1. "Landcover" is he specific ___ in the attribute table of the map 2. "=" is the ____ 3. "Built-up" is the specific ___

1. Column 2. Logical operator 3. criteria

MODULE 1 Flashcards by Trisha Romero

Process of searching a database to retrieve specific information that satisfies a specified set of criteria

Query or Querying

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Process of obtaining a map layer by directly working on its features and attributes

Spatial Query

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commonly used to query attribute tables in GIS

Logical Operators

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Querying a GIS map of landcover map for the presence of specific land cover can be done using what? (example)

“Landcover”=”Built-up”

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“Landcover” is he specific ___ in the attribute table of the map
”=” is the ____
“Built-up” is the specific ___

Column
Logical operator
criteria

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used along with the logical operators to query a particular map with compound expression or multiple criteria

Boolean Connectors

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the analyst can put additional criteria on the query to look up for a built-up, forest cover within the map of interest. how can this be implemented?

“Landcover”=”Built-up” OR “Landcover”=”Forest”

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used in order to look for the built-up and forested areas within the map

Boolean operator (“OR”)

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(Logical Operator attributes)

Equal to

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(Logical Operator attributes)
<>

Not equal to

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(Logical Operator attributes) <

Less than

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(Logical Operator attributes)
>

Greater than

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(Logical Operator attributes)
≤

less than or equal to

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(Logical Operator attributes)
≥

greater than or equal to

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(Boolean connector attributes)
for the condition to be evaluated as true, the logical expression on both sides of the ___ must be TRUE

AND

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(Boolean connector attributes)
The logical expression on one side or the other side of the __ must be TRUE

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(Boolean connector attributes) The logical condition on one and only one side of the ___ must be TRUE. If both logical expressions are true or both are false, the condition will be evaluated as FALSE.

XOR

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Spatial analysis refers to the numerical values that describes features of geographic data which length, areas, shape, and distance and direction between objects

Measurement

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In GIS, the distance between geographic objects (home & office) can be measured using the following:

Euclidean distance
Great circle
Network Distance

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length of the line segment between two geographic objects (A & B) calculated in cartesian coordinates (x & y) using the Pythagorean theorem

Euclidean distance (Pythagorean distance)

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Pythagorean Theorem Formula

a² + b² = c²
* a & b are the sides of right triangle
*hypotenuse

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shortest distance between two geographic objects measured using an arc along the surface of a sphere

great circle or spherical distance

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commonly used by ships and aircraft in order to save time and money when navigating

Great circle distance

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described as connected sets of edges and vertices

Networks

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the places that are being connected by edges

Vertices

the centerline of by directional road, the direction of traffic flow, or even lanes in a multi-lane highway

edges

the point where a city or settlement starts, intersection or turns and stop in a particular road network or route (bus stops, schools, hospitals)

vertices

characterised by dense road network, travling from one place to another occurs in where?

Route

Calculation of distance between places (vertices) includes the length of all roads (edges) covered to complete what?

Trip

Influence the distance traveled from one city location to another

Different traffic rules and restrictions

Process of converting geographic data into a more useful product that can be the basis of different application based on simple rules

Transformation

Common transformation methods applied in human settlements planning

1. Buffering 2. Points in a polygon 3. Polygon overlay

1. Process of generating a buffer polygon around a point, line, or polygon based on user-specified buffer distance 2. one of the most useful transformations in GIS environment

Buffering

Danger zones from fault lines, volcanoes, and other hazardous areas can easily be generated using?

Buffer operations include: a. variable width buffers b. multiple ring buffers c. doughnut buffer d. setback buffer e. non-dissolved buffer f. dissolved buffer

the size of the buffer zone varies across points, line, segments, or polygon

Variable buffer

series of buffers is created based on the user-specified distance and buffering intervals

Multiple ring buffers

created when buffering a polygon but excludes the polygon itself resulting in an output buffer polygon with a whole inside

Doughnut Buffer

created when buffering only the inside part of the polygon

Setback buffer

does not dissolve overlapping boundaries between buffers while in the dissolved buffer the overlapping boundaries are dissolved

Non-dissolved buffer

1. method that determines whether a point is inside or outside a polygon 2. used to count the total number of points within a particular polygon

Points in polygon

user can determine if there are (how many houses) is located within a particular danger zone/s

Points in polygon analysis

method for determining overlaps between two polygons

Polygon overlay

commonly overlayed to produce an output polygon that contains the combination of attributes of the two inputs polygon

