scholarly journals Effective Collaborative Mapping Based on Mobile Devices

2017 ◽  
Vol 65 (6) ◽  
pp. 2067-2072
Author(s):  
Ivo Pisařovic ◽  
David Procházka ◽  
Jaromír Landa ◽  
Jan Kolomazník ◽  
Karel Zídek ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Time Synchronization ◽  
Geographical Information ◽  
Time Data ◽  
Service Workers ◽  
Rescue Service ◽  
Share Data ◽  
Multiple Devices ◽  
Field Workers

There are numerous situations when it is utmost important to share efficiently some spatial data among a group of people. Floods can be taken as an obvious example. Many stakeholders including mayor or rescue service workers must have actual information about the conditions in the terrain. And most importantly, all of these can contribute to the information. Among these situations involving the crisis management, we dare to mention especially the inventory process. Traffic signs, road lanes, trees, lights and many other different object must be regularly maintained. Most of the organizations use some kind of geographical information system to keep the information about the maintained property. Our article is focused on development of mobile application that allows to acquire spatial data that are later used in these information systems. Thanks to real-time data synchronization between multiple devices, field workers can cooperate and share data immediately to an operating center or with the other workers. We describe the design of our mobile mapping application, comparison with other existing solutions and problems of real-time synchronization between different devices. Finally, we provide details about application usage in different municipalities.

scholarly journals Le portail SIGLA – un système d'information géographique sur Internet pour le programme portugais de surveillance entomologique de la fièvre catarrhale ovine

2009 ◽  
Vol 62 (2-4) ◽  
pp. 176
Author(s):  
H. Martins ◽  
T. Nunes ◽  
Fernando Boinas
Keyword(s):  
Real Time ◽  
Relational Database ◽  
Spatial Data ◽  
Temporal Distribution ◽  
Control Measures ◽  
Geographical Information ◽  
Time Data ◽  
Gis Technology ◽  
Web Mapping ◽  
Système D’Information

Bluetongue (BT) is an infectious non-contagious disease, whose transmission is commonly associated with an intermediate arthropod host from the Culicoides genre. A BT entomologi­cal surveillance programme was implemented in Portugal in May 2005 to collect data on the abundance, and spatial and temporal distribution of several species potentially involved in the transmission of the disease. At that time a simple local alphanumerical relational database was built to record all data. Although it fulfilled the initial objectives of data management, there was an increasing need to share this information in real-time with national veterinary authorities. Moreover, sharing this data in a map-based approach was not possible without con­siderable time-consuming effort. To overcome these needs, a new web-based system with geographical information system (GIS) capabilities was designed and is currently being devel­oped exclusively using Open Source Software (Portal SIGLA). The alphanumerical component was partially migrated from the previous system, though introducing query capabilities visually supported by the use of dynamic charts further enriched it.  The geographical component is now the development core, but it already contains several tools of a standard web mapping application (zooming, panning, distance and area measure­ments, activation/deactivation of spatial layers, legend panel, graphical and numerical scale…). This enterprise-level relational database with geographical functions also makes spatial editing available through the web and thus enables technicians with no GIS expertise to create and handle easily spatial data. The system democratizes GIS technology and provides veterinary officers with real-time data sharing. It helps to gain further insight into disease dynamics and thus to contribute to more effective sani­tary control measures. Future developments are mainly related to spatial querying of data through the form of choropleth and chart maps. This will further enrich the analysis capabilities of the system.

