Exam 1 Material

Displaying Rater data

- Drawing cells by: • unique value • graduated colors • stretched with graduated colors (more smooth transition) • multiband rasters • red-green-blue composite

Geographic information is represented in

- Vector: discrete data based on XY locations • points • lines • polygons - Raster: pixel/cell based data (continuous)

Representing Thematic Raster Data

- normally representing one particular phenomena ex) fire modeling

___% of all data has a spatial component

80

Which of the pictures below describes the Proximity topological relationship?

A B C D E E

Feature Classes

Found in a Geodatabase - Can be stored as a standalone - May also be annotation layers. OR In a feature Dataset - MUST share a common projection (enforced in a geodatabase)

Raster data is:

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

Geographers employ the four-tiered measurement classification scheme to describe the measurement scale of the data they are symbolizing on map. Based on information provided by the map, what data measurement type is used for the temperature scale?

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

GIS is a _______ of reality

abstraction

Cadastral

geospatial data talking about tax assessors (tax parcels)

sampling

selection of a subset of individuals within a population

Contiguity

some type of shared point or border between different types of features ex) the continuous US (not Alaksa and Hawaii)

GIS is a: Tool box

"A powerful set of tools for storing and retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes" - Peter Burrough Know your tools, GIS can: - Capture - Archive - Retrieve - Project - Analyze - Display • always read, understand, and follow the directions with tools

GIS as a: Information System

"An information system that is designed to work with data georeferenced by spatial or geographic coordinates. In other words, a GIS is both a database system with specific capabilities for spatially- referenced data, as well as a set of operations for working with the data"- Jack Estes - 5 main components to be considered a GIS system

Raster Data Model

- Continuous data - Use of a grid-cell data structure - Geographic area is divided into cells identified by row and column - define the world as a regular set of cells in a grid formate or pattern - cell size = cell resolution = cell dimension (length = width) - rasters are two-dimensional arrays of cells or pixels, spanning a rectangular area - each cell is assigned a distinct value (the values for the individual cells may represent discrete objects or continuous phenomena)

Fine vs Coarse resolution (test question)

- Fine pixels cover smaller area - Coarse pixels cover larger area

GIS queries

- GIS can be used to answer specific questions using spatial data Ex) "Show the locations of all properties with an area in excess of 1/2 an acre and an assessed value of under 200,000 in College Station" • A query could look like this: big_and_cheap = [area] > 0.5 and [parcel_assessment] < 200,00 and [property_location] = "College Station" - GIS queries are ad hoc or context specific - When building a GIS you usually don't know in advance what exact questions will be asked • This means GIS is a generic problem solving tool - Ex) Cholera outbreak in London, John Snow, used GIS to figure out how to target where the disease was coming from

Maps

- Maps are everywhere - When a map is made, decisions on what data to show (and how) drive the construction of the map - We use maps to answer spatial questions - We each have our own way of representing the world: our mental maps Maps are: - Communications Devices - Historical, cultural, & technological artifacts - Political Documents - Creators of Features - Tools When making a map, we you have unique abilities in decision: - Control over content - Control over area - Control over emphasis - Focus on spatial relationships - Analogue of the real world GIS output is a map

Measurement Scales: Ordinal

- Qualitative (not numerical) • not measurable - scaling based on hierarchy (rank/ordering) - can't determine distance between observations ex) - class ranking (only know rank but do not know GPA) - finishing position of racers (we don't know the distance or time separating them) - Mohs mineral hardness scale - Likert Scale (uses names: satisfied, very satisfied, very unsatisfied) - How satisfied are you with your current internet plan: theres no way to pin point the difference between the answers just know theres a hierarchal range in the answers

Measurement Scales: Nominal

- Qualitative (not numerical) • not measureable - Simplest level of measurement scale • discrete not continuous • NO order or rank - Objects classified into groups - Cannot perform any mathematical operations between classes - Can only determine equality or inequality ex) Democrat, Independent, Republican ex) apple vs orange

