Real estate contributes significantly to all major economies around the world. In particular, house prices have a direct impact on stakeholders, ranging from buyers financing companies. Thus, plethora of techniques been developed for real price prediction. Most existing rely different features build variety prediction models predict prices. Perceiving effect spatial dependence prices, some late...

An explosion of interest has been observed in disease mapping with the developments advanced spatial statistics and increasing availability computerized geographic information system (GIS) technology. This technique is known as “Disease Clustering” using this for future prediction termed “Geo-Spatial Disease Clustering”. Government, Medical Institutes, other medical practices gather large amoun...

Knowledge discovery in databases is a process that aims at the discovery of associations within data sets. The analysis of geo-referenced data demands a particular approach in this process. This chapter presents a new approach to the process of knowledge discovery, in which qualitative geographic identifiers give the positional aspects of geographic data. Those identifiers are manipulated using...

The need to geo-spatial data in different applications particularly for knowledge-based sustainable development is considerable. However, various problems encountered with production, dissemination and accessing geo-spatial data makes users to face with many difficulties when intending to use them. Spatial Data Infrastructure (SDI) is introduced as a solution to these problems. Success of an SD...

Security has recently become a major concern in distributed geo-infrastructures for spatial data provision. Thus, a lightweight approach for securing distributed low-power environments such as geo-sensor networks is needed. The first part of this article presents a survey of current security mechanisms for authentication and authorisation. Based on this survey, a lightweight and scalable token-...

In this paper we explore the advantages of using Self-Organized Maps (SOMs) when dealing with geo-referenced data. The standard SOM algorithm is presented, together with variants which are relevant in the context of the analysis of geo-referenced data. We present a new SOM architecture, the Geo-SOM, which was especially designed to take into account spatial dependency. The strengths and weaknes...