GIS exam Flashcards
(77 cards)
1
Q
What is terrain
A
An area of land ground
A particular geographic area
Terrian impacts on the direction of the flow of water, the clarity of the signal received by mobile phones or equipment, the attractiveness of scenery
2
Q
what are some common uses of DEMs?
A
Storage of elevation data for digital topographic maps in national databases
Creation of digital and analog orthophoto maps
Cut and full problems in road design and other civil or military engineering projects
3D displays of landforms for military purposes and for landscape design and planning
Analysis of cross-country visibility
Planning routes of roads, utilities, location of damns
Stat analysis and comparison of different kinds of terrain
Source data for derived maps, such as: aspect, profile curvature, shaded relief insolation, and hydrological and ecological modeling
Background for displaying thematic information or for combing relief data with thematic data such as soils, land use and vegetation
Providing data for simulation models of landscapes and landscape processes
3
Q
what are digital elevation models (AKA DEMS)
A
A digital model of height (elevation or altitude) represented as regulatory or irregular spaced points/lines height values (VECTOR) –> Triangulated irregular Network (TIN) is how it is represented
A model of a physical surface the utilize cells of a grid as elevation through an arbitrary datum (RASTER) –> Elevation Lattice or Altitude matrices are used to represent
It is a representation of the bare earth
4
Q
what are TINS (DEM)
A
-vector way of representing DEMs
-Developed by puecker et all to avoid data redundancy and create a more efficient system for computing slope from contour lines
-Vector polygon structure
-It is built by joining known point values into a series of triangles based on Delauney triangulation
4
Q
what are some Methods of representing DEMs
A
Line data can represent contours and profiles, and critical features such as streams, ridges, shorelines, and breaks in slope
Altitude matrices are regular grid cells which represent elevation above a datum (above sea level) –> RASTER
Triangulated irregular Networks (TINs): connected triangular facets based on Delauney triangulation of irregularly spaced nodes or observation points –> VECTOR
5
Q
what are altitude matrices (DEM) and some disadvan and advantages
A
raster way of representing DEM
Derived from remote sensing or interpolation from a grid of data points that are regularly or irregularly spaced
advantanges
-Good for calculating contours
-Excellent for generating derivative maps
-Easy to use and most available
-Provide fine spatial resolution
ASTER (advanced spaceborne thermal emission and reflection radiometer) global digital elevation model=30m interval
National and local DEMs = <5m resolution
Disadvantages
-Large amount of data redundancy in areas of uniform terrain
-Inability to adapt to areas of differing relief complexity without changing grid size
-Exaggerated emphasis along the axes of the grid for certain kinds of computations such as line-of-sight calculations
6
Q
what are the three sets of record in Delauney triangulation
A
- The node list
-consists of records identifying each node and containing its coordinates, the # of neighbouring nodes, and the start location of the identifiers of these neighbouring nodes in the pointer list - The pointer list
-contain all the essential altitude information and linkages, so they are sufficient for many applications such as slope mapping and hill shading.
(node list does this too) - The triangle list
-For associating other attributes with the triangles, it is necessary to be able to
reference the triangles directly. Using a triangle list to associate each directed edge with the triangle to its right establishes this.
7
Q
What does the Delauney triangulation allow (Diagram?)