Measurement Scales: Ratio

- Quantitative • measurable - has a known starting point (doesn't go below 0) - Ordering events with known distances separating the events - Are absolute - The scale of measurement has a zero as its origin - Most measurement in physical sciences done on ratio scales ex) • Kelvin absolute temperature scale • Elevation above sea level • height • number of people or populations • percentages • I think median age by state goes here too

Measurement Scales: Interval

- Quantitative • measureable - Measured numerical data from arbitrary starting points (no true 0 bc you can have negative numbers) - Know the distance between observations - Units are equal throughout, i.e., inches, degrees, acres - Chosen intervals may not have natural origins, and does not make sense to make ratios between numbers ex) • Fahrenheit Scale Temperature Scale • Celsius Scale Temperature Scale • SAT Scores

Data quality

- Spatial data standards (people try to enforce) are important because of the many different people using spatial data & the need to transfer data across people & projects - It is important to document how data have been transformed or manipulated to make it useful to other users • Description of data origin • Methods of development • Accuracy • Delivery format Spatial data standards may be categorized into 4 areas: 1) Media standards • physical form of data are transferred (CD-ROM, external hard drive, etc.) 2) Format standards • data file components & structures (# of files used to store a spatial data set & basic components contained in each file) 3) Accuracy standards • describes how faithfully a digital representation reflects the true shape, location, or characteristics of the phenomena represented in a GIS • Always errors in spatial data some common ones include: -- How features are conceptualized -- Methods of data collection & analysis -- Misunderstanding data collection methods -- Human error -- Out of date 4) Documentation • how we describe spatial data (metadata)

Geographical area unit aka Enumeration Unit

- Unit that data can be aggregated into: can be done in two ways 1) Artificial Areal - imposed by researchers - an attempt to organize reality or...to facilitate data collection ex) regions, census tracts, Standard Metropolitan Statistical Areas (SMSA) 2) Natural Areal ex) lakes, farms, cities, deciduous forests • although cities and farms are not natural they do have natural boundaries

Developing spatial awareness

- We organize real world phenomena into different categories & mental models - Data representation

Planar coordinate system

- a grid that shows locations on a flat (planar) surface - the location units are measured in distances - rather than being on a geographical scale it used a distance unit ex) feet or meters - every row in an attribute data set is only going to represent one feature (single entity) - each column in an attribute data set is a different attribute for each of these features

Topology (topological model)

- arrangement that defines how point, line, and polygon features share coincident geometry • in addition to having the geometric info it specifically focuses on how things are related in space - it ignores the geometric details and identifies the basic structure of how things are arranged in space ex) Subway map (posters not online)

Vector file types: Shapefiles

- do not have topological rules • contains no topology • some topology can be calculated on-the-fly 3 required files (test question) (3 types of shapefiles) 1) .shp - the file that stores the feature geometry (vertices) 2) .shx - the file that stores the index of the feature geometry 2) .dbf - the dBASE file that stores the attribute information of features (all the attribute info is stored)

Representing image raster data

- some type of image acquired through satellite or aerial photography that can capture light at several angles (a composite of several different bands or light images) • there are 3 different raster data set bands with 3 different imageries

Vector file types: Geodatabases

- storing data in relational databases • Geodatabases can store multiple files and file types in a single database. 3 types of geodatabases 1) .gdb (should use) - common file system folder (file GBD) • single user • no limit to how much you can store in it 2) .mbd (avoid using) - Microsoft access database (personal GBD) • has a limit of 2 gb • single user 3) enterprise - relational database • multiuser (multiple people can access it at once)

Map scale representation: representative fraction (RF) (test question)

- the ratio of distances on the map to same distances in the same world • Map scale is entire fraction - Need to know: • large scale maps will have a smaller denominator (closer up maps) • small scale maps will have larger denominator (farther away) • Metric scale→can be applied to scales based on powers of 10. E.g. 1:10,000, 1:100,000

