Exam 1 Test/ Ex 2 material

Many-to-many

(link only)

Data Model

For GIS specifically you have to have: - spatial data aspect - attribute data aspect (if both are not there you don't have spatial data) For a regular database y - if it doesn't need spatial data it might just need attribute data

The good, the bad, the and ugly

Good: Geodatabase - So much more functionality than the other two Bad: Shapefile - topological errors - she disagrees and thinks shapefiles are ugly Ugly: Coverage - older version of an attempt to have geodatabase features but is not effective - she disagrees and thinks Coverages are bad

Joins and relates

linking tables in arcGIS - both use a primary and foreign key in two different tables to create one inner join: an output row is created from rows that match on the join items across tables - most common outer join: saves information from t he non-matching rows using blank values for nonmatching items

Which of the following types of thematic maps is best suited to illustrate continuous data?

a) Choropleth b) Dot c) Proportional Circle d) Isarthithmic e) Cartogram

Union

combining two features into one table (either or)

Formal regions

created based on presence or absence of particular distinguishing features Zones can be based on: - Physical characteristics (watersheds) - Political (congressional districts, census blocks) - Cultural (BBQ regions of South Carolina)

Merge (vector)

difference between merge and dissolve is that Merge takes multiple inputs and makes one output - problem is where they overlap a merge will not tell you were they are overlapping - should only be used when updating data or when the exact same type is being merging together

one-to-many

relate (link only) 1 record in table 1 (destination table) and many records that match that record in table 2 (source) - problem: whatever record is first in the table 2 is the only thing that will actually get joined to table 1. Therefore you would lose alot of data Problomatic: Instead you need to use a relate

Attribute queries

selection of different types of features that have attributes that meet a certain kind of criteria (in arcGIS select by attributes tool) - normally called selections or queries

Spatial operations are usually applied _____ to solve problems

sequentially - chain of spatial operations specified with output of each operation serving as input of the next - in order for you to arrive at the spatial problem you are trying to solve you have to do it in steps

Local operations (raster)- Relational

true = 1 false = 0

Divide

trying to find which of those in the type column has both size 1 and 2 thus the resulting table is type m

Spatial data analysis: vector data

using a series of GIS operation to solve a problem (anything where you are using a series of operations to find an answer to a problem is spatial data analysis - make sure you look at your data first, important because depending on the type of data you have you may or may not be able to do certain types of analysis

Local operations (raster) - (Arrhythmic) (arithmic) (arithmetic)

will be asked to work through problems is this true or false? adding

Items have:

- A type (e.g., byte, float, string) - A domain → set of allowable values an item can take on (such as values 0-10 or "republican", "democrat", "independent") • constraining what a feature can be given in terms of particular attributes

Data Definition Language

- Allows the user to set up a database • How many attributes will there be? • What are the attributes types (Characters, Numbers)? • What are the lengths (widths) of each field? • What are the attributes of character data (UPPER CASE ONLY, are spaces allowable) • What are the types of numbers (integers, real numbers, positive, negative values)? • How much editing can a user do?

Integer-coded classes of features:

- Automatic display with different symbols - Behave as different layers during editing - Each subtype can have own default values - Stream lines attribute entry • automatically changes symbology when being coded

Shaded relief or Hillshade (raster)

- Calculates hypothetical illumination of a surface by determining illumination values for each cell • Evaluates the relationship between the position of the light source and the direction and steepness of the terrain • Used to recognize shapes of landform features - The relative radiance value ranges from 0 (black) to 1 (white) Know: Hillshades are used for cartographic purposes and recognizing features ONLY - wouldn't use this for slope

Classification Operators (vector)

- Classification (reclassification) used in conjunction with selection to categorize geographic objects based on a set of conditions • Example-polygons larger than 1 square mile = large, 1⁄2 square mile = medium, etc. - This process can modify or change the attribute tables for further analysis - Binary: most simple type: places objects into 2 classes (T or F, Yes or No, 1 or 2) - Natural Breaks (Jenks): Attempts to identify naturally occurring clusters of data • Often done by ranking values from low to high - Equal interval: splits classes by a uniform, specified interval • can use automated methods (specifies the number of output classes set apart at equal intervals - Equal area: Place an equal proportion of dataset into a specific number of classes • Often results in a visually balanced map • Sometimes can result in a skewed distribution (normally quantiles top 10%)

Viewsheds (raster)

- Collection of areas visible from a given point • Views from any non-flat location can be blocked by terrain - Viewsheds are managed for many parks & scenic areas (hide power lines, cell towers, etc...) - what you would be able to see from a particular location due to elevation

Buffer (vector)