A
A variable density and distribution of points to be used which reflects the changes in attribute values within an area
The structure model regards the nodes of the network as the primary units
The topological relations are built into the database by constructing pointers for each node to each of its neighboring nodes
The Neighbour list is sorted clockwise around each node, starting at north
A dummy node on the “reverse side” of the topological sphere onto with the TIN is projected represents the world outside the area modelled by the TIN
This dummy node assists with the describing of topology of the border points and simplify their processing
8
Q
what information can you get from DEM models/what are DEM derivatives
A
Slope (landslide susceptibility)
Aspect (solar insolation, vegetation)
Catchment or dispersal area (Runoff volume, soil drainage)
Flow path (distance of water flow to point)
Profiles
Viewshed (visibility)
8
Q
What are the slope and aspect in DEM
A
Defined as a plane tangent to the surface modelled by the DEM at any given point, and comprises of two components
Gradient/slope: the max change of altitude, measured in degrees; measure of gradient magnitude and influences ex flow velocity
Aspect; the compass direction of this maximum rate of change, measured in compass bearing (N, S); direction of flow, gradient direction
9
Q
What are convexity and concavity in DEM
A
Convexity: rate of change of a slope expressed as a plan convexity and profile convexity
Concavity: negative convexity
10
Q
what curvatures in DEM and what are the types
A
Profile curvature: indicated accelerated flow (convex) and areas with decreasing flow (concave); accelerated/slow flow
Tangential curvature: represents the area of convergent (concave) and divergent (convex) flow; convergent/divergent flow
Using directional filters to estimate slope and aspect
Derivate from the hypsometric curve are usually computed locally for each cell on an altitude matrix form data within a 3x3 cell kernel or “window” that is successfully moved over the map
Simplest finite difference estimates of gradient in the x direction at a point i,j is the maximum downward gradient
11
Q
what is the DEM Zevenbergen and thrones method for calculating slope
A
Shows how these attributes and the concave and convexity are computed from a 6-parameter quadratic equation fitted to the data in the kernel
12
Q
what is the DEM Horns method for calulcating slope in DEM
A
Uses all eight outer points of the window to determine optimal number of factors ?
13
Q
what is view shed
A
everywhere that is visible from a specific point
14
Q
what is - aspect: and trace one path
A
aspect- direction of the steepest downhill slope
trace one path: Follow aspect from cell to cell
15
Q
how can you encode direction in DEM
A
use a DIRECTION GRID
Each cell in the direction grid contains information that indicated to which of the eight neighbours the poath goes next. This information is coded according to the followjing diagram
16
Q
what is D8 algoritum for determining flow direction in DEM
A
Flow direction (FD): “steepest” neighbouring cell recieves flow
Only 8 possible directions
Cells connected together into local drain direction (LDD) netowkrs
Long linear flow lines
basically looks to neighbours and gives the steepest one the flow
17
Q
what is upstream accumulation in DEM when calculating flow direction
A
Each cell is linked to a downstream neighbour in the LDD network
Follow all paths, accumulate cell count downstream
Result: number of cells upstream of the current cell that discharge through cells
18
Q
What are the issues with DMS
A
- PITS !!
All neighbouring cells are higher
No outflow
Interpolation errors
Disrupt drainage topology
:cut through”: expand search and connect across pit
“fill up”: raise pit elevation until level with surroundings
-like a literal pit in a line where stuff gets suck in
19
Q
What are some misc featues of DEM
A
Stream channels: cells with more than N upstream elements
Ridges: cells with only 1 upstream element (itself)
Catchments: all the cells that are upstream contributing elements for a particular output point
Divided by ridge lines
20
Q
what is the wetness index in DEM and some difficulties with it
A
uses upstream accumulation and slope
-made by beven and kirkby
difficulties:
Slope, aspect depend on cell size
Streams are one cell wide
Accumulation done by simple gravity, no inertia
Dispersion, diffusion not modeled well
21
Q
What are sources of geospatial data
A
portals that hold historical data (current to historical)
- Global Geospatial data repositories
- Federal geospatial data repositories
- Provincial geospatial data repositories
- Open-source geospatial data repositories
- Municipal (local) geospatial data repositories
6.Commercial geospatial data repositories - Themes geospatial data repositories
- Remote sensing data repositories
22
Q
what are some GIS hardware considerations
A
In order to conduct and perform high end geospatial analyses you must consider more than just the tools a software offers or how to answer a question using those tools
1.Type of computer (personal, workstation, mainframe)
- CPU (speed, overlay procedures, input/output)
- memory (RAM vs ROM)
- Operating system (single person vs server based)
- Display (raster/vector)
- Input device (digitizing tablet vs screen digitizing)
- Output device (printers, scanners)
- Network environment (LANs)
- Storage (flash drives, clouds etc)
23
what are some Software considerations for GIS
1 Commerical GIS software ex Esri (ArcGIS)
2 Open-source GIS software ex. GRASS
3 Cost
4 Operating system
5 Data capture and data formats
6 Can it handle vector, raster, GPS etc
7 Database management
8 Cartographic output
9 Software support
10. Manuals, online support, Maintenace etc
24
what is GIS programming and two types
GIS software packages give you that flexibility to create and automate your own functions, and processes
1. object oriented programming
Collection of cooperating objects that can receive and process their own data as opposed to the traditional view in which a program is seen as a collection of functions or a list of instructions
2. python
Easy program language that is easy to use, powerful, uses efficient data structures
Uses elegant syntax and dynamic typing
25
Types of GIS application users
1. Pioneering (cutting edge, tackling new problems, high risk)
2. Opportunistic (risk is minimal, adopt tech once reward has be proven, students)
3. Routine (users that wait, common)
26
Types of GIS activity within an organization
1. Operational ex which buildings need repair
2. Management ex distributing courses
3. Strategic ex where to build a firehouse
27
what are some types of GIS softwares
1. Professional
2. Desktop
3. Handheld/remote
4. Component
5. GIS viewers
6.Internet GIS
7. GIS apps
28
GIS software/hardwares must meet the needs of users by appealing to what?
