24 Overlays Operation

Dr. Puneeta Pandey

 

1. Learning Objective

 

To understand the concept of overlay operation in GIS and its application in suitability analysis and other decision making processes.

 

2. Introduction

 

Overlay operation is an essential feature of GIS that involves combining both spatial as well as attributes data from two or more layers of spatial data. Spatial data is the data pertaining to location or space of a feature; while attribute data indicates description about the spatial features. Overlay operation is a crucial component of layer data stacking, in which one can look where the layers overlap above one another. Further, it is imperative to mention here that in an overlay operation, all the attributes of the features are carried through in the operation to create a new map of the data that has been overlaid.

 

Also, the overlay analysis can be used to combine the characteristics of several datasets into one to find specific locations or areas that have a certain attributes. This is helpful in carrying out site suitability analysis, for example, finding locations suitable for a particular land use or areas susceptible to some risk.

 

The steps for perform overlay analysis include defining the problem, breaking it into sub-models, determining the significant layers, transforming the data within a layer, weighting the input layers, adding and finally analyzing the layers.

 

3. Types of Overlay operations

 

In general, there are two methods for performing overlay analysis—feature overlay and raster overlay.

 

3.1 Vector/feature overlay: A vector overlay involves combining point, line, or polygon geometry and their associated attributes. All overly operations create new geometry and a new output geospatial data set. An example of vector overlay is the clip function that defines the area for which features will be output based on a “clipping” polygon. In this operation, only the geometry and attributes of the data layer are transferred to the result layer; not the geometry or attribute of the clipping layer.

 

In a vector-based system, the topological data is stored as points, lines and/or polygons. In a vector-based system, topological map overlay operations allow the polygon features of one layer to be overlaid on the polygon, point, or line features of another layer. Topological vector overlay operations can be classified via two methods:

 

A. By element type: It includes the elements such as point, line or polygons contained in the layers to be overlaid.

 

B. By operation type: If overlay is performed to generate a layer by using the operations of Union, Intersection or Boolean operation on the two input layers.

 

The following table identifies which overlay options exist for each possible combination of element types contained in the two input layers.

 

The key elements in feature overlay are the input layer, the overlay layer, and the output layer.

 

 

3.1 Tools in Vector Overlay

 

3.1.1 Erase: This tool creates a feature class by overlaying the input features with the polygons of the erase features. Only those portions of the input features falling outside the boundaries are copied to the output feature class.

Figure 1: Erase Tool

 

3.1.2 Identity: This tool computes a geometric intersection of the input features and identity features. The input features that overlap identity features get the attributes of those identity features.

Figure 2: Identity Tool

 

3.1.3 Intersect: It computes a geometric intersection of the input features. Features or portions of features which overlap in all the input layers and/or feature classes, after intersection, are written to the output feature class.

Figure 3: Intersect Tool

 

3.1.4 Spatial Join: Join attributes from one feature to another based on the spatial relationship.

 

3.1.5 Symmetrical Difference: Features in the input and update features that do not overlap are written to the output feature class.

Figure 4: Difference Tool

 

3.1.6 Update: It computes the geometric intersection of the Input Features and Update Features. The attributes and geometry of the input features are updated in the output feature class.

Figure 5: Update Tool

 

3.2 Raster Overlay

 

In raster overlay, numerous input layers are combined mathematically into a single output layer, where, each cell in the output layer is assigned a new value. For example, in raster overlay by addition, two input raster layers are added together to create an output raster with the values summed for each pixel.

 

The following tools describe the Raster overlay tools:

 

3.2.1 Zonal Statistics: This tool summarizes the values in a raster layer by zones or categories in another layer.

 

3.2.2 Combine: This tool assigns a value to each cell in the output layer based on unique combinations of values from several input layers.

 

3.2.3 Weighted Overlay: This tool overlays several raster layers using a common measurement scale and assigns weight to each layer based on its importance. Generally, favorable situations are assigned higher weightage. In this method, the values in the input rasters are reclassified followed by multiplying the value of each input raster by its weight and adding the resulting cell values to produce an output raster.

 

3.2.4 Weighted Sum: In this method, several raster layers are overlaid, followed by multiplying each layer by their given weight and summing them together.

 

However, as compared to Weighted Overlay tool, the weights assigned to the input rasters can be any value and the Weighted Sum tool output values are obtained by direct addition of the product of each cell value and its weight. Also, the attribute resolution of the values is maintained, since the values are not rescaled back to a defined scale.

