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Articles 1 - 30 of 59
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Examining Satellite Images Market Stability Using The Records Theory: Evidence From French Spatial Data Infrastructures, Chadi Jabbour, Anis Hoayek, Pierre Maurel, Zaher Khraibani, Latifa Ghalayini
Examining Satellite Images Market Stability Using The Records Theory: Evidence From French Spatial Data Infrastructures, Chadi Jabbour, Anis Hoayek, Pierre Maurel, Zaher Khraibani, Latifa Ghalayini
Journal of Spatial Information Science
The spatial data infrastructures (SDIs) which constitute a direct link between spatial data users and the large Earth observation industry, have a leading role in establishing market opportunities in the space sector. The spatial information supplied through various forms of SDI platforms exhibits large increases in demand volatility. The users' demand is unpredictable and the market is vulnerable to high evolution shifts. We study the effect of extreme demands for a particular type of spatial information, the satellite images. Drawing on two French SDIs, GEOSUD and PEPS, we examine the shifts occurring on their platforms and assess the probability of …
Don't Forget About Geography, Micah L. Brachman
Don't Forget About Geography, Micah L. Brachman
Journal of Spatial Information Science
Maps are a fundamental form of human communication, and for millennia geographers have created maps that measure and describe features and phenomena on the Earth's surface. Yet since the "quantitative revolution" of the 1960s, the ancient scientific discipline of geography has become increasingly devalued within the academe and misunderstood by the general public. A review of the academic affiliations and job titles of the esteemed authors from the JOSIS 10th anniversary edition is indicative of how constant rebranding and renaming of geography has resulted in fragmentation of the discipline. While terms such as "Spatial Data Science‚" have a cross-disciplinary appeal, …
The Impact Of Urban Road Network Morphology On Pedestrian Wayfinding Behaviour, Debjit Bhowmick, Stephan Winter, Mark Stevenson, Peter Vortisch
The Impact Of Urban Road Network Morphology On Pedestrian Wayfinding Behaviour, Debjit Bhowmick, Stephan Winter, Mark Stevenson, Peter Vortisch
Journal of Spatial Information Science
During wayfinding pedestrians do not always choose the shortest available route. Instead, route choices are guided by several well-known wayfinding strategies or heuristics. These heuristics minimize cognitive effort and usually lead to satisfactory route choices. Our previous study evaluated the costs of four well-known pedestrian wayfinding heuristics and their variation across nine network morphologies. It was observed that the variation in the cost of these wayfinding heuristics increased with an increase in the irregularity of the network, indicating that people may opt for more diverse heuristics while walking through relatively regular networks, and may prefer specific heuristics in the relatively …
Geocomputation 2019 Special Feature, Antoni Moore, Mark Gahegan
Geocomputation 2019 Special Feature, Antoni Moore, Mark Gahegan
Journal of Spatial Information Science
No abstract provided.
Modelling Orebody Structures: Block Merging Algorithms And Block Model Spatial Restructuring Strategies Given Mesh Surfaces Of Geological Boundaries, Raymond Leung
Journal of Spatial Information Science
This paper describes a framework for capturing geological structures in a 3D block model and improving its spatial fidelity, including the correction of stratigraphic, mineralisation and other types of boundaries, given new mesh surfaces. Using surfaces that represent geological boundaries, the objectives are to identify areas where refinement is needed, increase spatial resolution to minimise surface approximation error, reduce redundancy to increase the compactness of the model and identify the geological domain on a block-by-block basis. These objectives are fulfilled by four system components which perform block-surface overlap detection, spatial structure decomposition, sub-blocks consolidation and block tagging, respectively. The main …
Indigeneity And Spatial Information Science, Matt Duckham, Serene Ho
Indigeneity And Spatial Information Science, Matt Duckham, Serene Ho
Journal of Spatial Information Science
Spatial information science has given rise to a set of concepts, tools, and techniques for understanding our geographic world. In turn, the technologies built on this body of knowledge embed certain ways of knowing." This vision paper traces the roots and impacts of those embeddings and explores how they can sometimes be inherently at odds with or completely subvert Indigenous Peoples' ways of knowing. However advancements in spatial information science offer opportunities for innovation whilst working towards reconciliation. We highlight as examples four active research topics in the field to support a call to action for greater inclusion of Indigenous …
Inferring Movement Patterns From Geometric Similarity, Maike Buchin, Carola Wenk
Inferring Movement Patterns From Geometric Similarity, Maike Buchin, Carola Wenk
Journal of Spatial Information Science
Spatial movement data nowadays is becoming ubiquitously available, including data of animals, vehicles and people. This data allows us to analyze the underlying movement. In particular, it allows us to infer movement patterns, such as recurring places and routes. Many methods to do so rely on the notion of similarity of places or routes. Here we briefly survey how research on this has developed in the past 15 years and outline challenges for future work.