1. Education, awareness and training
2. Adoption of standard (Allows users to learn and accept new innovations )
3.GIS usability (training, design etc)
29
what are the direct costs and benefits of GIS
costs
1. hardware/software
2. data
3.human/administration
4. method for choosing system
benefits
1. savings
2. increased productivity and effectiveness
3. new products
30
what are the indirect costs and benefits of GIS
costs
1. reliance on computers
2. diminished working environment
3. need to get skilled workers
benefits
1. improved information sharing
2. better decision making
3. becoming more competitive
4. motivated workers
5. visualization of data
31
when Implementing a GIS how can you involve users and what are some user issues
involve them by using: User centered approach; users involved from beginning of process
User issues
1. Lack of upper management support
2.Concerns about technology, data conversion
3. Lack of GIS knowledge
4 Political disputes (territoriality)
5. Implementation
32
what are easons 3 reaons for GIS failure
Application and organizational mismatch
Acceptability by users
Non usability
33
what are easons suggestions to rectify GIS failures
User needs surveys
Benchmarking
Piolet studies
34
how can you properly implement GIS application
Direct conversion from old system to new (instant change)
Parallel conversion; both systems are running at the same time (too many resources and new demands)
Phase approach- old functions brough in first, then others follow
Trial and dissemination; piolet system
35
what are some Organizational changes in GIS
Relationships (internal and external)
Political interference
Restructuring within an organization
Policy changes
36
What is data sharing? and why do we do it?
Everyday people, organizations, institutions are collecting and generating vast amounts of geospatial information ex cashier asking for postal code
1. It alleviates cost of generation and collection
2. Enhances maintenance and quality control of the data = data improvements
3. For businesses and governments data is considered a “commodity”
4. Because of the internet and computer networked environments, data dissemination is made easy
37
what are some issues with data sharing
The ease of data dissemination can put into question the ownership of data
Cultural
Organization and legal ramifications when creating a dissemination tool (INCLUDEING metadata, exchange standards and spatial data infrastructure)
38
why is the creation of geospatial metadata is important?
(metadata is the data about your data)
Protects an institutions or organizations data investment
Helps users understand data
Enables discovery
Limits liability
Highlights prudent data stewardship
Reduces workload associated with questions about data
Reduces overall costs in the long term
39
what are types of geospatial (data) standards
1.Content standards
Not easy to share as they involve a lot of decision making and different viewpoints
2. Access standards
international organization for standardization (ISO)
3. Exchange standards
40
what is a Spatial Data Infrastructure and what may it include?
to share data efficiently and effectively, a foundation or infrastructure needs to be created (includes services and facilities, provides a common societal goal)
1. Policies that set the aims and objective
2. Technologies for the implementation
3. Standards for interoperability within and between infrastructures
4. Rules and regulations for the operation of the infrastructure
5. The resources needed to create, maintain and improve the infrastructure
41
The three biggest legal GIS issues are
1. Imposing use restrictions on taxpayers funded data
2. Privacy
3.Liability
42
what can the legal issue of privacy compromise?
