This add-in for the ArcMap geographic information system (GIS) offers multi-criteria decision analysis (MCDA) and visualization functions for vector data. The MCDA process is highly interactive and the results can be processed within ArcMap.
The add-in supports the following MCDA methods:
- Weighted Linear Combination (WLC)
- Ordered Weighted Averaging (OWA)
- Locally Weighted Linear Combination (LWLC)
The LWLC method includes the following neighbourhood definitions:
- K-Nearest Neighbors (KNN)
- Automatic (increases KNN until the result can be calculated)
Additional add-in features include:
- Maximum-score standardization procedure
- Score-range standardization procedure
- CSV export of the result table and parameters
- Classified and unclassed choropleth maps with diverging colour scheme
- Three modi to define the map rendering frequency
- Only polygon geometry is supported
- Criterion values must be numeric
- Rook contiguity for large data sets (> 1,000 polygons) is slow (several minutes processing time)
- Colour mixing gets mixed up - set one colour to white to reset
- Sessions are not persistent, MCDA results are lost when MCDA4ArcMap is closed - use right-click | Data | Export to save map layer containing results
- Developed for ArcMap 10.1 and the .Net Framework 4.0 or higher
- Download should appear as "ESRI AddIn File" - if ArcMap runs, this add-in will also work!
- The add-in (version 1.0) was developed by Steffan Voss,
Institute for Geoinformatics, University of Muenster, Germany, during his research visit in the
Department of Geography, Ryerson University, Toronto, Canada, from August 2012 to January 2013.
- The add-in is further developed by Steffan Voss (he commits code as golden_jubilee).
- This project was initiated and supervised by
Dr. Claus Rinner, Dept. of Geography, Ryerson University.
- Partial funding for Steffan's research from Dr. Rinner's
NSERC Discovery Grant is gratefully acknowledged.
- An earlier version of the LWLC tool for vector data in ArcMap was developed by Brad Carter for his
Master of Spatial Analysis (MSA) degree at Ryerson University.
See DOCUMENTATION tab for additional information.
Feel free to submit suggestions and bug reports.