Why Are Events Important And How To Compute Them In Geospatial Research?, May Yuan
Why Are Events Important And How To Compute Them In Geospatial Research?, May Yuan
Journal of Spatial Information Science
Geospatial research has long centered around objects. While attention to events is growing rapidly, events remain objectified in spatial databases. This paper aims to highlight the importance of events in scientific inquiries and overview general event-based approaches to data modeling and computing. As machine learning algorithms and big data become popular in geospatial research, many studies appear to be the products of convenience with readily adaptable data and codes rather than curiosity. By asking why events are important and how to compute events in geospatial research, the author intends to provoke thinking into the rationale and conceptual basis of event-based …
From Spatial To Platial - The Role And Future Of Immersive Technologies In The Spatial Sciences, Alexander Klippel
From Spatial To Platial - The Role And Future Of Immersive Technologies In The Spatial Sciences, Alexander Klippel
Journal of Spatial Information Science
Immersive technologies such as virtual and augmented reality have been part of the technology mindset in computer and geospatial sciences early on. The promise of delivering realistic experiences to the human senses that are not bound by physical reality has inspired generations of scientists and entrepreneurs alike. However, the vision for immersive experiences has been in stark contrast to the ability to deliver at the technology end; the community has battled nuisances such as cybersickness, tethers, and the uncanny valley for the last decades. With the 'final wave' of immersive technologies, we are now able to fulfill a long-held promise …
Thinking Spatial, Mohamed F. Mokbel
Thinking Spatial, Mohamed F. Mokbel
Journal of Spatial Information Science
The systems community in both academia and industry has tremendous success in building widely used general purpose systems for various types of data and applications. Examples include database systems, big data systems, data streaming systems, and machine learning systems. The vast majority of these systems are ill equipped in terms of supporting spatial data. The main reason is that system builders mostly think of spatial data as just one more type of data. Any spatial support can be considered as an afterthought problem that can be supported via on-top functions or spatial cartridges that can be added to the already …
Josis' 10th Anniversary Special Feature: Part Two, Benjamin Adams, Somayeh Dodge, Ross Purves
Josis' 10th Anniversary Special Feature: Part Two, Benjamin Adams, Somayeh Dodge, Ross Purves
Journal of Spatial Information Science
No abstract provided.
Josis' 10th Anniversary Special Feature, Benjamin Adams, Somayeh Dodge, Ross Purves
Josis' 10th Anniversary Special Feature, Benjamin Adams, Somayeh Dodge, Ross Purves
Journal of Spatial Information Science
No abstract provided.
Grand Challenges For The Spatial Information Community, Leye Wang, Ouri Wolfson
Grand Challenges For The Spatial Information Community, Leye Wang, Ouri Wolfson
Journal of Spatial Information Science
The spatial information (SI) community has an opportunity to address major societal and scientific problems including public health, climate change, air pollution, transportation, and others. Beyond the significant contributions made by the SI community, more can be done by focusing the efforts of the community, and generalizing them. Focus can be achieved by an IMAGENET-like spatial information database and competition. Generalization can be achieved by solving spatio-temporal information problems in disciplines such as neuroscience, chemistry, biology, astronomy, and engineering.
