Raster Analysis: Local Functions Overview

Raster Operators for Analysis: Local Functions

• Raster data model represents continuous data using grid cells, contrasting to object-based vector data model
• Raster analysis focuses on local, focal, zonal, and global functions, this lecture focuses on local functions
• Local functions analyze data on a cell-by-cell basis

Categories of Local Functions

1. Reclassification

• Binary Masking: assigns values (0 or 1) for absence/presence or suitability, often an intermediate step
• Classification Reduction: consolidates multiple attribute types into fewer classes, e.g., merging forests
• Classification Ranking: assigns ranks/weights for further analysis, like least-cost path analysis

2. Arithmetic Operations

• Includes addition, subtraction, multiplication, and division applied to corresponding cells across layers
• Example: converting elevation data from feet to meters by multiplying by 0.305

3. Logical Statements

• Boolean AND: both conditions must be true for a value of 1; otherwise, the output is 0
• Boolean OR: if either condition is true, the value is 1
• Logical queries and map algebra can be performed using raster calculators

4. Proximity Analysis

• Euclidean Distance: calculates the straight-line distance of each cell to the nearest source cell; useful for analyses like buffering

Key Takeaways

• Raster and vector operations are different due to data models
• Local functions focus on individual cells or corresponding cells across layers
• Local level serves as a foundation for advanced raster analysis (focal, zonal, global)

This quiz explores local functions in raster analysis within the raster data model, focusing on methods like reclassification, arithmetic operations, and logical statements. Understand how these functions operate on a cell-by-cell basis to analyze continuous data effectively.