Providing a framework for risk assessment in Geographic Information Systems (GIS) and Corporate Spatial Data Infrastructure (SDI) based on fuzzy logic

Kalantari Oskuei, Ali; Modiri, Mahdi; Alesheikh, Aliasghar; Hosnavi, Reza

Providing a framework for risk assessment in Geographic Information Systems (GIS) and Corporate Spatial Data Infrastructure (SDI) based on fuzzy logic

Document Type : Original Article

Authors

Ali Kalantari oskuei ¹

Mahdi Modiri ²

Aliasghar Alesheikh ³

Reza Hosnavi ⁴

¹ PhD Student in GIS (Geographic Information System), Department of Civil Engineering Surveying, Malek ashtar University of Technology, Tehran, Iran.

² Assoc. prof., Malek ashtar University of technology, Tehran, Iran.

³ Professor, Geomatics Engineerig Faculty, K.N.Toosi University of technology, Tehran, Iran.

⁴ Associate professor, Malek ashtar University of technology, Tehran, Iran.

Abstract

Efficient use and access to spatial data in the country need design and implementation of Geographic Information System (GIS) and Spatial Data Infrastructure (SDI). In this regard, every year numerous GIS projects are designed and implemented and recently developing spatial data infrastructures has also been considered by organizations. What seems in performing these activities has been neglected, is the lack of measures to avoid or reduce risks associated with them. Risk assessment is associated with the ambiguity and uncertainty and Fuzzy logic terminology is one of the procedures that can be used for achieving the uncertainties due to risk modeling and simultaneously helps researcher classify them. This paper presents a framework based on fuzzy logic, to study SDI/GIS risks as an integrated tool for Agricultural Organization of East Azarbaijan province. In order to conduct this research, 34 questionnaires were distributed. The risk factors were extracted from experts' opinions and then the identified risks, based on both classical and fuzzy methods were analyzed. The results showed that lack of server/backup risk has the highest risk (risk value =0.8) and insufficient funds ranked second (risk value=0.76). Also among the 10 superior ranked risks, it was observed that, the type of administrative and management risks were contributed from the majority of the cases.

Keywords

Fuzzy logic

Jahade Keshavarsi

Modeling

Spatial data

Threat