Exploring the potential of volunteered geographic information for modeling spatio-temporal characteristics of urban population: a case study for Lisbon Metro using foursquare check-in data

In recent years we have observed an incredible increase in location-specific information provided voluntarily by individuals and disseminated via the internet. The emergence of this Volunteered Geographic Information (VGI) as Goodchild first described it in 2007 has attracted considerable interest within the GIScience research community. As a special type of user generated content, it offers great potential to produce up-to-date and near real-time information related to any place on Earth, even though overall accuracy remains an issue of debate. Location sharing services (LSS) such as ‘foursquare’, ‘Gowalla’, and ‘Facebook Places’ collect hundreds of millions of user-driven footprints or ‘check-ins’. Those footprints provide a unique opportunity to study social and temporal characteristics of how people use these services and model patterns of human mobility. However, the amount and frequency of VGI is not evenly distributed and recent research considers it directly related to socioeconomic characteristics of its contributors (i.e.,geographic and economic constraints, individual social status) . Particularly in the context of population dynamics studies, VGI may provide a data source that is more accessible and current as well as less expensive and timeconsuming than traditional activity survey data. VGI generated on micro-blogging services and location-based social networks (LBSN) bear the greatest resemblance to the activity diary that time geographers are familiar with . Noulas et al. present a large-scale study of user behavior on the LBSN platform ‘foursquare’, analyzing user check-in dynamics and demonstrating how that reveals meaningful spatio-temporal patterns and offers the opportunity to study both user mobility and characteristics of urban spaces. In this study we compare functionally categorized location-specific foursquare check-in information picturing one working week in the Lisbon Metropolitan Area to a daytime working population surface produced in previous work. The objective is to analyze potential correlation patterns and explore options for modeling finescale spatio-temporal characteristics of urban land use based on VGI.Peer Reviewe

Modellierung raum-zeitlicher Bevölkerungsverteilungsmuster im Katastrophenmanagementkontext

Effektives Katastrophenmanagement erfordert möglichst genaue raum-zeitliche Informationen sowohl über Strukturen als auch über betroffene Personen. Während physische Strukturen sich in der Regel nur langsam verändern und daher auf kurze Sicht weniger zeitkritisch in der Erfassung sind, ist die räumliche Verteilung der Bevölkerung hochgradig variabel über die Zeit (Freire und Aubrecht 2012). Die direkte Erfassung potentiell betroffener Personen bei Katastrophen ist nicht oder nur sehr eingeschränkt möglich, daher wird bei der Planung vorbeugender Maßnahmen und der Abschätzung des Gefahrenpotentials die Bevölkerungsverteilung modelliert. Zensusdaten stellen dabei eine standardisierte Datengrundlage dar, die aber in zweierlei Hinsicht limitiert ist. Zum einen ist die räumliche Ausdehnung der Zählsprengel meist zu groß und unregelmäßig um auf lokaler Ebene ausreichend genaue Aussagen über die betroffenen Personen machen zu können, zum anderen repräsentiert der Zensus die Verteilung der Wohnbevölkerung, also den Ort, wo sich die Personen in der Regel in der Nacht aufhalten. Naturgefahren (und deren Auswirkungen) können räumlich sehr fein differenziert, sowie teils ohne Vorwarnung zu einem beliebigen Zeitpunkt auftreten. Es besteht daher die Notwendigkeit, Information zur Bevölkerungsverteilung sowohl in einem räumlichen Kontext zu verfeinern als auch die zeitliche Komponente mitzuberücksichtigen (Aubrecht et al. 2012)

Improving the planning of public facilities: considering the spatio-temporal distribution of population

This study employs a dasymetric mapping approach for modeling and mapping of the spatio-temporal distribution of population at high resolution in the Lisbon Metropolitan Area, Portugal, and concerns its use for territorial planning. The objective is to introduce nighttime and daytime population densities and to demonstrate the usefulness and importance of considering the dynamics of population change in the daily cycle in the process of planning public facilities.Peer Reviewe

