Gis Final Exam

Front 1

Types of vector data analysis

Back 1

buffering, overlay, distance measurement, network analysis

Front 2

Most common analysis of spatial data is what:

Back 2

buffer and overlay

Front 3

buffereing is:

Back 3

creating a proximity area around a selected point line, or polygon

Front 4

what is a buffer zone

Back 4

the newly created area within a specified distance from the selected features

Front 5

A buffere is a:

Back 5

polygon created at a specified distance from a point line or polygon

Front 6

a buffer around a point is:

Back 6

circular zones

Front 7

a buffer around a line is

Back 7

elongated polygons following the line feature, the polygong doenst' have to be on both sides of the line

Front 8

a buffer around a polygon is

Back 8

a zone extending outward from the polygon boundaries

Front 9

Buffer issues:

Back 9

1- you never want to forget the untits youw ant to use,
2- dissolving vs. not dissolving
3- use of different buffer distances
4-variation of buffere distances
5-multiple buffer zones
6-inclusions zones vx. exclusion zones

Front 10

What is dissolving:

Back 10

removing intersects of buffer zones so it is one seamless polygon feature

Front 11

what is overlay:

Back 11

MOST POWERFUL feature of modern GIS.
It is the ablitly to place the cartographic representation of a thematic information of a selected theme over that of another

Front 12

what is site suitablitly?

Back 12

examines social, economic, physical, biological and other criteria to locate potential sited for some purpose (part of overlay)

Front 13

what do overlay opperations combine:

Back 13

geometry and attributes of two feature maps to create an output

Front 14

Overlay procedure requires:

Back 14

an input map layre and an overlay map layer

Front 15

what can an output layer be in overlay:

Back 15

point, line, or polygon layer

Front 16

what must the overlay map layer and input map layer have in common:

Back 16

the same coordinate system

Front 17

The input layer can be what:

Back 17

a point, line or polygon

Front 18

The overlay layer must be a what:

Back 18

a polygon ***

Front 19

type of overlay polygong operations:

Back 19

1- point-in-polygon
2- line-in-polygon
3- polygon-in-polygon

Front 20

What are the common overlay methods:

Back 20

union, intersect, and identity

Front 21

Union overlay method is what:

Back 21

-OR
-both input/overlay =polygon layers
-combines the area extent from both maps

Front 22

Intersect overlay method is what:

Back 22

= AND
-preserves only features that are within common area
-output feature have attribute data from both layers
-input layer can be a layer of point, line or polygon

Front 23

Identity overlay method is what:

Back 23

= OR and AND [(Input layer) AND (overlay layer)] OR (input layer)
-preserves features that are within common area and features from input layer
-input layer can be a layer of point, line or polygon

Front 24

Buffers can be combined with what to analyze spaitail information:

Back 24

polygon overlayes

Front 25

What is vector line length:

Back 25

length of straight line calculated by pythagorean theorem using beginning and ending point locations

-length of curvillinear line calcultaed by adding lenghts of individual line segments

-uses coordinate system to figure out measurements

Front 26

To calculate area of vector polygon you:

Back 26

break complex polygon into simpler geometric shapes such as right triangles and rectangels whose area can be calculated

Front 27

Map manipulation is what:

Back 27

no attribute data combination, just about the geometry

Front 28

Examples of map manipulation are what:

Back 28

dissolve, clip, merge

Front 29

Map minipulation clipping is:

Back 29

cutting out a section of city (cookie cutting) ex. you could get jsut the roads of the city

Front 30

Map minipulation merging is what:

Back 30

seamless layer, erase

Front 31

Raster data analysis is based on what:

Back 31

based on cells and grids

Front 32

Raster data analysis can be performed on what:

Back 32

-individual cells
-a group of celss
-an entire grid
-a set of grids

Front 33

Common Raster data anaylsis operations:

Back 33

-local operations
-neighborhood operations
-zonal operations
-distance measurements

Front 34

What do you have to do before starting a raster data analysis:

Back 34

set up the environment covered by the analysis

Front 35

TO set up the env. covered by the analysis you can:

Back 35

-difine the extent of the environment (area extent-ArcView) (set window- ArcInfo)
-Define the size of the output grid cells (the size of the input grid cells) (set cell (ArcInfo))

