Bayesian is a belief network that is a probabilistic graphical model that deals with reasoning under uncertainty (e.g. determining the probabilities of a disease based on the symptoms).

Automated Remote Sensing of Underground Features

Mark Altaweel

Below ground mapping can now better utilize remotely sensed data to create more accurate maps.

Conceptual framework and BBN building process using inputs from GIS layers. Image: Gonzalez-Redin et. al, 2016.

GIS and Bayesian Belief Networks

Mark Altaweel

Bayesian belief networks (BBN) and GIS can be used as decision aides to give an idea of probability of events unfolding.

GIS and Stratified Heterogeneity

Mark Altaweel

A method to measure uneven distribution of landscape or population features in a given space is stratified heterogeneity.

Using R with GIS Software

Mark Altaweel

With the utility of R, many popular statistical procedures and more advanced analyses, including a variety of simulation applications, can be applied directly within GIS tools such as QGIS.

From Davies et al., 2016: "the results show good qualitative agreement, with 26 of the 33 boroughs showing rioter percentages in the same or adjacent bands as the data. The remaining discrepancy may be accounted for by factors specific to the London disorder, such as communication between groups, other activity patterns occurring at the time, or social factors beyond the scope of this work. "

GIS and Anti-Crime Measures

Mark Altaweel

This article takes a look at methods which demonstrate the wide and growing field of crime prevention utilizing spatial and GIS approaches.

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