A QGIS Plugin to perform Hotspot analysis based on the Python Spatial Analysis Library - PySAL.

The Hotspot analysis plugin associate the Z-scores and p-values (under Complete Spatial Randomness hypothesis) of the Gi* local statistic (Getis and Ord, 1992) for each feature of shapefile (points), with an assigned projected coordinate system and an associated positive numerical attribute. Output layer enables to indentify hotspots (or coldspots) in the input dataset as well as their statistical significance.

Positive and statistically significant Z-score indicates intense cluster of high values (hotspot). Negative and statistically significant Z-score indicates intense cluster of low values (coldspot).

Spatial relation between features is modeled using a Fixed Distance Band (expressed with the same unit of measure of the projected coordinate system of the input shapefile), which allows to compute Gi* for any element by considering its neighborhoods within this fixed distance. For more information, please refer to: Geospatial Analysis - 5th Edition, 2015 - de Smith, Goodchild, Longley

Dependency Requirements:

• PySAL
• Numpy
• Scipy

These libraries are not included in the QGIS core libraries and must be installed prior to the use of the plugin through the OSGeo4W Shell on Windows, or through terminal on Ubuntu and macOS (see the following).

Download get-pip.py , to enable PIP functionalities, which is available at this link: https://bootstrap.pypa.io/get-pip.py

Open OSGeo4W Shell as Administrator and change the working directory where the get-pip.py file is stored and type :

 $ python get-pip.py

(Further information regarding PIP installation can be found in: https://packaging.python.org/en/latest/installing/#install-pip-setuptools-and-wheel)

Download the following packages according to your Python version and your Operating System characteristics:

Numpy : https://pypi.anaconda.org/carlkl/simple/numpy/

Scipy : https://pypi.anaconda.org/carlkl/simple/scipy/

Note: for example, in the filename "numpy-1.10.0b1-cp34-none-win_amd64.whl " cp34, amd64 depicts python 3.4 and 64 bit Operating System

Change the directory to where the downloaded packages are stored and type the following commands:

 $ pip install numpypackagename
 $ pip install scipypackagename

Note: extension must be included with the filename

 $ pip install pysal

Download or clone the GitHub repository given below into QGIS Python Plugins folder: https://github.com/stanly3690/HotSpotAnalysis_Plugin/archive/master.zip

Note: default Plugins folder is:

 $ cd C:\Users\<your_user_name>\.qgis2\python\plugins

Open QGIS:

Go to Plugins -> Manage and Install plugins -> Settings -> Show also experimental plugins

In All plugins tab, look for HotSpotAnalysis and tick the checkbox.
A new icon for Hotspot Analysis will appear on the QGIS main panel.

Open a Terminal and type the commands:

 $ sudo apt-get install python-numpy
 $ sudo apt-get install python-scipy 

To install PySAL:

 $ sudo pip install pysal

Change directory to QGIS Plugins directory, default is :

 $ cd /usr/share/qgis/python/plugins 

Clone the GitHub repository into the earlier mentioned path:

 $  sudo git clone https://github.com/stanly3690/HotSpotAnalysis_Plugin 

Then Open QGIS:

Go to Plugins -> Manage and Install plugins -> Settings -> Show also experimental plugins

In All plugins tab, look for HotSpotAnalysis and tick the Checkbox.
A new icon for Hotspot Analysis will appear on the QGIS main panel.

If you installed QGIS on your machine using this source : http://www.kyngchaos.com/software/qgis , you would find the required dependencies (Numpy - Scipy - Pysal) in the list of the Optional Python Modules. You can install them directly from here: http://www.kyngchaos.com/software/python (strongly suggested)

Otherwise, open a Terminal and type the commands:

 $ sudo pip install numpy
 $ sudo pip install scipy 
 $ sudo easy_install pysal

Change directory to QGIS Plugins directory, default is:

 $ cd ~/.qgis2/python/plugins

Open the folder:

 $ open . 

Download and copy here the unzipped repository folder (suggested): https://github.com/stanly3690/HotSpotAnalysis_Plugin/archive/master.zip

or Clone the GitHub repository into the earlier mentioned path:

 $  sudo git clone https://github.com/stanly3690/HotSpotAnalysis_Plugin 

Then Open QGIS:

Go to Plugins -> Manage and Install plugins -> Settings -> Show also experimental plugins

In All plugins tab, look for HotSpotAnalysis and tick the Checkbox.
A new icon for Hotspot Analysis will appear on the QGIS main panel.

A demo exercise with the new plugin version here: https://github.com/stanly3690/HotSpotAnalysis_Plugin/blob/master/test_data/Hotspot_Analysis_UserGuide.pdf

An example of plugin application is available here: https://peerj.com/preprints/2204/

Plese cite this as:

Oxoli D, Zurbarán MA, Shaji S, Muthusamy AK. (2016) Hotspot analysis: a first prototype Python plugin enabling exploratory spatial data analysis into QGIS. PeerJ Preprints 4:e2204v4 https://doi.org/10.7287/peerj.preprints.2204v4

Presentation slides are available here: https://www.slideshare.net/mobile/danieleoxoli/hotspot-analysis-ogrs2016

Note: this material is based on the old version of the plugin!

#####Annuncement 12/2016 New check botton to eneable the usage of row standardized spatial weights

#####Annuncement 11/2016 With this new version, the output layer is displayed with an automatic style which enables hotspot and coldspot visualization. Moreover, a default Fixed Distance Band is dispalyed. This latter represents the minimum distance to ensure at least 1 neighbor to any element of the dataset in order to compute spatial weights for Gi*

#####Annuncement 10/2016 The current version does not require Pyshp as well as to specify the feature coordinates as two separate fields in the attribute table of the input shapefile. Only the numerical attribute must be included and selected using the graphical interface on QGIS. Nevertheless, be sure that your input shapefile is projected. The unit of measure in which you express the analysis distance must agree with the one of the projected coordinate system of your input layer.

###Future work

• Enable users to run hotspot analysis on polygonal grid or multipolygon shapefile
• Introduce Local Moran's I and Bivariate Local Moran's I computation

Bug tracker and Wiki

HotSpotAnalysis-plugin is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version

Copyright © 2016 Stanly Shaji/ Daniele Oxoli/ Mayra Zurbaràn/ Gabriele Prestifilippo - Politecnico Di Milano.

E-mail: [email protected]