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GIS > Key Terms > Flashcards

Key Terms Flashcards

1
Q

Geographic and Spatial

A

Geographic refers to the earths surface and near surface. Spatial refers to space

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2
Q

Spatial Data 3

A

refers to information about the locations and shapes of georgaphic features in space and the relation between them.

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3
Q

Database

A

GIS is database powered – a structured collection of spatial data and its related attribute data, organised for efficient storage and retrieval.

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4
Q

Spatial and Aspatial Queries

A

In the case of GIS, a database may be queried and the output displayed as a map / image. But it is essentially: “a request that examines feature or tabular attributes based on user-selected criteria and displays only those features or records that satisfy the criteria

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5
Q

Model

A

The term model is ambiguous: it has many different meanings depending on the context. A model is a simplification of reality, a map is one such example of a model. = an abstract of reality – cannot include all the information about reality

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6
Q

Data Model1

A

GIS is based on a second type of model, known as a data model.
A data model is defined as an abstraction of the real-world:
a mathematical construct for representing geographic objects or surfaces as thematic layers, including their spatial representation, attributes, portrayal and relationships

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7
Q

Rasters

A

photographs – made up of cells
every cell does have to be the same size , but in vector depending on the point the sizes of sections can be different

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8
Q

Vectors

A

made up of points lines or polygons – a way of representing the real world
when you join the points together you will always get a triangle

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9
Q

Spatial Data 4

A

Essentially it is any data that can be mapped to provide representations of the real world for quantitative or qualitative use.

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10
Q

Maps

A

are all abstracts of reality

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11
Q

Spactial Data Model

A

Rasters, Vectors (and TINs) are all examples of a data model.

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12
Q

Spatial Entites

A

aka a representation of the real world – like a square that represents a building – how we represent the real world on a map- every entity corresponds to a role on a table !
This is a requirement of GIS because in GIS we spatially organise things

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13
Q

Discrete Raster

A

A raster that typically represents phenomena that have clear boundaries with attributes that are descriptions, classes, or categories

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14
Q

Continuous Raster

A

how we represent natural phenomena that gradually changes- Raster in which cell values vary continuously to form a surface. Values exist on a scale relative to each other. It is assumed that the value assigned to each cell is what is found at the centre of the cell.

= a way of representing the real world where we have continues change

= each cell has some kind of relationship with its neighbor

= ‘neighborood relationship ‘ - the relationship between cells

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15
Q

Tobler’s law

A

that things close together are more likely to be related
one of the only geography laws

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16
Q

Raster Bands

A

recognize that we have different kinds of bands- a singular layer is made up of different bands sometimes

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17
Q

Single band raster

A

contain a single matrix of cell values. ,Elevation Data , Grayscale aerial imagery ,Scanned maps / document

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18
Q

Multiple band raster

A

contain multiple spatially coincident matrices of cell values representing the same spatial area ,TIFFs, IMGs ,Remotely Sensed Data , Spectral Data

= need to be aware of those differences but not important to the module

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19
Q

Digital Elevation Model

A

Digital representation of topography. Represented by cell based values with a single elevation (attribute) value representing the entire area of the cell. DEMs are typically used to represent terrain relief, and can be used to derive slope and aspect.

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20
Q

Topology

A

Topology studies properties of spaces that are invariant under any continuous deformation. It is sometimes called “rubber-sheet geometry” because the objects can be stretched and contracted like rubber, but cannot be broken.

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21
Q

Attributes

A

is whatever value is in the cell (in vector the thing on the screen connects to the screen and a row on the screen corresponds to that table)

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22
Q

Multiple band - remote sensing

A

Multiband refers to something that involves or operates across two or more bands
if we collapse them together into a singular layer , continuous data into categorical data

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23
Q

Vector Attributes

A

points, lines and polygons would have to be three different layers because you can only have one type on each layer

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24
Q

DEM

A

digital elivation model – a 3D version of the world surface = can have a vector or a raster version

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25
Q

triangular irregular Network (TINS)

A

A Triangular Irregular Network (TIN) is a way to represent a 3D surface. For example, they can show complex surfaces such as slopes and elevation. These types of models use triangles, which we form by connecting points called nodes. The nodes have X, Y, and Z coordinates. Each triangle is a facet in a TIN model.

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26
Q

WFS – Web Feature Service

A

either WFs or WMS would works but WFS allows us to see the attributes as well in CGIS = the computer code from a WFS is the data that QGIS needs= a lot of the time WFS will have passwords because companies dont want people to use them

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27
Q

Vectorization

A

A new layer will be created by digitising (drawing footpath lines) over an aerial photograph of the study area. This process is known as vectorisation, meaning the conversion of raster into vector (the reverse is called rasterisation).

