GISP Knowledge Condensed – Public

  1. `Conceptual foundations

    1. Knowledge of spatial relationships such as distance+- (e.g., horizontal and vertical), direction, and topology (e.g., adjacency, connectivity, and overlap) that are particularly relevant to geospatial data analysis

1.Distance – how far the object away from the reference object is

2.Euclidean Distance – exact distance between two coordinates sqrt((x1-x2)^2 + (y1+y2)^2))

3.Manhattan Distance – vertical plus horizontal distance – abs(x1-x2) + abs(y1-y2)

4.Internal Direction – where an object is located inside the reference object

5.External Direction – where the object is located outside of the reference object

Topology – see 2J and 4a

  1. Knowledge of standard spatial data models, including the nature of vector, raster, and object-oriented models, in the context of spatial data used in the workplace 

6.Spatial model – Basic properties and process for a set of spatial features

7.Vector – points, lines, polygons

8.Raster – composed of rectangular arrays of regularly spaced square grid cells and each cell has a value (attribute)

9.Pixel – smallest resolvable piece of scanned image – pixel is always a cell but a cell is not always a pixel

10.Geodatabase – object oriented spatial model (feature classes, feature datasets, nonspatial tables, topology, relationship classes, geometric networks)

  1. Understanding of the conceptual foundations on which geographic information systems (GIS) are based, including the problem of representing change over time and the imprecision and uncertainty that characterizes all geographic information 

11.Temporal – the world is constantly changing. A static map can only show one time period at once. Dynamic maps can allow a user to slide between different time periods to show changes. Multiple maps can be created to show the changes or somehow superimpose multiple time period pieces of data on a static map

12. Imprecision – all data is taken from a 3D globe and transferred to a 2D surface through spatial transformations (projections and datums) which causes distortions with the data

13.Uncertainty – The GIS data was created/collected at a certain point of time, may already be out of date

  1. Knowledge of earth geometry and its approximations, including geoids, ellipsoids, and spheres

14.geoid is the shape that the surface of the oceans would take under the influence of Earth's gravitation and rotation alone, in the absence of other influences such as winds and tides – used to reference heights, by registering ocean’s water level at coastal places using tide gauges – this is how the mean sea level is determined

15.reference ellipsoid is a mathematically defined surface that approximates the geoid, the truer figure of the Earth, or other planetary body

16.oblate ellipsoid – fits the geoid to a first order approximation – formed when an ellipse is rotated about its minor axis

17.sphere – As can be seen from the dimensions of the Earth ellipsoid, the semi-major axis a and the semi-minor axis b differ only by a bit more than 21 kilometres

GISP Knowledge Condensed - Public
GISP Knowledge Condensed – Public
GISP Knowledge Condensed - Public
GISP Knowledge Condensed – Public

First (direct) geodetic problem – Given a point (in terms of its coordinates) and the direction (azimuth) and distance from that point to a second point, determine (the coordinates of) that second point.

Second (inverse) geodetic problem – Given two points, determine the azimuth and length of the line (straight line, arc or geodesic) that connects them.

  1. Knowledge of georeferencing systems, including coordinate systems, spatial projections, and horizontal and vertical datums

18. spatial reference system (SRS) or coordinate reference system (CRS) is a coordinate-based local, regional or global system used to locate geographical entities

19. International Terrestrial Reference System (ITRS). It is a three-dimensional coordinate system with a well-defined origin (the centre of mass of the Earth) and three orthogonal coordinate axes (X,Y,Z)

20. map projection – transforming coordinates from a curved earth to a flat map

UTM – Universal Transverse Mercator – a global coordinate system – UTM zones are 6 degrees

21. horizontal datum  – model of the earth as a spheroid (2 components, reference ellipsoid and a set of survey points both the shape of the spheroid and its position relative to the earth)

22. vertical datum – reference point for elevations of surfaces and features on the Earth – could be based on tidal, seas levels, gravimetric, based on a geoid

23. NAVD88 – gravity based geodetic datum in North America

24. geodetic datum – set of control points whose geometric relationships are known, either through measurement or calculation

25. WGS 84 – World Geodetic System – reference coordinate system used by the Global Positioning System (GPS)

26.SRID integer – spatial reference system id numbers, including EPSG codes defined by the International Association of Oil and Gas Producers