Ontologies For Geospatial Information: Progress And Challenges Ahead, Christophe Claramunt
Ontologies For Geospatial Information: Progress And Challenges Ahead, Christophe Claramunt
Journal of Spatial Information Science
Over the past 50 years or so the representation of spatial information within computerized systems has been widely addressed and developed in order to provide suitable data manipulation, analysis, and visualisation mechanisms. The range of applications is unlimited and nowadays impacts almost all sciences and practices. However, current conceptualisations and numerical representations of geospatial information still require the development of richer abstract models that match the complexity of spatial and temporal information. Geospatial ontologies are promising modelling alternatives that might favour the implementation and sharing of geographical information. The objective of this vision paper is to provide a short introduction …
How Well Do We Really Know The World? Uncertainty In Giscience, Michael F. Goodchild
How Well Do We Really Know The World? Uncertainty In Giscience, Michael F. Goodchild
Journal of Spatial Information Science
There are many reasons why geospatial data are not geography, but merely representations of it. Thus geospatial data will always leave their user uncertain about the true nature of the world. Over the past three decades uncertainty has become the focus of significant research in GIScience. This paper reviews the reasons for uncertainty, its various dimensions from measurement to modeling, visualization, and propagation. The later sections of the paper explore the implications of current trends, specifically data science, new data sources, and replicability, and the new questions these are posing for GIScience research in the coming years.
Movement Analytics For Sustainable Mobility, Harvey J. Miller
Movement Analytics For Sustainable Mobility, Harvey J. Miller
Journal of Spatial Information Science
Mobility is central to urbanity, and urbanity is central to our common future as the world's population crowds into urban areas. This is creating a global urban mobility crisis due to the unsustainability of our 20th century transportation systems for an urban world. Fortunately, the science and planning of urban mobility is transforming away from infrastructure as the solution towards a sustainable mobility paradigm that manages rather than encourages travel, diminishes mobility and accessibility inequities, and reduces the harms of mobility to people and environments. In this essay, I discuss the contributions over the past decade of movement analytics to …
Geoai: Where Machine Learning And Big Data Converge In Giscience, Wenwen Li
Geoai: Where Machine Learning And Big Data Converge In Giscience, Wenwen Li
Journal of Spatial Information Science
In this paper GeoAI is introduced as an emergent spatial analytical framework for data-intensive GIScience. As the new fuel of geospatial research, GeoAI leverages recent breakthroughs in machine learning and advanced computing to achieve scalable processing and intelligent analysis of geospatial big data. The three-pillar view of GeoAI, its two methodological threads (data-driven and knowledge-driven), as well as their geospatial applications are highlighted. The paper concludes with discussion of remaining challenges and future research directions of GeoAI.
Volunteered And Crowdsourced Geographic Information: The Openstreetmap Project, Michela Bertolotto, Gavin Mcardle, Bianca Schoen-Phelan
Volunteered And Crowdsourced Geographic Information: The Openstreetmap Project, Michela Bertolotto, Gavin Mcardle, Bianca Schoen-Phelan
Journal of Spatial Information Science
Advancements in technology over the last two decades have changed how spatial data are created and used. In particular, in the last decade, volunteered geographic information (VGI), i.e., the crowdsourcing of geographic information, has revolutionized the spatial domain by shifting the map-making process from the hands of experts to those of any willing contributor. Started in 2004, OpenStreetMap (OSM) is the pinnacle of VGI due to the large number of volunteers involved and the volume of spatial data generated. While the original objective of OSM was to create a free map of the world, its uses have shown how the …
Spatial Data Science For Sustainable Mobility, Martin Raubal
Spatial Data Science For Sustainable Mobility, Martin Raubal
