Explanations of aChor QGIS Plugin

aChor Plugin is only suitable for polygon classification (in shapefile format).

Please load at least one polygon shapefile in the layer view of QGIS desktop, then enable the plugin.

aChor QGIS plugin provides five different methods. User can use -m parameter to define one of the wishes method to run class_achor.py script.

Local Extreme Values

As defined, a polygon feature has larger (smaller) value then any other surrounding features. This is a local maximum (minimum). Local extreme method is the defult, this include localmax and localmin.

  • Local extremes: -m  1
  • Local maximum: -m  2
  • Local minimum: -m  3
  • Hotspots and Coldspots

    The plugin include Getis-Ord Gi* method to compute Hotspot analysis. After calculation the script create three fields: Z-score, p-value and Gi-Bin.
    To include your own hotspot shapefile for classification, there must be a "Gi-Bin" field that has integer value ranges from -3 to 3.

    parameter: fdb (fixed distance band) The distance used to calculate Getis-Ord Gi*.

  • Hot and cold spots: -m  4
  • Neighbors

    The neighbor method compute the largest value difference between polygons and generate class break accordingly.

  • Neighbors: -m  5
  • Clusters

    The plugin use DBSCAN (Density-based spatial clustering of applications with noise) provided by scikit-learn to compute cluster patterns.

    To include your own cluster shapefile from any other sources, there must be a "dbscan" field that contains integer value; for each value represent one cluster.
    The 0 value means: noise or outliers.

    parameter: eps (neighbors of the core sample) The maximum distance between two samples.

  • Clusters: -m  6
  • Global Extreme Values

    The method preserve the global maximum and minimum value, in together with one of the following methods:

  • Quantile (default): -m  71
  • Equal interval: -m  72
  • Neighbors: -m  73
  • aChor PlugIn repository for Task-oriented data Classification of
    Choropleth Maps (on GitLab)

    Funding is provided by the German Research Foundation (DFG).


    See all projects