Journal of Spatial Analysis

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Air pollution has become one of the main problems of cities. Among the sources of air pollution, vehicular traffic plays an important role. Planning for efficient management and control of the air pollution caused by vehicular traffic requires accurate information on spatio-temporal dispersion of the pollutions. This research studies 3D spatio-temporal dispersion of NOx pollution caused by vehicular traffic at Valieasr-Fatemi intersection resides in Tehran, Iran. It is selected for being crowded and having the required meteorological and pollution data sensed by the Air Quality Control Corp. of Tehran Municipality.

This study uses GRAL that is a local micro-scale air dispersion model defined based on Euleran-Lagrangian dispersion models. It investigates the level of spatio-temporal autocorrelation generated by GRAL simulations at both 2D and 3D modes and discusses how it adapts with the reality.

Adopting the GRAL air pollution dispersion model, streets are defined as the linear source of pollution of NOx caused by vehicular traffic. The traffic rate is estimated based on street areas and directions, the designed average traffic velocity, traffic volume and car passage counting at the intersection. The 3D geometry of the buildings is also added to the model. All the required data that were available for winter of 2007 are gathered and introduced into the model.

The model is executed at 9 heights vary from 1.7 m to 52.5 m. These heights are defined covering a range from an average human level height to average building height and above. These levels are considered both separately in 2D mode and integrated into a 3D mode. The formation of NOx clusters is investigated analyzing their autocorrelation using Moran Index at global and local scale.

The calculated Moran-I at global scale at each 9 levels of heights, varies from 0.7 to 0.9 that depicts the validity of the GRAL model adopted to simulate the expected autocorrelation of pollution density affected by spatial issues. The Moran-I increases at higher levels as less air turbulence happens. However the result show that the turbulence increases temporarily at about 10m to 15m which are the average building heights. At local scale, the Moran-I/Anselin shows that HH clusters dominate at lower levels, around streets central areas that are farther from the buildings, and around the intersections. At higher levels, esp. higher than buildings average height, the LL clusters dominate. However the HH clusters formed around intersections, while are shrank, are still visible at high levels. The turbulence caused by building fronts and their down wash effect is also shown in the result as no definite cluster is formed near the buildings front and back.

The autocorrelation analysis is also carried for an integrated 3D model consists of all the 9 levels of heights. Considering the weight matrix for a 20m 2D neighborhood and 1m/s dispersion of the pollution vertically, the global calculated Moran-I equals 0.229 which shows existence of a spatio-temporal autocorrelation of the results generated by GRAL. At local scale the results show that the HH clusters have higher temporal dispersion rate than LL clusters.

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Accessibility to precise spatial and real time data plays a valuable role in the velocity and quality of flood relief operation and subsequently, scales the human and financial losses down. Flood real time data collection and processing, for instance, precise location and situation of flood victims may be a big challenge in Iran regarding the hardware facilities (such as high resolution aerial imagery devices) owned by the correspond organizations. To overcome the mentioned inabilities as well as reducing the financial costs for real time monitoring purpose of a flood, the current research intended to use the capacity of the flood victims and other volunteers to collect and upload real time data to rescue themselves. By means of this, flood real time spatial and non-spatial data collection is applicable via public and per-person participation based on the needs of each victims. The current Open Source workflow has been so designed that by using a browser like Mozilla, Explorer, Chrome and etc., and without the need for installing any software, the victim transmits his/her exact geographic location (captured automatically by the designed web service) and other multimedia data such as video-photo. Also, the flood-affected person announces the type of the damage and consequently, demanded rescue operation to the managers as a text information. After data processing on the server, the information is represented as a real time rescue map for decision making. The rescue plan may be mapped based on the singular aid as well as plural plan in the cluster form specialized for a particular group of victims in each bounding box. To design the web service, a client architecture for victims, other volunteers and managers has been developed, for implementing the service, Open Source technologies, server-side and client-side programming languages, Geoserver and WFS (Web Feature Service) standard adopted by OGC for spatially-enabled representation of victims demands, have been exploited. The research result is a browser-based service in which the client service offers automatic zooming to the current location of the clients and sends the rescue request including personal identifications and the type of injury using PHP (stands for Hypertext Preprocessor) and SQL (Structured Query Language). In the other side, on the client side designed for managers, the requested rescue submitted by the victims and other volunteers are mapped and displayed real time by OpenLayers and WFS. The result introduces an efficient applicable method for gathering real time and high accuracy geographic-multimedia-text data collection and consequently, extremely reduces the relief operation costs. Finally, the proposed methodology causes better performance and spatially clustering of victims to decrease the aftermath of the flood in a region like Iran suffers from the lack of expensive hardware technologies for precise data collection and transmission.