Two polygons

In hsp, it can be used to determine the proportion or the area of a particular settlement is under a particular zone

Polygon overlay

used to generalize geographic attributes or phenomena to reduce data complexity

measure of central tendency and dispersion

For attribute data, descriptive summaries such as the following can be calculated

1. minimum 2. maximum 3. mean 4. median 5. mode 6. standard deviation 7. variance 8. coefficient of variation

for locational data (geographic coordinates) the following can be calculated used as descriptive statistics

1. centroid 2. standard distance 3. standard deviational ellipse

measure the average location of a geographic phenomenon

centroid or mean center

measures how the geographic phenomenon is concentrated or dispersed with respect to the mean center

Standard distance

calculated using equation centroid

x= summation n | n=1 xi y= summation n| n=1 yi *refer to equation 1.4.1

measures how the geographic phenomenon is concentrated or dispersed with respect to the mean center

standard distance

measure the directional trend of the geographic phenomena

standard deviational ellipse

standard distance is calculated using

equation 1.4.2 (descriptive summaries)

concerned with finding the best value or solution

Optimization or spatial optimization

uses mathematical and computation methods in order to find the best solution to a geographic decision problem given well-defined conditions

optimization or spatial optimization

process of minimizing or maximizing an objective with respect to a given problem with geographic nature (spatial sampling, route selection, location-allocation, land-use allocation)

optimization or spatial optimization

can be used to find the optimal location for a single or multiple facility (health centers) with respect to the spatial distribution of demands (households)

Location-allocation analysis

how to solve optimization problems?

requires formulation of an objective function subject to a set of constraints

Optimization problems can either be

1. single objective problem 2. multi-objective problem

Finding the optimal route from settlement to the nearest healthcare facility requires what function?

Single-objective function: minimize travel time

Finding the optimal route from settlement to the nearest healthcare facility *For location-allocation of healthcare facility requires what function?

Two objective functions: 1. minimization of travel time from the settlement area to the healthcare facility 2. maximizing the number of households or settlements being served

Methods that can be used to solve spatial optimization problems which can range from

1. linear programming 2. integer programming 3. heuristic approaches

provides exact solution but requires large computational time and power

Linear and integer programming

provide solutions that can either be optional or not for a shorter period of time

heuristic approaches

Heuristic approach used in spatial optimization problems include:

1. naive or random strategy 2. total enumeration 3. greedy algorithm 4. simulated annealing 5. tabu search 6. metaheuristic 7. genetic algorithm

The use of standard statistical tests for hypothesis testing can be problematic when?

used in geographic or spatial data

(example) assumption of independence in samples is commonly not true in where?

geographic data due to spatial dependence

degree of spatial autocorrelation between independently observed or measured values in geographic space

Spatial dependence

Observed spatial autocorrelation illustrates?

Tobler's First law of geography - everything is related to everything else, but near things are more related than distant things"

spatial dependence of geogrpahic data can be tested using?

global and local measures of spatial autocorrelation

commonly used global measure of spatial autocorrection

1. Moran's I 2. Getis-G

commonly used as local indicators of spatial association (LISA)

Local Moran's I

defined as the presence of systematic variation in measured values in geographic space

Spatial Autocorrelation

Detecting the presence of spatial autocorrelation is important because

1. indicator of something interesting in the distribution of geographic values that requires further investigation in order to understand the underlying cause of that particular distribution 2. implies information redundancy which can affect the selection of methodology of spatial data analysis

accdg to Haining (2001) this may arise from any of the following situations

Spatial autocorrelation

accdg to Haining (2001), Spatial autocorrelation may arise from any of the following situations

1. measurement error 2. spatial interaction, dispersal, diffusion, and spill-over processes 3. model misspecification 4. inheritance by one variable through causal association with another 5. difference in representing large and small scale variation of geographic phenomenon

the presence or absence of spatial autocorrelation directly influences the ff:

1. spatial sampling 2. spatial interpolation 3. spatial data analysis 4. spatial modeling 5. statistical inference in spatial data

Accdg to Anselin (1995), it is any statistics that is an indicator of the extent of significant spatial clusters of similar values around a particular observation

local indicators of spatial association (LISA)

several LISA statistics

1. Local Moran 2. Local Geary 3. Local Getis 4. Local Getis-Ord 5. Local Joint Count 6. Local Quantile LISA 7. Local Neighbor Match test

MODULE 1 Flashcards

(79 cards)