ComplexNetGIS is an ArcGIS Arctoolbox for the visualisation and analysis of networks in a spatial domain. It was developed using Python programming language together with the use of the network library NetworkX.

The tool was built with the aim to read existing network data without having to redraw them in ArcGIS and to implement a network analysis inside ArcGIS without using third part software.

The tool is open source and distributed under the GNU General Public License. The open source nature of the tool code allows each skilled programming user to extend the tool functionalities according to his or her needs.

This website is intended to make the tool known to people interested to perform analyses on spatial networks using a GIS environment. We also aim to create a community of users and developers interested to extend and improve ComplexNetGIS functionalities.

Functions implemented

  • TXT2SHP reads a network edge file and converts it in a polyline and point shapefiles
  • Shp2TXT reads a polyline shapefile and build the network  structure
  • Degree&Clustering implements a degree analysis (number of connections for each node) and a  clustering analysis (level of connection between first neighbors of each node)
  • Centrality:  measures the level of centrality of each node through two network  indexes: degree centrality (for a whatsoever node v is the fraction of nodes it is connected to), betweenneess  centrality (number of shortest path passing through each node) and closeness centrality
  • Page Rank: <under construction>
  • Weighted analysis takes into account the strength of each link by developing a measure of the stregth of each node (sum of weights of the links departing from each node) and  the disparity Y2
  • Transport analysis develops a number of transportation indexes: Average of Detour Link Indeces, Average Network Detour Index, Topological Diameter, Spatial Diameter, Number of cycles, Max degree, Average degree, Min degree, Alpha index, Beta index, Gamma index, Eta index, Theta index , Topological Pi index, Spatial Pi index (for a review of these indexes check out the web page http://people.hofstra.edu/geotrans/eng/ch1en/meth1en/ch1m3en_2ed.html )
  • Cluster analysis:  <under contruction>