Estimating Fire Weather Indices via Semantic Reasoning over Wireless Sensor Network Data Streams

Wildfires are frequent, devastating events in Australia that regularly cause significant loss of life and widespread property damage. Fire weather indices are a widely-adopted method for measuring fire danger and they play a significant role in issuing bushfire warnings and in anticipating demand for bushfire management resources. Existing systems that calculate fire weather indices are limited due to low spatial and temporal resolution. Localized wireless sensor networks, on the other hand, gather continuous sensor data measuring variables such as air temperature, relative humidity, rainfall and wind speed at high resolutions. However, using wireless sensor networks to estimate fire weather indices is a challenge due to data quality issues, lack of standard data formats and lack of agreement on thresholds and methods for calculating fire weather indices. Within the scope of this paper, we propose a standardized approach to calculating Fire Weather Indices (a.k.a. fire danger ratings) and overcome a number of the challenges by applying Semantic Web Technologies to the processing of data streams from a wireless sensor network deployed in the Springbrook region of South East Queensland. This paper describes the underlying ontologies, the semantic reasoning and the Semantic Fire Weather Index (SFWI) system that we have developed to enable domain experts to specify and adapt rules for calculating Fire Weather Indices. We also describe the Web-based mapping interface that we have developed, that enables users to improve their understanding of how fire weather indices vary over time within a particular region.Finally, we discuss our evaluation results that indicate that the proposed system outperforms state-of-the-art techniques in terms of accuracy, precision and query performance.Comment: 20pages, 12 figure

Advancing Geospatial Data Curation

Digital curation is a new term that encompasses ideas from established disciplines: it defines a set of activities to manage and improve the transfer of the increasing volume of data products from producers of digital scientific and academic data to consumers, both now and in the future. Research topics in this new area are in a formative stage, but a variety of work that can serve to advance the curation of digital geospatial data is reviewed and suggested. Active research regarding geospatial data sets investigates the problems of tracking and reporting the data quality and lineage (provenance) of derived data products in geographic information systems, and managing varied geoprocessing workflow. Improving the descriptive semantics of geospatial operations will assist some of these existing areas of research, in particular lineage retrieval for geoprocessing results. Emerging issues in geospatial curation include the long-term preservation of frequently updated streams of geospatial data, and establishing systematic annotation for spatial data collections

Beyond data collection: Objectives and methods of research using VGI and geo-social media for disaster management

This paper investigates research using VGI and geo-social media in the disaster management context. Relying on the method of systematic mapping, it develops a classification schema that captures three levels of main category, focus, and intended use, and analyzes the relationships with the employed data sources and analysis methods. It focuses the scope to the pioneering field of disaster management, but the described approach and the developed classification schema are easily adaptable to different application domains or future developments. The results show that a hypothesized consolidation of research, characterized through the building of canonical bodies of knowledge and advanced application cases with refined methodology, has not yet happened. The majority of the studies investigate the challenges and potential solutions of data handling, with fewer studies focusing on socio-technological issues or advanced applications. This trend is currently showing no sign of change, highlighting that VGI research is still very much technology-driven as opposed to theory- or application-driven. From the results of the systematic mapping study, the authors formulate and discuss several research objectives for future work, which could lead to a stronger, more theory-driven treatment of the topic VGI in GIScience.Carlos Granell has been partly funded by the Ramón y Cajal Programme (grant number RYC-2014-16913

Synthesizing population, health, and place

This report on the Vespucci Institute on health geography in 2013 emphasizes the importance of research that connects population, health, and place from a holistic perspective. We review important trends related to Health GIS and highlight directions for future research in this area that were identified at the Institute