Spatial and Spatiotemporal Data Types as a Foundation for Representing Space-Time Data in GIS

2017 ◽  
pp. 1-28 ◽  
Author(s):  
Markus Schneider
Keyword(s):  
Spatial Data ◽  
Geographical Information Systems ◽  
Moving Objects ◽  
Spatial Databases ◽  
Query Languages ◽  
Geographical Information ◽  
Spatiotemporal Data ◽  
Data Types ◽  
Time Data ◽  
Use Of Data

A data type comprises a set of homogeneous values together with a collection of operations defined on them. This chapter emphasizes the importance of crisp spatial data types, fuzzy spatial data types, and spatiotemporal data types for representing static, vague, and time-varying geometries in Geographical Information Systems (GIS). These data types provide a fundamental abstraction for modeling the geometric structure of crisp spatial, fuzzy spatial, and moving objects in space and time as well as their relationships, properties, and operations. The goal of this chapter is to provide an overview and description of these data types and their operations that have been proposed in research and can be found in GIS, spatial databases, moving objects databases, and other spatial software tools. The use of data types, operations, and predicates will be illustrated by their embedding into query languages.

Spatial Autocorrelation and Association Measures

2011 ◽  
pp. 1502-1508
Author(s):  
J. Negreiros ◽  
M. Painho ◽  
I. Lopes ◽  
A.C. Costa
Keyword(s):  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Spatial Data ◽  
Regional Analysis ◽  
Geographical Information ◽  
Association Measures ◽  
Share Data ◽  
Definition Of ◽  
Graphic Database

Several classical statements relating to the definition of GIS can be found in specialized literature such as the GIS International Journal, expressing the idea that spatial analysis can somehow be useful. GIS is successful not only because it integrates data, but it also enables us to share data in different departments or segments of our organizations. I like this notion of putting the world’s pieces back together again (ArcNews, 2000). “GIS is simultaneously the telescope, the microscope, the computer and the Xerox machine of regional analysis and the synthesis of spatial data” (Abler, 1988). “GIS is a system of hardware, software and liveware implemented with the aim of storing, processing, visualizing and analyzing data of a spatial nature. Other definitions are also possible” (Painho, 1999). “GIS is a tool for revealing what is otherwise invisible in geographical information” (Longley, Goodchild, Maguire, & Rhind, 2001). Certainly, GIS is not a graphic database.

scholarly journals SPATIAL DATA INTEGRATION USING ONTOLOGY-BASED APPROACH

2015 ◽  
Vol XL-1-W5 ◽  
pp. 293-296 ◽  
Author(s):  
S. Hasani ◽  
A. Sadeghi-Niaraki ◽  
M. Jelokhani-Niaraki
Keyword(s):  
Data Integration ◽  
Real Time ◽  
Spatial Data ◽  
Service Oriented Architecture ◽  
Low Cost ◽  
Time Integration ◽  
Semantic Heterogeneity ◽  
Sources Of Information ◽  
Time Data ◽  
Service Oriented

In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.

Supporting Natural Hazards Management With Geospatial Technologies

2019 ◽  
Author(s):  
Diana Mitsova
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Natural Hazards ◽  
Spatial Data ◽  
Disaster Response ◽  
Early Warning Systems ◽  
Unmanned Aircraft ◽  
Time Data ◽  
Geospatial Technologies ◽  
Collaborative Efforts

On a global scale, natural disasters continue to inflict a heavy toll on communities and to pose challenges that either persist or amplify in complexity and scale. There is a need for flexible and adaptive solutions that can bridge collaborative efforts among public agencies, private and nonprofit organizations, and communities. The ability to explore and analyze spatial data, solve problems, visualize, and communicate outcomes to support the collaborative efforts and decision-making processes of a broad range of stakeholders is critical in natural hazards and disaster management. The adoption of geospatial technologies has long been at the core of natural hazards risk assessment, linking existing technologies in GIS (geographic information system) with spatial analytical techniques and modeling. Practice and research have shown that though risk-reduction strategies and the mobilization of disaster-response resources depend on integrating governance into the process of building disaster resilience, the implementation of such strategies is best informed by accurate spatial data acquisition, fast processing, analysis, and integration with other informational resources. In recent years, new and accessible sources and types of data have greatly enhanced the ability of practitioners and researchers to develop approaches that support rapid and efficient disaster response, including forecasting, early warning systems, and damage assessments. Innovations in geospatial technologies, including remote sensing, real-time Web applications, and distributed Web-based GIS services, feature platforms for systematizing and sharing data, maps, applications, and analytics. Distributed GIS offers enormous opportunities to strengthen collaboration and improve communication and efficiency by enabling agencies and end users to connect and interact with remotely located information products, apps, and services. Newer developments in geospatial technologies include real-time data management and unmanned aircraft systems (UAS), which help organizations make rapid assessments and facilitate the decision-making process in disasters.