- Creating a buffer based on a distance around a certain feature • the input feature is still an input but the buffer sets an new output - spatial analysis that modifies or creates new features that are less than or equal to a specified distance from one or more features - Can buffer point, line, or area features in raster or vector data • Distance is calculated based on Pythagorean formula Vector buffers always *datums or any type of geographic coordinate systems should not be used to do distance or area calculations. If you are using a buffer you need to make sure your data is projected.* Types of buffers: 1. Simple buffering - Uniform distance used for all features • Can create overlap, so features may need to be dissolved to where they become one large polygon 2. Compound buffers - Creates multipart buffers where they intersect • Creates new polygons where they DO overlap and are now new polygons/features 3. Nested Buffers - Used to produce multiple buffered zones • multiple buffer distances from each point. Values have to be nested (5, 10, 15, 20) 4. Variable Distance Buffer (falls under simple buffering) - Have a point later that you determine the buffer distance based on an attribute table. How do determine distance criteria for a buffer (how big a buffer is) 1. Arbitrary - best on the user's 'best -estimate" about size of buffer 2. Causative - buffer developed based on a priori (before the fact) conditions (based on a fact 3. Mandated - buffer dimensions that are required standards (i.e. federal mandates)

Structured Query Language (SQL)

- Database language used particularly for queries, which allows you to choose different types of data or features of data based on certain criteria • Allows for uses to define, describe and manipulate data in a database via a standardized set of instructions (moved now towards python)

Destination vs Source table (cardinality)

- Destination table is always your first table which you are taking things and adding them here. Will have a primary key - Source table will have a foreign key and is where data is coming from

Aspect (raster)

- Directional measure of slope (best with rough terrain) • Often used to determine the direction of water flow • Grouped into the four principal directions or eight principal directions - Can show • The steepest downhill direction at a point • The amount of sunlight an area will receive • Can be problematic in flat lands

GIS Data Formats

- ESRI formats - DGL: USGS Digital Line Graph - TIGER: US Census Bureau (enumeration unit) - DXF: Autocad Digital Exchange Format

Spline

- Fits a set of curves between sample points ("guide points") that minimize the total curvature. - Also known as radial basis functions. - Five different types: 1) Thin-plate splines 2) Spline with tension 3) Completely regularized spline 4) Multi quadric function 5) Inverse multi quadric spline

ESRI formats

- Geodatabase (ArcGIS) - Coverage (ArcInfo) • relly old version of ESRIs first attempts at creating Topology • Topological arc/node model. The basic vector data structure for ARC/INFO - Shapefile (ArcView) • don't have topology (most simplistic) associated with them (very old) - Export Format (used for interchange) • can export as a different format - Generate (simple topology, but ASCII) • can generate a network dataset or topology

Dissolve (vector)

- Helpful for reducing the amount of data you have especially if you don't need that county - identifies all features that contain or surround a set of target features - Often needed prior to applying an area based selection - Helps remove unneeded information - will combine anything with the same code into a singular feature - binary data can also be used apart of a dissolve only have 1 input and dissolving 1 output feature

Relational Databases

- Modern database based on a set of mathematical principles called relational algebra • Provide a specific set of rules for the design & function of these systems - Relational algebra takes relations (tables) as input & returns relations as output - Based on set theory • Fundamental rule of set theory is that no row (tuple) of data can be a complete duplicate of another

Terrain Analysis

- Normally comes as raster data but can come as vector - Being able to conduct terrain analysis is important: • Flood zones • Availability of surface water • Soil moisture • Water quality - Importance of terrain mapping & the difficulty of doing it manually have pushed its development in GIS • Ex. Manually determining slope is particularly important & very difficult, time consuming, & costly to do manually • Cannot build above slope of 18% - Most terrain analysis functions are neighborhood or focal functions that perform appropriate mathematical operations within a moving window

Database Management Systems (DBMS)

- Not a database but a software that allows you to work within a database - Designed to overcome data redundancies and inefficiencies • Provide data independence: changes in the database structure can be transparent to programs or users accessing data • Provide multiple views of data • Provide centralized control and maintenance Difference between database and DBMS: - Database houses all of the attribute data that you have. - DBMS allows you to manage the data in there

Problems with Interpolation

- Number of control points • More is generally better, but law of diminishing returns • More complex surface→more points needed to describe it - Location of control points • Not all points are equal • Try to capture the peaks and valleys of the surface (More samples are needed in areas where the surface changes rapidly (e.g. many changes in slope) than where it is regular) - Saddle points • if all the points are fairly close to each other, you could chose to draw a contour either way. A saddle point is somewhere where the contour could go either way - The area containing data points • Make sure your sample points extend outside the area of interest so you are interpolating and not extrapolating!

