7.2 Raster Surface Analysis

7.2 Raster Surface Analysis

Raster surface analysis is a cornerstone capability of ArcGIS Pro, heavily reliant on the Spatial Analyst extension. Unlike vector analysis, which focuses on discrete boundaries and geometries, raster analysis deals with continuous phenomena represented by grids of cells (pixels). The most common application of surface analysis involves topographic modeling using Digital Elevation Models (DEMs), but these techniques are equally applicable to continuous surfaces of temperature, precipitation, soil pH, or population density.

Mastery of raster analysis requires a deep understanding of how local, focal, zonal, and global operations interact with cell values. In this section, we will explore the foundational tools and workflows required for the ArcGIS Pro Associate certification.

Deriving Topographic Surfaces

A Digital Elevation Model (DEM) is a bare-earth raster surface where each cell value represents an elevation above a specific datum. While a DEM is useful on its own, its true power lies in the surfaces that can be derived from it. The Spatial Analyst 'Surface' toolset contains several critical algorithms.

Slope

The Slope tool calculates the maximum rate of change in value from a given cell to its eight immediate neighbors. It essentially measures the steepness of the terrain.

• Output Units: Slope can be calculated in Degrees (0 to 90) or Percent Rise (0 to infinity, where a 45-degree angle equals a 100% rise).
• Z-Factor: This is a crucial parameter. If your DEM's x,y coordinates are in decimal degrees (e.g., WGS 1984) but the z-values (elevation) are in meters, the slope calculation will be catastrophically wrong. The Z-Factor applies a multiplier to align the z-unit scale with the x,y-unit scale. If the units match (e.g., both are in meters), the Z-Factor should be 1.

Aspect

The Aspect tool determines the downslope direction of the maximum rate of change in value from each cell to its neighbors. It identifies the orientation of the slope.

• Output Values: Aspect is measured in degrees clockwise from 0 (due north) to 360 (due north again).
• Flat Areas: Cells in flat areas with zero slope are assigned a distinct value, typically -1, as they have no definitive downslope direction.
• Use Cases: Aspect is vital for solar insolation models, agriculture suitability (e.g., south-facing slopes in the northern hemisphere receive more sunlight), and microclimate analysis.

Hillshade

The Hillshade tool creates a shaded relief map of a surface by considering an illumination source angle and shadows.

• Parameters: It requires an Azimuth (the angular direction of the sun, typically 315 degrees or NW) and an Altitude (the angle of the sun above the horizon, typically 45 degrees).
• Multidirectional Hillshade: A modern advancement in ArcGIS Pro allows the generation of multidirectional hillshades, which combine light from multiple sources to illuminate complex terrain better than a single-source hillshade, avoiding completely black shadows in steep terrain.

Viewshed

The Viewshed tool identifies the cells in an input raster that can be seen from one or more observation points or lines.

• Mechanism: It draws a 3D line of sight from the observer point to every other cell in the raster, evaluating whether the elevation of intervening cells blocks the view.
• Observer Parameters: The analysis can be highly customized by adding specific fields to the observer feature class, such as OFFSETA (the height of the observer, like a fire tower) and OFFSETB (the height of the target being viewed).

Data Transformation: The Reclassify Tool

Often, continuous raster data is too granular for specific analyses. Site suitability modeling, for example, typically requires categorical rankings rather than continuous values. The Reclassify tool is used to reassign raster values based on a defined lookup table or classification scheme.

For example, consider a continuous slope raster where values range from 0 to 45 degrees. To model land suitable for building, you might want to categorize the slope into three distinct classes:

• 0 to 5 degrees: Highly Suitable (reclassified to a value of 3)
• 5 to 15 degrees: Moderately Suitable (reclassified to a value of 2)
• Greater than 15 degrees: Unsuitable (reclassified to a value of 1)

The Reclassify tool allows you to establish these breakpoints and assign new integer values to the cells. The output is a discrete raster, which is much easier to combine with other datasets in subsequent analyses.

Raster Calculator and Map Algebra

The Raster Calculator tool executes Map Algebra expressions, allowing you to perform complex mathematical and logical operations across multiple raster datasets on a cell-by-cell basis. This is a local operation (the calculation for a cell at location x,y relies only on the input cell values at that exact same location x,y).

Mathematical Operations

You can add, subtract, multiply, or divide rasters. For example, if you have a raster representing income and a raster representing expenses, you could calculate disposable income with the expression: "Income_Raster" - "Expenses_Raster"

Logical (Boolean) Operations

Raster Calculator is extensively used for Boolean logic (AND, OR, NOT) to find locations that satisfy multiple criteria. In Boolean logic, True is represented by 1 and False is represented by 0.

Suppose you need to find land that is both Highly Suitable for building (Slope Class = 3) AND located in a specific zoning area (Zoning = 1). The expression would be: ("Reclass_Slope" == 3) & ("Zoning_Raster" == 1)

The output raster will contain cells with a value of 1 where both conditions are met, and a value of 0 where one or both conditions fail.

Focal and Zonal Operations

While Raster Calculator performs local (cell-by-cell) operations, focal and zonal tools evaluate relationships based on neighborhoods and defined boundaries.

Focal Statistics

Focal operations calculate an output value for each cell based on the values of the cells in a defined neighborhood surrounding it.

• Neighborhoods: You can define a neighborhood as a rectangle, circle, annulus (donut), or wedge.
• Statistics: You can calculate the Mean, Majority, Maximum, Minimum, Range, etc., within that neighborhood.
• Use Case: A common use case is running a Focal Mean (a low-pass filter) using a 3x3 rectangular neighborhood to smooth a noisy elevation dataset by averaging out extreme spikes and pits.

Zonal Statistics

Zonal operations summarize the values of a raster dataset within the boundaries of another dataset (the "zones"). The zone dataset can be either a discrete raster or a vector polygon feature class.

• Mechanism: For example, you have a continuous raster of population density and a vector polygon layer of school districts. Zonal Statistics will calculate the specified statistic (e.g., Mean, Sum) of the population cells falling within each individual school district polygon.
• Output: The standard tool outputs a new raster, but the more commonly used Zonal Statistics as Table tool outputs a standalone table. This table can then be joined back to the original vector polygon layer, appending the raster summary statistics as new attributes for each district.

Mastering these core raster analysis techniques—deriving surfaces, reclassifying continuous data, applying Map Algebra, and summarizing data zonally—provides a comprehensive toolkit for tackling complex spatial problems in the ArcGIS Pro environment.