Modeling of dangerous phenomena and innovative techniques for hazard evaluation and risk mitigation

Society is frequently exposed to and threatened by dangerous phenomena in many parts of the world. Different types of such phenomena require specific actions for proper risk management, from the stages of hazard identification to those of mitigation (including monitoring and early-warning) and/or reduction. The understanding of both predisposing factors and triggering mechanisms of a given danger and the prediction of its evolution from the source to the overall affected zone are relevant issues that must be addressed to properly evaluate a given hazard

The ASCAT soil moisture product: a review of its specifications, validation results, and emerging applications

Many physical, chemical and biological processes taking place at the land surface are strongly influenced by the amount of water stored within the upper soil layers. Therefore, many scientific disciplines require soil moisture observations for developing, evaluating and improving their models. One of these disciplines is meteorology where soil moisture is important due to its control on the exchange of heat and water between the soil and the lower atmosphere. Soil moisture observations may thus help to improve the forecasts of air temperature, air humidity and precipitation. However, until recently, soil moisture observations had only been available over a limited number of regional soil moisture networks. This has hampered scientific progress as regards the characterisation of land surface processes not just in meteorology but many other scientific disciplines as well. Fortunately, in recent years, satellite soil moisture data have increasingly become available. One of the freely available global soil moisture data sets is derived from the backscatter measurements acquired by the Advanced Scatterometer (ASCAT) that is a C-band active microwave remote sensing instrument flown on board of the Meteorological Operational (METOP) satellite series. ASCAT was designed to observe wind speed and direction over the oceans and was initially not foreseen for monitoring soil moisture over land. Yet, as argued in this review paper, the characteristics of the ASCAT instrument, most importantly its wavelength (5.7 cm), its high radiometric accuracy, and its multiple-viewing capabilities make it an attractive sensor for measuring soil moisture. Moreover, given the operational status of ASCAT, and its promising long-term prospects, many geoscientific applications might benefit from using ASCAT soil moisture data. Nonetheless, the ASCAT soil moisture product is relatively complex, requiring a good understanding of its properties before it can be successfully used in applications. To provide a comprehensive overview of the major characteristics and caveats of the ASCAT soil moisture product, this paper describes the ASCAT instrument and the soil moisture processor and near-real-time distribution service implemented by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). A review of the most recent validation studies shows that the quality of ASCAT soil moisture product is – with the exception of arid environments –comparable to, and over some regions (e.g. Europe) even better than currently available soil moisture data derived from passive microwave sensors. Further, a review of applications studies shows that the use of the ASCAT soil moisture product is particularly advanced in the fields of numerical weather prediction and hydrologic modelling. But also in other application areas such as yield monitoring, epidemiologic modelling, or societal risks assessment some first progress can be noted. Considering the generally positive evaluation results, it is expected that the ASCAT soil moisture product will increasingly be used by a growing number of rather diverse land applications.The Austrian Science Fund (FWF) through the Vienna Doctoral Programme on Water Resource Systems (http://www.waterresources.at/,DK-plusW1219-N22

Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas

This paper introduces a novel top-down approach to geospatially identify and distinguish areas of mixed use from predominantly residential areas within urban agglomerations. Under the framework of the World Bank’s Central American Country Disaster Risk Profiles (CDRP) initiative, a disaggregated property stock exposure model has been developed as one of the key elements for disaster risk and loss estimation. Global spatial datasets are therefore used consistently to ensure wide-scale applicability and transferability. Residential and mixed use areas need to be identified in order to spatially link accordingly compiled property stock information. In the presented study, multi-sensor nighttime Earth Observation data and derivative products are evaluated as proxies to identify areas of peak human activity. Intense artificial night lighting in that context is associated with a high likelihood of commercial and/or industrial presence. Areas of low light intensity, in turn, can be considered more likely residential. Iterative intensity thresholding is tested for Cuenca City, Ecuador, in order to best match a given reference situation based on cadastral land use data. The results and findings are considered highly relevant for the CDRP initiative, but more generally underline the relevance of remote sensing data for top-down modeling approaches at a wide spatial scale

