Geographic Information Systems Overview

Geographic Information Systems (GIS)

Passing or Failing

• Factors determining success:
  • Attending classes.
  • Punctuality.
  • Paying attention.
  • Submitting assignments on time.
  • Working smart.
  • Consulting with instructors.
  • Asking questions and participating in class.
  • Making a deliberate choice to pass.

Quote for the Semester

• "The capacity to learn is a GIFT; the ability to learn is a SKILL; the willingness to learn is a CHOICE." - Brian Herbert

Introduction to GIS

• Many professionals are becoming interested in learning GIS to better understand their environment.
• Environment refers to the geographic space of a study area and the events that occur there.
• Examples of professions using GIS:
  • Urban planners: studying urban fringe growth and quantifying population growth in suburbs.
  • Biologists: assessing the impact of slash-and-burn practices on amphibian species.
  • Natural hazard analysts: natural hazard risk profiling.
  • Geologic engineers: determining optimal building locations in earthquake-prone areas by analyzing rock formations.
  • Mining engineers: identifying best prospect copper mines based on extent, depth, and ore quality.
  • Geoinformatics engineers: finding best sites for telecommunication relay stations considering land prices and terrain.
  • Programmers: developing algorithms for spatial analysis and studying human behavior using big data (e.g., Twitter, Facebook, WhatsApp).
• All these professionals work with data related to space and positional information.
• Positional data indicates where things are, were, or will be.
• The primary purpose of GIS is to maintain data about geographic space.
• The world is constantly changing, necessitating monitoring of these changes, both natural and man-made.
• Most GIS applications focus on understanding phenomena with geographic, temporal, and spatial-temporal dimensions, considering variations based on location and time.
• GIS can be defined by the stages of working with geographic data:
  • Data preparation and entry.
  • Data analysis: reviewing data to discover patterns.
  • Data presentation: presenting analysis results appropriately.

Definition of GIS

• A computerized system that facilitates data entry, analysis, and presentation, especially when dealing with georeferenced data.
• Functionality includes:
  • Support for various coordinate systems.
  • Methods for computing with georeferenced data.
  • Flexibility in presentation parameters like color scheme, symbol set, and medium.
• Other definitions:
  • A computer system capable of assembling, storing, manipulating, and displaying geographically referenced information.
  • An organized collection of computer hardware, software, geographic data, and personnel for efficient data management.

GIS Description: Primary Roles

• Collection: Gathering data from various sources like remote sensing, terrestrial surveys, and paper maps.
• Storage and management: Administering and tracking data, including integrating various datasets into a common database for efficient digital storage.
• Retrieval: Easy and efficient selection and viewing of data in a variety of ways.
• Conversion: Changing data from one form or map format to another, or converting geographic projections to make data more useful.
• Analysis: Analyzing data to produce insight and new information using data investigation techniques, statistical procedures, and other methodologies.
• Modelling: Simplifying data to understand how things work, explaining data meaning, generalizing data, or providing a simple explanation of reality (e.g., creating a contour map from elevation data).
• Display: Presenting data in various formats like maps, graphs, and reports for easy understanding.

GIS Features

• Users expect to define requirements and interact with the system through a user-friendly interface (icons).
• An information system aims to improve decision-making ability.
• It involves a chain of operations from planning data collection to data storage, analysis, and the use of derived information in decision-making.
• Maps are examples of GIS outputs.

GIS Components

• Six primary components of a GIS:
  • Organization and people
  • Applications
  • Methodology
  • Data
  • Software
  • Hardware

GIS Components Explained

• Organization and people:
  • The most important part of a GIS infrastructure.
  • GIS needs dedicated people and facilities for success.
• Applications:
  • Uses, questions, or “customers” of GIS.
  • The purpose of its production, such as environmental analysis or city planning.
• Methodology:
  • Procedures, techniques, and ways of using GIS data.
  • The problem being addressed determines the approach.
  • It also determines the type of data to be used.
• Data:
  • The heart of GIS operations.
  • Much emphasis is on the data, from input through analysis to presentation.
  • The nature of the data determines the methodology.
• Software:
  • Computer programs needed to run GIS (e.g., ArcGIS, QGIS).
• Hardware:
  • The machinery on which GIS operates, including computers, printers, plotters, and digitizers.

GIS as Multidisciplinary

• Uses data and techniques from many professions and academic disciplines, with applications in diverse fields.
• Adopted by phone companies, banks, advertising firms, emergency services, and many public and private activities.
• A major information and decision-support technology.
• Ideal for dealing with multidisciplinary problems because it integrates data from various sources with different formats.

Are Maps True Representations of Reality?

• Maps can be distorted.
• Example: Countries that fit into Africa.

Map Distortions

• Canada, Russia, the United States, and Europe appear greatly enlarged on some maps.
• Distortion is largest near the poles.
• Greenland appears about the same size as Africa on the Mercator projection, but in reality, it is no bigger than the Democratic Republic of Congo.