Front 36

What is a mask grid in raster data anaylsis:

Back 36

-a grid (or set of grids) used as a way to difine the area extent of the analysis
-in that case the extent of the analysis is defined by the cells of the mask grid that do not have a value of "no data" ("no data" is different from the '0' value)

Front 37

Raster data anaylsis common operation: LOCAL OPERATION

Back 37

-core raster data anaylsis
-consists of cell-by-cell operations based on preset or made up functions

Front 38

Local operation: types of functions include:

Back 38

-arithmetic
-logartithmic
-trigonometric
-power
*applied by one cell at a time
*can be applied on single grid or with multiple grids

Front 39

Local operations with a single grid:

Back 39

each cell value in the output grid is the result of the mathematical operation using the corresponding (overlapping) cell value in the input grid
ex. -floating point grid to integer grid -slope in percent to slope in degrees -universal soil loss equation

Front 40

Local operations with several grids;

Back 40

-similar to vector overlay anaylsis
-allows more possiblities for local operations ex. the combine operation (several grids)

Front 41

Raster data anaylsis common operation: NEIGHBORHOOD OPERATIONS

Back 41

-involves a focus cell and a set of cells in its vicinity (neighborhood)
-the value of the focus cell is computed with the values of the selected neighbor (surrounding) cells
-the selection of surrounding cells is based on the distance &/or the directional relationships to the focus cells
-the operation may or may not use the focus cell value

Front 42

Some neighborhood operations:

Back 42

-* x-by-x window = (ex. 3x3) the focus cell is always in the middle (most commonly used)
-circle neighborhood= figure out radius of circle & figures out the cell values inside circle
-Annulus = (doughnut shaped) cells that fall into the doughnut are used for computaion
-wedge neighborhood= cells insde the wedge are used. ex. data simplification and terrain analysis

Front 43

Raster data anaylsis common operation: ZONAL OPERATIONS

Back 43

*operation used to describe the geometry of zones (in a single grid) or to summarize the cells values by zone.
zones, disconnected zone, continuous zone

Front 44

a zone is:

Back 44

connected (continous zone/1 region) or disconnected groups (2 regions)of cells with same values

Front 45

Characterisitcs of zonal operations:

Back 45

zonal operations are performed either on a -single grid (discription of zone geometry) or on two grids (summary of cell values by zones)

Front 46

Description of zone geometry (on single grid)

Back 46

area is the sum of cells times cell area
ex. cell size = 2m => Cell area = 4msquared

Front 47

Zonal operations perimeter:

Back 47

it is the sum of the lengths of the boundary of each region of the zone
ex. cell size =2m
Zone B : perimeter = 2x10=20m (you get 10 by counting the sides of the cells you want to caluculate)

Front 48

Zonal operations thichness:

Back 48

radius (in cell length) of the largest circle that can be drawn within each zone

Front 49

Zonal operations centroid:

Back 49

consists of the parameters of the ellipse that best approximate each zone: centroid, major axis, minor axis
(major axis is the longest one, centroid is point in middle, minor axis is the smallest)

Front 50

Using operation syntax to summarize cell values by zones (on two grids) you:

Back 50

used input, zonal operator, and zonal grid to get an output grid

Front 51

Raster data analysis common operation: DISTANCE MEASURE OPERATIONS

Back 51

-extended neighborhood operation or global operation
-it consists of calculated distances away from source cells in a single grid

Front 52

Princle of distance computation:

Back 52

it is based on the node-link relationship
*node is VERY import. for computation - there are diagonal link, and lateral link , reference cell and direct neighbor cells

Front 53

Princle of distance compuation:

Back 53

-its node represents its center
-its links are the segments connecting its node to the nodes of the adjacent celss
-direct neighbor is a cell connected on the side (lateral link)
-diagonal neighbor is a cell connected by its angle (diagonal link)

Front 54

Line Length (raster)

Back 54

from node to node (not side to side)

Front 55

Physical distance measure of application of distance measurment operations:

Back 55

-straight-line distances away from source cells (similar to a buffer or source cells with continuous distance ex. buffer around stream network)
-reclassification=> discrete/homogeneous zone
-slice operation => equal-area/equal-interval zones)
-Allocation (allocaion grid, watershed)

Front 56

Raster Anaylsis tools: overlays

Back 56

called Map Algebra (you can +, - , / ) can make use of more than 2 layers

Front 57

another name for terrain:

Back 57

land surface

Front 58

Land surfaces are:

Back 58

-undulated, continuous, and 3D
-they are measured and anylays generaged from elevation data

Front 59

elevation data of land surfaces include:

Back 59

-slope(rate of change in elevation0
-apect (orientation of slope)
-watershed
-stream network
-flow accumulation

Front 60

The Z value in terrains:

Back 60

-represent the elevation data in GIS
-they are not stored as part of the coordinate system, but as attribute data (vector data z value sotred in numerical field of attribute tabel, in raster data z is stored as cell values in grid)

Front 61

Common data for terrain analysis

Back 61

DEM and TIN
DEM- most common input data for terrain anayl.
-its quality determines the accuracy of the anaylsis
-needs to be converted to specific software format (grid for ArcView/ArcGIS/ArcInfo)

Front 62

Terrain Maping includes:

Back 62

contouring, vertical profiling, hill shading, hypsometric tinting, and 3D View

Front 63

Terrain Maping CONTOURING:

Back 63

ISOLINE-line connecting points of equal value in a thematic map
CONTOUR LINE: line connecting points of euql elevation-it is the isoline for a topographic map
CONTOUR INTERVAL- verticle distance between two consecutive contour lines

Front 64

Goal of contouring:

Back 64

gerated contour line or isoline to show the distribution of continous phenomenon

Front 65

Caseof elevation in contouring:

Back 65

-close contour line=>steep terrain
-'V' indicate stream direction (pointing upstream)
-traditionally helps calculate slope

Front 66

Terrain Maping: VERTICAL PROFILING:

Back 66

construction of diagram showing the change in elevation along a line on a map

Front 67

Goal of Vertical Profiling:

Back 67

vizualize the changes in elevation along a linear feature of the map, or along a user difined line

Front 68

Terain Mapping: HILL SHADING:

Back 68

it is the simulation of the image of a terrain under the sun light
-slope facing incoming light are bright while slopes opposite to the sun are dark

Front 69

Goal of Hill shading:

Back 69

display the shape of lang features

Front 70

Hill shading is also called:

Back 70

shaded relief and shading

Front 71

Terrain Maping: HYPSOMETRIC TINTING

Back 71

consists of displaying the elevation zones in different colors

Front 72

Goal of hypsometric tinting:

Back 72

to visualize the progression in elevation

Front 73

Another name for hypsometric tinting

Back 73

layer tinting

Front 74

Terain mapping:PERSPECTIVE VIEW (3D)

Back 74

it is the thre dimensional view of the terrain

Front 75

Perspective View is controlled by 4 parameters:

Back 75

1) The viewing azimuth- angle between north and the line defined by the target (on the surface) and the point of observation=> 0`-360`
2)the viewing angle- angle between the surface (horizontal) and the line defined by the target (on the surface) and the point of observation=> 0`-90` (@90` no longer view it as 3D but as 2D)
3) the view distance- distance b/w the ovbservation point and the target
4) the z-scale or verticle exaggeration factor- ratio b/w the verticle and horizonal scales

Front 76

Terrain Mappaing: 3D DRAPING-

Back 76

superimposition of thematic layers with a perspective view

Front 77

Terrain anaylsis- SLOPE:

Back 77

it is the rate of change in elevation
-percent slope= (verticle distance/horizontal distance)x100
-degree slope= arctan (verticle distance/horiz. distance)

Front 78

Terrain anaylsis- ASPECT:

Back 78

it is the orientation of slope (you can use 0`- 360` or cardinal orientation

Front 79

Terrain anaylsis- VIEWSHED ANALYSIS:

Back 79

*consists of using elevation grids to generate topography related hydrology features such as: watershed and sub-watershed, stream network, flwo accumulation (depth)
-watershed=catchment=basin
-DEM=> field elevation=> flow direction grid=> flwo accumulation grid