Journal of Spatial Information Science
The constant rise of urban mobility and transport has led to a dramatic increase in greenhouse gas emissions. In order to ensure livable environments for future generations and counteract climate change, it will be necessary to reduce our future CO2 footprint. Spatial data science contributes to this effort in major ways, also fuelled by recent progress regarding the availability of spatial big data, computational methods and geospatial technologies. This paper demonstrates important contributions from Spatial data science to mobility pattern analysis and prediction, context integration, and the employment of geospatial technologies for changing people's mobility behavior. Among the interdisciplinary research …
On The Semantics Of Big Earth Observation Data For Land Classification, Gilberto Camara
On The Semantics Of Big Earth Observation Data For Land Classification, Gilberto Camara
Journal of Spatial Information Science
This paper discusses the challenges of using big Earth observation data for land classification. The approach taken is to consider pure data-driven methods to be insufficient to represent continuous change. I argue for sound theories when working with big data. After revising existing classification schemes such as FAO's Land Cover Classification System (LCCS), I conclude that LCCS and similar proposals cannot capture the complexity of landscape dynamics. I then investigate concepts that are being used for analyzing satellite image time series; I show these concepts to be instances of events. Therefore, for continuous monitoring of land change, event recognition needs …
Data-Driven Agriculture For Rural Smallholdings, Kerry Taylor, Martin Amidy
Data-Driven Agriculture For Rural Smallholdings, Kerry Taylor, Martin Amidy
Journal of Spatial Information Science
Spatial information science has a critical role to play in meeting the major challenges facing society in the coming decades, including feeding a population of 10 billion by 2050, addressing environmental degradation, and acting on climate change. Agriculture and agri-food value-chains, dependent on spatial information, are also central. Due to agriculture's dual role as not only a producer of food, fibre and fuel, but also as a major land, water and energy consumer, agriculture is at the centre of both the food-water-energy-environment nexus and resource security debates. The recent confluence of a number of advances in data analytics, cloud computing, …
Trustworthy Maps, Amy L. Griffin
Trustworthy Maps, Amy L. Griffin
Journal of Spatial Information Science
Maps get used for decision making about the world's most pressing problems (e.g., climate change, refugee crises, biodiversity loss, rising inequality, pandemic disease). Although maps have historically been a trusted source of information, changes in society (e.g., lower levels of trust in decision makers) and in mapmaking technologies and practices (e.g., anyone can now make their own maps) mean that we need to spend some time thinking about how, when, and why people trust maps and mapmaking processes. This is critically important if we want stakeholders to engage constructively with the information we present in maps, because they are unlikely …
Ontology Of Core Concept Data Types For Answering Geo-Analytical Questions, Simon Scheider, Rogier Meerlo, Vedran Kasalica, Anna-Lena Lamprecht
Ontology Of Core Concept Data Types For Answering Geo-Analytical Questions, Simon Scheider, Rogier Meerlo, Vedran Kasalica, Anna-Lena Lamprecht
Journal of Spatial Information Science
In geographic information systems (GIS), analysts answer questions by designing workflows that transform a certain type of data into a certain type of goal. Semantic data types help constrain the application of computational methods to those that are meaningful for such a goal. This prevents pointless computations and helps analysts design effective workflows. Yet, to date it remains unclear which types would be needed in order to ease geo-analytical tasks. The data types and formats used in GIS still allow for huge amounts of syntactically possible but nonsensical method applications. Core concepts of spatial information and related geo-semantic distinctions have …
Geospatial Privacy And Security, Grant Mckenzie, Carsten Keßler, Clio Andris
Geospatial Privacy And Security, Grant Mckenzie, Carsten Keßler, Clio Andris
Journal of Spatial Information Science
No abstract provided.