 

Thus, the Weighted Overlay tool is commonly used for suitability modeling while the Weighted Sum tool is useful when model resolution is to be maintained or when floating-point output or decimal weights are required.

 

3.2.5 Fuzzy Overlay: Fuzzy overlay technique is used to analyze the relationships between all the sets for the multiple criteria in the overlay model. Since the process of fuzzification is based on the degree of membership to a set, the overlay techniques are based on set theory. This technique transforms the input raster into a scale of 0 to 1, indicating the possibility of a suitable membership in a set, based on certain functions. Thus, fuzzy overlay follows the steps of defining the problem, breaking it into sub-models, determining significant layers, reclassifying the data values to belong to a specified set, and transformation to the possibility of belonging to the favorable class or set (from 0 to 1).The present fuzzy set overlay techniques are ‘fuzzy And’,‘fuzzy Or’, ‘fuzzy Product’, ‘fuzzy Sum’, and ‘fuzzy Gamma’. Each of these techniques describes the cell’s membership relationship to the input sets. For example, the fuzzy And overlay type creates an output raster where each cell value is given the minimum assigned fuzzy value for each of the sets the cell location belongs to. The fuzzy Or type returns the maximum value of the intersection of the sets.

 

Many a times, fuzzy logic for overlay is compared to binary overlay analysis. The major difference is that in binary overlay analysis; each cell is evaluated whether it is in a specified class or not, for each criterion; while in overlay analysis, the cell is assigned a value of 1 for all the input criteria that are considered to be potentially favorable. Thus, in binary overlay analysis, if no location fulfils all the criteria, then there is no possibility of second option. Also, only values of 0(absent) or 1(present) is used, which implies there is no relative weighting of the locations that meet the criteria.

 

Weighted overlay analysis attempts to address these limitations by assigning each cell value on a defined continuous scale such as a 1 to 10 scale, with 10 being the most preferred relative to the criteria. It does not classify each cell on a 1 or 0 binary scale. This is followed by adding each reclassified criteria; and the cell locations with the highest summed values are the most preferred relative to the input criteria.

 

4. Point, Line and Polygon overlay for vector and raster model

 

4.1 Point-in-polygon: In the vector model, the point-in-polygon overlay determines the points lying inside a polygon. For example, all the ATMs located in the settlement areas. Thus, the output layer, the points have the additional information whether or not the ATMs are in the settlement area. In the raster model, the points are visible through the addition of the two input layers.

Figure 6: Point in Polygon overlay

 

4.2 Line-in-polygon: This involves the overlay of lines and polygons, for example, location of road in the settlement area. In the vector model, the original is cut into shorter segments by the intersection points. In the raster model, the interest areas are identified by addition.

Figure 7: Line-in-polygon Overlay

4.3 Polygon-on-polygon: In the vector model, intersection of polygons results in new topology; be it new polygons or island polygons. In raster overlay, the cell values of the input layers are calculated.

Figure 8: Polygon-in-polygon Overlay

 

Summary

 

It is obvious that all analysis in GIS begins with overlay operations. Thus, overlay analysis is very useful in decision making with GIS. Decision support in GIS is based on the suitability analysis to support decision-makers for issues pertaining to spatial and environmental planning. Various environmental and spatial models are used to provide solutions to various environmental problems such as land use land cover analysis, watershed management, wetland monitoring and so on. Multi-Criteria Evaluation (MCE) is used for multiple selection criteria and fulfilling only a single objective. In Multiple-Objective Evaluation (MOE), the weights assigned to various land use categories are evaluated for better decision-making.

 

References

  • http://pro.arcgis.com/en/pro-app/tool-reference/analysis/an-overview-of-the-overlay-toolset.htm
  • http://desktop.arcgis.com/en/arcmap/10.3/analyze/commonly-used-tools/overlay-analysis.htm
  • http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/understanding-overlay-analysis.htm
  • http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/an-overview-of-the-overlay-tools.htm
  • http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/applying-fuzzy-logic-to-overlay-rasters.htm
  • http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-fuzzy-membership-works.htm
  • http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-fuzzy-overlay-works.htm
  • https://learn.canvas.net/courses/464/pages/unit-7-dot-6-overlay-operations http://www.gitta.info/Suitability/en/html/BoolOverlay_learningObject1.html
  • Heywood, I.; Cornelius, S.; Carver, S., 2006. An Introduction to Geographical Information Systems 3rd Edition. New York: Longman [p. 238-243].