Development and implementation of a GIS-based tool for spatial modeling of seismic vulnerability of Tehran

Achieving sustainable development in countries prone to earthquakes is possible with taking effective measures to reduce vulnerability to earthquakes. In this context, damage assessment of hypothetical earthquakes and planning for disaster management are important issues. Having a computer tool capable of estimating structural and human losses from earthquakes in a specific region may facilitate the decision-making process before and during disasters. Interoperability of this tool with wide-spread spatial analysis frameworks will expedite the data transferring process. In this study, the earthquake damage assessment (EDA) software tool is developed as an embedded extension within a GIS (geographic information system) environment for the city of Tehran, Iran. This GIS-based extension provides users with a familiar environment to estimate and observe the probable damages and fatalities of a deterministic earthquake scenario. The productivity of this tool is later demonstrated for southern Karoon parish, Region 10, Tehran. Three case studies for three active faults in the area and a comparison of the results with other research substantiated the reliability of this tool for additional earthquake scenarios

VGI BASED URBAN PUBLIC TRANSPORT

Recent advances in information technology have made geographic information system (GIS) a powerful and affordable tool for planning and decision making in various fields such as the public transportation. These technologies such as the social network (e.g. face-book, twitter), new technologies such as ubiquitous, mobile, Web 2.0, geo tagging and RFID can help to create better shapes and forms of the communication and geo-collaboration for public. By using these, user-generated content and spatial information can be easily and quickly produced and shared in a dynamic, interactive, multimedia and distributed environment. The concept of volunteered geographic information (VGI) has been introduced by the transaction from consultation to content interaction. VGI describes any type of content that has a geographic element and has been voluntarily collected. In other words, ordinary users; without a professional training, can participate in generating and using the spatial information. As a result, the gaps between the producers and users of GIS and spatial information, has been considerably reduced. Public transportation is one of the most important elements of the transportation system. Rapid growth of the cities has resulted in high increase of demand for the public transportation which created new challenges. Improvement of the desirability of public transportation can increase its efficiency, reduction of the environmental pollution (such as air and noise pollution), traffic problems, and fuel consumption. Hence, development of an urban public transportation system which is responsive to citizen's need and motivates them to use public transportation system is one of the most important objectives and issues that urban planners and designers are concerned about. One solution to achieve this, goal is to develop public transportation system by assistance from the system users. According to approach, users are considered as the valuable resources, because people who are in constant contact with the system can have detailed and updated information about the problems, solutions and they are affected by the related implemented policies. Thus user involvement is an essential part in public transport decision making process. Although GIS in transportation (GIS-T) has been used for data collection, spatial analysis, and spatial modeling, due to recent promotions, GIS-T is moving towards the use of capabilities of VGI to user-centric services. The main goals of this paper are two as follows: First is to survey and review the key concepts of the geo-collaboration, to introduce and present fields to utilizing the VGI in the public transportation system to improve the performance of that system. The Second goal is to propose a VGI-based public transport conceptual framework. in this paper in the first part capabilities of VGI is explored, and areas of public transport that can utilize the public involvement is assessed and classified. Then, by surveying the related works in this context, a classification based on the models of participation is provided. Finally, a VGI-based conceptual framework for organizing a public participation for performance measurement of urban public transport for Tehran city is proposed. Results of this paper show that utilizing VGI presents an efficient solution for public transport problems

Coastline shift analysis in data deficient regions: Exploiting the high spatio-temporal resolution Sentinel-2 products

In most developing countries, coastline shift monitoring using in-situ (ground-based) data faces challenges due, e.g., to data unreliability, inconsistency, deficiency, inaccessibility or incompleteness. Even where practically applicable, the traditional “boots on the ground” methods are labour intensive and expensive, thus imposing burden on poor countries struggling to meet other urgent pressing daily needs, i.e., food and medicine. Remote sensing (RS) techniques provide a more efficient and effective way of collecting data for coastline shift analysis. However, moderate spatio-temporal resolution RS products such as the widely used Landsat products (30 m and 16 days) may be insufficient where high accuracy is desired. In 2015, Sentinel-2 Multi-Spectral Instrument (MSI) remotely sensed products with higher spatio-temporal resolution (10 m and 5 days) and high spectral resolution (13 bands), which promises to improve coastline movement monitoring to high accuracy, was launched. Using two war-impacted countries (Liberia and Somalia) as case studies of regions with data deficiency or of poor quality, for the period 2015–2018, this contribution aims at (i) assessing the suitability of the new freely available high spatio-temporal Sentinel-2 products to monitor coastline shift, (ii) assessing the possibility of filling the missing Sentinel-2 gaps with Landsat 8 panchromatic band (15 m) products to provide alternative data source for mapping of coastline movements where Sentinel-2 data is unusable, e.g., due to cloud cover, and (iii), undertake a comparative analysis between Sentinel-2 (10 m), Landsat panchromatic (15 m), and Landsat multi-spectral (30 m). The results of the evaluation indicate 23% (on average) improvement gained by using Sentinel-2 compared to the traditional Landsat 30 m resolution data (i.e., 32% for Liberia and 14% for Somalia). A comparison of 100 check points from Google Earth Pro (i.e., surrogate in-situ reference data) show 91% agreement for Liberia and 85% for Somalia, indicating the potential of using Sentinel-2 data for future coastal shift studies, particularly for the data deficient regions. The results of comparative studies for Sentinel-2, Landsat panchromatic (PAN), and Landsat multi-spectral (MS) show that the percentages of Sentinel-2 and Landsat PAN that falls within 10 m threshold is much higher than Landsat MS by 35% and 26%, respectively, and for the 2016–2017 period, they provide more detailed mapping of the Liberian coastline compared to Landsat MS (30 m). Finally, panchromatic Landsat data with 15 m resolution are found to be capable of filling the missing Sentinel-2 gaps, i.e., where cloud cover hampers its usability