1. Personal privacy
ex Data aggregation , Databases – credit card companies, Location- addresses, postal codes Tracking- mobile services, Data surveillance (algorithms)
2. Lack of understanding
When starting to use geospatial data, GIS specialists aren't aware of data restrictions and can be too excited about research and not consider how or if it can be used . Government has imposed data protection laws, Consent in required, Sensitive information cannot be given out
3. Ethical use
Military use (invading countries)
Surveillance (SWAT teams, Patriot Act)
43
What are some types of liability? How is liability regulated in GIS?
types: Contract, Privacy, IP (intellectual property)
GIS liability
- Disclaimers are used
-Location based on accuracy (position on the map to what is on ground)
-Attribute based accuracy
-Resolution
-Currency and completeness of maps
-History of datasets
44
What is the Legal management strategy for GIS liability
Cho highlights a few points to set up a simple risk management framework
Step 1- identify the legal risks
Step 2- quantify these risks
Step 3- develop strategies to reduce, transfer, manage, or accept the identified risks
Step 4- adopt procedures to monitor, audit, and implement training programms for staff to ensure compliance with the risk management strategy
45
What are the three steps in GIS project design
1. Project identification (rich picture (schematic view of problem) OR root definition (two perspective viewpoints))
2. Design and choose a data model (conceptual data model or physical implementation)
3. Design analysis (Cartographic modelling )
46
what are the steps of making conceptual data models (hard system approach) when designing and chooding a data model when making a GIS project
1. Lexical phase (objectives) = define problem (application), define boundaries (study areas), choose entities that revolve around the problem (real world features), establish the states of these entities (attributes)
(Develop rich picture or root definition)
2. Parsing phase = relationships between entities are defined
(Create a list of actions the system must be able to preform)
3. Modelling phase (Identify a list of system inputs and outputs )
4. Analysis phase = validation of the modelling process. Testing to see how well the model stands up to reality
(Group activities, inputs, and outputs into a logical chronological order )
47
what is a conceptual data models (hard system approach) when designing and chooding a data model when making a GIS project
A high-level view that is independent of the computer (hardware) system. So, it captures that main element and aspects of the problem
-has entities (system elements), states (characteristics) , and
48
what is cartograhic modelling
Generic way of expressing and organizing the methods by which spatial variables and operations are selected and used to develop an analysis schema
In geographic data processing methodology that views maps as variables in algebraic expressions, here instead of variable symbols represent numerical attributes of map elements
Numbers assigned to symbols in an equation interact to generate new numbers using mathematical operators
49
what are the four stages of implementing a a cartographic model
1. Identify the map layers or spatial data sets required; Raster/vector data models, satellite image, (mergeable) non-spatial data
2. Use “natural language” to explain process of moving data available to a solution; Express in words the actions that one wishes to perform on the georgical data
3. Draw flowchart
4. Annotate flowchart
50
what are some project management approaches
1. Waterfall approach
2. Prototyping approach
3. GANNT chart
4. PERT chart
51
what is the waterfall approach and what are some problems with it
Linear process for the management, development and implementation of an IT system
So the inputs from the 1st phase informs the secon phase, the outputs from the second phase informs the third
It provides a structured framework for the management of the project
It helps to outline budgets and resources
Approach includes
1.A feasibility study
2.System investigation and analysis
3.System design
4..Implementation, review, and maintenance
5.problems
problems
1. Context of the business which is the system is being developed for is never fully addressed
2. Linear nature of this approach does not allow for change in scope to occur
3. The user is never at the center of this design. It focuses on flow of information rather than understanding why
4. Heretical and technocentric view of system development
52
what is the Prototyping approach and what are some problems with it
It includes the user. Needs are identified by the user
So users have regular and direct involvement in the design of the system
Changes to the system are more fluid and flexible
You can abandon the system if it fails to meet the needs of the users
Time and budget are available, so several prototypes can be built
problems:
1. Difficult to manage = lots of users = lots of ideas and opinions
2. Resource implications ex when to stop
53
what are three problems with implmenting GIS project designs
Data in the wrong format
Lack of GIS knowledge
People always changing their minds
54
5 stages of the risk management plan
Identify the risks
Rate the risks
Establish triggers
Identify mitigating actions
Identify the owner of risk
55
what are the project evaluation tests to see if it meets its goals
Ask each user if they are using the application, is so how, when and why?
Does it make realistic sense?
What changes and modifications needed to be made after the “rich picture” or “root definition” process
56
what are some advanced GIS applications
1. Network based applications (Routing, waterflow)
Remote sensing-basednapplications
(Land change use, Animal tracking)
Hydrologic/climate-based applications ‘
(Groundwater monitoring, Hurricane tracking)
Environmental applications
(Air/water pollution, Erosion risk)
3D applications (Geology/ urban planning)
Health application
Rates of a disease by age, area etc
Crime applications
Business applications
Programming/AI
57
REVIEW: What is GIS?