Topological relationships (test question)

1) Connectivity - geographic features that connect or intersect each other • subway lines: where do different lines or polygons connect 2) Adjacency (Contiguity) - Geographic features that are adjacent (contiguous) to others • do some features share or are adjacent at some point or line (the continuous US - 48 states excluding Hawaii and Alaska) 3) Containment - Geographic features that are contained within a polygon • not overlapping B is within the polygon of A 4) Relative Direction - Indicates the relative position between geographic features • geographic maps: don't want to send someone down a one way street (has directionality with a line) or could be like utilities (water goes in sewer comes out) 5) Proximity - Indicates which geographic features are near others • know how close things are to each other

Vector File types

1) Coverage - one of the earliest versions. Oddly put together 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

GIS must be composed at least 3 things:

1) Database containing attribute information 2) Spatial or Map information 3) A way to link (1) and (2)

Spatial data is categorized in 3 ways

1) Discrete - vector data 2) Continuous - raster data 3) Summarized by geographic area

5 components of GIS

1) Hardware (computer and additional equipment) 2) Data (vector or raster) 3) Methods (guidelines, specs, procedures & standards for analyzing & applying gis) 4) Methods (guidelines, specs, procedures & standards for analyzing & applying GIS) (ask questions, choose, collect, & analyze the data, interpret results) 5) people

Gathering GIS data (collecting GIS data) - 2 main types of data collection

1) In situ spatial data: data collected in person or on the ground - NAVSTAR Global Positioning System (GPS) - Land surveying (just because it is a survey doesn't mean its not on the ground- you had to physically go or physically go mail a survey to someone and collect it and that survey is tied to some location) - Census - Digitization of historical hard-copy maps and other geospatial data 2) Remote sensing - Obtain data with no physical contact (Ariel machinery; drone, airplane, or some kind of camera associated with it)

Classifying geographic problems

1) Scale or level of geographic detail • city or state 2) The basis of their intent or purpose • why? • normative uses - focus on design • Positive uses-focus on advancing the science • Curiosity -driven science ("blueskies") • Applied science or research 3) Timescale of the problem • Operational, tactical, strategic • how relevant is data to the current time, is it going to be applicable in another time

2 problems that can affect vector data are: (two errors of vector data models) (Test question)

1) polygon inclusions - areas that are a part of the polygon but different • False area homogenous assumptions • Unresolved inclusions -- Too much effort to fix -- Present in almost all polygons ex) not removing the sidewalk from the grass polygon - is an error but often times done on purpose 2) boundary generalizations - can be done on purpose • in order to avoid creating such a complex feature, make a generalization. Not bad unless you need them to be incredibly accurate - incomplete representation of boundary locations - Describes difference between the true curve & how it is represented with multiple smaller line segments

four most common type of probability sampling (non directed sampling)

1. Simple Random - Assign numbers to objects & use random number generator to sample 2. Systematic - Decide pattern of sampling (e.g. every 10th tree) 3. Stratified - Group & sample subsets of populations (e.g. political survey) 4. Cluster - Chose like participants e.g. truck owners

Vector Data Model Types (Test question)

3 types of vector data models 1) spaghetti - 1st genereration vector files • Many errors/inefficient and no way to check for the errors • everything stored independently so you can't reference how the points relate to one another • Yes you could input coordinates for different types of features but there were no rules to ensure the way that the coordinates were entered actually met the rules that were necessary for these features 2) topological - Store information on how they relate to each other • if there is any type of linking feature, it will tell you there is a polygon to the right of that feature or to the left of that feature (if we have all of the info we can say polygon one is adjacent to polygon 2 - important because: • enables relationships to be established between feautes • allows error detection to be done in a GIS 3) topological warped