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28
Q

Snapping

A

Snapping involves connecting a geometric vertex or edges of one feature to another. Snapping is an important setting when editing or creating GIS data because it ensures that edges and vertices that need to be adjoining are cleanly connected.

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29
Q

Entity

A

Individual point, line or polygon (area) = vector = the thing you see on the screen

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30
Q

Attribute non-spatial data about an entity

A

if its in a table its an attribute = if its on the screen its in a table (vector)

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31
Q

Attribute

A

Raster: Value of cell (e.g. some absolute value such as elevation or the cell number refers to data in an attribute table)

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32
Q

Feature

A

the thing in the real world - A real world object encoded in a GIS database

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32
Q

Data layer

A

A dataset for the area of interest. -will only be one thing

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33
Q

Image

A

Raster data layer (e.g. photograph)

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34
Q

Cell

A

A single pixel in a raster image. (can use cell and pixel interchangeably)

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35
Q

Function / Operation

A

A data analysis procedure – the thing that we’re doing

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36
Q

Measurement Tool in Spatial Analysis

A

Allows clicking two points to measure distance between them.

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37
Q

Cartesian vs. Ellipsoidal Measurements

A

Cartesian: Assumes a flat world, suitable for small-scale measurements but inaccurate for large distances.

Ellipsoidal: Considers the Earth’s curvature, providing more accurate results for long distances.

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38
Q

Measurement of Areas

A

Can also measure areas, accuracy depends on the scale of the study.

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39
Q

Adding Measurement Attributes

A

Functions available to add measurement attribute data to layers, like adding geometry attributes.

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40
Q

Segment Function

A

Allows creating lines with clicks, each click adds a row to an attribute table.

41
Q

Interactive Attribute Tables

A

Attribute tables are not interactive; recalculations are needed if paths are changed.

42
Q

Spatial Analysis

A

Spatial analysis is like solving puzzles with maps. It’s a way of examining geographic patterns and relationships to uncover insights about the world around us. It helps us understand how things are connected in space and how they change over time.

43
Q

Queries in Spatial Analysis

A

Queries in spatial analysis are like asking questions about maps. They help us find specific information or patterns within geographic data. By asking the right questions, we can uncover valuable insights about locations, relationships, and characteristics of features on the map.
They can be requests to select features or records from a database which are often expressed as statements or logical expressions.

44
Q

Aspatial Queries

A

Concerned with attributes within the database table, regardless of spatial information.

45
Q

Spatial Queries

A

Focus on location, distance, and other spatial properties visible on the screen.

46
Q

Query Results

A

Typically return 1 for true and 0 for false for both Raster and Vector data.

47
Q

Combining Queries

A

Queries can be combined between layers to refine results

48
Q

Query Outputs

A

Output of a GIS query is usually a map.

Final answers are generated by combining layers where both conditions are true.

49
Q

Spatial Query2

A

A statement or logical expression that selects geographic features based on location or spatial relationship. For example, a spatial query might find features, which intersect, touch, or cross another feature.

50
Q

Map Overlay

A

Geometric intersection of two or more datasets to combine, modify, or update features in a new output dataset.

Different types of overlay can yield different results for vector and raster data.

51
Q

Vector Overlay

A

Overlays polygons from one layer over polygons from another layer, using Boolean terminology.

Changes or cuts can alter the attribute table.

52
Q

Vector Overlay Types

A

Intersection: Computes the geometric intersection of input features, retaining areas where both conditions are true.

Clip: Extracts features from one layer that lie entirely within a boundary defined by features in another layer.

53
Q

Raster Overlay

A

Combines pixel or grid cell values in each data layer using Boolean, arithmetic, or relational operators to create a new composite layer.

Resolution impacts data size; doubling resolution quadruples data size. Understanding
the resolution is crucial.

54
Q

Map Algebra

A

Involves using maps as variables in equations to combine data layers using mathematical, logical, or Boolean operators, creating new data layers.

55
Q

Types of Operators

A

Mathematical: Perform arithmetic operations.

Boolean: Evaluate true or false conditions.

Relational: Assess specific relational conditions (outputs true as 1, false as 0).

56
Q

Raster Calculator

A

Tool allowing the use of maps in calculations, as rasters are composed of numbers.

57
Q

Local Operations

A

Applied cell by cell, requiring both layers to be of the same size.

58
Q

Global Operation

A

Applied from the perspective of each cell, affecting values across and down but not diagonally due to differing distances.

59
Q

Focal Operations

A

Change cell values based on their neighboring cells, such as calculating slope.

60
Q

Map Subtraction

A

Subtracting one map from another reveals differences, useful for calculating changes such as temperature fluctuations on a planet.

