Disponible con licencia de Business Analyst.
Suitability analysis in ArcGIS Business Analyst Pro is used to rank and score sites based on multiple weighted criteria. First, create a suitability analysis layer. Then, add suitability criteria, such as variable-based, point layer-based, or field-based criteria. Optionally, set criteria properties to alter the weight, influence, and threshold of each suitability criterion. Finally, calculate the suitability scores for the sites.
This workflow can answer questions such as the following:
- Which region of the country is most suitable for expansion?
- Within the selected region, which area is most conducive to growth?
- Within the market selected for expansion, which candidate site is best?
- How does weighting the existence of competitors as two times more important than the number of people in the service area change the suitability score?
Perform the suitability analysis workflow
To perform a suitability analysis, complete the following steps:
- On the Analysis tab, click Business Analysis to open the gallery, and click the Suitability Analysis button .
The Make Suitability Analysis Layer tool opens in the Geoprocessing pane.
- For Input Features, choose the locations you want to rank.
You can choose a feature layer from the project or browse for hosted or shared content.
- Use the Layer Name parameter to set the name of the suitability analysis layer that will be created.
- Click Run .
The suitability analysis layer is created and added to the Contents pane.
- To proceed with the analysis, click the new suitability analysis layer to open the Suitability Analysis ribbon, and click the ribbon to view the workflow options.
- Click the Add Criteria button to add criteria to the suitability analysis layer to define the analysis.
A drop-down menu appears with the following suitability criteria options:
- Click Add Variables from Data Browser to add demographic and business data variables from the data browser. Examples of variable-based criteria include demographic, socioeconomic, and spending data.
- Click Add Fields from Input Layer to add variables based on the numerical fields in the input layer. Examples of field-based criteria include square footage, available parking spaces, and existence of important amenities.
- Click Add Point Layer to add variables based on spatial relationships between the input layer and a given point layer. Examples of point layer-based criteria include competitor locations, which may negatively impact candidates, or customers, likely having a positive impact on candidates if nearby.
- For the Add Variables from Data Browser option, do the following:
- Choose Input Suitability Analysis Layer, which is the suitability analysis layer that will be used in the analysis.
- Click the Add button to add variables using the data browser. Optionally, click Save List to save the variables as a custom list, or click Remove all to remove all the selected variables.
- For the Add Fields from Input Layer option, do the following:
- Choose Input Suitability Analysis Layer, which is the suitability analysis layer that will be used in the analysis.
- Under Fields, select fields from the suitability analysis layer to be used as criteria.
- For the Add Point Layer option, do the following:
- Choose Input Suitability Analysis Layer, which is the suitability analysis layer that will be used in the analysis.
- Choose the Site Layer ID field, which is the field that assigns unique values for each site in the suitability analysis layer.
- Under Point Features, choose the layer that contains the points to be used as suitability criteria.
- Define the spatial relationship to be used as criteria by choosing one of the following options:
- The Count criteria type returns the total points that fall within each of the suitability analysis layer candidate areas.
- The Weight criteria type aggregates and returns the total of a numeric field value, such as sales, falling within each suitability analysis layer candidate area.
- The Minimal Distance criteria type returns the distance of the closest point to each of the suitability analysis layer candidate areas.
- Click Run in the suitability criteria pane you chose.
The suitability score is automatically calculated when you add suitability criteria or set criteria properties. A suitability score is returned in three places:
- Suitability analysis layer polygons are shaded in the map, illustrating score rankings.
- A suitability analysis layer in the Contents pane returns hierarchal shading that corresponds with the map results, along with value ranges.
- Click the Attribute Table button on the Suitability Analysis tab to view the Suitability Analysis results table, which shows scores for individual criteria, as well as the overall scores, returned as new fields. Each row in the table represents a different site.
- Optionally, click Suitability Criteria on the Suitability Analysis tab to modify the suitability criteria.
The Suitability Analysis pane appears. You can modify each suitability criterion by doing the following:
- Change the Weight value of a variable to make it more or less impactful in the analysis. By default, all variables have the same weight. Increasing the weight of a variable makes it more important to the analysis. The total weight of all the suitability criteria adds up to 100. Optionally, click the Lock button to lock the settings for a variable, or if it's locked, click the Unlock button to unlock the settings for a variable.
- Click Additional Options to change the Threshold value of a variable to narrow the results of the suitability analysis by setting the Minimum and Maximum values.
- Click Additional Options to change the Influence setting of a variable. By default, the influence is set to positive, which means that the higher the value of the variable, the greater its effect on the final score. Optionally, change it to Ideal influence, which defines an ideal value for the variable, or Negative influence, which means that the lower the value of the variable, the greater its effect on the score.
- To undo the suitability criteria modifications, click the Reset Weights button on the Suitability Analysis tab.
This resets the criteria weights to their original settings.
- To remove a suitability criterion from the analysis, click the X on the criterion or use the Remove Suitability Criteria geoprocessing tool.
Calculate a suitability score
Suitability scores are calculated by comparing criteria across all candidate sites. Each criterion receives both a score and weighted score, which are returned as new attributes. A final score is also returned. It summarizes individual weighted scores into an overall ranking.
A suitability score can be returned from the Calculate Suitability Score geoprocessing tool, or you can click Calculate in the Suitability Score group.
The Suitability Score tab includes an Auto Calculate check box. If checked, a score is automatically calculated any time criteria parameter settings change.
Understand your results
A suitability score is returned in three places:
- Suitability analysis layer polygons are shaded in the map, illustrating their rankings.
- A suitability analysis layer in the Contents pane is updated to return hierarchal shading that coincides with the map results, along with representative values.
- Results are also returned in the suitability analysis layer attribute table. Scores for individual criteria, as well as the other scores, are returned as new fields.
Geoprocessing tools
The suitability analysis workflow uses the Suitability Analysis toolset, which includes the following tools:
- Make Suitability Analysis Layer
- Add Field Based Suitability Criteria
- Add Point Layer Based Suitability Criteria
- Add Variable Based Suitability Criteria
- Set Criteria Properties
- Calculate Suitability Score
- Remove Suitability Criteria
You can use these geoprocessing tools directly to perform the same analysis and build and run queries through a Python script or a model. Before starting the suitability analysis workflow, select the Business Analyst data source. You can run the suitability analysis using either a local or online dataset.