Highlighting Current Trends in Volunteered Geographic Information

Volunteered Geographic Information (VGI) is a growing area of research. This Special Issue aims to capture the main trends in VGI research based on 16 original papers, and distinguishes between two main areas, i.e., those that deal with the characteristics of VGI and those focused on applications of VGI. The topic of quality assessment and assurance dominates the papers on VGI characteristics, whereas application-oriented work covers three main domains: human behavioral analysis, natural disasters, and land cover/land use mapping. In this Special Issue, therefore, both the challenges and the potentials of VGI are addressed

Citizen OBservatory WEB (COBWEB): A Generic Infrastructure Platform to Facilitate the Collection of Citizen Science Data for Environmental Monitoring

COBWEB has used the UNESCO World Network of Biosphere Reserves as a testbed for researching and developing a generic crowdsourcing infrastructure platform for environmental monitoring. A major challenge is dealing with what is necessarily a complex problem requiring sophisticated solutions balanced with the need to present sometimes unsophisticated users with comprehensible and useable software. The components of the COBWEB platform are at different Technology Readiness Levels. This short paper outlines the overall solution and points to quality assurance, standardisation and semantic interoperability as key areas requiring further attention

Citizen OBservatory WEB (COBWEB): A Generic Infrastructure Platform to Facilitate the Collection of Citizen Science data for Environmental Monitoring

The mass uptake of internet connected, GPS enabled mobile devices has resulted in a surge of citizens active in making a huge variety of environmental observations.  The use and reuse potential of these data is significant but currently compromised by a lack of interoperability.  Useable standards either don’t exist, are neglected, poorly understood or tooling is unavailable.  Large volumes of data are being created but exist in silos.  This is a complex problem requiring sophisticated solutions balanced with the need to present sometimes unsophisticated users with comprehensible and useable software.  COBWEB has addressed this challenge by using the UNESCO World Network of Biosphere Reserves as a testbed for researching and developing a generic crowdsourcing infrastructure platform for environmental monitoring.   The solution arrived at provides tools for the creation of mobile Applications which generate data compliant with open interoperability standards and facilitate integration with Spatial Data Infrastructures.  COBWEB is a research project and the components of the COBWEB platform are at different Technology Readiness Levels. This paper outlines how the overall solution was arrived at, describes the main components developed and points to quality assurance, integration of sensors, interoperability and associated standardisation as key areas requiring further attention.

Rapid flood inundation mapping using social media, remote sensing and topographic data

Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively

Earth observation for citizen science validation, or citizen science for earth observation validation? The role of quality assurance of volunteered observations

Environmental policy involving citizen science (CS) is of growing interest. In support of this open data stream of information, validation or quality assessment of the CS geo-located data to their appropriate usage for evidence-based policy making needs a flexible and easily adaptable data curation process ensuring transparency. Addressing these needs, this paper describes an approach for automatic quality assurance as proposed by the Citizen OBservatory WEB (COBWEB) FP7 project. This approach is based upon a workflow composition that combines different quality controls, each belonging to seven categories or “pillars”. Each pillar focuses on a specific dimension in the types of reasoning algorithms for CS data qualification. These pillars attribute values to a range of quality elements belonging to three complementary quality models. Additional data from various sources, such as Earth Observation (EO) data, are often included as part of the inputs of quality controls within the pillars. However, qualified CS data can also contribute to the validation of EO data. Therefore, the question of validation can be considered as “two sides of the same coin”. Based on an invasive species CS study, concerning Fallopia japonica (Japanese knotweed), the paper discusses the flexibility and usefulness of qualifying CS data, either when using an EO data product for the validation within the quality assurance process, or validating an EO data product that describes the risk of occurrence of the plant. Both validation paths are found to be improved by quality assurance of the CS data. Addressing the reliability of CS open data, issues and limitations of the role of quality assurance for validation, due to the quality of secondary data used within the automatic workflow, are described, e.g., error propagation, paving the route to improvements in the approach