4 distortions – Distance – Direction – Shape – Area

27.Mercator Projection – Preserves shape and direction, area gets distorted – projecting earth onto a cylinder tangent to a meridian

28.Azimuthal Equidistant – planar (tangent) – used for air route distances – distances measured from the center are true – distortion of other properties increases away from the center point

29.Cylindrical equal-area projections – preserves area, shape and distance gets distorted near the upper and lower regions of the map – straight meridians and parallels – meridians are equally spaced and the parallels are unequally spaced

30.Conic projections – preserves directions and areas in limited areas – distorts distances and scale except along standard parallels – generated by projecting a spherical surface onto a cone

Choosing a projection:

– 31.Latitude: Low-latitude areas (near equator) use a conical projection; Polar regions use a azimuthal planar projection 

– 32.Extent: Broad in East-West (e.g., the US) use a conical projection; Broad in North-South (e.g., Africa) use a transverse-case cylindrical projection 

– 33.Thematic: If you are doing an analysis that compares different values in different locations, typically an equal-area projection will be used

  1. Cartography and Visualization

    1. Knowledge of contour mapping

34.contour line – (aka isoline, isopleth, or isarithm) a function of two variables is a curve along which the function has a constant value – joins points of equal value on a line

35.contour interval – difference in elevation between successive contour lines

  1. Knowledge of basic physical geography (e.g., types of boundaries, continents, landforms, and topography)

36. Physical geography – branch of natural science which deals with the study of processes and patterns in the natural environment like the atmosphere, hydrosphere,biosphere, and geosphere

37.divergent plate boundaries – boundaries where plate move away from each other

38.transform boundaries – one plate slides horizontally past another plate

39.convergent boundaries – two plates move toward each other

40.Continents are understood to be large, continuous, discrete masses of land, ideally separated by expanses of water – physical geography may include islands on the shelf because they are structurally part of the continent

41.landform – a natural feature of the Earth's surface (hills, mountains, plateaus, canyons, valleys, bays, peninsulas, and seas)

42.Topography is a field of geoscience and planetary science comprising the study of surface shape and features of the Earth and other observable astronomical objects including planets, moons, and asteroids

  1. Understanding of how data collection methods influence map design and representation

43.Primary data – collected specifically for the purpose of a researcher’s particular study

44.Secondary data – collected for another purpose by someone other than the researcher

5 types of measurement – physical measurement, observation of behavior, archives, explicit reports, computational modeling

45.Physical Measurement – recording physical properties of the earth or its inhabitants – size, number, temperature, chemical makeup, moisture, etc.

46.Observation of behavior – observable actions or activities of individuals or groups – not thoughts, feelings or motivations

47.Archives – records that have been collected primarily for non-research purposes (secondary)

48.Explicit reports – beliefs people express about things – surveys

49.Computational Modeling – models as simplified representations of portions of reality

50. Quantitative data – numerical values, measured on at least an ordinal level but could be on a metric level

51.Qualitative data – nonnumerical or numerical (nominal) values that have no quantitative meaning

52. Deceptive mapping – maps can be distorted for propaganda, military protection, ignorance

  1. Knowledge of graphic representation techniques, including thematic mapping, multivariate displays, and web mapping

53.thematic map is a type of map especially designed to show a particular theme connected with a specific geographic area

54.Choropleth – areas are shaded according to prearranged key, each shading or color type represents a range of values

55.Proportional Symbol – symbol drawn proportional in size to the size of the variable being represented

56.Isarithmic or Isopleth – lines of equal value are drawn (contour lines) or ranges of similar values are filled with similar colors or patterns

57.Dot – shows distribution of phenomena where values and locations are known – place a dot where the location of variable is

58.Dasymetric – alternative to choropleth – ancillary information is used to model internal distribution of the phenomenon 

59.Multivariate displays putting more than two sets of data on one map (i.e. single map shows population density and annual rainfall and cancer rates)

60.web mapping – process of using maps delivered by GIS – web maps are both served and consumed

  1. Knowledge of principles of map design, including symbolization, color use, and typography, for a variety of print and digital formats layout elements – a title, map, legend, map scale, supporting media, north arrow, metadata (sources, currency of information, projection, copyright, authorship)

