Geo-information quality assurance in disaster management

Abstract

Disaster management depends on large volumes of comprehensive, accurate, relevant, on-time geo-information that various organizations systematically create and maintain. One cannot assure geo-information quality (G-IQ) without first being able to measure it meaningfully and establishing a causal connection between the source of G-IQ change, the G-IQ problem types, the types of activities affected, and their implications. In this article we propose a G-IQ assurance framework. In contrast to context-specific IQ assurance models, which usually focus on a few variables determined by local needs, our framework consists of comprehensive typologies of IQ problems, related activities, and a taxonomy of IQ dimensions organized in a systematic way based on semiotic theories and practices. The framework can be used as a knowledge resource and as a guide for developing G-IQ measurement models for many geo-information technologies which can offer a variety of opportunities to aid management and recovery in the aftermath of disasters. The framework was validated and refined by enhancing G-IQ generated by remote sensing through the technologies of photogrammetry.