# GIS 1 Final exam

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 Author: akatherine ID: 291168 Filename: GIS 1 Final exam Updated: 2014-12-11 00:50:08 Tags: GIS Folders: Description: Final exam Show Answers:

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1. Interpolation
Takes measured values at points and distributes them across a raster, estimating the values in between the measurements
2. Three different interpolation methods are common:
• Inverse Distance Weighted (IDW)
• Splining
• Kriging
3. Neighborhood
An area of specific size and shape around a cell
4. Zones
• Regions of a raster or a feature class that share the same attribute/integer value
• Need not be contiguous
5. Resampling
• Values converted to a raster with a different cell size
• Must also occur anytime two rasters with different cell sizes are analyzed together
6. 3 methods of resampling
• Nearest neighbor: the new cell is given the value of the old cell that falls at or closest to the center of the new cell. Best for categorical rasters
• Bilinear resampling: a distance-weighted average is taken from the four nearest cell centers. Works better for continuous rasters, like elevation.
• Cubic Raster Analysis convolution: determines a new value by a curve fit through the nearest 16 cell centers.
7. DEM
Digital Elevation Model
8. Table has three fields that are always present
• ObjectlD field: containing a unique ID for the table rows
• Value field: showing each unique cell value
• Count field: indicating how many cells contain that value
9. Spatial Joins Criteria
• Join two tables based on a common spatial relationship
• One feature inside another
• One feature closest to another
• Spatial joins always create a new, permanent data layer, rather than being temporary like attribute joins
• Can join points to points, polygons to polygons, lines to points, and nearly any combination of the three types of data
10. Distance join units
• Given in stored map units
• Decimal degrees cannot be easily converted to miles or km because the conversion factor varies with latitude
• Better to use a projected coordinate system…
11. Summarized join
• Can choose from several statistics, such as minimum, maximum, average, and so on
• All numeric attributes in the source table are summarized using the statistics you choose and placed in the output table.
• String fields cannot be summed or averaged, of course, so they are not included in the output table.
• won't work with categorical data
• Ex: group the cities according to the airport they served, sum the population, makes a table. Now every airport has one record
12. Spatial Join Cardinality
• Simple joins: One-to-one, many-to-one cardinality
• Summarized joins (many records from the source): One-to-many, many-to-many
13. Point to point joins
• Which attraction is the closest to each hotel? Enforces a one to one cardinality…
• How many attractions are best accessible from each hotel? One to many cardinality…must use summarize
14. Map Overlay
• Forces the road features to split at the land use boundaries.
• Each new segment falls inside one land use category.
• The tables can be now joined, providing a basis for calculating total road lengths in each land use category.
• Two major types of overlay: Extraction functions & Overlay with attributes
15. Extraction functions
• Extraction functions combine the features but do not combine the tables.
• Includes clip and erase
16. Overlay with attributes
• Combine both the features and the tables
• Includes intersect and union
17. Clip
• Extracts features within the boundary
18. Erase
• Keeps features outside the boundary
19. On-the-fly clipping
• Temporary clip applied to a map layout
• Does not create new layers or affect lengths or areas of the source layers
• Can be performed on many layers simultaneously
• Can be removed when no longer needed
• Set as a data frame property
20. Overlay with attributes
• Joins features based on common location
• Forces features to split when they overlap each other, creating new features
• Enforces one-to-one cardinality between features in order to join attributes
• Similar to an spatial join
• Combines attributes based on common location (inside join)
• Enforces one-to-one cardinality between features
21. Types of overlay
• Union-combines and keeps all features
• Intersect-combines features and keeps what is common to both
22. Results from overlay
• Combine features spatially, producing all possible new features
• Combine attribute tables, bringing original values from each table and assigning to each new feature
• New spatial data set is created with features and attribute table
23. Slivers
• Tiny polygons created during geoprocessing
• Result of slight differences in boundaries
• Can build up as a result of multiple operations
24. Solutions for slivers
• use the tolerance setting has some problems
• The shape of the polygons are changed
• It might not be acceptable for many projects
• Use Eliminate to get rid of slivery polygons
25. Dissolve
• Eliminates all of the attributes in the table except the dissolved one
• Can choose to summarize the other attributes
26. Model Builder
• Create models built from sequences of tools
• Store processing steps for later reference
• Execute models repeatedly with different inputs
• Share models with others
• A way to string functions together to create a work flow
• Useful for grouping sets of related functions for repeated use
• Models are created inside your toolboxes
• Models can be shared with others
• Models can be converted to scripts for more advanced looping and control development.
