Data Or Attributes (for a vector dataset) Record Field (Attribute)--- It could be either numeric or text) The Shape Field/Object ID tells about the type of vector feature (point/polygon/line)… It is where the coordinates are also stored (you do not see them here)

56. REVIEW: Trade-off between Spatial and Spectral Resolution In order to maintain a reasonable level of energy (or signal) reaching the camera (or imaging system), the relation between the pixel size (or pixel area) and spectral bandpass (channel width) must be considered: Pixel area Spectral bandpass Energy

57. Example: Transformation Let’s do a simple example – We would like to calculate new coordinates for point A(x=1, y=1), i.e., we want to convert coordinate system (x,y) to (x’,y’). – We assume a 1 st order (affine) transformation works fine – All the six coefficients (for affine transformation) are given (a0=1, a1=1.1, a2=0.4 and b0=0.2,b1=1.8,b2=0.8) – x’ and y’ are the new coordinates for (x,y) in the new coordinate system – Continue on next Slide >>>>

58. Resampling coordinate 68 65 70 80 Pixel value x x’ 78 7378 74 69 y 1 1 2 3 2 3 1 2 3 1 2 3 y’ e.g., Average of 80 and 68 would be the pixel’s new value

59. Orthophoto Vs. Aerial photos (or Remotely sensed Imagery)

61. Homework & Lab Read chapter 4 (Data quality) and answer the question: – HW: all questions except Q1 and Q2 Lab this week: Review on ArcGIS