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Maritime traffic prediction is a crucial task for increasing the efficiency of port operations and safety, especially in congested regions. A huge amount of automatic identification system (AIS) da...

Recommender systems (RS), as supportive tools, filter information from a massive amount of data based on the determined preferences. Most of the RS require information about the context of users su...

Iran, as a seismic country, is situated over the Himalayan-Alpied seismic belt and has faced many destructive earthquakes throughout history. Therefore, it is very important to evaluate the possible damage to the existing infrastructure based on statistical and spatial analysis. In this study, a new model is developed to analyse seismic damages based on seismic hazard assessment and extraction of the vulnerability function for all features of fuel infrastructure. To consider uncertainty analysis in the model, Monte Carlo simulation is used based on 10,000 iterations. The results of hazard analysis indicated that peak ground acceleration is about 0.18 g and there is slight to moderate damages to the desired fuel infrastructure in the study area. Moreover, sensitivity analysis is also performed to determine how median, standard deviation (or beta), grid size, attenuation relationships, liquefaction and landslide susceptibility impact the seismic loss. Last but not least, the effect of input parameters of earthquake scenarios including magnitude, focal depth and focal distance are also analysed in conjunction with regression analysis. The results of the study show that magnitude and focal distance are the most sensitive parameters in which the expected damage to the fuel infrastructure is reduced by about 25% if the epicentre of the earthquake is moved from 10 to 25 km.

Analyzing the spatial behaviors of moving-point objects (MPOs) and discovering their movement patterns have been of great interest to the geographic information science community recently. These interests can be explored through analyzing similarities in the MPO trajectories. Because movements of objects take place in various contexts, their trajectories are also highly influenced by such contexts. Therefore, it is essential to fully understand the contexts and to realize how they can be incorporated into movement analysis. This article first proposes a taxonomy for contexts. Then, a modified version of dynamic time warping called context-based dynamic time warping (CDTW) is introduced, to contextually assess the multidimensional weighted similarities of trajectories. Ultimately, the results of similarity searches are utilized in discovering the relative movement patterns of the MPOs. To evaluate the performance and effectiveness of our proposed CDTW method, we run several experiments on real datasets tha...

Urban sprawl has become a remarkable feature in urban development, especially in developing countries, in the last decades. To face this phenomenon, it is required to first forecast auto-spreading ...

Advances in GIS and databases for dealing with spatiotemporal frameworks are leading to efficient querying, analyzing, and reasoning about moving objects/agents. However, contemporary frameworks on spatiotemporal logics are usually limited to qualitative approaches, such as the numerous studies on spatiotemporal databases that focus on observations, ignoring the intended movements of the agents. Moving object databases, on the other hand, can handle queries about the location, velocity, and time by assuming some agents to be targets. However, reasoning about the plan of moving agents, especially on the network and the achievability of such a plan, still remains a challenge. Studies on vehicle routing are often about the centralized planning of moving agents from scratch and do not deal with intended plans. Based on a plain move predicate, this paper presents a generic framework that can be used for representing and reasoning about plans of moving agents. Concepts from motion, network structure, graph theory, predicate logic, and constraint satisfaction are used to create the framework. We have also provided efficient algorithms for checking the consistency of the movement and extracting compatible plans along with some discussions on computational analysis, logical deduction, and flexibility. Finally, we have demonstrated the application of the methodology by developing NETwork-based Move Atoms Planning System NETMAPS. The experiments show how NETMAPS can overcome an inconsistent movement plan and deliver advantageous suggestions to an executive agent.

Structured study of spatial objects and their relationships leads to a better cognition of the geospatial information and creates the concept of context at a higher level of abstraction. This study is aimed at providing a comprehensive definition of the context for geospatial objects. A combination of binary qualitative spatial relationships (i.e. direction, distance, and topological relations) among the members of a set of spatial objects will be used accordingly. In addition, by incorporating the general concept of context, obtained from either static data (attributes in a database) or dynamic data (sensors), the compact context of spatial objects will be introduced. Our framework for presentation of the involved knowledge and conception about the objects in context is also explored using ontology and description logic because of powerful conceptualization of relationships, either spatial or non-spatial, integrally. For this purpose, the hierarchies of main structure and object properties are formed at ...