62.symbols – represent things on a map accuracy – difficult to assess, all maps show a selective view of reality – instead should ask if the map is appropriate for my purposes scale – 1:100 – one inch represents 100 inches in the real world

Large scale (more zoomed in) shows more detail than small scale (more zoomed out)

65.Symbolization variables – size, shape, orientation, pattern, hue, value

66.Quantitative – size and value

67.Qualitative – shape, pattern, hue

GISP Knowledge Condensed - Public
GISP Knowledge Condensed – Public

68.typography – the design of text, point size, line length, typefaces

  1. Understanding of how the selection of data classification and/or symbolization techniques affects the message of the thematic map

69.Classification – objects with similar symbols – up to 7 classes recommended but should stick to 5 – classes should be exhaustive (describe all possible values) and should not overlap (no value can fall into two classes)

70.Equal range – equal distance between class breaks

71.Quantiles – equal number of observations in each class

72.Standard deviation – class breaks based on distance of standard deviation from the mean.

73.Natural breaks – class breaks conform to gaps in data distribution.

  1. GIS Design Aspects and Data Modeling

3 data models

74.Conceptual model – describes spatial objects as well as logical and topological relationships between spatial objects and the captured spatial entities

75.Data Structure Model – expresses the spatial objects of the conceptual model in terms of transfer data structures – based on traditional relational and network models – data structures viewed as spatial data structures are both vector and raster models

76.Transfer Model – express the logical constructs of the transfer form in terms of implementation-media constructs.

  1. Knowledge of data exchange procedures

transfer constructs (based on data models): (1) logical constructs solely pertaining to this standard, (2) constructs relating to the implementation method, and (3) constructs solely pertaining to the transfer media.

77.File based transfer – data is in a structured file format.

78.Application Programming Interface (API) – data is accessed and exchanged as needed between software systems

79.Web services – data is accessed and exchanged over networks and the internet between software components, using http and other web based protocols.

  1. Knowledge of security restrictions on data (e.g., user permissions and access rights)

80.Data owner – user who creates tables, feature classes owns those datasets.

81.User access – database must verify the user accounts that connect to it.

82.Authentication – database checks the list of users to make sure a user is allowed to make a connection – Operating System (OS) authentication or Database Authentication

83.Groups – grant users based on their common functions.

84.Public role – right granted to anyone connected to database

  1. Knowledge of database administration

Basic tasks

85.Backup and recover databases – test backup and recovery plan, ensure backups done on schedule

86.Database security – prevent hackers, security models, tasks – authentication, authorization, auditing (making sure the right people have the right access)

87.Storage and capacity planning – disk storage is needed and monitor disk space and watch growth trends

88.Performance monitoring and tuning – identify bottlenecks, tuning (indexing, queries on speed of return, right monitoring tools, capacity of server hardware)

89.Troubleshooting – quickly ascertain problem and correct it

90.Other – High availability and ETL functions – Data extraction, transformation, and loading

  1. Knowledge of systems architecture and design

91.Requirements Phase – user needs assessment and workflow loads analysis (baseline and peak traffic)

92.Design Phase – Infrastructure requirements, network communication capacity, hardware and software procurement, software development and data acquisition must be identified

93.Construction Phase – system procurement, data acquisition and database design, authorization for application design and development, prototype testing

94.Implementation Phase – Initial deployment and operational testing, final system delivery, user training, system maintenance operations

95.Capacity Planning Tool (CPT) – developed as a framework to promote successful GIS system design and implementation

  1. Understanding of the enterprise environment

96.Enterprise GIS Environment – broad spectrum of technology integration of enterprise technologies connected by local area networks, wide area networks, internet communications

97.Enterprise technologies – database servers, storage area networks, windows terminal servers, web servers, map servers, desktop clients

GISP Knowledge Condensed - Public
GISP Knowledge Condensed – Public

  1. Knowledge of schemas and domains and how they interact

98.schema – structure or design of the database or database object (table, view, index, stored procedure, trigger) – defines the tables, fields in each table, relationships between fields – a schema will include information on which fields have domains and what those domains are