Advantages of Vector data

Advantages - Good representation for focus on 'things' (objects) • Accurate graphic representation at all scales (where things are located on the earth, and the shape of things which also being a lot easier to retrieve and update) - Retrieval, updating & generalization of graphics & attributes possible - Topology can be described explicitly (can't do this with raster data) • Enhances adjacency & network analysis • More accurate overlay analysis

GIS data models

All spatial data models are approaches for storing the spatial location of geographic features in a database 1. Raster - Use of a grid-cell data structure - Geographic area is divided into cells identified by row and column 2. Vector - Each vertex consists of an X coordinate and a Y coordinate

Precision

Consistency of a measurement method. Exactness of measurement or description - Areal: Smallest feature that can be displayed, recognized, or described - Rasters = pixel resolution - Temporal: amount of time between measurements (daily versus annual) - Attribute: Discrimination between types (Douglas fir versus conifer) - When possible, positional accuracy should be quantified (mean & spread of the positional & attribute errors)

GIS does not exist without _____

Data - majority of GIS users time is spent creating and organizing data (70%) - Very expensive & time consuming - most project cost - Can be tedious - Data can be found from existing sources or created -look for existing sources first - Data are stored in files (database)Ga

Measurement in geography

Discrete - form a separate entity • different features - can only exists only as whole objects • can exist as one costumer or multiple costumers - often represented in GIS as a vector data type ex) the line is covering some area but the beginning of the line starts at one coordinate and ends at another, if it was just points it would just be a GPS locator - should always have a closed polygon Continuous - exist spatially between observation points • land usage or elevation (different value associated with different elevations) - normally depicted by pixels - fractional parts allowed - often represented in GIS as a raster data type ex) all converted into individual cells if you need features that are defined, detailed and pretty you should use vector data over raster data

Cell resolution (raster data models) (test question)

Distance that one side of the grid cell represents on the ground - higher resolution (Fine Pixels) = smaller grid cell and higher precision, but more storage (slower processing speed) - smaller resolution (Coarse Pixels) = larger grid cell, and low precision, and less storage (but faster processing speed)

Roger Tomlinson

Father of GIS - created a mapping system in 1966 for Canada (started off as Canada Geographic Information System (CGIS)

Topological Rules (test question)

Topological model - planar - planar demands no overlap of features on same layer - topology only works on features in a geodatabases, shapefiles do NOT have topology - planar relationships can be enforced between layers • Force lines to connect between layers (hydrants, water lines) • Housing data (polygons) not crossing property lines - can make your own rules: can make a rule that houses within a data layer can not cross a boundary line • also need to know the word MUST ("points must be contained within a line segment" must means its topological and has a rule associated with it)

Vector Data Models

Use discrete (non continuous) elements in the form of points, lines, & polygons to represent real world geometry - make vector models more complex by adding more vertices • Point (one verticy) • Line (beginning and ending vertices) • polygon (the starting and ending coordinate are always the same) 2

Vector data models structure: points

Use single coordinate pairs (X,Y) to represent the location of an entity (no dimension) - Light poles - Fire hydrants - Cities

Map scale representation: Verbal scale (test question)

Verbal description of the representative fraction - used to clarify the representative fraction ex) "one centimeter equals 100 km" ex) "one inch to the mile"

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 a

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 c

Which of the following statements best describes a map?

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

Who is considered that father or GIS ?

a) Abbé Jean Picard b) Eratosthenes c) Roger Tomlinson d) Michael Goodchild e) None of the above c

__________ 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 b

_______ 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 c

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

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

Which of the following is something you should consider when selecting map colors?

a) Consider choosing colors for the color blind b) Lighter colors for lower values and Darker colors for higher 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 e

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 c

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 c

Map ___________ is the relationship of the distance on the map to the distance on the ground.

a) Generalization b) Scale c) Abstraction d) Feature generalization b

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 b

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 c

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 c

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 d

Which of the following is NOT a projected coordinate system?