Primary Operators (in terms of tables not actual polygons)

- Restrict - Project - Join - Divide - Union - Intersection - Difference - Product

Spatial Analysis Operations

- Selection (Set Algebra) - Classification - Dissolve - Merge - Buffer - Overlay Operations • Clip • Erase • Union (either or) • Intersect • Symmetrical Difference (Complement) - Network Analysis

DEM

- Slope/Aspect • Calculate : raster Slope is calculated using a symmetrical 3 by 3 moving window (can use 5 by 5) where elevation values are found for each window - Additional Topographic Parameters - Hillshading - Visibility: what can be seen from a certain point - Hydrological Modeling

Spatial Autocorrelation

- Spatial autocorrelation → correlation of a variable with itself through space - Many theories and models implicitly assume an underlying spatial pattern in the distribution of the subject of interest - Positive autocorrelation: cluster - Negative Autocorrelation: Dispersion of points through space - No autocorrelation: random

Database behaviors

- Subtypes • categorizing different features in a feature class • Can use subtypes to constrain possible feature attributes • prevents incorrect attributes and increases accuracy and efficiency - Attribute Domains • giving additional constraints as a subtype • Two different types of attribute domains 1) Range Domains: Valid range of values for a numeric attribute (ex, "class enrollment can range from 1 to 105")-- (all 3 of the red boxes in the image below are range domains, feature class, subtypes, domains) 2) Coded Value Domains: Valid set of attributes (ex, only certain land use types) • Can use domains to constrain possible feature attributes • prevents incorrect attributes and increases accuracy and efficiency - Relationships - Validation Rules

DEM: TIN Triangulated Irregular Networks (vector)

- TINs represent terrain height by storing series of x, y, & z point locations • Use measured points with elevation values (z) stored at nodes - The points are connected by a network of irregular triangles called a Delaunay Triangulation • Lines from one triangle cannot cross or overlap another through convergent circles for each set of triangle points - Don't use every single data set Know: triangles vary in their size and automatically more complex version of terrain model Z-value or Z-tolerance Maximum allowable difference in z-units between the height of the input raster and the height of the output TIN. • Controls how closely the TIN approximates the original raster surface (spatial filtering) - Larger Z-tolerance = fewer points kept to form TIN (KEPT FEWER POINTS= NOT AS COMPLEX= NOT AS ACCURATE = COARSE POINTS = LOWER RESOLUTION) - Smaller Z-tolerance = more points kept to form TIN (MORE DETAIL = MORE POINTS = MORE RESOLUTION = FINE POINTS = MORE RESOLUTION) as you change your z tolerance on a TIN it does change the triAngles and nodes have to store and detail

Hierarchical databases

- The structure of the first DBMS (Historical) - Doesn't work so well because in many instances there over lap between records - modern day databases are not hierarchal they are relational bc when you have a hierarchy you can't intermingle between data

Selection operations

- algebra or boolean algebra - adjacency operations (id features that touch other features)

Adjacency operations

- identify features that touch other features (share a boundary) - Defined as sharing a boundary for some distance greater than zero - can have levels of adjacency can be 1st level (directly touching), 2nd level (touching something thats touching something), or 3rd level (touching something that touching something thats touching the main thing)

Restrict

- if the row isn't darkened in grey it is not pushed through to the next table (restricted)

Entity

- is a collection of related data items that can be treated as a unit. - - A specific entity is called an instance of that entity.

Different types of adjacency operations

- share a line (rooks contiguity) - share a node (point) or line - queens contiguity - containment selection: identifies all features that contain or surround a set of target features (LDOT & evacuation routes)

Geodatabase

- storing data in relational databases (find relationship pathways through files) • Object-oriented model can characterize features more naturally by defining object types, topological, spatial and general relationships, and interactions - Brings physical model closer to logical model Picture - left column: not geodatabase specific - right column is geodatabase specific "If it is in a geodatabase its a feature class, if it is not it is a shapefile"

Match which of the following answers with their appropriate classification type description

1) Natural Breaks (Jenks) - Data classification or reclassification techniques attempt to identify naturally occurring clusters of data 2) Equal Area - Data classification or reclassification technique where class boundaries are defined to place an equal proportion of dataset into a specific number of classes 3) Binary - The simplest type of classification or reclassification technique 4) Equal Interval - Data classification or reclassification techniques that splits classes by uniform, specified interval

2 things to think about when looking at a bell curve

1) Shape 2) Central Tendency

Choose which accuracy type correctly represents the following examples of types of accuracy is being affected. You will use one of the options more than once.