Assessing the effectiveness of crowdsourced geographic information for solid waste management in Timor-Leste : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Sciences (Information Technology) at Massey University, Albany, New Zealand

Dili, the capital city of Timor-Leste has been faced with serious solid waste problems in recent years. Responding to this issue, the government has adopted various policies including setting up solid waste collection sites in community areas and outsourcing collection to the private sector to collect waste directly from homes in several areas. Despite, these efforts, waste is still found scattered on the roads and disposed of in rivers and open lands. A proper solid waste management strategy is necessary to transform the city into a clean city. In order to develop an effective solid waste management strategy, reliable data and public participation are required. This study, therefore, investigated whether crowdsourcing, in particular, Volunteered Geographic Information (VGI) can effectively be used to collect data about solid waste disposal and collection practices in Dili and raise awareness of the impact of waste disposal practices among the public. The study result demonstrated that crowdsourcing is a viable method for collecting solid waste data. Challenges such as collecting accurate location-specific data still remain, hence, the crowdsourced dataset may not entirely substitute for the usual traditional dataset. At this stage, however, the collected data can still be utilized as a supplementary data source. In the future, by improving data collection methodologies, such as using smaller rewards or providing necessary facilities, a crowdsourcing-based data collection method could be utilized as an adequate substitute for traditional data source because of its ability to collect data in real- time with lower operational costs. This approach is feasible for a developing country such as Timor-Leste where critical area such as waste management has less priority for funding

Citizen observations contributing to flood modelling : opportunities and challenges. Páginas 1473-1489

Especialización en traducción técnica y científica. Idioma Inglés.La traducción de un texto especializado como es el caso de Citizen observations contributing to flood modelling: opportunities and challenges implica un trabajo riguroso y exhaustivo por parte del traductor, quien debe utilizar todos sus conocimientos y recursos adquiridos para triunfar en la práctica. El grado de especificidad del tema del texto asignado, de reciente creación, la alta densidad terminológica, sumados a la complejidad propia del discurso científico, implicaron un gran desafío para su traducción y análisis. Para llevar a cabo una traducción que transmita el mismo significado del original, fue fundamental documentarse ante un texto de un calibre tan específico y complejo como lo son los textos interdisciplinares especializados en hidrología y áreas afines, recurrir a la ayuda de expertos en el tema y estar actualizados en programas informáticos que contribuyen al proceso traductor.Fil: García Rulli, María Alejandra. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina

Mapping and the Citizen Sensor

Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies

Using Geographic Relevance (GR) to contextualize structured and unstructured spatial data

Geographic relevance is a concept that has been used to improve spatial information retrieval on mobile devices, but the idea of geographic relevance has several potential applications outside of mobile computing. Geographic relevance is used measure how related two spatial entities are using a set of criteria such as distance between features, the semantic similarity of feature names or clustering pattern of features. This thesis examines the use of geographic relevance to organize and filter web based spatial data such as framework data from open data portals and unstructured volunteer geographic information generated from social media or map-based surveys. There are many new users and producers of geographic information and it is unclear to new users which data sets they should use to solve a given problem. Governments and organizations also have access to a growing volume of volunteer geographic information but current models for matching citizen generated information to locations of concern to support filtering and reporting are inadequate. For both problems, there is an opportunity to develop semi-automated solutions using geographic relevance metrics such as topicality, spatial proximity, cluster and co-location. In this thesis, two geographic relevance models were developed using Python and PostgreSQL to measure relevance and identify relationships between structured framework data and unstructured VGI in order to support data organization, retrieval and filtering. This idea was explored through two related case studies and prototype applications. The first study developed a prototype application to retrieve spatial data from open data portals using four geographic relevance criteria which included topicality, proximity, co-location and cluster co-location. The second study developed a prototype application that matches VGI data to authoritative framework data to dynamically summarize and organize unstructured VGI data. This thesis demonstrates two possible approaches for using GR metrics to evaluate spatial relevance between large data sets and individual features. This thesis evaluates the effectiveness of GR metrics for performing spatial relevance analysis and it demonstrates two potential use cases for GR