The Distribution Network Reconfiguration Based on Spatial Data Mining

2013 ◽  
Vol 427-429 ◽  
pp. 2748-2751
Author(s):  
Jia Yin Sui ◽  
Ying Nan Wang ◽  
Zhe Ren
Keyword(s):  
Data Mining ◽  
Real Time ◽  
Spatial Data ◽  
Distribution Network ◽  
Load Forecasting ◽  
Spatial Data Mining ◽  
Geographical Information ◽  
Network Reconfiguration ◽  
Distribution Network Reconfiguration ◽  
Gis System

Distribution network reconfiguration is one of the essential functions of the DMS system; it can be attributed to a number of constraints of large-scale nonlinear combinatorial optimization problem in mathematics. The characteristic of load change of time and space will affect the results of load forecasting. Distribution network reconfiguration relies on the load forecasting results. This paper proposes the more realistic distribution reconfiguration scheme based on the GIS system with space information through spatial data mining. For the real-time and efficiency of effective assurance data, the interface design in GIS system and distribution automation system are also proposed. The geographical information and real-time information are connected seamlessly, so that this two system information is highly unified. The solution can provide the data basis for distribution reconfiguration scheme accurately, and improve power supply reliability of distribution network. It shows that through the example: GIS based on the spatial data mining can provide load in quantity, time, space prediction for the deeper research of distribution network reconfiguration.

Decision Support System of Production Scheduling Based on WEBGIS

2012 ◽  
Vol 457-458 ◽  
pp. 1521-1528
Author(s):  
Ling Fan ◽  
Qiang Lu ◽  
Mao Lin Liao ◽  
Gui Shan Ren
Keyword(s):  
Decision Support ◽  
Real Time ◽  
Production Scheduling ◽  
Geographical Information ◽  
Time Data ◽  
Coordinated Development ◽  
Management Level ◽  
Well Production ◽  
Data Volume ◽  
Real Time Information

As the validity period of production data is short and data volume is big, a real-time data base is designed as the system database. Based on WEBGIS technique, Geographical Information System is designed, moreover, the production system, water flood system and power system are integrated into the system, thus laying foundations for production scheduling. Through analyzing real-time information stored in the database, early warning of well production and decision support can be provided for production managers, thus improving management level and promoting the coordinated development of the oilfield.

scholarly journals Impact of Fog and Cloud Computing Applications to Reserve a Seat in Railways

2020 ◽  
Vol 13 (1) ◽  
pp. 28
Author(s):  
Gajender Kumar Kumar
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Real Data ◽  
Third Parties ◽  
College Level ◽  
Time Data ◽  
Data Pipeline ◽  
Real Time Data ◽  
Multiple Devices ◽  
Sensor Cloud

