GIS Fundamental Tasks and Properties

GIS Fundamental Tasks

• GIS processes involve input, manipulation, management, query and analysis, and output (visualization).

Key Properties of Spatial Data

• Projection: Converts 3D Earth to a 2D map; distortion is inherent.
• Scale: Ratio of map distance to ground distance.
• Accuracy: Ensures map data reflects real-world distances.
  • Positional: Closeness of features to their real-world locations
  • Consistency: Match of feature characteristics in the database and real world
  • Completeness: Presence of all real-world features in the database
• Resolution: Smallest recognizable feature on a map, especially for raster data.

Input (Data Entry)

• Data input is encoding data for a database.
• Accurate databases are critical for successful GIS projects.
• Data quality is crucial to GIS project success.
• Data sources include primary (directly collected GIS data) and secondary (analog or digital data).
  • Examples of primary data: Remote sensing images, GPS data, field surveys.
  • Examples of secondary data: Existing digital maps, databases, paper maps.

Manipulation

• Data transformation or manipulation is necessary for compatibility between different data sources and programs.
• Transformation needs may occur due to variations in scale and coordinate systems of data sets.
• Data manipulation types include: projection changes, data aggregation, generalization, and removal of unnecessary data.
• Transformations can be temporary (for display) or permanent (for analysis).

Management (Data Storage)

• A database is a structured collection of data in rows and columns.
• Database management systems (DBMS) help store, organize, and manage data.
• DBMS software supports the creation, storage, manipulation, and retrieval of large datasets.
• Relational database design is common in GIS, storing data in tables with common fields to link tables together.

Geodatabase

• Geographic information can be stored and managed in a geodatabase (GDB), a spatial database
• GDBs allow uniformly storing GIS data in one central location.
• Supports various GIS data types (attributes, features, satellite/aerial images, GPS coordinates).
• GDBs make spatial data models easier to create and ensure accuracy.

Query

• Querying allows answering questions about geographic features and their attributes and their relationships.
• Structured Query Language (SQL) is used to query databases.
• Two main query types:
  • Database queries (select by attribute).
  • Spatial queries (select by location).

Data Querying - Select by Attribute

• SQL query expressions select features that match criteria.
• Query examples use criteria from attribute tables to select features.

Data Querying - Select by Location

• Tool for selecting features based on their location relative to other features.
• Selection options (e.g. intersect, within) let you query features based on location relationships with other features in a layer.

Analysis (Spatial Analysis)

• Allows combining various data sources to solve geographic problems.
• Creates new information by computer processing of geographic data.
• Uses geographic properties to answer questions and identify trends.
• Analysis types include identifying patterns, analyzing suitability, detecting change over time.

Analysis - Vector Analysis (Buffering)

• Answers questions "what's near what?"
• Creates buffer zones by measuring distances from features (points, lines, polygons)
• Accuracy depends on the consistency of measurement units.
• Result: Buffer zone (new feature) represented as a polygon.

Analysis - Vector Analysis (Overlay)

• Combines geometries and attributes of multiple layers.
• Combines characteristics of several datasets into one.
• GIS software facilitates spatial analysis and querying of data across different layers.
• Combines layers to build new maps.
• Accuracy depends on layers and coordinate systems. Creating a new layer.

Analysis - Raster Analysis (Reclassification)

• Reassigns values in a raster dataset.
• Simplifies raster data.
• Easier to interpret as the data values are more manageable.
• Categorizing data values, enabling further analysis.

Analysis - Statistical Analysis

• Extracts additional information about distributed attribute values, spatial trends, or patterns.
• Uses statistical techniques on GIS data to generate information like distributions, means, and trends.
• Identification and confirmation of spatial patterns is a common application.

Output (Visualization)

• GIS outputs include hardcopy maps, statistical summaries, and modelling solutions.
• Output often presented as maps, graphs, and three-dimensional views for effective communication and understanding of the geographic information.
• Provides ways to display map results in different formats to users.
• Provides output in various formats (e.g., multimedia, reports).

Explore the essential tasks and key properties of spatial data in GIS. This quiz covers topics such as data input, accuracy, resolution, and projections, providing a comprehensive understanding of how GIS operates in real-world applications.