99. data dictionary – catalog or table containing information about the datasets stored in a database

100. domain – the range of values for a particular metadata element

101.attribute domain – enforces data integrity, identify what values are allowed in a field in a feature class

102.coded value domain – attribute domain that defines a set of permissible values for an attribute in a geodatabase – it has a code and its equivalent value

103.range domain – type of attribute domain that defines the range of permissible values for a numeric attribute

104.spatial domain – allowable range for x,y coordinates and for m, z values

  1. Knowledge of digital file management

File creation, edit, management, back up data, keep track of files, organize files

105. Individual files – shapefiles, file gdb, personal gdb, tables, spreadsheets, CAD, rasters

106. Databases – direct connection to relational database management systems and big data databases – manage tables and feature classes in database

107. Geodatabase – stores GIS in central location for easy access

108. Cloud – store files in the cloud to be accessible anywhere

Editing data can be multi or single user editing

109. Control of big data – visualize multiple different types

110.Integrate enterprise – data stored in big business systems to extend their analytical capabilities

111.Data rules and relationships – define relationships between datasets and set rules (domains and subtypes)

112. Manage metadata – describes content, quality, origin, and other characteristics of data

113.Secures data – flexibility and control over how GIS platform is deployed, maintained, secured, and used

114.Versioning – allows multiple editors to edit one database by creating “duplicates” of the base data – changes are recorded with addition and deletion tables – versions can be created or deleted – edits are isolated in that version until admin merges changes – edits can be posted to parent version – DEFAULT is the root version

  1. Knowledge of database design

115.Database design – process of producing a detailed data model of a database

Design process – 

116.Conceptual schema – Determine where relationships and dependency is within the data.

117.Logical Data Model – Arrange data in a logical structure that can be mapped into the storage objects supported by the database management system

118.Physical database design – Physical configuration of the database on the storage media – detailed specification of data elements, data types, indexing options, and other parameters residing in the DBMS data dictionary – modules, hardware, software

  1. Knowledge of database general structure (e.g., tables and data)

119.Tables – collection of related data held in structured format within a database, contains fields and rows

120.Views – result set of a stored query on the data – users can query – virtual table computed dynamically from data when the view is accessed

121.Sequences – ordered collection of objects in which repetitions are allowed (finite or infinite) number of elements is the length of the sequence

122.Synonyms – Alias or alternate name for a table, view, sequence or other object

123.Indexes – data structure that improves the speed of data retrieval operations in a database table – causes more storage space and additional writes – quickly locate data in the database – indexes can be on multiple columns


Database Links

124.Snapshot – state of a system at a particular point in time – can be a backup

125.Procedure – subroutine available to applications that access a relational database system (data validation, access control mechanisms)

126.Trigger – procedural code automatically executed in response to certain events on a particular table or view in a database

127.Functions (subroutine) – sequence of program instructions that perform a specific task

128.Package – built from source with one of the available package management systems

129.Non-schema objects – users, roles, contexts, directory objects

  1. Knowledge of geospatial data structure (e.g., topology rules)

130.Equals – a = b – topologically equal

131.Disjoint ab = ? – no point in common

132.Intersects – ab ≠ ? – some common interior points

133.Touches – (a ∩ b ≠ ?) ∧ (aο ∩ bο = ?) – a touches b, at least one boundary point in common but no interior points

134.Contains – a ∩ b = b – feature b is within a

135.Covers – aο ∩ b = b – every point of b is a poiTnt of a

136.Covered By – Covers(b,a) – every point of a is a point of b

137.Within – a ∩ b = a – a is within b

138.Crosses – a crosses b at some point

139.Overlaps – a and b have common interior points

GISP Knowledge Condensed - Public
GISP Knowledge Condensed – Public

  1. Understanding of desktop, server, enterprise, and hosted (e.g., cloud) applications available, including their benefits and shortcomings

140.Desktop – individual user on a computer, make maps, data analysis, data creation

141.Server – bring GIS into the hands of everyone in organization, allows access to web GIS, control of GIS data on your own infrastructure, control over how GIS platform is deployed, maintained, secured and used

142.Hosted (cloud) – ability to discover, use, make, and share maps with any device anywhere, anytime – access other users maps and data – connect more people outside of the organization and share the latest maps, data, and ideas

