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Deriving distance datasets.

In many cases we need to know the distance for each location in a geographic area to certain features - roads, shopping malls, police stations, etc. Generally this is a task performed in a raster environment because the raster model is better suited for representing continuous data. In order to use raster analysis in ArcGIS however one needs to have Spatial Analyst which is an excellent but costly option. If somebody needs to perform heavy spatial analysis on continuous data this additional cost will be justified, but if someone needs occasionally to derive a dataset that describes continuous phenomenon the price of Spatial Analyst is an overkill.  

In this article we will discuss how to derive distance datasets using plain ArcGIS (any license) with the help of the ET GeoWizards functions.

Point dataset representing the sources

The point grid created

For the example with extent of about 150 x 90 kilometers we used a cell size of 1 kilometer. The point grid created has about 4000 points.

 Source dataset has the features to which we want to calculate the distances. The features can represent many different entities:
  • points -  towns, police stations, schools, cell towers, etc.
  • lines - streets, rivers, etc.

STEP1: In order to split spatially the area of interest we will create a grid of regularly spaced point using the Point Grid function of ET GeoWizards.

  • The extent of the point grid should be a bit larger of the source points.
  • The cell size (the distance between the points of the point grid) should be carefully selected:
    • It should be small enough to be able to represent the distances adequately
    • It should not be too small, because this will create a very large dataset and the processing will be difficult.

    The functions of ET GeoWizards are tested on point grids with up to 500,000 points, but we do not recommend using grids with more than 200,000 points.

Result of Point Distance symbolized using the distance field.

 STEP 2: The Point Distance function will calculate the distance from each point of the grid to the closest point of the source dataset. The search tolerance should be large enough to find the distance to the furthermost points of the point grid.
The TIN derived symbolized with the minimum elevation.

The TIN derived symbolized with the azimuth calculated - shows the direction for each point to the closest source

STEP 3: The next step will be to create a continuous surface from the point grid with assigned distance to the source points.
  • Build TIN function using the ET_Distance field as elevation source will create a continuous PolygonZ dataset. The z values will represent the distance to the closest source point.
  • Analyze TIN function will calculate several characteristics for each 3D polygon

We can use:

  • the Minimum elevation field to symbolize the distance to the closest point
  • the Aspect field to represent the Euclidian direction from each location to the closest source. 

Distance Contours.

STEP 4: The Interpolate Contours function will generate isolines connecting the points with equal distance from the source points.  Each polyline will have Height attribute which in this case will reflect the distance from the source points.
Thiessen Polygons

Creating Thiessen polygons from the dataset derived in STEP 2 above can give us another continuous dataset representing the distances to the source points. 
Distances to a polyline dataset

The same approach can be applied to calculate the distances to a polyline source features. 

See ET GeoWizards User Guide for more information

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Copyright: Ianko Tchoukanski