Spatio-Temporal Population Distribution and Evacuation Modeling for Improving Tsunami Risk Assessment in the Lisbon Metropolitan Area

Lisbon, Portugal, is subject to significant risk of tsunami, and was hit by a very destructive earthquake-triggered tsunami during daytime in 1755. The Regional Plan for Territorial Management for the Lisbon Metropolitan Area (PROT), under discussion, includes a tsunami hazard map, showing that significant urbanized areas may be at risk of inundation. In order to consider the time dependence of population exposure to tsunami threats, we map and analyze the spatio-temporal population distribution in the daily cycle in the Lisbon Metropolitan Area. High-resolution day- and nighttime population distribution maps are developed using ‘intelligent dasymetric mapping’, i.e. using areal interpolation to combine best-available census data and statistics with land use and land cover data. Mobility statistics are considered for mapping daytime distribution, and empirical parameters used for interpolation are obtained from a previous modeling effort of part of the study area. In combination with the tsunami hazard map, information on infrastructure, land use and terrain slope, the modeled population distribution is used to assess people’s evacuation times, applying a GIS-based evacuation modeling approach to the city of Lisbon. The detailed spatio-temporal population exposure assessment allows producing both day- and nighttime evacuation time maps, which provide valuable input for evacuation planning and management. Results show that a significant amount of population is potentially at risk, and its numbers increase dramatically from nighttime to daytime, especially in the zones of high susceptibility. Also, full evacuation can be problematic in the daytime period, even if initiated immediately after a major earthquake. The presented approach is considered to greatly improve risk mapping and assessment and can benefit all phases of the disaster management process

A Portable Base Station Optimization Model for DPM A Portable Base Station Optimization Model for Wireless Infrastructure Deployment in Disaster Planning and Management

ABSTRACT Disaster response requires communications among all affected parties including emergency responders and the affected populace. Wireless telecommunications, if available through a fixed structure cellular mobile network, satellites, portable station mobile networks and ad hoc mobile networks, can provide this means for such communications. While the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and mobile network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures of the deployment or minimizing overall 'cost' (including time aspects) to deploy. This work-in-progress does not focus on the question of what entity will operate the portable base during a disaster, but on optimizing the placement of mobile base stations or similar network nodes for planning and real time management purposes. An optimization model is proposed for the staging and placement of portable base stations to support disaster relief efforts

Volunteered Geo-Dynamic Information for Health-Risk Exposure Assessment - A FRESHER Case Study. GI_Forum|GI_Forum 2016, Volume 2 – open:spatial:interfaces|

In this paper we discuss the use of volunteered geo-dynamic information (VGDI) for assessing exposure to health risks and improving analysis of associated dynamic aspects in urban settings. VGDI is introduced as an alternative and complementary data source to traditional geodata whereby both spatial and temporal aspects are highlighted. Within the FRESHER project several health-related parameters are modelled, including air pollution and access to fast food restaurant locations. We discuss how Foursquare data (and VGDI in general) can benefit integrative smart urban analytics and provide sample illustrations for a test case area in Lisbon, Portugal

Earth observation open science and innovation

This book is published open access under a CC BY 4.0 license. Over  the  past  decades,  rapid developments in digital and sensing technologies, such  as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. The digital transformation is revolutionizing our ability to monitor our planet and transforming the  way we access, process and exploit Earth Observation data from satellites. This book reviews these megatrends and their implications for the Earth Observation community as well as the wider data economy. It provides insight into new paradigms of Open Science and Innovation applied to space data, which are characterized by openness, access to large volume of complex data, wide availability of new community tools, new techniques for big data analytics such as Artificial Intelligence, unprecedented level of computing power, and new types of collaboration among researchers, innovators, entrepreneurs and citizen scientists. In addition, this book aims to provide readers with some reflections on the future of Earth Observation, highlighting through a series of use cases not just the new opportunities created by the New Space revolution, but also the new challenges that must be addressed in order to make the most of the large volume of complex and diverse data delivered by the new generation of satellites.