143.Enterprise GIS – integrated through entire organization so that a large number of users can manage, share, and use spatial data and related information to address a variety of needs, including data creation, modification, visualization, analysis, dissemination

Enterprise GIS can utilize both hosted (cloud) and server but if organizational data is not stored in the cloud, only data is accessed from the cloud, then it’s not quite an enterprise system

  1. Working knowledge of GIS hardware and software capabilities (e.g., application servers, data servers, storage devices, and workstations)

Software runs on a variety of hardware types – centralized servers to desktop computers

Software may rely on DBMS type, OS type

144.System infrastructure – hardware, software, and communication network – required information products and spatial and non spatial data resources – essential spatial analysis, display, and reporting functions, needed data management resources, anticipated number of end users within the department

  1. Knowledge of data models, including vector, raster, grid, TIN, topological, hierarchical, network, and object-oriented

145.Vector – coordinate based data model that represents points, lines, polygons – point represented by a coordinate pair, lines and polygons have an ordered list of vertices – attributes associated with each feature

146.Raster – defines space as an array of equally sized cells in rows and columns – single or multiple bands – each cell has 1 attribute value – raster coordinates are stored by ordering the matrix

147.Grid – parallel and perpendicular lines for reference as a map projection or coordinate system

148.TIN – Triangulated Irregular Network – portions vector data into contiguous, nonoverlapping triangles – create Delaunay triangles

149.Advantages of TIN – small areas with high precision elevation data – more efficient storage than DEM or contour lines

150.Disadvantage of TIN – requires very accurate data source and costs are expensive, TIN production and use are very computer intensive)

151.Topological – features need to be connected using specific rules

152.Hierarchical – database that stores related information in a tree-like structure – records can be traced to parent records to a root record

153.Network – collection of topologically connected network elements (edges, junctions, turns) – each element is associated with a collection of network attributes

154.Object Oriented – data management structure stores data as objects (classes) instead of rows and tables as a relational database

  1. GIS Analytical Methods

    1. Knowledge of overlay analysis

155.Overlay analysis – Define problem – Break problem into submodels – Determine significant layers (some of these layers may need to be created) – Reclassify or transform data within a layer

156.Spatial overlay – process of superimposing layers of geographic data that cover the same area to study the relationship between them

157.Overlay – two or more maps or layers are superimposed for showing relationships between features

Vector Overlay Tools

158.Identity Input features, split by overlay features

159.Intersect Only features common to all input layers

160.Symmetrical Difference Features common to either input layer or overlay, layer but not both

161.Union All input features

162.Update Input feature geometry replaced by update layer

Raster Overlay Tools

163.Zonal Statistics – Summarizes values in a raster layer by zones (categories) in another layer—for example, calculate the mean elevation for each vegetation category

164.Combine – Assigns a value to each cell in the output layer based on unique combinations of values from several input layers.

165.Single Output Map Algebra – Lets you combine multiple raster layers using an expression you enter—for example, you can add several ranked layers to create an overall ranking

166.Weighted Overlay – Automates the raster overlay process and lets you assign weights to each layer before adding (you can also specify equal influence to create an unweighted overlay)

167.Weighted Sum – Overlays several rasters multiplying each by their given weight and summing them together.

  1. Functional knowledge of planar geometry (e.g., points, lines, and polygons) required to convert real world examples into spatial concepts

168.plane – flat, 2 dimensional surface

169.point – single coordinate pair

170.lines – ordered lists of coordinate pairs

171.polygons – ordered lists of coordinate pairs that reconnect

I think this question will ask “you have a river, what is the best geometry representation of a river”

  1. Knowledge of algebra (e.g., deriving values from a basic formula)


  1. Knowledge of statistics (e.g., descriptives, summary statistics, and R-squared) 

172.Descriptive statistics – discipline of quantitatively describing the main features of a collection of information – Summarizes a sample to learn about the population

173.Summary statistics – used to summarize a set of observations

174.Coefficient of determination – R squared – number that indicates how well data fit a statistical model – fit to a line or curve – a 1 indicates the line fits perfectly with the data – 0 indicates the line does not fit at all (data is random)

