Malaysia has experienced various disasters either natural or manmade disaster. One of the critical phases in Disaster Management System life cycle is response phase. In this phase, connectivity analysis such as a navigation service to help emergency rescue (ER) units reach at disaster area on time is necessary. Nowadays, commercial navigation system seems not appropriate to be used by ER units as they have different preferences. In addition, location information that is vital was not fully utilized in disaster management, especially in doing multi-task analysis. Thus, the real potential of GIS technology in managing spatial data including real-time (moving objects) data of ER units may influence the quality of the service. However, the services should be supported by a good data model. In order to eliminate inappropriate information, incomplete data, and overloaded information from Database Management System (DBMS) sent to the user, this paper will present the framework of integrated routing application for emergency response units embedded with context-aware.

<span id="docs-internal-guid-9754d3d8-7fff-a7d2-6605-1c8f8c5a707a"><span>The classification method in the spatial analysis modeling based on the multi-criteria parameter is currently widely used to manage geographic information systems (GIS) software engineering. The accuracy of the proposed model will play an essential role in the successful software development of GIS. This is related to the nature of GIS used for mapping through spatial analysis. This paper aims to propose a framework of spatial analysis using a hybrid estimation model-based on a combination of multi-criteria decision-making (MCDM) and artificial neural networks (ANNs) (MCDM-ANNs) classification. The proposed framework is based on the comparison of existing frameworks through the concept of a literature review. The model in the proposed framework will be used for future work on the traffic accident-prone road classification through testing with a private or public spatial dataset. Model validation testing on the proposed framework uses metaheuristic optimization techniques. Policymakers can use the results of the model on the proposed framework for initial planning developing GIS software engineering through spatial analysis models.</span></span>

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