Binary Models in Feature Interpretation (Vector and Raster) : Application and Types (Especially for GATE-Geospatial 2022)

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A binary model uses logical expressions to select spatial features from a composite feature layer or multiple raster. The output of a binary model is in binary format: 1 (true) for spatial features that meet the selection criteria and 0 (false) for features that do not.

Binary Models defines two types of models: vector-based binary model and raster-based binary model.

Applications of Binary Models

  • Siting analysis is probably the most common application of the binary model. A siting analysis determines if a unit area (i.e.. , a polygon or a cell) meets a set of selection criteria for location a landfill, a ski resort, or a university campus. There are at least two approaches to conducting a siting analysis. One evaluates all potential sites. Although the two approaches may use different sets of selection criteria, they follow stringent criteria for evaluation.
  • Binary models can be used for change detection. Sometimes binary models are used at the beginning state of modeling.
  • Another consideration in siting analysis is the threshold values for selection. Well-defined or โ€œcrispโ€ threshold values are used in the example in raster-based method to remove land from consideration: the road buffer is exactly 1 mile and the minimum parcel size is exactly 5 acres. These threshold values automatically exclude parcels that are more than 2 miles from heavy-duty roads or are smaller than 5 acres.

Types of Binary Models

There are two types of binary models:

Diagram Shows Two Types of Binary Models

Vector-Based Binary Model

The vector-based method requires the output vectors, with representing a criterion. Vector-based method proceeds by:

Steps in Raster Model

  1. Gather all layers (land use, flood potential, road, and slope) relevant to the selection criteria. A DEM can be used to derive a slope raster, which can then be converted to a vector layer.
  2. Select heavy-duty roads from the road layer, and create a 1-mile buffer zone around them.
  3. Intersect the road buffer zone layer and other layers. Intersect, instead of other overlay operations, can limit the output to areas within 1 mile to heavy-duty roads.
  4. Query the composite feature layer for potential industrial sites.
  5. Select sites, which are equal to or larger than 5 acres.

Example of Vector-Based Logical Model

Figure Shows Vector-Based Binary Model

An illustration of a vector-based logical model. The two maps at the top are overlaid so that their attributes of Suit and Type are combined.

A logical expression, Suite AND Type , results in the selection of polygon 4 in the output.

Raster-Based Binary Model

The raster-based method requires the input raster, with each raster representing a criterion. A local operation with multiple raster can then be used to derive the raster-based model from the input raster.

Steps in Raster Model

To solve the same problem as in vector-based method, the raster-based method proceeds by:

  1. Derive a slope raster from a DEM, and a distance to heavy-duty road raster.
  2. Convert the land use and flood potential layers into raster with the same resolution as the slope raster.
  3. Use a local operation with multiple raster to query for potential industrial sites.
  4. Use a zonal operation to select sites, which are equal to or larger than 5 acres. (The size of a site can be computed by multiplying its number of cells by cell resolution) .
Figure Shows Raster-Based Binary Model

To build a raster-based binary model, use the query statement, [Raster 1] AND [Raster 2] , to select three cells (shaded) and save them to the output raster.

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