Geographic Data and Databases

• GIS uses spatial data as its primary component.
• Spatial data occupies geographic space and has a specific location according to a world referencing system.
• GIS datasets contain spatial data and associated nonspatial data, all termed spatial data.
• Geographic data consists of location, shape, and size as spatial components.
• Descriptions and associated data are the nonspatial attributes.

Geographically Referenced Data

• This differentiates GIS from other information systems.
• Data describes both the locations and characteristics of spatial features.
• These are termed spatial data and attribute data, respectively.
• Spatial data is further categorized into two types: discrete features and continuous features.

Discrete and Continuous Phenomenon

• Two basic measures of the geographic landscape:
  • Discrete data:
    • Distinct features with definite boundaries and identities.
    • Constitute separate entities.
  • Continuous data:
    • Does not have definite borders or distinctive values.
    • Transition from one measure to another is implied.

Examples of Discrete and Continuous Features

• Discrete features:
  • Individually distinguishable features that do not exist between observations.
  • Examples include points (wells), lines (roads), and areas (land use types).
• Continuous features:
  • Features that exist spatially between observations.
  • Examples include elevation, temperature, and precipitation.
  • These features are represented on a map within the GIS environment.

Attribute Data

• Describes the characteristics of spatial features.
• For a land parcel, the attribute data could include:
  • Name of owner
  • Size of land parcel
  • Contacts of owner

Types of Spatial Data

• Three main types of spatial data:
  • Point:
    • A spot (or location) that has no physical or actual spatial dimensions but does have a specific location.
  • Line:
    • One-dimensional feature having only length, no width.
    • Has a beginning and an end.
    • Represents linear features that are either real (roads or streams) or artificial (administrative and property boundaries).
  • Polygon:
    • An enclosed area.
    • A 2D feature with at least three sides.
    • Examples: agricultural fields, land parcels, and political districts.

Data Models

• Vector (Points, Lines, Polygons)
• Raster (Cell, Pixels, Elements)

Vector Data Model

• Points, lines, and polygons.
• More closely resembles the real world.

Advantages of Vector Data Model

• Less data redundancy.
• Discrete features are represented clearly and continuously.
• Topology of spatial features can be more clearly identified.
• Greater precision in computation of spatial properties and processing of map features.

Disadvantages of Vector Data Model

• Complex data structure.
• Expensive technology.
• Analysis is complex.

Raster Data Model

• Areas broken into pixels or cells.
• Each cell contains data.
• Good at representing dense data, such as land cover and elevation.

Advantages of Raster Data Model

• Simple data structure.
• Cheap technology.
• Simple analysis.
• Same grid cell for several attributes.

Disadvantages of Raster Data Model

• Large data volume.
• Inefficient use of computer storage.
• Difficult network analysis.
• Less accurate or attractive maps.
• Loss of information when using large cells.

GIS and the 4 Ms

• Like any other Information System, GIS is associated with 4 Ms based on the key activities involved:
  • Measurement
  • Monitoring
  • Modelling
  • Mapping

Terminologies

• Data: \text{Representations that can be operated upon by a computer}.
• Spatial data: Data that contains positional values.
• Information: \text{Data that has been interpreted by a human being}. Human perception and mental processing leads to information, and hopefully understanding and knowledge.

Applications of GIS

• Applications exist for both man-made structures and the natural environment (e.g., boundaries of natural vegetation and land parcels).
• A second distinction in applications of GIS stems from the overall purposes of use of the system.
• Project-based GIS applications versus institutional GIS applications.
• \text{Priori defined where as the other has no priori defined or is indefinite}

Spatial Data Relationships

• Features on maps relate to one another in different ways.
• Tobler’s first law of geography.
• Some of the relationships are listed below:
  • Distance:
    • \text{Shortest path connecting two points}.
    • Can easily be deduced using a scale.
  • Distribution: Collective location of features; dispersal of features.
  • Density: \text{Number of items per unit area}.
  • Pattern: Consistent arrangement of features.

Proximity Relationships

• Three common proximity / neighborhood characteristics:
  • Connectivity:
    • Considers features that connect or at least touch.
    • Connected features may have some meaningful association.
    • Streams that connect may be part of the same hydrologic system.
    • Stream and road connection could indicate a bridge or drainage pipe.
  • Contiguity:
    • This is another aspect of connectivity.
    • Polygons with shared borders probably have functional relationships proportional to the amount of border that is shared.
  • Adjacency:
    • Nearness or the features that are close to each other.
    • Buffer zones are usually used.

Time and GIS Data

• Time is an important data quality element.
• Can be expressed in terms of data quality, dynamic data and trends.
• Very important in understanding the processes affecting and shaping physical and cultural landscapes.
• Dynamic data: \text{Changing data}.
• The universe is continually evolving.
• Time is an important attribute to consider.
• Trends:
  • Determined by comparison of data over time (temporal trends).
  • Spatial trends: \text{changing shape, size or position over time}.
  • Non-spatial: \text{changing attributes}.

The GIS Database