-an integrated set of hardware, software, data, people, and procedures designed to capture, store, analyze, and present spatial or geographic information
-allows you to visualize spatial relationships and patterns by linking attribute (non-spatial) data to locations on Earth
-supports tasks from simple map making to complex analyses such as network routing, terrain modeling, and environmental assessments.
58
REVIEW: How is data collected for usage in GIS
1. In Situ
ex. field surveys and land surveys
2. Remote Sensing
ex. LiDAR and RADAR
3. Digitizing and Scanning
ex. manual and automated digitizing
4. existing databases and geocoding
ex. data from government or postal codes
59
REVIEW: Why are projections, coordinate systems and datums imperative to any geospatial work?
A. How do these principles work together? How can you recognize each of them
backbone of spatial referencing
Datums: provides the mathematical model (usually an ellipsoid) and reference framework for measuring locations on the Earth. It establishes a “zero” point for elevation and geographic coordinates.
Coordinate system: These systems, like geographic (latitude/longitude) or Cartesian (easting/northing in UTM), provide the numerical framework that assigns specific coordinates to locations. They make it possible to record and express positions in a consistent manner.
Projections:Since the Earth is three-dimensional and curved, map projections are mathematical transformations used to “flatten” the globe onto a two-dimensional surface. Although every projection introduces some distortion (in area, shape, distance, or direction), selecting a projection that minimizes the distortion for your particular purpose is critical.
work together:
The datum defines the shape and reference surface of the Earth. --> noted by year and name
The coordinate system uses this datum to assign numerical positions. --> indicated by units ex degrees for geographic systems, meters/feet for projected
The projection then converts these coordinates from the curved (3D) Earth into a flat (2D) map while trying to preserve specific properties (such as shape, area, or distance). --> directly listed along with distortion characteristic
60
REVIEW: Define and explain the 2 spatial data models and their associated data structures and why they are important for GIS analysis. What are the pros and cons of each?
1. Raster Data Model:
Structure:
Raster data is organized into a grid (or matrix) of cells (pixels), where each cell holds a value representing information (such as elevation, temperature, or land cover).
Pros:
-ideal for continuous data like aerial photography, satellite imagery, or digital elevation models.
-Easily integrated into grid-based analyses such as map algebra, neighborhood operations, and hydrological modeling.
-Straightforward to represent variation in phenomena over space.
Cons:
-Can produce large datasets, especially at high resolutions.
-Data redundancy in areas of uniform attributes.
-The fixed cell size may not optimally capture fine details in areas with complex terrain.
2. Vector Data Model:
Structure:
Vector data represents the world using discrete geometric entities: points, lines, and polygons. For instance, roads (lines), wells (points), and lakes (polygons) are modeled with coordinates that define their shapes.
Pros:
-High precision for discrete objects.
-Efficient representation of boundaries and network connectivity (for instance, in transportation or utility networks).
-Topological relationships can be embedded (e.g., connectivity and adjacency), useful for network analyses.
Cons:
-Managing complex topologies requires strict data integrity rules.
-More complex operations (such as buffering and overlay) can be computationally intensive.
-Not as straightforward as raster for representing continuous phenomena without interpolation.
61
REVIEW: Databases and DBMS, why are they necessary for a GIS
Databases provide the foundation for managing large volumes of both spatial and attribute data. A robust Database Management System (DBMS) supports:
1. Centralized Data Storage: Reducing redundancy and ensuring that data is stored consistently in one place.
2. Efficient Querying and Analysis: Enabling users to run spatial and non-spatial queries that combine various datasets.
3. Multi-user Access and Data Integrity: Allowing multiple users to work concurrently while maintaining data security and consistency.
4. Backup, Recovery, and Administration: Essential features for safeguarding valuable geospatial data.
62
REVIEW: How is chens entity relationship model important in creating a relational database and its attributes
Chen’s model is important because it offers a systematic way to design a relational database:
1. It identifies entities (such as “roads,” “buildings,” or “parcels”) and defines their attributes.
2. It establishes relationships (one-to-one, one-to-many, many-to-many) between these entities.
3. This conceptual schema makes it easier to design databases that can accurately link spatial features with their attribute information. This improves data retrieval, accuracy, and analytical capabilities.