61
Q

Map Algebra Realtional

A

Use the rastor calculator to find out if somehting is sutiable = it will change the map w colours output w t or f

62
Q

Reclassification

A

Process of inputting values and deriving new output values.

Involves replacing input values with new raster cell values.

Often used to simplify or alter the interpretation of existing raster data.
Can be applied to both raster and vector data.

Simplifies or classifies results, serving as an answer to a query.

Example: Creating a table in Excel and inputting values for reclassification.

63
Q

Automatic Data Classification

A

For more complicated statisitics

Useful for many classes in one feature file (when it is practically not possible to manually classify into groups).

Typically used for raster

Requires classification schemes (algorithms or mathematical formula) which will combine various classes into a single group.

64
Q

Classification Using Statistics

A

data presented in a different way that can cause different results

Equal-interval Classification
Natural Breaks Classification
Quantile Classification

all three methods give different interpretations without corrupting the data

65
Q

Equal-interval Classification

A

A data classification method that divides a set of attribute values into groups that contain an equal range of values. = more intuitive but ‘ doesnt respect the data’

66
Q

Natural Breaks Classification

A

A method of data classification that partitions data into classes based on natural groups in the data distribution. Natural breaks occur in the histogram at the low points of valleys. = harder to communicate but better for statisitics

67
Q

Quantile Classification

A

A data classification method that distributes a set of values into groups that contain an equal number of values. = uses the data with fixed intervals but the intervals are based on the number of values within that class

68
Q

Vector classification using vector

A

Classifying vector data involves assigning various symbols to features (different objects within the same layer) based on their attributes. This makes it easy for map users to visually understand the attributes of different features.

69
Q

Neighborhood functions / proximity analyses

A

Analyzing the relationships between an entity and its surrounding entities or attributes involves examining how one entity is related to others nearby.

This is crucial because many questions rely not only on what exists at a specific location but also on what surrounds that location.

A common and effective method for analyzing these relationships is by using spatial analysis techniques.

70
Q

Buffering

A

A zone constructed outward from an object (point or line) to a specific distance (user defined)

71
Q

Setback

A

Definition: A zone inside a polygon constructed a fixed distance from the edge.

It’s a zone within the buffer area.
Buffers may sometimes overlap, but data from only one singular buffer is typically needed.
Each buffer represents one row; when connected, the lines dissolve together.

Often simplifies processes, such as in the butterfly project.

Important note: Once intersections are dissolved, this action cannot be undone.

72
Q

Rastor Neighborhood Operations

A

Neighborhood operations are commonly used for data simplification on raster datasets. An analysis that averages neighborhood values would result in a smoothed output raster with dampened highs and lows as the influence of the outlying data values are reduced by the averaging process.

73
Q

Focal Operations

A

Change a value based on its neighboring cells

Neighbourhood Statistics is a focal function that computes an output raster where the value at each location is a function of the input cells in a specified neighbourhood of the location.

Borning for one cell but useful when changing more than one cell

74
Q

Moving Window

A

Definition: A grid pattern that processes each cell in a raster dataset by shifting across the dataset.
​
Usefulness: It’s handy for calculating local statistics, detecting edges, and smoothing data.
​
Smoothing Effect: It smooths data by averaging and reducing random noise.
​
Impact of Window Size: Larger windows make data coarser and increase smoothing.
​
Manipulation: It allows adjusting map appearance without compromising statistics, letting you confirm or challenge certain phenomena.

75
Q

Low pass filter

A

removes the randomess when smoothing data

76
Q

High pass filter

A

difference between the smoothed map from the original making it a map of the noice – useful for seeing if the sensor is working correctly

77
Q

Topographic Functions

A

Definition: Utilize Digital Elevation Models (DEMs) to depict slope (inclination), aspect, and hillshading.

Methodology: These functions are typical neighborhood processes, where each pixel in the resultant layer is influenced by its own elevation value as well as those of its surrounding neighbors.

Characteristic: Essentially, they apply neighborhood functions on top of elevation models to generate information about slope, aspect, and hillshading.

78
Q

DTM and DSM

A

DTM – ground surface with nothing else

DSM – is the ground and building with it

= rastor can be both

= Vector triangular irregular network – different kind of digital elevation model

79
Q

SlopeTool

A

The Slope tool measures the steepest slope between each cell by considering the values of its eight neighboring cells within a 3x3 window.

80
Q

Aspect Tool

A

Neighborhood analysis as well

The angle the slope is facing

The aspect tool calculates the compass direction that a topographic slope faces, with the aspect value for each cell in the raster calculated using an algorithm that incorporates the values of the cells eight neighbours (3 x 3 window) – usually measure in degrees.