1) Tree data is categorized by general type, not by specific species/genus. - Attribute accuracy 2) Building dataset for 2018 is missing new buildings built within the last year. - Completeness 3) Accuracy of wells in a point shapefile is +/- 1 meter - Positional accuracy 3) Metadata shows that David Bowie of the USDA created a tree shapefile in 2010. - Lineage 4) Houses are represented by points on roads, but there are some tat are not on the road. - Logical consistency 5) Elevation dataset has contours lines that cross each other. - Logical consistency

Intersection

2 tables and look for which records in both tables match and put them into one

Difference between geodatabase and shapefile

2) Shapefiles - don't have topology associated with them but can convert them 3) Geodatabases - feature classes are in geodatabases • have to have a feature class to create topology (BOTH are Vector file types)

Algebraic funcitons

< LessThan > GreaterThan = EqualTo < > Not Equal To can be applied alone or in combination

Which of the pictures in the Figure 2 above describes the Adjacency topological relationship?

A B C D E

Which of the pictures in the Figure 2 above describes the Proximity topological relationship?

A B C D E

Moran's I

A statistical global measure. Takes the distance about every feature in a feature class and then it will look at those values and in relationship with each other. It will tell you if something is clustered or random or dispersed but will not tell you WHERE closer to +1 = clustered closer to -1 = dispersed

Ecological Fallacy

Bias that may occur because association among variables at an aggregate level does not necessarily represent the same associated relationship among individuals • An error of inference due to a failure to distinguish between different levels of organization

Slope (raster)

Calculate: raster Slope is calculated using a symmetrical 3 by 3 moving window (can use 5 by 5) where elevation values are found for each window • Four nearest cells Best for calculating slope on smooth terrain (rooks contiguity) (Formula used to calculate slope at each cell center then combined) • 3rd order finite difference, Best for calculating slope on rough terrain (queens contiguity) • Gives a higher weight to cells near the center than corner cells

Join

Can take 2 tables and combine them - Keys: columns that relate tables together (columns in all of the tables that are the same (don't have to be labeled the same but have to be the same) - Primary key: wherever you want everything to go is the first column that has to match something else - Foreign key: Everything beyond the first column (primary key). Not the primary key you use to get the second table connected to the first but an additional column int the second table you have to use to get the 3rd table connected - type has to be the same for each column (can't have numeric and string and try and join them) - has to be same format (all lower case or all upper case)

Spatial scope: vector data

Characterized by: - local • uses the data at only one input location. ex) Just based on the population density by state (you don't include influences from other states - focal (neighborhood) • Uses both local & nearby location: based on neighbor or predetermined region ex) use n eighbors for a particular calculation or there are pre-determined zones apart of the calculation (normally more common with raster data but does happen in vector) - zonal • (by-zone functions) create output grids based on a pre-defined neighborhood: has a predefined neighborhood ex) watershed - global • Uses data values from the entire input layer ex) rank comes into play here: using info for the entire data set

Spatial Scope (raster)

Characterized by: 1) Local - Operate on a single grid cell at a time with no reference to their neighboring cells •Trigonometric •Exponential/logarithmic • Reclassification •Selection •Statistical •Other 2) Focal (Neighborhood) - does take into account neighboring cells (still take into account rook and queen contiguity) 3) Zonal - Have a predetermined zone that classifies as a zone 4) Global - every cell is used *remember of grid cells aren't same projection or overlaid right you prob shouldn't compare them (not same cell size) - only if there is literally no other option- need them to match and need them to have the same area to overlay*

Inverse Distance Weighting (IDW)

Creates a raster surface - Non linear weighted combination of sample points • when you do slope calculations but using distance - Determines the surface at regular intervals using a linearly weighted combination of sample points - Weighting is a function of inverse distance - IDW is a weighted average - Sensitive to clustering and outliers can smooth data using a larger weight

Interpolation methods

Creating a continuous surface from a set of points. • Assumes there is spatial autocorrelation Types - Linear: draw lines in between equal points - Non-Linear • Triangular Irregular Networks (TINS): Thiessen Polygons: Polygons drawn in such a way that their boundaries define the area that is closest to each point relative to all other points • Inverse Distance Weighting (IDW) • Spline • Nearest Neighbor • Trend Surfaces • Kriging

Most critical data set needed when making a terrain analysis

DEM: digital elevation model Two different types of DEM 1) Digital Surface Models (DSM) contain elevation info about all features in the landscape including trees, buildings, etc 2) Digital Terrain Models (DTM) contain elevation info about the bare Earth surface without vegetation, building, etc

Hydrologic Modeling (raster)

DEMs also used extensively in hydrologic analysis to calculate terrain variables Watersheds: Contiguous region of land that all drains to a single location called the watershed outlet - Easiest to identify watersheds once the flow direction is determined & then traced uphill until a downhill flow direction is reached Flow direction: Calculated either on or below the surface with flows most often following the direction of the steepest descent (global function: using data from all neighbors) - Pits / Sinks random errors in DEMs where cells are lower than all surrounding cells • Random errors in the source DEM - Discontinuities between DEM layers (edge-matching) - Artifacts of resampling (reprojection, georectification) Flow accumulation: Uses flow direction to determine how much water will flow into a specific cell - can create streams or stream networks if you set a threshold

