Environmental Decision-making utilizing a Web GIS to Monitor Hazardous Industrial Emissions in the Valencian community of Spain

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Air pollution is a critical issue in contemporary times. For this reason, officials and environmental managers are in need of suitable tools for visualization, manipulation and analysis of environmental data. Environmental concerns in Europe have encouraged the European Environmental Agency (EEA) to create the European Pollutant Release and Transfer Register (E-PRTR). The E-PRTR is vital and valuable because society will benefit if the data are used to improve monitoring and consequently advance environmental management. However, the data are not accessible in an interoperable way, which complicates their use and does not allow for a contribution to environmental monitoring. This paper describes a Web GIS system developed for the monitoring of industrial emissions using environmental data released by the EEA. Four research objectives are addressed: (1) design and create an interoperable spatial database to store environmental data, (2) develop a Web GIS to manipulate the spatial database, facilitate air pollution monitoring and enhance risk assessment, (3) implement OGC standards to provide data interoperability and integration into a Web GIS, (4) create a model to simulate distribution of air pollutants and assess a population’s exposure to industrial emissions. The proposed approach towards interoperability is an adoption of servicebased architecture for implementation of a three-tier Web GIS application. This system’s prototype is developed using open source tools for the Valencian Community of Spain

Towards social paradigms for mobile context-aware computing in smart cities

Ponència presentada a la 11ª Conferencia Ibérica de Sistemas y Tecnologías de Información (CISTI 2016) celebrada a Gran Canaria els dies 15-18 de juny de 2016Mobile context-aware computing is an essential component of the smart cities infrastructure. Attempts were made to develop a model that can effectively represent a system in device to support context-aware behavior. The purpose of this paper is to identify deficiencies of the previously developed model and propose solutions to improve it.The authors gratefully acknowledge funding from the European Commission through the GEO-C project (H2020- MSCA-ITN-2014, Grant Agreement Number 642332, http://www.geo-c.eu/). Carlos Granell has been partly funded by the Ramón y Cajal Programme (grant numbers RYC-2014- 16913

Sociology Paradigms for Dynamic Integration of Devices into a Context-Aware System

Ubiquitous and m obile context - aware computing is an essential component of the smart cities infrastructure. Widely available wireless networks, the maturity level of distributed computing and the increasing number of mobile devices have significantly influenced the human experience with computing. In the present paper, we discuss the need for a model that will be able to represent a formal structure of a context - aware system in a device . The core functionality of the model is expected to expose context - aware behaviour and support dynamic integration of mobile devices and context - aware behaviour. The major contribution of this work is to identify deficiencies of the existing model which is using the notions from sociology such as Role, Ownership and Responsibility.The authors gratefully acknowledge funding from the European Commission through the GEO-C project (H2020-MSCA-ITN-2014, Grant Agreement Number 642332, http://www.geo-c.eu/)

Supporting Urban Energy Efficiency with Volunteered Roof Information and the Google Maps API

The Heat Energy Assessment Technologies (HEAT) project uses high-resolution airborne thermal imagery, Geographic Object-Based Image Analysis (GEOBIA), and a Geoweb environment to allow the residents of Calgary, Alberta, Canada to visualize the amount and location of waste heat leaving their houses, communities, and the city. To ensure the accuracy of these measures, the correct emissivity of roof materials needs to be known. However, roof material information is not readily available in the Canadian public domain. To overcome this challenge, a unique Volunteered Geographic Information (VGI) application was developed using Google Street View that engages citizens to classify the roof materials of single dwelling residences in a simple and intuitive manner. Since data credibility, quality, and accuracy are major concerns when using VGI, a private Multiple Listing Services (MLS) dataset was used for cross-verification. From May–November 2013, 1244 volunteers from 85 cities and 14 countries classified 1815 roofs in the study area. Results show (I) a 72% match between the VGI and MLS data; and (II) in the majority of cases, roofs with greater than, or equal to five contributions have the same material defined in both datasets. Additionally, this research meets new challenges to the GEOBIA community to incorporate existing GIS vector data within an object-based workflow and engages the public to provide volunteered information for urban objects from which new geo-intelligence is created in support of urban energy efficiency