Methosm: A Methodology For Computing Composite Indicators Derived From Openstreetmap Data, Dumitru Roman, Tatiana Tarasova, Javier Paniagua
Methosm: A Methodology For Computing Composite Indicators Derived From Openstreetmap Data, Dumitru Roman, Tatiana Tarasova, Javier Paniagua
Journal of Spatial Information Science
The task of computing composite indicators to define and analyze complex social, economic, political, or environmental phenomena has traditionally been the exclusive competence of statistical offices. Nowadays, the availability of increasing volumes of data and the emergence of the open data movement have enabled individuals and businesses affordable access to all kinds of datasets that can be used as valuable input to compute indicators. OpenStreetMap (OSM) is a good example of this. It has been used as a baseline to compute indicators in areas where official data is scarce or difficult to access. Although the extraction and application of OSM …
Exploring The Effectiveness Of Geomasking Techniques For Protecting The Geoprivacy Of Twitter Users, Song Gao, Jinmeng Rao, Xinyi Liu, Yuhao Kang, Qunying Huang, Joseph App
Exploring The Effectiveness Of Geomasking Techniques For Protecting The Geoprivacy Of Twitter Users, Song Gao, Jinmeng Rao, Xinyi Liu, Yuhao Kang, Qunying Huang, Joseph App
Journal of Spatial Information Science
With the ubiquitous use of location-based services, large-scale individual-level location data has been widely collected through location-awareness devices. Geoprivacy concerns arise on the issues of user identity de-anonymization and location exposure. In this work, we investigate the effectiveness of geomasking techniques for protecting the geoprivacy of active Twitter users who frequently share geotagged tweets in their home and work locations. By analyzing over 38,000 geotagged tweets of 93 active Twitter users in three U.S. cities, the two-dimensional Gaussian masking technique with proper standard deviation settings is found to be more effective to protect user's location privacy while sacrificing geospatial analytical …
Privacy, Space And Time: A Survey On Privacy-Preserving Continuous Data Publishing, Manos Katsomallos, Katerina Tzompanaki, Dimitris Kotzinos
Privacy, Space And Time: A Survey On Privacy-Preserving Continuous Data Publishing, Manos Katsomallos, Katerina Tzompanaki, Dimitris Kotzinos
Journal of Spatial Information Science
Sensors, portable devices, and location-based services, generate massive amounts of geo-tagged, and/or location- and user-related data on a daily basis. The manipulation of such data is useful in numerous application domains, e.g., healthcare, intelligent buildings, and traffic monitoring, to name a few. A high percentage of these data carry information of users' activities and other personal details, and thus their manipulation and sharing arise concerns about the privacy of the individuals involved. To enable the secure‚Äîfrom the users' privacy perspective‚Äîdata sharing, researchers have already proposed various seminal techniques for the protection of users' privacy. However, the continuous fashion in which …
Bridging Space, Time, And Semantics In Giscience, Margarita Kokla, Eric Guilbert, Mir Abolfazl Mostafavi
Bridging Space, Time, And Semantics In Giscience, Margarita Kokla, Eric Guilbert, Mir Abolfazl Mostafavi
Journal of Spatial Information Science
No abstract provided.
Georeferencing Places From Collective Human Descriptions Using Place Graphs, Hao Chen, Stephan Winter, Maria Vasardani
Georeferencing Places From Collective Human Descriptions Using Place Graphs, Hao Chen, Stephan Winter, Maria Vasardani
Journal of Spatial Information Science
Place descriptions in everyday communication or in online text provide a rich source of spatial knowledge about places. Such descriptions typically consist of references to places and spatial relationships between them. An important step to utilize such knowledge in information systems is georeferencing the referred places. Beside place name disambiguation, another challenge is that a significant proportion of place references in such descriptions are not official place names indexed by gazetteers, thus cannot be resolved easily. This paper presents a novel approach for georeferencing places from collective descriptions using place graphs, regardless of whether they are referred to by gazetteered …
A Grounding-Based Ontology Of Data Quality Measures, Franz-Benjamin Mocnik, Amin Mobasheri, Luisa Griesbaum, Melanie Eckle, Clemens Jacobs, Carolin Klonner
A Grounding-Based Ontology Of Data Quality Measures, Franz-Benjamin Mocnik, Amin Mobasheri, Luisa Griesbaum, Melanie Eckle, Clemens Jacobs, Carolin Klonner
Journal of Spatial Information Science
Data quality and fitness for purpose can be assessed by data quality measures. Existing ontologies of data quality dimensions reflect, among others, which aspects of data quality are assessed and the mechanisms that lead to poor data quality. An understanding of which source of information is used to judge about data quality and fitness for purpose is, however, lacking. This article introduces an ontology of data quality measures by their grounding, that is, the source of information to which the data is compared to in order to assess their quality. The ontology is exemplified with several examples of volunteered geographic …