Curvature (raster)

Derivative of slope but decides if the slope is curved inwards or outwards - Profile Curvature • An index of the surface profile shape in the steepest downslope direction - Plan Curvature • The profile shape in the direction perpendicular to the steepest downslope direction

Statistical Principles: Types of Distances

Euclidean Distance: - Straight line from point A to point B • can be calculated with Pythagorean Theorem • "as the crow flies" Manhattan "Network" Distance: - Can't go straight from point A to point B but have to travel on a road system - often has costs associated with them • even if one segment looks shorter, if the cost of that like is more than the cost is more

Global functions (raster)

Euclidian distance

Trend Surface

Happens in 2D space - its calculating general trends, it is probably the most generalized and smoothest form of interpolation that there is - typically gives you some type of direction - Extension of statistical regression into 2 (or 3) dimensions • Geographic coordinates part of the regression - Surface minimizes the squared deviations from the trend • Trend surface doe snot necessarily pass through the sampled points!

one-to-one

Join or relate (link): in destination table (table 1) 1 record matches 1 record in source table (table 2)

Many-to-one

Join or relate (link): many records in destination table (table 1) that matches one record in source table (table 2)

difference between a join and relate

Join: take data from another table and add it to the table you are joining things to - have to have at least 2 tables and have to have a common column or attribute in the two tables that match completely relate: creates a new table that has joined features but these features are not tied directly to some time of geocoded shapefile or feature class - the two tables are not physically merged they are just relationships between the tables

Kriging

KRIGING IS Stochastic: Deterministic means if we were to take sample points and interpolate its surface and we kept the input values or parameters and we ran that same process over and over and over we should all get the same output which is called deterministic HOWEVER Stochastic (probabilistic) is based on probabilities and it can change from one output to another even if the inputs were the same Three Components of Kriging 1) Drift (or structure) • the general "trend" of the surface 2) Variations from drift or trend • these still are related to one another (spatially autocorrelated) 3) Random Noise • uncorrelated

Local Moran's I

LISA statistic (Local Indicator of Spatial Association) - will tell you where the cluster occur - finds the spacial autocorrelation for each feature not just the study area as a whole - does it for every feature in the data set (more detail)

Calculations for moving cells

Mode: number or numbers that occur most often - 12 & 4 Median: right all the numbers down and then cross out one # from both side until reach middle - 8 Average: add all numbers in box and divide by total - 9.11 Minimum: smallest # - 4 Maximum: largest # - 17 Range: largest - smallest - 13

Boolean algebra functions

Or (inclusive) add And (exclusive) multiply Not used mainly to combine set algebra conditions and create compound spatial selections

Zonal Functions (raster)

Pre-defined zone Spatial scope which operators have predefined regions

Rows within the "instnaces" are called (row in a database is called a _____)

Row in an attribute table is called - observations - features - records - n-tuple

Kurtosis

Shape of our distribution peak. - High kurtosis/positive kurtosis = sharper peak and longer, fatter tails - Low kurtosis/negative kurtosis = rounded peak and shorter, thinner tails - 3 = normal distribution bell shape • (Note: it says 0 in the book because that formula subtracts 3. That amount is sometimes referred to as excess kurtosis)

Descriptive spatial statistics

Spatial data tends to not follow randomness Types: - Mean Center ("Center of Mass") • Spatial measure of central tendency, bases it off distance from each other rather than values in a histogram - Weighted Mean Center • Geometric mean may be outside polygon boundaries - Standard Distance • concentration or dispersion around geometric mean (spatial equivalence to standard deviation) - Standard Deviation Ellipse • Summarizes central tendency, dispersion, and directional trends • Find the axis going through maximum dispersion (angle of rotation)

Descriptive Statistics

Summarizes general characteristics of your data 3 Categories - Measures of Central Tendency • Mean: Average value (Sum of values / number of values. Heavily influenced by outlier values) • Median: Middle value (Number at the 50% mark by count. Only use in ordered/ranked data) • Mode: Most common (Value that occurs most frequently. - Dispersion/Variability "Spread" of your data • Variance: Average squared distance of observations from mean value • Standard Deviation: Average distance of observations from the mean. (√variance.) (Standard error = used when an estimate has been made for the standard deviation of an unknown mean) - Measures of Frequency Skewness: How asymmetric our distribution is. • = 0 for symmetric distribution (even on both sides) • Median > Mean = NEGATIVE skew (tail on left bulge on right) • Median < Mean = POSITIVE skew (tail on right bulge on left) (bimodal = extreme tastes = political views, 2 humps with a valley in the middle)