a) NAD 1983 UTM Zone 17N b) NAD 1927 State Plane, Idaho East c) North American Datum 1927 d) All the above are projected coordinate systems c

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 b

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 d

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) a

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

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

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

a) The Data Source b) The Scale Bar c) The Legend d) The Thematic Symbols a (partial credit for d)

Which of these is one of the three 3 goals of GIS that help people do their work better, faster, and cheaper?

a) Visualization b) Data Management c) Improved Methodology d) "Only a, and b" e) All of the above e

Maps and GIS both _______ reality

abstract - Take things taken from the real world and represent them in ways that are not necessarily accurate

Common raster representation

all letters that identify what characteristics are present in each cell will be changed to be represented by a number and each number represents those original categories

Raster data models: Cell size (test question)

cell size should be no more than twice the desired accuracy and precision of the data being represented ex) if you need to have a measurement that has up to 10 meters accuracy then your cell size should be no more than 2x 10 meters = data should be no more than 20 meters

Aspatial data

data with no spatial component associated with attributes

Geospatial data

data/information with explicit geographic positioning information

John Snow

father of epidemiology

Number of cells required to cover a given area increase _______ as the cell dimension gets smaller (test question)

quadratically - cutting ell dimension in half increases the number of cells by factor of 4 - accuracy improves as the number of cell dimensions increase - cell dimension also affects positional accuracy (the smaller/finer resolution the more accurate you become)

The problem of mixed pixels

some cells within raster data grids are mixed between more than 1 category - Solutions: • winner takes all: the category that takes up majority of the cell will be identified as such • can choose a feature you are most interested in (if you are more int erested in where water occurs on the map and cell with water in it will be identified as water) • Identify edges: if more than one category is present than you label the entire cell as an edge leaving it to be neither of the other options

Assign and create Raster data models that represent the real world

will always be generalizing the final measurement per cell - through generalization • value applies to the center point of the cell. • This single value will represent the entire area of the cell regardless if it is no all the same

What can you do with raster data and what can you represent?

you can represent both continuous and discrete phenomena - Continuous phenomena: some type of measurement that occurs in all places across an extant. Doesn't have real boundaries ex) elevation - Discrete phenomena: has boundaries ex) land cover

Raster data models: attribute table

There is no FID field in these tables (unlike vector data models) - raster data is based on the count of certain values - can't split raster data set in an attribute table by individual cells (will always be aggregated by type and value and then a count of how many of those values are present)

Data quality: Spatial data standards may be categorized into 4 areas: Accuracy

Four main ways to describe spatial data accuracy: (Five components of data quality) (test question) 1) Positional accuracy - how close objects are to true location - where it is located on earth, accurate up to a foot (measurement of how far you are from the actual distance (where the polygon is located) - Deviation of an objects recorded position from its true ground position • Relative Positional Accuracy: Positioning of features in relation to each other --- a greater concern than absolute accuracy • Absolute Positional Accuracy: Location with respect to the coordinate system being used 2) Attribute accuracy - how different attributes are from true values/How closely the recorded measurements estimate the true real-world values - does the attribute match the feature its been assigned, doesn't make sense (inaccuracy in the table) 3) Logical Consistency - Inconsistent data (roads through lakes) - where are the features and are the consistent - ex) creating road networks, addresses are given points on the road so it is a logical consistency (either placed in a consistent logical format or are representing features that would not normally be in that area but for a real reason -- driving directions locate a house as it is in the middle of the street - Largely concerned with topology errors& contradictory relationships 4) Completeness - does data capture all of the features it intends to represent (may not due to generalizations such as small land use changes within larger areas) - missing data - Does data have unclassified areas? - Does data support your experimental design or stated design goals? 5) Lineage - The historical & compilation aspects of the data - Who created it? When? What standards were adhered to? Areal extent & resolution? Digitized or scanned? Reprojections used? Data simplified?