INTRODUCING AN AGENT-BASED OBJECT RECOGNITION OPERATOR FOR PROXIMITY ANALYSIS

Object selection is a basic procedure in a Geographic Information System (GIS). Most current methods for doing so, select objects in two phases: create a simple distance-bounded geometric buffer; and intersect it with available features. This paper introduces a novel and intelligent selection operator based on the autonomy of the agent-based approach. The proposed operator recognizes objects around one object only in one step. In the proposed approach, each point object acts as an agent-automata object. It then senses its vicinity and identifies the surrounding objects. To assess the proposed model, the operator is designed, implemented, and evaluated in a case study. Finally, the results are evaluated and presented in details in the paper

DEVELOPING A SPATIAL PROCESSING SERVICE FOR AUTOMATIC CALCULATION OF STORM INUNDATION

With the increase in urbanization, the surface of earth and its climate are changing. These changes resulted in more frequent floodingand storm inundation in urban areas. The challenges of flooding can be addressed through several computational procedures. Due to its numerous advantages, accessible web services can be chosen as a proper format for determining the storm inundation. Web services have facilitated the integration and interactivity of the web applications. Such services made the interaction between machines more feasible. Web services enable the heterogeneous software systems to communicate with each other. A Web Processing Service (WPS) makes it possible to process spatial data with different formats. In this study, we developed a WPS to automatically calculate the amount of storm inundation caused by rainfall in urban areas. The method we used for calculating the storm inundation is based on a simplified hydrologic model which estimates the final status of inundation. The simulation process and water transfer between subcatchments are carried out respectively, without user’s interference. The implementation of processing functions in a form of processing web services gives the capability to reuse the services and apply them in other services. As a result, it would avoid creating the duplicate resources

MULTI-DIMENSIONAL PATTERN DISCOVERY OF TRAJECTORIES USING CONTEXTUAL INFORMATION

Movement of point objects are highly sensitive to the underlying situations and conditions during the movement, which are known as contexts. Analyzing movement patterns, while accounting the contextual information, helps to better understand how point objects behave in various contexts and how contexts affect their trajectories. One potential solution for discovering moving objects patterns is analyzing the similarities of their trajectories. This article, therefore, contextualizes the similarity measure of trajectories by not only their spatial footprints but also a notion of internal and external contexts. The dynamic time warping (DTW) method is employed to assess the multi-dimensional similarities of trajectories. Then, the results of similarity searches are utilized in discovering the relative movement patterns of the moving point objects. Several experiments are conducted on real datasets that were obtained from commercial airplanes and the weather information during the flights. The results yielded the robustness of DTW method in quantifying the commonalities of trajectories and discovering movement patterns with 80 % accuracy. Moreover, the results revealed the importance of exploiting contextual information because it can enhance and restrict movements

ASSESSMENT OF COMPLETENESS AND POSITIONAL ACCURACY OF LINEAR FEATURES IN VOLUNTEERED GEOGRAPHIC INFORMATION (VGI)

Recent advances in spatial data collection technologies and online services dramatically increase the contribution of ordinary people to produce, share, and use geographic information. Collecting spatial data as well as disseminating them on the internet by citizens has led to a huge source of spatial data termed as Volunteered Geographic Information (VGI) by Mike Goodchild. Although, VGI has produced previously unavailable data assets, and enriched existing ones. But its quality can be highly variable and challengeable. This presents several challenges to potential end users who are concerned about the validation and the quality assurance of the data which are collected. Almost, all the existing researches are based on how to find accurate VGI data from existing VGI data which consist of a) comparing the VGI data with the accurate official data, or b) in cases that there is no access to correct data; therefore, looking for an alternative way to determine the quality of VGI data is essential, and so forth. In this paper it has been attempt to develop a useful method to reach this goal. In this process, the positional accuracy of linear feature of Iran, Tehran OSM data have been analyzed

INCORPOARATION OF GEOSENSOR NETWORKS INTO INTERNET OF THINGS FOR ENVIRONMENTAL MONITORING

Thanks to the recent advances of miniaturization and the falling costs for sensors and also communication technologies, Internet specially, the number of internet-connected things growth tremendously. Moreover, geosensors with capability of generating high spatial and temporal resolution data, measuring a vast diversity of environmental data and automated operations provide powerful abilities to environmental monitoring tasks. Geosensor nodes are intuitively heterogeneous in terms of the hardware capabilities and communication protocols to take part in the Internet of Things scenarios. Therefore, ensuring interoperability is an important step. With this respect, the focus of this paper is particularly on incorporation of geosensor networks into Internet of things through an architecture for monitoring real-time environmental data with use of OGC Sensor Web Enablement standards. This approach and its applicability is discussed in the context of an air pollution monitoring scenario