Automatic reconstruction of itineraries from descriptive texts

Esta tesis se inscribe dentro del marco del proyecto PERDIDO donde los objetivos son la extracción y reconstrucción de itinerarios a partir de documentos textuales. Este trabajo se ha realizado en colaboración entre el laboratorio LIUPPA de l' Université de Pau et des Pays de l' Adour (France), el grupo de Sistemas de Información Avanzados (IAAA) de la Universidad de Zaragoza y el laboratorio COGIT de l' IGN (France). El objetivo de esta tesis es concebir un sistema automático que permita extraer, a partir de guías de viaje o descripciones de itinerarios, los desplazamientos, además de representarlos sobre un mapa. Se propone una aproximación para la representación automática de itinerarios descritos en lenguaje natural. Nuestra propuesta se divide en dos tareas principales. La primera pretende identificar y extraer de los textos describiendo itinerarios información como entidades espaciales y expresiones de desplazamiento o percepción. El objetivo de la segunda tarea es la reconstrucción del itinerario. Nuestra propuesta combina información local extraída gracias al procesamiento del lenguaje natural con datos extraídos de fuentes geográficas externas (por ejemplo, gazetteers). La etapa de anotación de informaciones espaciales se realiza mediante una aproximación que combina el etiquetado morfo-sintáctico y los patrones léxico-sintácticos (cascada de transductores) con el fin de anotar entidades nombradas espaciales y expresiones de desplazamiento y percepción. Una primera contribución a la primera tarea es la desambiguación de topónimos, que es un problema todavía mal resuelto dentro del reconocimiento de entidades nombradas (Named Entity Recognition - NER) y esencial en la recuperación de información geográfica. Se plantea un algoritmo no supervisado de georreferenciación basado en una técnica de clustering capaz de proponer una solución para desambiguar los topónimos los topónimos encontrados en recursos geográficos externos, y al mismo tiempo, la localización de topónimos no referenciados. Se propone un modelo de grafo genérico para la reconstrucción automática de itinerarios, donde cada nodo representa un lugar y cada arista representa un camino enlazando dos lugares. La originalidad de nuestro modelo es que además de tener en cuenta los elementos habituales (caminos y puntos del recorrido), permite representar otros elementos involucrados en la descripción de un itinerario, como por ejemplo los puntos de referencia visual. Se calcula de un árbol de recubrimiento mínimo a partir de un grafo ponderado para obtener automáticamente un itinerario bajo la forma de un grafo. Cada arista del grafo inicial se pondera mediante un método de análisis multicriterio que combina criterios cualitativos y cuantitativos. El valor de estos criterios se determina a partir de informaciones extraídas del texto e informaciones provenientes de recursos geográficos externos. Por ejemplo, se combinan las informaciones generadas por el procesamiento del lenguaje natural como las relaciones espaciales describiendo una orientación (ej: dirigirse hacia el sur) con las coordenadas geográficas de lugares encontrados dentro de los recursos para determinar el valor del criterio ``relación espacial''. Además, a partir de la definición del concepto de itinerario y de las informaciones utilizadas en la lengua para describir un itinerario, se ha modelado un lenguaje de anotación de información espacial adaptado a la descripción de desplazamientos, apoyándonos en las recomendaciones del consorcio TEI (Text Encoding and Interchange). Finalmente, se ha implementado y evaluado las diferentes etapas de nuestra aproximación sobre un corpus multilingüe de descripciones de senderos y excursiones (francés, español, italiano)

FOSS4G 2016 Proceedings: Academic Program - selected papers and posters

This Conference Proceedings is a collection of selected papers and posters submitted to the Academic Program of the International Conference for Free and Open Source Software for Geospatial (FOSS4G 2016), 24th to 26th August 2016 in Bonn, Germany. Like in previous FOSS4G conferences on national and international level the academic papers and posters cover an extensive wide range of topics reflecting the contribution of the academia to this field by the development of open source software components, in the design of open standards, in the proliferation of web-based solutions, in the dissemination of the open principles important in science and education, or in the collection and the hosting of freely available geo-data

Investigating the Role of Geospatial Technologies as a Supplement to Environmental Education: Development of an Environmental Data Collection Application and Its Implementation in the Classroom

Informal STEM (Science, Technology, Engineering, and Math) education refers to science learning that takes place in a non-traditional setting, such as a museum, a library, and outside a classroom, based on the methods different from the traditional pen-to-paper style of classroom learning. A critical component of Informal STEM education is to ensure student understanding and using available technologies to better analyze and convey scientific data, particularly for the data that are spatial in nature. Combining mobile technologies with geographic information systems (GIS) in field data collection provides unique opportunities for students to feel stimulated and engaged in what they are learning and to take ownership of their own learning process.In this thesis, I developed a publicly available and open access data collection application and investigated its impacts on students’ engagement and perception of the incorporation of technology in their learning within the environmental science curricula. The analyses of pre- and post-surveys indicate that the inclusion of geospatial technologies as a part of curricula can significantly boost students’ engagement by allowing the opportunities to 1) take the lead on their own research, 2) view field data in real-time as opposed to looking at a database in hindsight, and 3) view and analyze multiscale data as it is presented during field analysis. The findings of this study are consistent with previous studies, suggesting a strong correlation between the inclusion of geospatial technologies as a part of curricula and student engagement and performance

Submeter-level Land Cover Mapping of Japan

Deep learning has shown promising performance in submeter-level mapping tasks; however, the annotation cost of submeter-level imagery remains a challenge, especially when applied on a large scale. In this paper, we present the first submeter-level land cover mapping of Japan with eight classes, at a relatively low annotation cost. We introduce a human-in-the-loop deep learning framework leveraging OpenEarthMap, a recently introduced benchmark dataset for global submeter-level land cover mapping, with a U-Net model that achieves national-scale mapping with a small amount of additional labeled data. By adding a small amount of labeled data of areas or regions where a U-Net model trained on OpenEarthMap clearly failed and retraining the model, an overall accuracy of 80\% was achieved, which is a nearly 16 percentage point improvement after retraining. Using aerial imagery provided by the Geospatial Information Authority of Japan, we create land cover classification maps of eight classes for the entire country of Japan. Our framework, with its low annotation cost and high-accuracy mapping results, demonstrates the potential to contribute to the automatic updating of national-scale land cover mapping using submeter-level optical remote sensing data. The mapping results will be made publicly available.Comment: 16 pages, 10 figure