Selection Operators (vector)

Two types: 1) Algebra • true or false in terms of equal or not equal to • less than • greater than • equal to • not equal to 2) Boolean: given a conditional statement (can use complex or compound situations) • Or (inclusive) • And (exclusive) • Not (everything but)

Triangular interpolation methods

Use these points as either the centroids of boundaries (Thiessen polygons) or as the nodes (Delaunay polygons) to create the surface

Nearest Neighbor

Uses many of its neighbors to calculate that particular sample point but it doesn't weight them - Z-value of new location is determined using n nearby control points • Value of new location is assigned value of the nearest neighbor - Polygons define a region around each sample point where the values are all equal - Abrupt transitions between polygons

Neighborhood analysis (raster)

Very similar to adjacency analysis: you decide what the neighbors are that are apart of a calculation are. Do this by a Roving Window - Block function prevents repeating data uptake from a focal function

The Universal Transvers Mercator (UTM) projection was designed to ensure that scale variation within each of the zones was true to within which of the following ratios?

a) "1 part in 1,000,000" b) "1 part in 100,000" c) "1 part in 10,000" d) "1 part in 1,000

Which of the following map scales covers the largest area (small scale map)?

a) "1:1,000" b) "1:10,000" c) "1:100,000" d) "1:1,000,000"

Which of the following statements is incorrect?

a) "Abbé Jean Picard and Isaac Newton suggested that earth was best described as a prolate spheroid and as an oblate spheroid, respectively" b) Eratosthenes was the first person to calculate the circumference of the earth c) Roger Tomlinson is considered that father or GIS and coined the term Geographic Information Science (GISci) d) All of the above are true

__________ is the closeness of results of observations to the true values or values accepted as being true, while ___________ is the exactness of a measurement or description.

a) "Accuracy, Positional Accuracy" b) "Accuracy, Precision" c) "Error, Quality" d) "Precision, Accuracy"

Which of the following map classes correctly preserves shape (at least of small areas) and which one correctly preserves direction?

a) "Azimuthal, Conformal" b) "Conformal, Azimuthal" c) "Equal Area, Conformal" d) "Equidistant, Equal area"

Which of the following describes the 5 components of GIS?

a) "Data, People, Software, Computers, Hardware" b) "Data, People, Clients, Computers, Methods" c) "Hardware, Data, Software, Methods, People" d) "Methods, Data, Clients, Maps, Products"

Which of the following statements is correct concerning how geographic locations are stored in a GIS for projected coordinate systems (PCS) and geographic coordinate systems (GCS)?

a) "PCS: Longitude and Latitude as decimal degrees, GCS: Eastings and Northings as meters" b) "PCS: Longitude and Latitude as degrees minutes seconds, GCS: Eastings and Northings as meters" c) "PCS: Eastings and Northings as meters, GCS: Longitude and Latitude as decimal degrees" d) "PCS: Longitude and Latitude as meters, GCS: Eastings and Northings as decimal degrees" e) "PCS: Eastings and Northings as degrees minutes seconds, GCS: Longitude and Latitude as meters"

Which of the following best describes the two major types of GIS data?

a) "Raster (made of Grid Cells, Continuous), Vector (made of Points, Lines, Polygons, Discrete)" b) "Raster (made of Points, Lines, Polygons, Discrete), Vector (made of Grid Cells, Continuous)" c) "Database (made of Grid Cells, Continuous), Vector (made of Points, Lines, Polygons, Discrete)" d) "Raster (made of Grid Cells, Discrete), Vector (made of Points, Lines, Polygons, Continuous)"

What are the tree file extensions required to have a shapefile?

a) .shp, .shx, .dbf b) .shx, .sbn, .prj c) .prj, .dbf, .shp d) .shp, .shx, .prj .shp: main file .shx: index file .dpf: dBASE table (only need to know top three but be aware of the list of shapefiles)

Which of the following map scales will have features on the map that are the least generalized (large scale map, more detail)?

a) 1:1,000 b) 1:10,000 c) 1:100,000 d) 1:1,000,000

What year will the next major change in US datums occur?

a) 2020 b) 2021 c) 2022 d) 2023 e) nothing is changing in the next 5 years

A reference base that describes the size and shape of the Earth is:

a) A coordinate system b) A projection c) A datum d) A map

Which of the following statements best describes a map?

a) A map is a graphical representation of the physical and cultural environment b) A map is a representation of the physical environment that can be touched or seen c) A map is a graphical representation of the physical environment that can be touched or seen d) A map is a representation of the physical and cultural environment e) All of the above definitions are equally correct