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Designing and implementing a 3D indoor navigation web application
              Extended abstract
Nowadays, due to the complexity of interior space of buildings, the need arises for indoor navigation inside such spaces. Indoor navigation systems may be helpful for emergency evacuation of the crowd in natural hazards such as earthquake as well as human-made disasters. These systems can also act as a decision support system for officials. Literature survey on indoor navigation services shows that a large number of researches have been conducted around designing and implementing such systems but automatic indoor spaces topology extraction of the current building information models remains as a challenge. This research aims to introduce, design and implement a web-based indoor navigation system using CityGML data model in LOD4 (level of detail) to overcome the mentioned problem.
The architecture of the current research is a browser-based web application service such that the data model processing and graph creation is implemented on the server side, the client interface and calculated path are represented on the client side (browser). Through the CityGML data model processing, firstly, the building navigable spaces such as room floor, doors and stairs are extracted and then, each space as a node and the connections between the nodes are defined as edges, are imported to the navigation graph. Programming on the server side has been performed by Python language and web development languages including HTML (Hypertext Markup language), JavaScript, JQuery and AJAX are used on the client side. Cesium virtual globe has been exploited to display the data model and the calculated route.
To evaluate the introduced methodology and designed service, a three floor house with CityGML format in LOD4 was used as the case study. Generally, a client can request a 3D calculated path by selecting the source and destination points on the client browser. The server receives the request and returns the response as a 3D line to the client browser on the Cesium environment. In addition, a descriptive graphical user interface for visual inception of the route is offered to the users on their browser.
One of the advantages of the designed web application is that, the service is implemented on the browser. Hence, all devices equipped with a browser have possibility to run the 3D routing service. Besides the mentioned cross-platform capability, average expectation time of the graphical interface loading, data module processing and path finder module are 7.03 milliseconds, 12.42 seconds and 2.44 seconds respectively that visits a valuable criteria in emergency situations like an earthquake phenomenon. Regarding this fact that CityGML is a new data model and supported by a few software, the introduced architecture causes less implementation costs as well as automation of these systems.
 
Keywords: 3D indoor navigation, web application, interior space of buildings

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Designing a Volunteer Geographic Information-based service for rapid earth quake damages estimation


Introduction
The advent of Web 2.0 enables the users to interact and prepare free unlimited real time data. This advantage leads us to exploit Volunteer Geographic Information (VGI) for real time crisis management. Traditional estimation methods for earthquake damages are expensive and time consuming. In contrast, volunteer and web-based service are near real time with almost no cost services. the lack of accessible real time data collection services causes delayed-emergency responses for disasters like an earthquake. This drawback is critical when we encounter a problem like buried people with valuable seconds for emergency rescue operation.
The current research aims to design and implement a web-based volunteer data collection service for rapid estimation of earthquake damages and number of buried people.

Methodology
To investigate the capacity of VGI in rapid estimation of earthquake, a technical frame work based on the web technologies has been programmed and implemented. The designed service is comprised of server and client sides.
The client side is a two-side browser-based service includes volunteers (users) and managers pages. On the user page, volunteers have a web page to enter and fill in the blank forms and taking a photograph of the target building and compare it with pictures. They watch the sample pictures in different level of damages and compare their building with the samples and give a grade of the most similar picture with their building. This grading process leads the server to analysis and classify the incoming data and create the heatmaps for managers. On the managers page two online discrete heatmaps for the both earthquake damages and buried people are displayed. In fact, the heatmaps present the online and real time quantitative situation of the building damages and buried persons as hot spots. These hotspots have the first priority for giving emergency services. The manager page also exploits query tools to request different level of details and classes from the server side.
The server side is responsible for receiving, saving, spatial analysis and transmission of the requested result to the client side. This task is carried out by the exchange side. As the citizens are entered to the browser-based service and fill in the blank forms for building damages based on the mentioned guideline and report the buried people, These forms are transmitted to the server side and a geo-server performs spatial analysis including Heatmap, distance and clustering analysis. Then, a real time damage and buried people map are prepared and delivered to the client side. The server updates the created maps whenever a new data is submitted. By this, a real time damage and buried people maps are accessible for official managers to conduct a goal-oriented emergency operation and a preliminary earth quake damages on city building blocks.
After the technical frame work has been designed, it was tested in Oshanvieh city by 132 volunteers on the scene for an earthquake.

Results and discussion
To investigate the capability of volunteer geographic information for earth quake afterwards, the designed service mentioned in the methodology was utilized on Oshnavieh city. It was assumed that an earthquake has occurred. 132 volunteers participated for the data collection process. According to the crisis management organization experts, 102 reports of the total 132 reports are correct that shows the accuracy of 76.52 percent. Besides the building damage level based on the defined guideline, the citizens also select their vital needs after the earthquake.
  the most requested vital needs are warm stuffs, medicine, water and foods respectively. Unfortunately, the participation rate is ranged from some seconds after the earthquake to three days. This means that some citizens have filled and transmitted their data three days after the earthquake.
In the following, a comparison between the designed service and traditional earthquake damage estimation methods (in situ) was carried out. The result shows that field-based methods for a city like Oshnavieh need about 20 days. However, the designed volunteer-based service what is programmed and implemented in the current research does this job by 3 days.

Conclusion
As the results show, the proposed service designed in this research implements the damage estimation process 6.5 times faster than the governmental procedures. This proves the efficiency of the research achievements. Besides the velocity, traditional damage estimation methods are expensive compare to volunteer-based data collection and processing which are almost free, scalable and pervasive.

Keywords: Volunteer Geographic Information (VGI), earthquake damage estimation, heatmap, oshnavieh city.