Application of Agent-Based Modelling (ABM) and Geographical Information System (GIS) for Analysing and Predicting Crime Patterns
In recent years, the Malaysian agencies and authorities have become interested in understanding crime behaviours using crime mapping techniques. Crime is seen in all cities in Malaysia but understanding crime is extremely complex as it is highly diverse and has many causes. A greater understanding of such phenomena is crucial for improving polices and developing effective crime prevention strategies. The use of Agent-Based Modelling (ABM) allows one to study individuals who are involved in each crime event and how these individuals interact with each other and their environment. The virtual environment can be modelled using Geographical Information System (GIS) and it can be made as realistic as possible by incorporating geospatial data for the area of study. The aim of this research is to predict the crime patterns occurence base on location, time and types by using ABM and GIS techniques. The research has been supported by Insitut Sosial Malaysia and the result will be used to help in producing a policy for the government in combacting crime.
Automated Credibility Assessment of Volunteered Geographic Information (VGI) for Flood Hazard Management
Within the framework of Web 3.0 mapping applications, the information can be collected by volunteers, store on a database and distributed in multiple digital formats through the World Wide Web. This type of information was termed ‘Volunteered Geographical Information’ (VGI) by Goodchild (2007). Volunteer’s participation in data collection is playing an increasingly important role in the management of emergency events due to the adoption of mobile and Internet technologies. However, to date there has been no automated and systematic framework for credibility analysis of VGI. The research explores solutions for challenges facing the usage of VGI in hazard management by investigating current tools for assessing VGI, which can be used for flood hazard management. To fulfill the goal the research focuses on two main parts; in the first step data about flood would be collected from volunteers, second by classifying the data which are more related to flood will be analyzed to qualify its credibility through a filtering to the datasets by statistics, geostatistics and content analysis. The result of this research will aid in exploiting the hidden potential of VGI in flood hazard management, also the decision makers will be able to monitor developmental activities to reduce risk and damage. Which would prove that the use of Web 3.0 technologies such as social media and map mashups to be effective for gathering and disseminating geospatial data to members of the public.