  1. Knowledge of basic programming (e.g., scripting, object oriented, query, and extensible)

175.Object oriented programming (OOP) – programming paradigm based on concept of “objects” which are data structures that contain data in the form of fields (aka attributes) and code in the form of procedures (aka methods) – most common are class based

176.Extensibility – system design principle where the implementation takes future growth into consideration – level of effort to extend the system and implement the extension

  1. Knowledge of raster/vector principles

177.vector – a coordinate based data model that represents features such as points, lines, polygons

178.raster – defines space as an array of equally sized cells arranged in rows and columns, single or multiple bands – each cell contains an attribute value

179.Vector Advantages – represent point, line, area very accurately; more efficient than raster in storage; supports topology; interactive retrieval; enables map generalization

180.Vector Disadvantages – less intuitively understood; multiple vectors overlay is computationally intensive; display and plotting vectors can be expensive

181.Raster Advantages– easy to understand; good to represent surfaces; easy to input and output; easy to draw on a screen; analytical operations are easier

182.Raster Disadvantages – inefficient for storage; compression techniques not efficient with variable data; large cells causes information loss; poor at representing points, lines, areas; each cell can be owned by only one feature; must include redundant or missing data

  1. Knowledge of scales (e.g., visual, verbal, relative, absolute, physical, and display vs. data)

183.Verbal scale – expresses in words a relationship between a map distance and ground distance: one inch represents 16 miles

184.Visual scale – graphic scale or bar scale

185.Representative scale – representative fraction or ratio scale 1:24,000 – 1” = 24,000”

186.Absolute scale – system of measurement that begins at a minimum or zero point and progresses in only one direction

187.Relative scale (arbitrary) – begins at some point selected by a person and can progress in both directions

Physical scale – ?

188.Display vs Data – The data is built at a certain scale/accuracy but once the data is displayed in any other format that the one it was made for, the scale gets warped. Ex: a map made as 9”x10” that is then scaled down and printed in a newspaper.

  1. Knowledge of units of measurement (e.g., conversion and angular vs. metric)

189.1 mi – 5280 ft

190.1 ft = .3048 m

191.1 mi = 1.6093 km

192.1 international nautical mile = 2025.4 yd = 6076.12 ft

193.90° in a right angle, 194.60 minutes of arc in one degree, 195.60 seconds of arc in a minute

196.Radians – 360° is a whole circle – 2pi x radius is the circle

197.Bearings – angle less than 90° within a quadrant defined by the cardinal directions

198.Azimuth – angle between 0° and 360° measured clockwise from north

GISP Knowledge Condensed - Public
GISP Knowledge Condensed – Public

  1. Data Manipulation

    1. Knowledge of selection queries (e.g., attribute, spatial, and location)

199.Attribute – New Selection, Add to Selection, Remove from Selection, Subset Selection, Switch Selection, Clear Selection



Within a distance

200.Contains – features contain an input polygon (input polygon is selected)

201.Completely contains – features must be completely in an input polygon (input polygon selected)

202.Contains Clementini – features must be completely in the input polygon but if it’s on the boundary, it will not be selected

203.Within – features will be selected if inside a selecting polygon

204.Completely within – features will be selected if completely within selecting polygon – no overlap

205.Within Clementini – features will be selected and cannot be entirely on the boundary of the features

206.Are Identical To – features are identical to input layer

207.Boundary Touches – features will be selected if they have a boundary that touches a selecting features – must be completely inside or outside the polygon

208.Share a Line Segment With – features selected if they share a line segment

209.Crossed by the Outline of – Input features will be selected if they are crossed by the outline of a selecting feature

210.Have their Center In – Features will be selected if their center falls within a selecting feature

Catined by – Same as within

  1. Knowledge of different data types (e.g., SHP, GDB, Coverage, DGN, TXT, and IMG) and formats (spatial, rendered, and tabular)

SHP – shapefile

.shp – shape format – feature geometry itself

.shx – shape index format – positional index of the feature geometry to allow seeking forwards and backwards quickly

.dbf – attribute information

.prj – projection format

.sbn & .sbx – spatial index

.shp.xml – geospatial metadata in XML format

GDB – geodatabase

.gdb – file geodatabase

.mdb – personal geodatabase based on microsoft access

coverage file – point, arc, node, route, route system, section, polygon, and region

