Distance raster analysis involves examining the spatial distance of each raster cell from its neighboring cells (sources), thereby reflecting the relationship between each cell and its nearest source. This analysis not only considers surface distances but also accounts for various cost factors. Through distance analysis, valuable insights can be obtained to guide resource management and planning, such as calculating emergency earthquake rescue distances from affected areas to the nearest hospital, or evaluating service areas for chain supermarkets.
Distance raster analysis primarily includes three aspects:
- Generating distance raster: Calculating the distance from each cell to the nearest source (object of interest), with three types: Euclidean distance, surface distance, and cost distance, corresponding to the following functions:
- Generate Line Distance Raster: Produces corresponding line distance raster, straight-line direction raster, and straight-line allocation raster based on source dataset.
- Generate Surface Distance Raster: Generates surface distance raster, surface direction raster, and surface allocation raster based on source dataset and surface raster.
- Generate Custom Cost Distance Raster: Creates cost distance raster, cost direction raster, and cost allocation raster based on source dataset and cost raster.
- Analyzing shortest paths from targets to sources using direction and allocation rasters;
- Calculating shortest paths between two points (source and target), including minimum cost paths and shortest surface distance paths.
Basic Concepts
First, let's understand fundamental concepts related to distance raster analysis.
Source: Objects or features of interest, such as schools, roads, or fire hydrants.
Source Dataset: Dataset containing sources, which can be 2D point, line, region, or raster datasets. For raster datasets, cells not representing sources must be NoData.
Distance: Includes Euclidean distance, cost distance, and surface distance:
- Euclidean distance refers to the straight-line distance from each cell to the nearest source;
- Cost distance represents the actual accumulated cost to reach the nearest source based on weighted cell attributes;
- Surface distance calculates the actual surface distance from cells to the nearest source using surface raster data.
Euclidean distance can be considered as the simplest form of cost measurement. In practice, surface obstacles like rivers or mountains often require detours, making cost distance an extension and refinement of Euclidean distance analysis.
Cost Raster: Required for generating cost distance rasters and calculating minimum cost paths. Cost rasters determine the expense required to traverse each cell. Cell values represent per-unit traversal costs and must be non-negative. For example, a cost raster showing vehicle resistance across terrains might use values representing resistance per kilometer traveled. The total cost equals unit cost (cell value) multiplied by cell size. Cost units can be length, time, currency, or unitless values like reclassified slope, aspect, or land use types.
Compute Shortest Path
Shortest path analysis calculates optimal routes from targets to nearest sources using target point data, distance rasters, and direction rasters generated through distance raster functions. Examples include determining paths from suburban areas to nearest shopping malls.
For instance, analyzing routes from residential areas (region dataset) to nearest shopping malls (point dataset). First, generate cost distance raster and cost direction raster using malls as sources. Then perform shortest path analysis using residential areas as targets with the generated rasters to obtain optimal routes.
Three path types are available:
- Pixel Path: Generates a path for each raster cell, representing each target cell's distance to the nearest source.
As shown below, using red points as sources and black-bordered polygons as targets, this method produces shortest paths indicated by blue cells.
Figure: Pixel Path Analysis - Zonal Path: Creates one path per continuous zone of equal raster values, showing each target zone's shortest path to the nearest source.
As shown below, using red points as sources and black-bordered polygons as targets, this method produces shortest paths indicated by blue cells.
Figure: Zonal Path Analysis - Single Path: Generates one optimal path for all target cells, representing the absolute shortest path across the entire target area.
As shown below, using red points as sources and black-bordered polygons as targets, this method produces shortest paths indicated by blue cells.
Figure: Single Path Analysis
Calculate Shortest Path Between Two Points
Calculates the shortest path between specified source and target points. Based on surface or cost rasters, this can determine shortest surface distance paths, minimum cost paths, or surface-distance optimized cost paths.
Cost Distance
Minimum cost path calculation requires cost rasters to determine traversal expenses. Cell values represent per-unit traversal costs. For example, a vehicle resistance cost raster might show resistance per kilometer traveled, with total cost being unit cost multiplied by cell size. Cost units can be length, time, currency, or unitless values. Real-world analyses often involve multiple weighted factors (e.g., road construction costs considering length, land use, slope, and population proximity). Note: Cost values cannot be negative.
Related Topics
Generate Surface Distance Raster
Generate Custom Cost Distance Raster