27. Ground control points (GCPs)
• Location on the surface of the Earth
• Can be identified on the imagery and map
• Coordinate system (UTM, StatePlane)
28. Registered Image
Control must be visible on layers
29. The National Standard for Spatial Data Accuracy (NSSDA)
• Implements a statistical approach to estimate the positional accuracy of points on maps and in digital data
• The accuracy is relative to georeferenced ground positions of higher accuracy
30. National Map Accuracy Standards (NMAS)
• Specifies that 90% of the well-defined points that are tested must fall within a specified tolerance:
• For map scales larger than 1:20,000, the NMAS horizontal tolerance is 1/30 inch
• For map scales of 1:20,000 or smaller, the NMAS horizontal tolerance 1s 1/50 inch
31. Interpolation
Estimate gridded values between known points
32. Three methods of Interpolation in ArcGIS
• Inverse distance weighted
• Kriging
• Splining
33. Spatial interpolation
A computational procedure of estimating (calculating/predicting) the surface values for a continuous geo-spatial variable at unsampled locations within the area where a sample of surface values given.
34. Gridding
Interpolating irregularly distributed points to a regular grid is the most frequently performed type of spatial interpolation in GIS
35. Inverse Distance Weighted (IDW) Interpolation
• Due to surface autocorrelation, the closer sample values, the more similar the surface values.
• The weight of a sample point is assigned according to the inverse of its distance to the point being estimated.
• The closer the sample value, the greater the weight is assigned.
36. Exponent m
• Size of exponent m affects the shape of the surface
• Larger m will result in higher peaks while lower m will give a more gentle surface
37. Search for neighboring points
• Fixed radius: regardless the number of point, take all the points in the radius range
• Fixed number of neighbors: regardless the search radius, and find the closest neighboring points until the condition is satisfied
• Quadrant or octant searching: Distribute the searching efforts into four or eight directions equally
38. Minimum Curvature Spline Interpolation
• Used to interpolate along a smooth curve.
• Force a smooth line to pass through a desired set of points
• Uses a piecewise polynomial to provide a series of patches resulting in a surface that has continuous first and second derivatives
39. Interpolation options
• Regularized
• Tension
40. Regularized Spline
• Incorporates the third derivative terms into minimization
• Ensures a smooth surface together with smooth first-derivative surfaces.
• It is useful if the second derivative is needed
41. Tension Spline
• Incorporates the first derivative terms to the minimization
• Surface is smooth but the first derivative is not smooth
42. Kriging Interpolation Method
• Similar to Inverse Distance Weighting (IDW)
• Uses the minimum variance method to calculate the weights rather than applying an arbitrary or less precise weighting scheme
• Computationally intensive;
• Provide an estimate of the potential amount of error for the output
43. Common operations about raster data
• Build statistics
• Build pyramids
• Convert to vector
• Convert from vector
• Resampling
• Reclassification
44. Nearest neighbor resampling
• Grabs the value from the old cell that falls at the center of the new cell
• It preserves the original value and should always be used with categorical data, or when the original data values need to be preserved.
• It is the fastest method.
45. Bilinear resampling
• Calculates a new value from the four cells that fall closest to the center of the new cell
• Uses a distance-weighted algorithm based on the old cell centers
• Best used with continuous data such as elevation.
46. Cubic convolution resampling
• Calculates a new value from the sixteen cells that fall closest to the center of the new cell
• Uses a distance-weighted algorithm based on the old cell centers
• best used with continuous data such as elevation
• most time-consuming method
47. Zonal statistics of lines
• Zones defined by the zone layer (watersheds)
• Generates statistics for each zone from the value grid (slope)
• Output is either a raster, or a table
48. ArcMap
Application that is part of ArcGIS that is meant for actually drawing, editing, and tracing map images
49. Digital Elevation Model (DEM)
• Used to refer specifically to a regular grid of spot heights
• Simplest and most common form of digital representation of topography
50. Slope
simplest way is to use a 3x3 window centered on the point. The maximum slope on the basis of a comparison of a central target cell with its neighbors
51. Aspect
• The deepest downslope direction
• Vegetation, crops, fruits between slopes facing north and south
• Wind generators: face the prevailing winds rather than be sheltered from them.
• The aspect at each location determines the direction of water flow over the terrain surface.
• N = 0 with degrees increasing clockwise
52. Image Simulation - Hillshaded Relief Map
• each pixel's illumination computed from its slope relative to a hypothetic "sun".
• Assume that light source infinitely far away from surface and the light is coming from a constant direction and elevation angle.
• The continuous tonal variations give an impression of shadow produced by the interaction of the sun with topographic surface, thus making the map looks more like a photograph.
53. Viewshed
• Areas visible from a set of observation points
• region that is visible from a given vantage point in the terrain
54. Density
Calculate from point distributions
55. Reclassification
• Changing the values of the grid by applying some scheme set up by the user
• Ended up with fewer classes, which is also a kind of data aggregation process
56. Spatial Analyst
• An extension to ArcGIS
• Installed under Complete or Custom option