63
REVIEW: How do you get different types of spatial data into a GIS and what quality issues should you be concerned about? Can you fix them? How?
Data Import Methods:
1. Digitizing: Converting paper maps or images into digital vector formats using digitizer tablets.
2. Scanning: Creating raster images from physical documents, then georeferencing these images.
3. Remote Data Acquisition: Downloading data from satellite imagery, airborne sensors, or existing online repositories.
4. Geocoding: Converting textual address data into spatial points.
5. Direct Database Imports: Importing already digital spatial data (shapefiles, geodatabases, etc.) into a GIS.
Quality Issues to Consider:
1. Accuracy and Precision: Errors in measurement (positional error) or in attribute information can affect analysis.
2. Completeness: Missing data or attributes can lead to incomplete analysis.
3. Consistency: Data coming from different sources may use different scales, coordinate systems, or classifications.
4. Temporal Currency: Data might be outdated, which is critical if changes in the environment are rapid.
5. Geometric and Topological Errors: Overlaps, gaps, or misaligned features in spatial data.
Ways to Address Quality Issues:
1. Data Cleaning and Editing: Use GIS tools for error detection, such as visual inspections, duplicate checks, or statistical outlier tests.
2. Reprojection and Transformation: Ensure data uses consistent coordinate systems, datums, and projections.
3. Metadata Documentation: Document data lineage to know how, when, and by whom data was collected and processed.
4. Using Quality Control Procedures: Methods such as double digitizing or employing algorithms to “fill in” missing data can improve data quality.
64
REVIEW: Understand how VARIOUS vector (geoprocessing) and raster (grid based) models work, along with knowing which tools are necessary to generate these models
1. Vector Models:
-Represent data via discrete features (points, lines, polygons).
-Common Tools/Operations:
1.Buffering (creating zones of influence around features).
2.Overlay analysis (combining several vector datasets).
3. Network analysis (determining optimal routes or service areas).
4. Topological editing and validation are critical to maintaining data integrity.
-Software Tools: ArcGIS, QGIS, and other specialized geoprocessing tools provide functionality for these operations.
2. Raster Models:
-Represent data via a continuous matrix of cells (grid cells), each with a numeric value.
-Common Tools/Operations:
1. Map Algebra (applying mathematical operations across cell values).
2. Reclassification (changing cell values based on new criteria).
3. Neighborhood or zonal statistics (calculating local statistics within a moving window or defined zone).
-Software Tools: ArcGIS Spatial Analyst, GRASS GIS, IDRISI, and similar packages are well suited for grid-based analyses
vector operations often rely on geometry and topology tools, whereas raster analysis leverages cell-based calculations and map algebra.
65
REVIEW: Why is data sharing important and how is it done?
Importance of Data Sharing:
1. It reduces the costs associated with data collection because multiple organizations can use the same datasets.
2. Sharing improves data quality over time by promoting standardization and collaborative updates.
3. Enhanced interoperability allows various applications and agencies to integrate and analyze spatial data together, supporting better decision-making.
4. Data sharing often fosters innovation, as open-source initiatives and geoportals enable access to wide-ranging datasets.
How It’s Done:
1. Geoportals and Data Repositories: Web platforms hosted by government agencies, universities, or commercial groups publish spatial metadata and data files.
2. Standards and Protocols: International standards (e.g., ISO, GML) ensure that shared data can be used across different software platforms.
3. Spatial Data Infrastructures (SDI): These frameworks provide the policies, technologies, and standards to enable efficient data sharing on local, regional, or global scales.
The combination of open standards, centralized repositories, and clear metadata ensures that spatial data is readily discoverable and usable by diverse stakeholders.
66
REVIEW: If you wanted to implement a GIS into your workplace, what would you need to think about to make it happen? What impacts would be bringing a GIS have on your organization? What do you need to consider if you are trying to manage a GIS project
Hardware and Software Requirements:
1. Evaluate the level of computing power needed (personal computers vs. workstations vs. servers) based on the complexity and volume of analyses.
2. Choose appropriate GIS software (proprietary solutions like ArcGIS or open-source options such as QGIS and GRASS) that fit your organization’s budget and technical requirements.
3. Plan for peripheral devices (digitizers, high-resolution displays) and reliable network environments for multi-user access.