As India's largest employer has gone digital, this is the beginning of mass acquisition in a new dimension. Indian Railways serves on a peripheral scale in the size of each aircraft. It carries 23,000 passengers and over 3 million tonnes daily, with more than 12,000 passengers traveling at 115,000 km and 7000 stations. But as the nation's largest employer has begun to digitalize its services operations, it is beginning to gain mass in an emerging dimension. The network collects around 100 datasets per user (one truffle is enough to store 500–1000 movies). This passenger booking plate has 25 million users, leading to approximately 800,000 daily transactions. Such is the creation of a digital scale railway ecosystem, a fertile ground for entrepreneurs, employers and large scale technology for testing and testing. And while Railways has made a good start by integrating third parties with third parties, the company can create a seamless experience in booking, payment and other services at the top of the railway data pipeline. Here we have several ways to verify a passenger or passenger ticket, which will be discussed one by one on Fig.1. We understand here that the N computer system (server) is available in the availability center and the availability train provided by the NECC (North Eastern Carrying Corporation Ltd). Each seat or chair acts as a spring (Smart) chair, which means that we are connected to a ticket scanner or chair that can scan tickets and send the actual data to the field node (fog node). Later, the latest analysis will result in the proposed data and the final data that will be sent to the cloud. We are connected to multiple devices to share real-time data and updated real-time data on the cloud. We have created a fog environment and a cloud environment. We have implemented this with the help of clipping and sending data by sending real data separately. We have created a smart gateway between military (Servers) and customer (sensor), cloud and customer (sensor). In this paper, there is the solution that can enhanced the chances of getting confirm ticket, based on individual server load in coaches of the train, according to the increase in the number of sensors request, in the context of processing and considering three cases , it is an answer by analysing cloud-fog scenario. Up to this implementation the simple round robin algorithm is also used solution for load balancing purpose. The method is implemented by using a class student attendance system in a college level.

Near real-time monitoring of post-fire erosion after storm events: a case study in Warrumbungle National Park, Australia

2018 ◽  
Vol 27 (6) ◽  
pp. 413 ◽  
Author(s):  
Xihua Yang ◽  
Qinggaozi Zhu ◽  
Mitch Tulau ◽  
Sally McInnes-Clarke ◽  
Liying Sun ◽  
...  
Keyword(s):  
Real Time ◽  
National Parks ◽  
Spatial Data ◽  
Soil Loss ◽  
National Park ◽  
Field Measurements ◽  
Geographical Information ◽  
Rainfall Erosivity ◽  
Storm Events ◽  
Erosion Risk

Wildfires in national parks can lead to severe damage to property and infrastructure, and adverse impacts on the environment. This is especially pronounced if wildfires are followed by intense storms, such as the fire in Warrumbungle National Park in New South Wales, Australia, in early 2013. The aims of this study were to develop and validate a methodology to predict erosion risk at near real-time after storm events, and to provide timely information for monitoring of the extent, magnitude and impact of hillslope erosion to assist park management. We integrated weather radar-based estimates of rainfall erosivity with the revised universal soil loss equation (RUSLE) and remote sensing to predict soil loss from individual storm events after the fire. Other RUSLE factors were estimated from high resolution digital elevation models (LS factor), satellite data (C factor) and recent digital soil maps (K factor). The accuracy was assessed against field measurements at twelve soil plots across the Park and regular field survey during the 5-year period after the fire (2013–17). Automated scripts in a geographical information system have been developed to process large quantity spatial data and produce time-series erosion risk maps which show spatial and temporal changes in hillslope erosion and groundcover across the Park at near real time.

scholarly journals SeaGIS Abruzzo: A publicly available atlas of marine uses and natural resources in the Adriatic Sea Region

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Carla Ippoliti ◽  
Alessio Di Lorenzo ◽  
Riccardo Caprioli ◽  
Sandro Pelini ◽  
Annamaria Conte ◽  
...  
Keyword(s):  
Spatial Data ◽  
Adriatic Sea ◽  
Geographical Information ◽  
The European Union ◽  
Resource Exploitation ◽  
Web Based ◽  
Digital Repositories ◽  
Sea Bottom ◽  
Share Data ◽  
Cross Border Cooperation

In the Adriatic Sea, the European Union supported a cross-border cooperation research program, during which digital spatial data on shellfish production and relaying areas, regulated conditions on fishing activities, protected areas and restocking structures, administrative boundaries and sea bottom characteristics, were collated from digital repositories in various institutions and paper documents. A web-based geographical information system was developed to share data of the sea facing the Abruzzi region and to explore the spatial distribution of marine resources and maritime activities, thus focussing and facilitating fisheries management and providing a potential support to the regional planning of resource exploitation.

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