GIS Final Review

GIS Fundamentals

• What does GIS stand for?

  • Geographic Information Systems

• Functionality of GIS

  • GIS allows entering and managing attributes and information of drawn features.

  • True/False: GIS will not allow entry and management of attributes:

    • Answer: False

• Characteristics of GIS

  • Associated with other geospatial disciplines (Remote Sensing, GPS)

  • Stores information in databases

  • Computer-based data management

Data Structures

• Cellular Data Structure

  • Raster: A grid of rows and columns for storing images.

  • Vector: A coordinate-based structure for representing geographic features.

• Data Types

  • Spatial Data: Oil & gas facilities on a map are spatial data.

  • Attribute Data: Addresses and specific information about facilities.

Examples and Applications of GIS

• ESRI Plenary Video Examples:

  • Land use patterns

  • Conservation possibilities

  • Real estate patterns

  • Job growth possibilities

• Examples of Spatial Data in GIS:

  • Polygons representing endangered species habitats

  • Health care facilities represented as points

Data vs Information

• Definition Comparison

  • Data put into context does not correctly define information:

    • True/False: Data is information in context:

      • Answer: False

• Attribute Data Insight:

  • Indicates "what" is happening at a location.

  • True/False: Attribute Data is what is happening:

    • Answer: True

Map Scales and Projections

• Map Scale Definitions:

  • A scale of 1:5,000 is a larger scale than a scale of 1:200,000:

    • True/False:

      • Answer: False

• Map Projection Impact:

  • Provides a frame for measuring locations on Earth’s surface.

  • Helps transform 3-dimensional data to 2-dimensional maps.

• Local Datums:

  • Developed for specific geographic areas (like North America):

    • True/False:

      • Answer: True

• Stereographic Projection Usability:

  • Preserves local shape and direction.

Database Management

• DBMS Definition:

  • A system for storing, organizing, retrieving, and manipulating databases.

• Geodatabase:

  • Used for storing and working with spatial data.

• RDBMS Relationships:

  • Components include Primary Key, Foreign Key, and Tables.

• Layer Combination:

  • Combining land parcel and soils layers is feasible.

SQL and Data Structures

• SQL Definition:

  • Structured Query Language.

• Not Spatial Data Representations:

  • Records and Tables are not representations of spatial data.

• Data Quality Fundamentals:

  • Topology ensures data quality and analyzes spatial relationships.

Shapefiles and Digitizing

• Shapefile Definition:

  • A stand-alone group of files outside a geodatabase.

• Elevation Representation:

  • Can be shown through raster or vector data models.

• Manual Digitizing Types:

  • Tablet digitizing and heads-up digitizing.

• Important Concepts in Digitizing:

  • Precision and Accuracy Relationship:

    • Precision is not dependent upon accuracy:

      • True/False:

        • Answer: False

  • Dangling Nodes:

    • Caused by undershooting or overshooting in digitizing.

Data Processing

• Coordinate Transformation:

  • Converts from scanned maps/tablet digitizer to standard map coordinates (Registration).

• Primary Data vs Secondary Data:

  • It is not always better to use secondary data over primary.

• Logical Accuracy Ignorance Scenario:

  • Failure to disclose flood potential information constituted ignoring logical accuracy.

• Cascading Errors:

  • Result from incorrect coordinate systems while overlaying maps.

Spatial Data Types

• Data for Mapping Rivers:

  • The National Hydrography Dataset (NHD) is relevant for mapping rivers.

• Geocoding Location Features:

  • Use the Geographic Names Information System (GNIS) for feature labels.

Geoprocessing and Analysis

• ModelBuilder in ArcGIS Pro:

  • Useful for sequential analysis and repetitive tasks.

• Dissolve Operation:

  • Merges neighboring boundaries with the same attribute value.

• Raster File Characterization Needs:

  • Requires cell size, number of rows/columns, values at each cell, and coordinates of origin.

Data Representation and Analysis

• Cell Value Absence in Raster:

  • Cells without data do not always have a value of zero.

• Choosing Raster vs Vector Model:

  • Prefer raster for multiple calculations among layers.

• Multispectral Sensors:

  • They can have more than 4 bands.

• Interpreting Digital Elevation Models:

  • White represents peaks and black areas represent stream and river bottoms.

Remote Sensing and Image Classification

• Interpolation Definition:

  • Predicts unknown cell values from known data points.

• Zonal Statistics:

  • Considers cell values in groups of similar cells.

• Geocoding Basics:

  • Assigning geographic coordinates to location descriptions.

GPS and Trilateration

• GPS Functions:

  • High orbits maintain survivability; radar stations measure ephemeris.

• Trilateration Purpose:

  • To determine location on Earth’s surface using signals from satellites.

• Trilateration Expansion:

  • Third/fourth satellites confirm precise locations.

Electromagnetic Energy and Remote Sensing

• Interactions of Electromagnetic Energy:

  • Energy can be absorbed, reflected, or transmitted.

• Visible Light Range:

  • Ranges from 0.4 to 0.7 micrometers.

• Active Sensors:

  • Source of energy is not primarily from the sun; this is true for passive sensors.

Image Classification Techniques

• Classification Methods in Remote Sensing:

  • Supervised: Based on training sites defining each class.

  • Unsupervised: Classes determined by algorithms.

Aerial Imagery and Remote Sensing

• Black and White Aerial Imagery Sensors:

  • Utilize panchromatic sensors for visible spectrum.

• Temporal Resolution Importance:

  • Key for monitoring changes in forest cover over time.

• Distance Models:

  • Best for locating nearest protected habitats for endangered species.

ArcGIS Functionalities

• Weighted Overlay Analysis:

  • Can utilize multiple thematic layers for assessment.

• Shapefile Format:

  • Shapefiles are vector file formats.

• Symbology Tool in ArcGIS:

  • Changes the appearance of a layer.

• Layer Addition and Projection Tools:

  • Project Tool: Converts layers to another coordinate system.

  • Define Projection Tool: Establishes known coordinate systems for unknown layers.

Data Analysis Tools

• Interpolation Tool in ArcGIS:

  • Used to generate estimated maps based on known data.

• Adding XY Point Data:

  • In ArcGIS, it converts tables to point features.

• Land Mask Requirement:

  • Necessary to exclude areas in interpolation.

Digitizing and Mapping

• Polygon Feature Creation:

  • Start by creating a new polygon shapefile.

• Digital Layer Modification:

  • Changes to elements such as north arrows can occur in layout view.

• Merge Purpose in ArcGIS:

  • Combine map features or data layers into one feature.

• Additional Analysis Features:

  • Clip Tool used for precise outline cutting of features.

Data Relationships and Statistics

• Attribute Table Statistics:

  • Provides Mean, Sum, Standard Deviation information.

• Data Types in ArcGIS Fields:

  • Includes short int, double, date, BLOB, and float types.

• Ungrouping Layers:

  • Use Multipart to Singlepart tool for layer separation.

Geocoding and Address Matching

• Geocoding Considerations:

  • Field names must match for addresses to be geocoded successfully.

• Locator Tool Usage:

  • The Create Locator tool aids in address and point feature conversion.