raster data models

Question 1

Object view

Answer 1

-collection of well defined, discrete and spatially referenced objects
-boundaries are well defined
-the entire geographic space is not occupied, only where objects exist
-each object is identified and described through the attribute table
-time changes represented as object location, shape and attribute changes

Question 2

Field view

Answer 2

-events that vary continuously across geog space
-boundaries are fuzzy
-the geog space is mutually exclusive and collectively exhaustive
-each space partition is represented by a category or value
-time changes represented as a snapshot of cell changes

Question 3

Remote sensing

Answer 3

Electromagnetic spectrum is an organized arrangement of electromagnetic radiation using energy, wavelength or frequency

Question 4

Radiometric resolution

Answer 4

7 bit: 0-127
8 bit: 0-255
9 bit: 0-511
10 bit: 0-1023

Question 5

Rasterization

Answer 5

Process of converting form vector to raster

Question 6

Vectorization

Answer 6

The process of converting from raster to vector

Question 7

Raster (natural world)

Answer 7

Good for continuous data
Better rep of spatial variability
Good for data derived from remote sensing

Applications: forest change, landslide modeling

Question 8

Vector (human world)

Answer 8

Good for data with definite boundaries
Network analysis capabilities are possible
Best for graphic output

Applications: census analysis, routing problems

Question 9

Taste data analysis

Answer 9

Local
Focal
Zonal
Global

Question 10

Types of raster spatial data analysis

Answer 10

Density mapping (kernel density)
Multicriteria evaluation (MCE)
Neighborhood analysis

Question 11

Density mapping

Answer 11

Provides a measure of the density distribution of features in the data

Starts with a vector layer (point data layer)
Creates a raster output data layer
Calculate the number of points/raster cell

Question 12

Multicriteria evaluation (MCE) problems

Answer 12

Difficult to understand when 4 or more data layers are involved
Data layers may have different degrees of importance
Data cut off values (threshold values) are subjective
Various decision makers may have different views of layer importance

Question 13

MCE

Answer 13

Combines data based on importance
Importance is represented by a weight (1-100)
Data layers and weights are combined by mathematical equation