DGN – AutoCAD and MicroStation

Txt – Text

IMG – Image

LiDAR – remote sensing technology that measures distance by illuminating a target with a laser and analyzing the reflected light

Raster – .jpg, .tif, .gif

Rendered file formats are raster formats

More info 5e

  1. Knowledge of different field types

Short integer – between -32768 and 32768

Long integer – between -2,147,483,648 and 2147483647

Float (single-precision floating-point numbers)

Double (double-precision floating-point numbers)

Text – could be a coded value – assign to an integer through a domain


BLOBs – data stored as a long sequence of binary numbers – ArcGIS stores annotation and dimensions as BLOBs – images, multimedia, bits of code

Object Identifiers – Unique IDs and FIDs

Global Identifiers – Global ID and GUID – data types store registry style strings consisting of 36 characters enclosed in curly brackets

Raster field types – raster can be stored within the geodatabase

Geometry – point, line, polygon, multipoint, multipatch

  1. Knowledge of data relationships (e.g., one to one and many to many)

1-1 – each object of the origin table can be related to 0 or 1 object of the destination table

1-Many – each object in the origin table can be related to the multiple objects in the destination table

Many-Many – multiple objects of the origin table can be related to multiple objects of the destination table

  1. Knowledge of data collection, transfer, and format conversion (e.g., export formats, properties, and settings)

Primary source – collected in digital format specifically for use in a GIS project

Secondary source – data captured for another project but reused for this project

Data Transfer Standards

Transfer – follow Spatial Data Transfer Standard (SDTS) – Federal Information Processing Standard (173)- robust way of transferring GIS data between computers with no information loss, including metadata

Industry Standards – typically don’t exchange topology, only graphic info; large number of format translators

Open GIS Consortium (OGC) – non profit, international, voluntary consensus standards organization – created GML or Geography Markup Language – XML based encoding standard

Vector Formats

PostScript – page definition language to export or print a map

Digital Exchange Format (DXF) – AutoCAD – no topology but lots of details

Digital Line Graph (DLG) – distributed by the government and most GIS packages will import but extra manipulation needed

TIGER – block level maps of every village, town, and city in US

Shapefile – vector data format stores location, shape, and attributes

Scalable Vector Graphics (SVG) – extension of the XML language

ArcInfo Coverage – stores set of thematically associated data considered to be a unit

ArcInfo Interchange File (.e00) – known as ArcGIS export file

Geodatabase – object oriented data model represents features and attributes as objects

Raster Format

Standard – rows and columns with a header information

Tagged Image File Formats (TIFF) – associated with scanners

GEO-TIFF – puts latitude/longitude at edges of pixels

Graphic Interchange Format (GIF) – image files for sharp edges and few gradations of color

Joint Photographic Experts Group (JPEG) – variable-resolution compression system with both partial and full resolution recovery

Digital Elevation Model (DEM) – 30 meter elevation data 1:24000 7.5 minute quadrangle maps or 1:250,000 3 arc second digital terrain data

Band Interleaved by Pixel (BIP) or Band Interleaved by Line (BIL) – good at storing different brightness levels

RS Landsat – satellite imagery and BIL information are combined

Raster to Vector is not difficult based on pixel value

Vector to Raster is very difficult because pixels may distort the lines or exact point locations and would need to be re-digitized

  1. Knowledge of data quality, including geometric accuracy, thematic accuracy, resolution, precision, and fitness for use

  1. Geospatial Data

    1. Knowledge of metadata and its standards (e.g., ISO and FGDC)

metadata – information that describes the content, quality, condition, origin and other characteristics of data or other pieces of information

Federal Geographic Data Committee (FGDC) – who, what, when, where, why and how – include title, abstract and date, geographic extent and projection info, attribute label definitions and domain values

Content Standard for Digital Geospatial Metadata (CSDGM)

ISO 19115 – developed for documenting vector and point data and geospatial services (web-mapping, data catalogs, and data modeling applications)

ISO 19115-2 – adds elements to describe imagery and gridded data as well as data collected using instruments (monitoring stations and measurement devices)

