Application of Gis in Road Classification Case Study: Kiambu County

Abstract

Effective infrastructure is a key precondition for sustainable national economic and social growth. Roads play a significant role in economic development. Understanding the global road classification characteristics could help countries to efficiently manage their roads. Road classification has not been done adequately due to the many challenges that exists: the classification process has evolved or was developed as a one-off exercise. As a result, there is little available documentation guiding classification procedures. In Kenya, the road classification guidelines were done in 2009 and after that a new constitution came into place and the guidelines and standards have not been revised. The guidelines and the manuals are implemented manually by officers in the relevant authority and hence road classification processes tend to be biased. The main study objective was to carry out road classification using GIS. Specifically, it sought to identify the criteria used to do road classification, create a GIS model that will classify roads and finally compare automatically classified roads with the manually classified roads. The achieved results include a list of criteria for road classification and a GIS Model used to carry out road classification. Also, a map showing the classified roads and subsequent comparison maps showing road classes A to F have been created. A total of 1858 km were automatically classified in Classes A, B, C, D, E and F which accounts for 34.5% of the total gazetted roads. The results show that some roads automatically classified in Classes A, D and E had been omitted yet they met the criteria. Classes D and E were the most affected. Some roads automatically classified in Classes B, C and F had been elevated yet they did not meet the criteria, Class C being the most affected. The results reveal that during manual classification there is either inclusion of roads that do not meet the criteria or omission of roads that meet the criteria. This was understood to mean that there is bias in the manual system since the judgement of classification is not scientific. The GIS spatial modelling techniques can be used to consider and integrate various criteria resulting into informed decisions which help avoid bias in the road classification process. To achieve sustainable development in the roads sector, the roads geodatabase should be updated and well maintained by road authorities since it is key in making informed decision.