Raster Analysis and Geoprocessing Concepts

Raster Analysis Review

• Overview of Raster Analysis
  Understanding of various functions in raster analysis including local, neighborhood, zonal, and global functions, as well as their applications in digital elevation models and spatial data.

Context of Raster Model

• The raster model is characterized by its continuous nature, allowing for advanced analytical possibilities. This lecture will explore these functions and tools for analysis.

Road Map of Lecture

• Key topics include:
  • Calculating Euclidean Distance Surfaces
  • The Reclassify Tool
  • Calculating Slope and Aspect Surfaces (Review)
  • Selecting a Raster Region (Review)
  • Map Algebra
  • The Model Builder
  • Citing Spatial Data

Calculating Euclidean Distance Surfaces

• Definition:

  • Describes each cell's relationship to sources based on straight-line (as-the-crow-flies) distance.

• Three Main Euclidean Tools:

  1. Euclidean Distance: Measures distance from each cell to the closest source.
  • Example: Distance to the nearest town.
  1. Euclidean Direction: Identifies direction from each cell to the nearest source.
  • Example: Direction to the closest town.
  1. Euclidean Allocation: Identifies cells allocated to a source based on proximity.
  • Example: Finding the closest town.

Source Identification

• The source is where objects of interest are located (e.g., roads, shopping malls).
• If the source is a raster, it contains just values of source cells; otherwise, it gets converted.
• Algorithm:
  • Uses the Pythagorean Theorem c^2 = a^2 + b^2 to calculate the hypotenuse from the source cell to surrounding cells.
• Output values are floating-point distance measurements; cells equidistant from sources are assigned based on scanning order (the first encountered source).

Limitations of Euclidean Distance

• It assumes straight-line movement, which may not be realistic due to geographical features (rivers, steep slopes).
• In such cases, consider using Cost Distance tools for realistic results.

The Reclassify Tool

• Purpose: to change raster values for various analytical reasons, such as grouping, adjusting for new information, or converting to a common scale.
• Common methods of reclassification:
  • Individual values, ranges of values, intervals, using functions.
• Ranges must not overlap outside defined boundaries to prevent value confusion during processing.

Calculating Slope and Aspect Surfaces (Review)

• Slope Tool: Identifies steepness in each raster cell.
  • Lower slope values indicate flatter terrain; higher values indicate steeper terrain.
• Aspect Tool: Identifies the compass direction of the downhill slope.

Selecting a Raster Region (Review)

• A zone consists of cells with the same value, and regions are contiguous areas within a zone.
• Disconnected regions may need separate processing through the Region Group method.

Map Algebra

• Utilizes an algebraic approach for spatial analysis with raster datasets.
• Functions resemble matrix algebra where cell positions influence calculations directly.
  • Groups of Map Algebra operators: Arithmetic, Relational, Boolean, Bitwise, Combinatorial, and Logical.

The Model Builder

• A visual programming language used for building geoprocessing workflows.
• Models automate and document spatial analysis procedures by chaining processes visually.
• It allows the dragging of layers and tools into a model for direct interaction.

Citing Spatial Data

• Importance includes giving credit to data creators, enhancing analysis credibility, and facilitating data verification by others.
• Citatation Format:
  • Title, Author, Date, Source (website and URL if applicable), Type of data.
• Example:
  King County. (2006). Parks in King County. Washington State Geospatial Data Archive [Shapefile]. Retrieved from https://wagda.lib.washington.edu/data/geography/wa_counties/king/index.html.

Summary of Lecture Topics

• Explored various aspects of raster analysis including distance calculations, reclassification, slope and aspect evaluation, region selection, Map Algebra, Model Builder, and guidelines for citing spatial data.