User Training and Organizational Readiness:
1. Ensure staff receive formal training and ongoing support.
2. Engage potential users early in planning to identify requirements and encourage buy-in.
3. Consider workflow changes and the adoption of new business practices that align with GIS capabilities.
Project Management Considerations:
1. Develop a clear project scope using methods such as rich pictures and root definitions to articulate the purpose and requirements.
2. Use a phased or pilot implementation approach to test and refine the system before full-scale deployment.
3. Conduct cost–benefit analyses to justify the investment and measure return on investment.
Impacts on the Organization:
1. GIS can improve decision-making, operational efficiency, and resource allocation.
2. It fosters better data-driven communication between departments.
3. Integration of GIS might require organizational restructuring or new roles dedicated to spatial data management.
67
REVIEW: If your instructor was to give you an environmental problem to solve, how would you try to figure it out with the theory and the tools you have been exposed to? How much detail should you provide?
1. Problem Definition:
-Clearly outline the problem (e.g., mapping pollution sources, assessing habitat loss, or evaluating watershed dynamics).
-Gather and document the scope and scale, including temporal and spatial extents.
2. Data Collection & Integration:
- Identify necessary datasets (e.g., remote sensing imagery, in situ measurements, existing maps, census data) and ensure they are in or transformed into the proper coordinate system, projection, and datum.
-Use digitizing for hardcopy data, geocoding for address-based records, and direct imports from reliable databases.
3. Analysis & Modeling:
-Choose appropriate spatial data models (vector for discrete sources like factories; raster for continuous data such as elevation or pollutant concentration).
-Utilize vector geoprocessing tools (buffering, overlay, network analysis) to assess relationships and impacts.
-Apply raster analysis (map algebra, reclassification, and zonal statistics) to model continuous phenomena.
4. Interpreting the Results:
-Produce maps, reports, and visualizations that capture the analysis details.
-Include metadata and document assumptions, limitations, and any error correction methods applied.
-Provide sufficient detail so that the methodology can be replicated and stakeholders can assess the reliability of the findings, but remain concise enough to convey the key conclusions and action points
68
based on lab; if asked to where contaminates are highest based on bathymetry and hydraulic what do you do?
1. download spatial data from an online national geoportal website
3. set connections and links to your data folders and spatial datasets
3. add spatial layer into ArcPro and use some of the main tools to navigat and change your map
4. view attribute tables of each layer and calculate basi statistics of specific attribute columns
5. change your map symbols and add labels to your map
create a map layout with important cartographic elements and export it
69
based on lab; if asked to observe projects and identify areas of distortion//how distortion affects visualization and potential analysis what do you do?
- Change the projection view (to see different ones)
-through properties --> coordinate system folder --> projected coordinate systems folder
-use on the fly projections tools in arc pro and tissots indicatrix method to identfy levels of distortion of projections
-compare and contrast suitability of these projections according to your needs
70
based on lab; if asked to convert projection, coordinate system and datums what do you do?
ex. take different layers and merge them into one
-identify the difference between a GCS (geographic coordinate system) and a PCS (projected coordinate system)
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- define and project your shapefiles from a GCS to a PCS
- all layers need to be the same so if one is a unprojected GCS it needs to be given a proper label and datum and then reprojected into UTM
-analysis --> data management toold --> define projection, select the coordinate system of intrest (ex WGS1984) (now it is proper GCS)
- transform datums from one type to another
- data management toolbox --> project --> the output should be in a spatial reference from the projected coordinate system colder (NAD 1983 zone 17)
- use "measure" tool to detemerine distances between geographic entities
- measure distance between points on two different layers, it will show fi there is any discrepancies
- probably a datum issue if so ex make sure the daum is in the same year
-merge shapefiles
- data mangement tool and then merge the layers
71
based on lab; if asked how vector and raster data models are structured and how data quality can be impacted what do you do?
