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Articles 481 - 510 of 5315
Full-Text Articles in Social and Behavioral Sciences
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 …
Integrated Science Of Movement, Urska Demsar, Jed A. Long, Katarzyna Sila-Nowicka
Integrated Science Of Movement, Urska Demsar, Jed A. Long, Katarzyna Sila-Nowicka
Journal of Spatial Information Science
Recent technological advances in movement data acquisition have enabled researchers in many disciplines to study movement at increasingly detailed spatial and temporal scales. Yet there is little overlap in the sharing of methods and models between disciplines, despite similar research objectives and data models. Attempts to bridge this gap are leading towards the establishment of an overarching interdisciplinary science, termed the Integrated Science of Movement. Here we present opportunities and challenges of this process and outline the crucial role that GIScience as a discipline with a focus on space, place, and time can play in the integrated science of movement.
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 …
Cartographic Generalization, Monika Sester
Cartographic Generalization, Monika Sester
Journal of Spatial Information Science
This short paper gives a subjective view on cartographic generalization, its achievements in the past, and the challenges it faces in the future.
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 …
Mining Urban Perceptions From Social Media Data, Yu Liu, Yihong Yuan, Fan Zhang
Mining Urban Perceptions From Social Media Data, Yu Liu, Yihong Yuan, Fan Zhang
Journal of Spatial Information Science
This vision paper summaries the methods of using social media data (SMD) to measure urban perceptions. We highlight two major types of data sources (i.e., texts and imagery) and two corresponding techniques (i.e., natural language processing and computer vision). Recognizing the data quality issues of SMD, we propose three criteria for improving the reliability of SMD-based studies. In addition, integrating multi-source data is a promising approach to mitigating the data quality problems.
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.
What Spatial Environments Mean, Thora Tenbrink
What Spatial Environments Mean, Thora Tenbrink
Journal of Spatial Information Science
Language is one of the most prominent means of representing human thought. Spatial cognition research has made use of this fact for decades, exploring how humans perceive and understand their spatial environments through language analysis. So far, this research has mainly focused on generic cognitive aspects underlying everyday purposes such as knowing where objects are, how they relate to each other, and how to find one's way to a familiar or unfamiliar location. However, human concepts about space can be threatened by change, as the environment changes. Across the globe, people become increasingly aware of climate-change related threats to their …
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.
Spatio-Temporal Visual Analytics: A Vision For 2020s, Natalia Andrienko, Gennady Andrienko
Spatio-Temporal Visual Analytics: A Vision For 2020s, Natalia Andrienko, Gennady Andrienko
Journal of Spatial Information Science
Visual analytics is a research discipline that is based on acknowledging the power and the necessity of the human vision, understanding, and reasoning in data analysis and problem solving. Visual analytics develops methods, analytical workflows, and software tools for analysing data of various types, particularly, spatio-temporal data, which can describe the processes going on in the environment, society, and economy. We briefly overview the achievements of the visual analytics research concerning spatio-temporal data analysis and discuss the major open problems.
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, …
Beyond Spatial Reasoning: Challenges For Ecological Problem Solving, Christian Freksa
Beyond Spatial Reasoning: Challenges For Ecological Problem Solving, Christian Freksa
Journal of Spatial Information Science
This vision piece reflects upon virtues of early computer science due to scarcity and high cost of computational resources. It critically assesses divergences between real-world problems and their computational counterparts in commonsense problem solving. The paper points out the different objectives of commonsense versus scientific approaches to problem solving. It describes how natural cognitive systems exploit space and time without explicitly representing their properties and why purely computational approaches are less efficient than their natural role models, as they depend on explicit representations. We argue for investigating spatio-temporally integrated methods to spatial problem solving. We contrast these methods to sequential …
Wayfinding And Navigation Research For Sustainable Transport, Stephan Winter
Wayfinding And Navigation Research For Sustainable Transport, Stephan Winter
Journal of Spatial Information Science
Spatial information science contributes to the foundations of sustainable transport development. This article focuses especially on the role that research on human wayfinding and navigation plays when it comes to designing digital connectivity and autonomy in urban transport.
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 …
An Algorithm For The Selection Of Route Dependent Orientation Information, Heinrich Loewen, Angela Schwering
An Algorithm For The Selection Of Route Dependent Orientation Information, Heinrich Loewen, Angela Schwering
Journal of Spatial Information Science
Landmarks are important features of spatial cognition and are naturally included in human route descriptions. In the past algorithms were developed to select the most salient landmarks at decision points and automatically incorporate them in route instructions. Moreover, it was shown that human route descriptions contain a significant amount of orientation information, which support the users to orient themselves regarding known environmental information, and it was shown that orientation information support the acquisition of survey knowledge. Thus, there is a need to extend the landmarks selection to automatically select orientation information. In this work, we present an algorithm for the …
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.
Editorial, Ross Purves, Benjamin Adams
Editorial, Ross Purves, Benjamin Adams
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 …