Spatial Data Models Overview

Spatial Data Models

• Spatial data models represent objects in a spatial database and their relationships
• They provide formal methods for representing and manipulating spatially referenced information

Vector Data Models

• Vector data models represent real-world features as points, lines, and polygons
• Vertices define the points of lines and the corners of polygons
• Examples of Vector data models include: points (e.g., locations of schools), lines (e.g., roads), and polygons (e.g., parks)

Raster Data Models

• Raster data models represent features as a grid of cells (pixels)
• Each cell has a value corresponding to the feature at that location
• Examples of Raster data include satellite images, elevation maps, and land cover maps

Discrete Data

• Discrete data exists at specific locations within a defined space
• Examples include: Lookout towers, streams, and snail habitats

Continuous Data

• Continuous data exists everywhere within a specified space
• Examples include elevation and precipitation

Vector Data Model Shapes

• Points: represent location only (e.g., points)
• Lines: represent length and are connected points (e.g., roads)
• Polygons: represent enclosed areas (e.g., parks, lakes)

Vector Topography Principles

• Connectivity: lines and points are connected
• Adjacency: relationship between neighboring polygons
• Containment: one polygon entirely enclosed within another

Raster Data Types

• Land cover
• Terrain
• Satellite images

Raster Model Pros & Cons

• Pros: faster, easier to understand, easier to print
• Cons: less accurate, lines can become fat, only one value per cell

Scale Maps

• Small scale maps show less detail (e.g., 1:300,000)
• Large scale maps show more detail (e.g., 1:1,000)

Cartographic Design

• Principles relate to data plotting (scale, size, shape, patterns), labeling (font, size), legend (properties, size, and borders)

Common Map Elements

• Title, focal element, supportive elements (legend, scale bar, north arrow), balance (elements equally weighted)

Choropleth Maps

• Choropleth maps use shading or patterns to represent data values in proportion

Isolines

• Isolines: lines connecting points of equal value (e.g., contour lines on maps)

Contour Maps

• Contour maps use isolines to show elevation and terrain shape

RGB Color Models

• Represent colors as mixtures of red, green, and blue, with brightness on a scale of 0-255
• White is full intensity of all colors

Color Contrast and Harmonies

• High contrast: colors opposite each other on the color wheel
• Low contrast: colors next to each other on the color wheel
• Complementary, Analogous

Color Selection for Maps

• Use different colors for categories, shades of same color for quantities, and shades of two colors for diverse quantities

Attribute Types

• Nominal: names or unique identifiers (e.g., county names)
• Ordinal: rank categories (e.g., snail habitat suitability)
• Categorical: distinct groups or classes (e.g., rock type)
• Interval: numeric scale with a meaningful zero point (e.g., temperature)
• Ratio: numeric scale with a true zero point (e.g., population)

Data Representation Methods

• Nominal data: single symbol map
• Categorical data: unique colors
• Ordinal data: unique values or graduated colors
• Interval & Ratio Data: divide into classes, varying size and thickness of symbols, hue

Data Symbolization Principles

• Brain seeks patterns
• Color over shape

Coordinate Systems

• Spherical: latitude and longitude
• Cartesian: numerical coordinates

Datum

• Datum: reference for a system of coordinates that defines the size and shape of the earth, and its location
• Ellipsoid: model of the earth's shape used to create a surface for mapping computations

Horizontal and Vertical Datums

• Horizontal datum: coordinates of specific locations (longitude/latitude)
• Vertical datum: a reference surface in measuring elevation

Coordinate System Types

• Local or world-centered data

Geoid

• Model of global mean sea level used to measure elevation precisely
• It is closest to the true shape of the Earth

Spheroid

• A simplified 3D geometric shape of the Earth that is easier to work with mathematically
• It is a good approximation of the Earth's shape

Map Projections

• Project a spherical Earth onto a flat map surface preserving either shape, area, direction or distance (but not all at once)

This quiz covers the fundamental concepts of spatial data models, including vector and raster data models. It examines how real-world features are represented and the differences between discrete and continuous data. Test your understanding of spatial databases and their applications in geography.