Based on its neighbor it will respond based on the way that it is facing

81
Q

Hilshading Tool

A

The hypothetical illumination of a surface according to a specified azimuth and altitude for the sun, which creates a three-dimensional effect that provides a sense of visual (shaded) relief

Just changes the way that we look at the map

Not statisical analysis

We create a fake sun and the shading is based on its neighbor

A good way of communicating a map without color

82
Q

Viewshed Analysis Tool - 3D DEM based

A

The viewshed analysis tool is useful when you want to know, for example, what can be seen from one or more points.

It tells you what you can and cannot see based on where a person is standing

83
Q

Spatial Intererlation

A

Where we have gaps in out knowledge =

e.g. a satelitte is trying to take a photo but there is a cloud

= it makes a guess on whats missing and tries to fill in the wholes

84
Q

Extrapelation

A

Going beyond the data to guess the future

85
Q

Network analysis

A

Using google maps to find out how far and how long it will take us to get from A to B

Can factor in traffic , road network and other layers can be included

86
Q

Spatial entities

A

(e.g. tree, roads, habitat) can be described in terms of points, polylines and/or polygons (area). Non-spatial data (data without inherently spatial qualities such as a description) or attributes have to be stored in a tabular format, linked to these entities.

87
Q

Attribute Tables

A

provide information and/or description of spatial entity (e.g. point = tree, polyline = road, and polygon = grass field) . - classes as a common thing – something that all the entities have in common

88
Q

Field

A

the same thing as a colum on a table - something that all the entities will have in common

89
Q

Symbolism Attribute Table

A

The table controls how we change the symbol

90
Q

Rastor attributes

A

Whatever is in the value of the cell
Rastor calculator to extract attributes

91
Q

Vector attribute

A

Can join tables to make more complicated queries

The nature of the queries you can make is based on the relationship

92
Q

Layerfiles

A

In QGIS LAYERS can come in many filetypes but the most common are vector shapefiles and raster Tiffs. The style (display) of a layer is set manually or via an imported style guide. The style settings will be lost if you open the layer in a new project or transfer the file to another person…..but you could save the style setting and transfer that too

93
Q

Fileformat rastor

A

Raster layers, such as IMG, GEOTIFF, and TIFF, utilize a grid-cell data structure where the geographic area is divided into cells identified by rows and columns. Note that raster data layers created within GIS are usually, but not always, permanent. IMG files may reduce file size but may also result in data loss, which is why TIFF is typically preferred.

94
Q

Fileformat Vector

A

Shapefiles (*.shp) are used to store the geometric location, shape, and attributes of VECTOR features. A shapefile comprises a set of related files and can accommodate only one feature class, which could be a point, polyline, or polygon.

MANDATORY FILES:

*.shp: Contains the feature geometry.
*.shx: Serves as a positional index of the feature geometry.
*.dbf: Stores columnar attributes of each entity in dBase IV format, directly openable in software like Excel. These files are essential for the shapefile to function as a complete dataset.
OTHER FILES (12 in total):

*.prj: Provides projection information and the coordinate system. These are supplementary files for additional data.
Remember:

A shapefile can consist of a maximum of 15 files.
Changing a layer in the browser automatically updates related files.
When sharing a layer, ensure to include all associated file formats from the browser.

95
Q

Hierarchal system

A

In GIS, a hierarchical system refers to the organization of geographic data into layers or levels based on their scale or detail:

Base Layers: Provide general features covering large areas.
Intermediate Layers: Offer medium-level detail for specific regions.
Top Layers: Provide the highest level of detail for specific features in smaller areas.
This structure allows for efficient data management and analysis at different scales or levels of specificity in GIS.

96
Q

Root folder

A

In GIS, a root folder refers to the main directory where GIS data, projects, and related files are stored. It serves as the starting point for accessing and managing GIS data and workflows.

97
Q

Relational System

A

In GIS, a relational system refers to a database management approach where data is organized and stored in tables that are related to each other based on common attributes. This model allows for efficient management, querying, and analysis of spatial and attribute data

98
Q

Spatial Joins

A

A function that combines the attributes in two layers based on distance (one feature closest to another) or containment (one feature inside another)

99
Q

Merging Layers

A

Merge’ combines two or more raster layers, such as merging 100 aerial photos into a single layer.
Similarly, ‘Merge vector layers’ combines multiple vector layers of the same type.
Note that ‘Explode lines’ performs the opposite action by breaking apart connected lines into separate entities.

100
Q

Summary Statistics in GIS

A

Summary statistics can be obtained with the “purple E thing” in GIS, similar to summary functions in R. This tool allows users to calculate statistics such as mean, median, sum, minimum, maximum, standard deviation, and count for attribute data associated with geographic features.

GIS (8 decks)

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