Dr. Thompson is most likely to use the map to the right as a bad example of which of the following cartographic problems?

a) A poor choice for position of the title b) A poor selection of a map projection c) Poor selection of units (miles versus kilometers) d) Too much wasted space (e.g. too much whitespace) e) None of the Above

Based on what you know about projections, which of the following map projections is most likely used as the basis of the State Plane Coordinate System for states that are elongated N-S, such as Idaho?

a) Albert Equal Area Conic b) Lambert Conformal Conic c) Transverse Mercator d) Oblique Mercator e) None of the Above

______ are not often used for terrain analysis but are among the most effective ways to communicate the shape & structure of terrain features visually.

a) Aspect b) Shaded relief map (Hillshade) c) Watershed d) Slope

What developable surface was used to create the map (Map 2)?

a) Azimuthal b) Conic c) Cylindrical d) Oblique e) None of the Above

What developable surface was used to create the map above?

a) Azimuthal b) Conic c) Cylindrical d) Oblique e) None of the Above

_______ of a raster model is the distance that one side of a grid cell represents on the ground.

a) Cell dimension b) Locational balance c) Resolution d) All the above

The above map depicts the comparison between community social vulnerability scores and damages and flood levels, using Census Tracts as enumeration units. Based on the information in both the map and the description, answer the following: What TYPE of map is shown in the image above?

a) Choropleth b) Isarithmic c) Dot Density d) Feature

The main horizontal datums used in the U.S. are WGS1984, NAD1983 and _____________, while the two vertical datums used are NGVD1929 and ________________.

a) Clark 88, NAVD1988 b) NAD1927, NGVD1998 c) NAD1995, NGVD1987 d) NAD1927, NAVD1988

The figure illustrates which of the following vector overlay operations?

a) Clip b) Erase c) Union d) Intersect

In GIS, the Boolean Expression (A AND B) an also be accomplished for vector features with which of the following overlay operations

a) Clip b) Erase c) Dissolve d) Intersect e) Union

In a Moran s I, if the value of closer to 1 and is statistically significant (?>= 0.05), then the data is spatially ____________.

a) Clustered b) Dispersed c) Random d) None of the above

The most common type of buffering method in ArcGIS is ___________.

a) Compound buffering b) Simple or fixed distance buffering c) Nested buffering d) Non of the above

To which class of maps does the map above belong?

a) Conformal b) Equal Area c) Equidistant d) Azimuthal e) None of the Above

To which class of maps does the map above belong? (map 2)

a) Conformal b) Equal Area c) Equidistant d) Azimuthal e) None of the Above

Which of the following is NOT something you should consider when selecting map colors?

a) Consider choosing colors for the color blind b) Lighter colors for higher values and Darker colors for lower values c) Be aware of color associations that may be offensive d) Maintain logical color relationships (forest type) e) All of the above are true

Which of the following contains information about all features on the landscape, including trees, buildings, etc.?

a) Digital Surface Model b) Digital Terrain Model c) Triangular Irregular Network d) Raster e) Vector

Points, lines and polygons are considered to be:

a) Discrete data b) Continuous data c) Aspatial data d) Metadata

You work for the city of College Station and have been asked to identify all parcels, of the city that are located within 100m of the stream. Which of the following vector overlay operations would you most likely employ as your first step

a) Dissolve b) Buffer c) Clip d) Union

___________ ignores the geometric details & identifies the basic structure of how things are arranged in space.

a) Euclidean space b) Topological space c) Conceptual space d) None of the above

The number of cells required to cover a given area increases _____________ as cell dimension gets smaller.

a) Exponentially b) By a factor of two c) Quadratically d) Trick question as the number of cells decrease as cell dimension gets smaller

Two major components of a datum include 1) the specifications of the ellipsoid being used and 2):

a) Format of data being used in the analysis (vector or raster). b) A defined projection. c) Set of surveyed points & lines. d) All the above.

The transformation of coordinate locations from the Earth s curved surface onto flat maps is called:

a) Geodesy b) Map projection c) Map generalization d) Coordinate selection

Click on the link below to answer the following question. Rick Astley will never: This is obviously a freebie question. Pick any answer. Seriously. Don t over think this.

a) Give you up b) Let you down c) Run around and desert you d) All of the above e) I have no idea who Rick Astley is .

