GIS Quiz 8
area suitability (site selection)
-determine which areas are best suited to certain applications by taking into consideration many relevant factors -many different methods have been developed to evaluate site suitability
common measurement of shape
-S=P/3.54*sqrt(A) -P= perimeter -A= area -normalized; the compactness of a circle is 1 -the more contorted the area, the higher the shape measure
issues with length measurement
-abstracted polyline is never a perfect representation of the real world equivalent -always tend to cut corners -length of polyline tends to be shorter than the length of the object it represents -exception is when the object is truly straight -measurements in GIS usually based on 2D features -an undulating surface won't be accounted for -measurement may be substantially shorter than reality
heuristics
-algorithms designed to work quickly -come close to providing the best answer without guaranteeing the best solution will be found
optimization
-analysis of patterns to create improved designs -GIS applications focus on design are normative uses -implemented as spatial decision support system
descriptive summaries
-attempting to summarize useful properties of datasets in one or two statistics -borrow many concepts and techniques from non-spatial statistics
measurement of area
-based on coordinates of polygon vertices -breaks complex shapes into a series of trapezia -area of these is then calculated and summed -area outside of the polygon is subtracted from this sum
density estimation
-creates interpolated points from known samples -creates a field from discrete objects -field's value at any point is an estimate of the density of discrete objects at the point -should not be applied to continuous fields
major steps of boolean overlay analysis
-data processing: collect datasets that represent the individual requirements -suitability ranking: suitability of each dataset is determined using binary logic -overlay: intersection of suitable areas from each dataset will be the areas that satisfy all the pertinent requirements
indexing
-datasets evaluated may be quite diverse -overlaying these factors in their raw form will not produce a meaningful result -ordinal measurement scale is applied to each of the datasets
density dot mapping
-effective -objects remain discrete
spatial decision support system (SDSS)
-enables GIS to provide instant feedback upon what if scenarios -need geographic analysis to make a decision
routing problems
-ensures the path of a vehicle is the most efficient one possible -service vehicles, delivery trucks, etc. -constrained to a given network -discrete rather than continuous -based on the shortest path
measurement using GIS tools and digital databases is
-fast -reliable -accurate
the traveling salesman problem
-find the shortest tour from an origin through a set of destinations and back to the origin -potential number of tours will grow exponentially with each additional destination -GIS designed to employ Heuristics
weighted overlay
-if parameters are continuous in nature then the overlay of discrete objects will be insufficient -overlay of continuous data requires continuous datasets -spatial analyst permits the conversion of discrete data into continuous data -useful when attempting to compare both data types
fragmentation statistics
-measure the degree of fragmentation of spatial data sets -useful in landscape ecology -habitat fragmentation affects the success of a certain species -plant/animal pops less likely to survive in highly fragmented landscapes that have potentially dangerous regions between habitable patches
point of minimum aggregate travel (MAT)
-minimizes the sum of distances from each point to the center -may be a good candidate point to site any central service such as schools and hospitals -no simple mathematical expression
dispersed distribution
-negative spatial autocorrelation -presence of one point may make others less likely in its vicinity -commonly the result of competition for space
various indices of fragmentation
-number of patches -size distribution -average shape of patches
boolean overlay based analysis
-operation is via polygon overlay -also called sieve mapping process
centroid (mean center)
-point at which an imaginary, flat, weightless, and rigid map would balance perfectly if weights of identical value were placed on it so that each weight represented the location of a single entity within a population -found by taking the weighted average of coordinates
random distribution
-points located independently -all location are equally likely
clustered distribution
-positive spatial autocorrelation -some locations are more likely than others -presence of one point may attract others to its vicinity -identification is necessary first step prior to isolation of a cause
shape and gerrymandering
-process of redrawing political boundaries in a manner to provide a group or political party an advantage -cracking and packing -districts are created in GIS
measures of spatial pattern
-random -clustered -dispersed
measurement of shape
-shape is a property of many objects of interest in geography -description of which may be verbal
kernel function
-shape of the kernel is dependent upon a distance parameter -increasing the distance produces a broader, flatter shape -kernels summed to produce a composite surface -smoothness of the resulting field depends on the width of the kernel -kernels should merge together to produce a continuous surface
great circle metric
-shortest distance between two points on a spherical globe -decimal degrees -lat/long
pythagorean/straight-line metric
-simplest metric -shortest distance between two points -only suitable for planar projections
weighting
-some criteria are more important than others -order of importance may be implemented by weighting the indexed datasets
network distance
-sum distance of network segments along a travel route must be calculated -each segment is calculated using the pythagorean metric
choropleth mapping
-units may be contiguous, but still discrete -internal variation within mapping unit is removed by the areal averaging process
dispersion
-used to measure spread of points around a center -mean distance from the centroid is a simple measurement of dispersion in 2D
kernel density
-values associated with each point are spread out, starting from the point location, to the specified radius -density is greatest at the point location -diminishes to 0 when reaching the specified radius
packing
concentrating the opposing party's voting power into one district
cracking
minimizing the voting power of the opposing party's supporters by spreading the across districts
point density
points or lines that fall within the search area are summed then divided by the search area size to get each cell's density value
major drawback of boolean logic
produces abrupt discontinuities that don't reflect the continuous nature of many controlling factors
metric
rule for determining distance between points in space