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Task: Comparable Properties Locator Model

Display Name: Comparable Properties Locator Model

Description: The Comparable Property Locator application was developed to automate the process of locating comparable properties based on both real estate characteristic similarities, and distance to a user supplied reference property. The resulting selection set is a grouping of the most similar properties that are also the most proximal to the reference property. To locate comparable properties this application utilizes a geospatial algorithm that can be divided into three functional stages: a criteria matching stage, a distance analysis stage, and a data selection stage. Criteria Matching- A standardization is applied to all of the attributes of interest by performing a z-transformation, where each value is subtracted from the mean for all of the values, and then is similarly divided by the standard deviation for all values. This standardization ensures all of the attributes are placed on the same scale even when they are represented by very different types of numbers. Next, for each candidate the algorithm subtracts the standardized values from those of the reference object, squares the differences, and adds the squared differences together, so that the sum becomes the basis for the similarity index for that candidate. The resulting similarity index is then used to rank each candidate from the smallest index (most similar) to largest index (least similar), using a returned results threshold parameter (25) to parse out the 25 candidates exhibiting the smallest similarity indexes. Distance Analysis- In this stage point distance analysis is performed in order to record the distances from the centroids of each of the 25 comparable property candidates returned in the previous stage to the centroid of the reference property. Data Selection- The last stage pares down the selection set of comparable properties by creating a grouping that exhibit qualities of both similarity and proximity to the reference property. This final grouping is achieved in two steps: firstly, by determining the median distance value from all of the distance values returned in the previous distance analysis stage, and secondly, by selecting only those comparable properties that have a distance value less than the median.

Category:

Help URL: https://maps.grundyco.org/arcgis/rest/directories/arcgisoutput/GeoProcessingServices/CompsLocatorModel_Fabric_GPServer/GeoProcessingServices_CompsLocatorModel_Fabric/Model2.htm

Execution Type: esriExecutionTypeAsynchronous

Parameters:


Supported Operations:   Submit Job

Child Resources:   Metadata