Cell size should be no more than ____________ the desired accuracy & precision for the data being represented.

a) Half b) Triple c) Twice d) Four times

Which of the following terms most appropriately describes the structure of historical databases?

a) Hierarchical b) Relational c) Database Management Systems (DBMS) d) "All of the above (a, b, & c) are appropriate" e) "None of the above (a, b, & c) are appropriate"

Georeferencing:

a) Is the ability to locate features accurately in a geographic space b) "Includes information about datums, ellipsoids and coordinate systems" c) Refers to the science that studies the size and shape of the earth d) a & b only e) All of the above

Which of the following statements is NOT true about an Ordinal data measurement scale?

a) It is hierarchical b) It is a rank ordering c) Increments between observations can be quantified d) Symbols may change in size to show variation in rank

Which of the following statements best describes the term Cartography?

a) It is the art of map making b) It is the science of map making c) It is the art and science of map making d) It is those techniques in GIS that are involved with making a map

Universal Transverse Mercator coordinate system works well for measuring:

a) Large areas b) Multi-State Mapping c) Small Areas d) UTM is not a coordinate system e) a & b only (UTM is not a projection)

The State Plane coordinate system works well for measuring:

a) Large areas b) Multi-State Mapping c) Small areas d) State Plane is not a coordinate system

__________ is problematic for classical statistical tests, such as ANOVA and ordinary least squares (OLS) regression, that assume independently distributed errors

a) Nearest Neighbor Analysis b) Quadrat Analysis c) Spatial Autocorrelation d) Moran s I

What is the data measurement scale of the data (levels of social vulnerability and FEMA loss) plotted in the map?

a) Nominal b) Ordinal c) Interval d) Ratio

The general process of interpreting what can be sensed in the real world into representational symbols is known as:

a) Normalization b) Abstraction c) Interpolation d) Cartographic Generalization

If you are joining a table with owners (source) to a table of parcels (destinations), where 1 owner owns many parcels, what type of cardinality relationship is being described? The order of the options is based on Source table-To-Destination table.

a) One-to-One b) Many-to-One c) One-to-Many d) None of the above

Which of the following can represent NON-TOPOLGY editing?

a) Polygons must not have gaps b) Lines must not intersect c) Polygons must not overlap d) Edge matching for polygon continuity

A _____ domain is a range of valid values for a numeric attribute, while a ______ domain is a valid set of attributes.

a) Range, Subtype b) Coded Value, Range c) Range, Coded Value d) Range, Relationship

Geographers employ the four-tiered measurement classification scheme to describe the measurement scale of the data they are symbolizing on map. The map below investigates the distribution of neighborhood house price-to-income ratios across the U.S. and location of homeowners. However, the price-to-income ratio is calculated as one data measurement type (methods described in the bottom left corner), but displayed in the legend as another data measurement type. Based on information provided by the map, what data measurement type is used to calculate the price-to-income ratio variable, and what type is used to symbolize the price-to-income ratio? Hint - look at more than just the map legend.

a) Ratio, Interval b) Ordinal, Ratio c) Interval, Nominal d) Ratio, Ordinal e) Interval, Ordinal

The general shape of the Earth is typically described using a:

a) Spheroid b) Ellipsoid c) Oval d) Both a. & b.

The true shape of the Earth (determined by the density of Earth s effect on gravitational pull) is best described using a:

a) Spheroid b) Geoid c) Ellipsoid d) Both a. & b.

Which of the following map elements has the most important intellectual standing and hence should appear at the highest visual level (e.g., be perceived by the map percipient as the most important)?

a) The Basemap b) The Graticule c) The Legend d) The Map Body

If someone reduces or enlarges a map on a photocopier or by printing, which of the following statements is true?

a) The graphical scale bar will remain correct b) The representative fraction scale will remain correct c) The verbal scale will remain correct d) All three scales will remain correct e) None of the scales will remain correct

Which of the following are true about queries?

a) They concern the selection of attributes in a table that meet one or more selection criteria b) The simplest form of queries is on-screen query (point & click) used for information gathering & updating c) Are part of only database management d) Only A & B are true e) None of the above are true

For selections/queries, Boolean Algebra uses the functions Less Than, Greater Than, Equal To, or Not Equal To

a) True b) False

The figure from the Bolstad textbook below illustrates which of the following relational algebra operations that can be used with tables?

a) Union b) Intersect c) Extract by Criteria d) Join e) None of the above

Which of these is NOT one of the three 3 goals of GIS that help people do their work better, faster, and cheaper?

a) Visualization b) Improved Methodology c) Data Management d) Spatial Analysis

Which of the following is NOT a projected coordinate system?

a) World Geodetic System 84 b) NAD 1983 UTM Zone 17N c) "NAD 1927 State Plane, Idaho East" d) All of the above are projected coordinate systems

Local operations (raster) - Boolean

and - both of the two tables don't have a 0 = 1 (top left cell) - one of the two tables has a 0 = 0 (bottom left cell) - if one of the cells is blank or has the letter n = space (left middle cell) or - one one the cells has a value - if one of the cells has a space (nothing) and the other has something then they get a 1 (important pic)