- identify vector data models by their structure and by comparing a coverage to a shapefile and how each deal with topography
- string of coordinate pairs, areas (polygons)
- topology are the geometric relationships that exist between entities located in space
-identify raster data models and their structure by viewing raster vegetation data as raster GRIS and ASCII based formats
-model comprised of a tessellation based on a grid of geometric shaped cells called raster/pixels --> grid of points, lines, area, and surfaces --> the cells have corresponding measurements/descriptions assigned for the entity that falls within them
-view ascii file, change band colours, convert raster <-> vector
-understand the impact vector and raster conversions have on each model type
-conversion tools --> to raster --> feature to raster
-conversion tools --> from raster --> raster to polygon
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based on lab; if asked to digitize a vector polygon layer and construct simplied databased for queries what do you do?
ex. location of infected trees
- development a queryable geospatial tree database by
- adding point- based data from a table based file --> display X, Y data
- joining attributes from other data sources into the main database --> Join and Relates --> Join
- adding/deleting fields for calculation and maintenance purposes --> Field:Add (and edit table)
- performing basic statistics on specific attributes --> Calculate Field tool by right clicking on a column
-perform a geometric transformation using the Georeference tool on a scanned image and rectifying and preparing it for digitization procedures
-Georeference tool --> assign control points to both layers (to transform computer coordinate to UTM easting and northings) --> control point table and input UTM coordinates (RMS < 4)
-use the rectified image as a base for manually digitizing a polygon layer of the riverside areas parks and green zones
-Insert --> create new polygon shapefile in UTM NAD83 Zone 17N with polygons
-highlight all the desired areas in the Table of Contents --> edit --> create and then trace
-add a text based field to put the polygons in
-conduct attribute and location queries using your new tree and parks feature datasets
-select by location and select by attribute tools with SQL syntax in order to find where trees with a specific attribute are
73
based on lab; if asked to find a specific location based on given criteria what do you do?
- extract and export feature information that meets the given criteria
- use the buffer, intersect, erase, and calculate geometry tools to conduct your vector overlay analysis
- for the layers with distance criteria use the analysis tools --> Buffer tool -> the distance should be a value of whatever the limit is with the correct units and dissolve all outputs features into a single feature
-if you need to isolate first ex only expressways then use the select attribute tool, once selected use the buffer tool
-may need to also use select by attribute to isolate a polygon
-can intersect layers ex two different polygons analysis --> tools --> intersect --> this will kinda act as base that gets narrowed down
-narrow down area by using analysis --> tools --> erase and get rid of each previous buffered area from base
-create new filed (area) based on final area attribute table and calculate geometry of the area final site
-use the feature to raster conversions, euclidean distance, reclassify and raster calculator tools to conduct your boolean raster analysis
-use boolean raster analysis (setting up criteria to be a yes or no approach)
-set workplace environment (to ensure same resolution for each layer) geoprocessing --> environments and then set base
-add all the vector layers then analysis --> spatial anaylsis --. distance --> euclidean distance (calculate this for each layer)
-can select out by attribute then calculate euclidean distance if needed
-take the base layer (soil here) --> conversion tools --> to raster --> feature to raster
-reclassify each raster layer based on the given criteria based on yes/no boolean based approach spatial analyst tools --> reclassify and in the reclassification table use 1 and 0 (only one 1)
-construct workflow diagrams outlining each process
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based on lab; if asked to tag location of a specific entity and use density approach to delineate areas what do you do? ex species distribution
- create point density raster models using the Point Density tool in Spatial Analyst
-create points from table --> XY table to points
-Geoprocessing ribbion --> environments -> processing extent
-select out each feature (ie species) of intresest then spatial analyst tools --> point density
- Combine all raster layers using algebraic functionality (addition) through the Raster calculator tool
-spatial analyst --> map algebra --> Raster calculator and multiply each of the layers
75
based on lab; if asked to match addresses to a standardized locator and generate a drivetime what do you do?
- generate a standard address locator table from a street network file for accurately geolocating any address given to you
-set up locator file; add folder connection from catalog pane to a geodatabase and drag streets out of it
-map addresses using the Locate tool in ArcPro
-analysis --> tools --> create locator tool and set country/region parameer and streets as the pirmary table, role should be street addresses
-use locate button to find any addresses
-Import a table of multiple addresses through the geocoding tool and determine the match percentage of each address
-analysis --> tools --> geocode addresses tool and set parameters
-Utilize Network Analyst and its tools to obtain response times from an incident to the nearest station
-in terms of drive time clock network analysis --> closest facility
-import facilities of interest use locate tool to input a incident address
-closest facility layer --> travel settings --> facilities to text box (narrow down to closest within x minutes)also input towards/away facilities
-check direction group to see exact directions
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