Types of Geospatial Data

GIS & Spatial Analyses concerned with locations and properties/ attributes of features

What is GIS

Geographic Informations Systems - a computer based system to aid in the collection, maintenance storage, analysis, output, and distribution of spatial data and information - what makes it unique is that it is driven by spatial data • instead of just having a table that you would see in excel you have to have spatial or map data 1) Tool Box 2) Information System 3) Approach to Science

3 Goals of GIS

Help people and companies do their work better, faster, cheaper through: 1) Visualization: provides quicker more accurate representation of spatial data 2) Data management: makes it easier to keep spatial data accurate and updated 3) Spatial analysis: helps users make more informed decisions

Dimensionality

How many dimensions can a feature take - Points: 0, XY coordinate - Lines: 1, Length between 2 XY coordinates - Areas (polygons): 2, Length and Width - Continuous Surfaces: 3, Length Width and height

Data representation

How these entities are organized and encoded digitally - important because it controls how people will view certain aspects which are portrayed In GIS real world objects are represented as - points - lines - areas - surfaces (when height is added)

Data measurement

In order to compare objects across space we have to measure them Level of measurement depends on - Type of object - What we want to know or analyze - Ability to make measurements at our selected scale Measurement scales: 1) Nominal 2) Ordinal 3) Interval 4) Ratio • increasing in complexity, greater permissible statistical approaches

Data sampling

Inferences about the sample are used to make predictions about the population as a whole Spatial sampling in GIS is either directed or non directed sampling - Directed - Sampling that is based on our ability to make samples from our target data e.g. mobile home study need to sample mobile home residents Non-random so less scientific (limitation) - Non directed -Probability sample • Preferred as it reduces bias (more scientific) • random • 4 types of non directed sampling (probability sampling)

Vector data models structure: Lines

Linear features (lines or arcs sets of coordinate systems) are represented as line. Most often represented as an ordered set of coordinate pairs - Long straight lines = 2 coordinate pairs (start & end) - Curved linear features = series of short lines - Nodes: Starting points & ending points - Vertices: Intermediate points, coordinate along the line or polygon feature that is not the start or the end in order to make a line that doesn't have a bunch of squiggles in it you need to order them

Vector data models structure: Polygons

Polygons are formed by a set of connected lines - Areas features most often represented by closed polygons (polygons have to be closed) - Attributes can be attached to the entire line, line segments, nodes, & vertices along the line - Polygons starting coordinate is always the ending coordinate as well (test question) - the interior region of the polygon may entirely enclose other polygons (you can have complex polygons w/ holes Simple Polygon: - Composed of lines with a common beginning/en ding node Complex Polygon: - Contains "islands" - Both external and internal boundaries • the polygon is NOT overlapping the other the polygon is NOT within the other polygon it is being surrounded • counties and county boundaries should never overlap (that is an error)

Map scale representation: Graphical scale (test question)

Scale bar - out of the 3 types of measurement scales graphical scale is the only 1 that stays correct after reproduction (making the map smaller or larger)

Geospatial

Subset of the spatial applied specifically to the Earths surface and near surface

GIS is a: Science

Term coined by Michael Goodchild (USCB) • argued that GIS and its use raises fundamental questions that deserve a systematic study in their own right • the science behind the systems - Questions that can be asked • how do we represent the earth's surface? • How do we assess how good this representation is? • How useful/understandable is this representation to a user? • How do we analyze and display geographic data?

Quality and Completness

The appropriateness of the data for an application The U.S. Spatial Data Transfer Standard (SDTS) identifies five components of data quality: - PositionalAccuracy - AttributeAccuracy - Lineage- Logical Consistency - Completeness

Map Scale

The relationship of the distance on the map to the distance on the ground - scale is is important and changes the considerations you have to take but theres a difference between spatial analysis and map scale Map scale is represented in 3 ways 1) Representative fraction 2) Graphical scale 3) Verbal scale