The Internet of Things (IoT) is the concept of everyday objects that make us live in the era of the IoT. The spatial characteristics of things around us can be considered the reins of the IoT operability. In other words, the spatial variation of a thing can be the core of the IoT reaction. For example, the spatial variation in crop indicates the requirement and characteristic of agriculture production. Also, the spatial variation of a human movement can alarm the security and monitoring systems. This issue agitates the contemplating of the ''Internet of Spatial Things (IoST)'' concept. For the first time, this paper draws an inspiration towards the perspective vision of the IoST, which is concerned with revise IoT with the spatial perspective. The IoST concept is argued by the presentation of its definition and architectural components. Besides, the IoST layers are discussed in details. Furthermore, a new proposed reference model of the IoST is proposed. Finally, the new trends and open issues regarding the IoST are aroused. INDEX TERMS Internet of Things (IoT), Internet of Spatial Things (IoST), spatial, framework.

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Geographic Information Systems (GIS) have become a fact of our life as they are being used by more people and organizations for more complex decision problems than ever before. The use of GIS can achieve valuable benefits for individuals, organizations and society; however, the achievement of these benefits depends on the success of GIS. While information systems (IS) success models have received much attention among researchers, there is a general scarcity of research conducted to measure the GIS success. This paper proposes a success model for measuring GIS success by extending and modifying previous IS success models. The developed success model consists of two main levels: GIS project diffusion success, and GIS post-implementation success. The first level identifies the critical success factors (CSFs) that influence the success of GIS adoption at each stage of the diffusion process. The second level of the proposed model identifies and organizes the success dimensions (outcome measures) of GIS in temporal and causal relationships. In order to assess the relationships among the success dimensions, 11 hypotheses were tested. Data were collected through a questionnaire that was distributed to 252 GIS users/managers in Egypt and abroad. The empirical results support 6 hypotheses and reject 5 hypotheses.

Six GIS-based spatial interpolation methods were compared to determine their suitability for estimating mean monthly air temperature (MMAT) surfaces, from data recorded at nearly 31 meteorological stations representing different climatic conditions in Western Saudi Arabia. The eventual purpose of producing such surfaces is to help making air temperature data be available for a wide variety of scientific uses. The interpolation techniques included four deterministic methods (Inverse Distance Weighted, Global Polynomial, Local Polynomial, and Radial Basis Function (Thin-Plate Spline) and two geostatistical methods (Ordinary Kriging, and Universal Kriging). Quantitative assessment of the continuous surfaces showed that there was a large difference between the accuracy of the six interpolation methods and that the geostatistical methods were superior to deterministic methods. This work also revealed systematic spatial and temporal variations of temperatures in western Saudi Arabia.