Mobile GIS for enhanced property tax collection: a case of Lusaka province local authorities
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Property tax is a means of raising the much-needed revenue for local authorities in Zambia. However, the local authorities are faced with problems of identifying and capturing properties that qualify for property tax. This has resulted in them having a significant number of properties that are not assessed and in the process depriving them of the finances that they require to provide basic services to the communities in their jurisdictions. The aim of this study was to develop a prototype field based GIS Application that local authorities can use to identify and capture properties and create a database that will provide knowledge of rateable properties in their localities for the efficient collection of property tax. A study was carried out in four local authorities in Lusaka province to assess the current methods used to identify and capture properties and to investigate the challenges that are experienced. The literature revealed that low levels of property tax collection are also experienced in other developing countries and attempts that have been made to develop software applications to help in property identification and tax collection have used expensive software development tools, and the systems developed lacked real time field based features. The methodology used in the study involved a ground truth exercise that was conducted in four local authorities and one planning authority in Lusaka province. Purposive homogenous sampling was used and 40 questionnaires were administered to staff in senior and middle management involved in the property tax administration process. In addition, structured interviews were used for the purposes of understanding the current procedures and processes. The developed field based GIS Application has features that allow the capture of property spatial, attribute and image data. It was was designed to run on the Andriod operating system version 4.3 and above. The application was trialed in the field in Parkview Estates of Kafue local authority in realtime using a laptop computer and a mobile phone. The mobile device’s Internet speed and the saving of the property attribute, spatial and image data on the laptop using the phone’s WIFI (802.11 b/g/n) did not manifest any adverse latency during the mapping sessions. The latency was less than 100 milliseconds (0.10 seconds) on average. Ten properties were successfully mapped during the trial and the design of the system successfully met the user requirements that were formulated.
The University of Zambia
- Natural Sciences