  1. Understanding of the difference between quality control and quality assurance in the context of a given geospatial project

Quality Assurance – process oriented and focuses on defect prevention

-Establishment of good quality management system and assessment of its adequacy – periodic audits – managerial tool

Quality Control – product oriented and focuses on defect identification

-Finding and eliminating sources of quality problems through tools and equipment – corrective tool

  1. Knowledge of data archiving and retrieval

Archiving – captures, manages, and analyzes data changes – most often done with gdbs

Retrieval – similar to a back up

  1. Knowledge of the differences among a join, merge, a union, a clip, and an intersect

Join – combine two attribute tables into one using a common key between tables

Merge – Combines multiple input datasets of the same data type into a single new output

Append – Combines datasets of same data type into an existing dataset

Union – Combines input features with another feature dataset

Clip – Extracts input features that overlay the clip features (keeps inputs attributes)

Intersect – Extracts features which overlap in all layers to new feature class (joins attribute tables)

  1. Knowledge of basic geomatics

Geomatics – science and technology of gathering, analyzing, interpreting, distributing, and using geographic information (includes surveying, mapping, remote sensing, GIS, GPS)

  1. Knowledge of basic field data collection 

Field Data collection

Planning, preparation, digitizing and transfer, editing and improvement, evaluation

Remote Sensing – 3 resolutions – spatial, spectral (electromagnetic spectrum measured), temporal (repeat cycle)

Ground survey – expensive and time consuming

GPS – 24 satellites – orbit earth twice a day – revolution every 12 hours – altitude of about 12,000 miles – started by us department of defense in the 1970’s for military 

Space segment – NAVigation Satellite Timing and Ranging (NAVSTAR) constellation – GPS satellites which transmit signals on two phase modulated frequencies – transmit a navigation message that contains orbital data for computing the positions of all satellites

Standard Positioning Service – signal broadcast for civilian use

Horizontal location – 3 satellites are required

Vertical position – min 4 satellites are required

Calculate distance by measuring the time interval between the transmission and reception of a satellite signal

Trilateration – used to determine position of the GPS receiver

-Accuracy dependent on type of GPS receiver, field techniques, post processing of data, error from various sources

3 types of GPS receivers – Recreational Grade, Mapping Grade, Survey or High Accuracy Grade

GPS errors

-Multipath – errors caused by reflected GPS signals arriving at the GPS receiver – nearby structures and other reflective surfaces

-Atmosphere – GPS signals can experience delays when traveling through the atmosphere – Common atmospheric conditions can affect GPS signals such as tropospheric delays and ionospheric delays

-Distance from Base Station – differential correction will increase the quality of the data, accuracy is degraded slightly as the distance from the base station increases

-Selective Availability – intentional degradation of the GPS signals by the department of defense (DOD) to limit accuracy for non-U.S. military and government users – currently turned off, but can turn it back on whenever

Noise – error is the distortion of the satellite signal prior to reaching the GPS receiver and or additional signal piggy backing onto the GPS satellite signal

PDOP – Position Dilution of Precision – collect data when there is an optimum satellite availability (four or more) and when satellites are in an appropriate configuration to produce an acceptable (lower) PDOP value – higher PDOP values are bad – 

PDOP values – set to 6 or less. Higher levels will be less reliable data

Signal to Noise Ratio (SNR) mask – set the value of the SNR mask higher to help minimize noise error – user manufacturer recommendations

Elevation Mask – set it to 15 degrees – default angle to minimize the amount of atmosphere through which the satellite signal has to travel

Data Collection Rate (sync rate) – recommended to collect point data at 1-second interval – collect polygon and line data at a 5 second interval – collect point data at the same data collection interval as the base station

Datum – GPS receivers are designed to collect GPS positions relative to the WGS84 datum – can designate what datum to be used

GPS coordinates

Latitude/Longitude – Degrees/Minutes/Seconds (DMS) 43o 5’ 20”

Latitude/Longitude – Decimal Degrees (DD) 43.088889o

Latitude/Longitude – Degrees and decimal minutes – 43o 5.33333’

UTM 18 – (4740283N, 434057E)

State Plane – US feet – (312608N, 313525E)

US National Grid – (18T WN 7125315437)

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