Virtual representation and simulation of spatio-temporal phenomena is a promising goal for the production of an advanced digital earth. Spread modeling, which is one of the most helpful analyses in the geographic information system (GIS), plays a prominent role in meeting this objective. This study proposes a new model that considers both aspects of static and dynamic behaviors of spreadable spatio-temporal in cellular automata (CA) modeling. Therefore, artificial intelligence tools such as adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA) were used in accordance with the objectives of knowledge discovery and optimization. Significant conditions in updating states are considered so traditional CA transition rules can be accompanied with the impact of fuzzy discovered knowledge and the solution of spread optimization. We focused on the estimation of forest fire growth as an important case study for decision makers. A two-dimensional cellular representation of the combustion ...

This study proposes a solution for the topological representation and interpretation of moving regions under vagueness in a geographic information system (GIS). The problem is multifaceted, and different aspects will be discussed. We investigate the impact of several types of fuzzy logic on results and address which is more convenient for the region connection calculus under fuzziness (FRCC). By recognising that the main and basic relation to evaluate topological relations is the connection relation, we adopt a qualitative strategy based on fuzzy inference and resemblance relations. We also define topological differences and introduce fuzzy transition relations (FTRs) to distinguish how a transition from one topological situation to another occurs for a pair of objects during a time period. As pure topological relations are not sufficient for a complete qualitative perception, an orientation-based method (OBM) will be proposed. Using this method, we can interpret, for example, a region that partially over...

The GIS-T (Geographic Information System for Transportation) dynamic segmentation (DS) technique can be effectively employed by pavement management systems (PMS) to provide more detailed information on road conditions by using the segments. In most cases, segments present attributes that change frequently either spatially or non-spatially. In order to ensure correct and successful decision-making processes in transportation-related activities, regular updates and revision of segmented data are essential. Manual updating of the segmented data is a complex and time-consuming process. Thus, it is highly beneficial to provide an easy and efficient way to update segments. This paper presents a rule-based method for automatic updating of road segments using the DS technique. The proposed approach was implemented for the Road Maintenance and Transportation Organisation (RMTO) of Iran on road network data of Tehran city. The experimental results indicate many useful aspects of this approach that made it efficient...

The appearance of the semantic web has caused an ever-increasing use of ontologies as formal tools to represent knowledge explicitly in various applications. Since data integration is an essential part of information systems, ontology alignment is becoming more important in the web world. Moreover, applications on the web such as agents need to fuse information automatically and on-the-fly. This paper presents a methodology to automate spatial ontology alignment. In this paper, linguistic scales and extensional information of ontologies as demonstrators of concept semantics along with the structural information of ontologies are used to discover semantic correspondences in a new way. A procedure to compose results from extensional and intensional approaches is presented and error sources and fusion issues are highlighted. The methodology is tested on a case study, which is related to two ontologies containing road data. The results of the ontology alignment indicate a precision of 0.81, and a recall of 0....

Numerous classification algorithms have been developed, many of which are highly specific and only solve a reduced class of problems. Maximum likelihood classification (MLC) is the most widely used classification method. The underlying assumption in performing MLC is that the prior probability of land cover is equal. However, a priori occurrence probability has a crucial effect on classification results. The objective of this paper is to improve the accuracy of MLC using a priori information in a knowledge-based system. The mathematical formulations and the strategy are presented. Estimates of a prior probability through crop areas, crop calendar, and some a priori probability about agricultural practices have been used in augmenting the probability of pixels. An industrial agricultural field, Moghan Plain in northwestern Iran, has been selected for testing. A total of 176 ground truth points were identified and measured in the field, and 323 fields were used for accuracy evaluation. Prior probabilities w...