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Articles 31 - 60 of 200
Full-Text Articles in Geography
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 …
Identifying The Use Of A Park Based On Clusters Of Visitors' Movements From Mobile Phone Data, Roberto Pierdicca, Marina Paolanti, Raffaele Vaira, Ernesto Marcheggiani, Eva Savina Malinverni, Emanuele Frontoni
Identifying The Use Of A Park Based On Clusters Of Visitors' Movements From Mobile Phone Data, Roberto Pierdicca, Marina Paolanti, Raffaele Vaira, Ernesto Marcheggiani, Eva Savina Malinverni, Emanuele Frontoni
Journal of Spatial Information Science
Planning urban parks is a burdensome task, requiring knowledge of countless variables that are impossible to consider all at the same time. One of these variables is the set of people who use the parks. Despite information and communication technologies being a valuable source of data, a standardized method which enables landscape planners to use such information to design urban parks is still broadly missing. The objective of this study is to design an approach that can identify how an urban green park is used by its visitors in order to provide planners and the managing authorities with a standardized …
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 …
Use Of Gis To Find Optimum Locations For Anaerobic Digestion Or Composting Facilities In Maine, Usha Humagain
Use Of Gis To Find Optimum Locations For Anaerobic Digestion Or Composting Facilities In Maine, Usha Humagain
Electronic Theses and Dissertations
As per US EPA, in 2017, 41 million tons of food waste was generated, but only 6.3% was diverted from landfills (US EPA, 2020). When landfilled or incinerated, organic waste (food waste, sludge, manure, agricultural waste) causes environmental pollution through greenhouse gas emissions, land, water, and air pollution. In contrast, if we compost or digest organic waste, we can generate soil additives and a mixture of methane and carbon dioxide gas to produce electricity or energy. Both digestion and composting reduce greenhouse gas emissions, improve the land through additives, and boost the economy. Many countries are adopting anaerobic digestion and …
Integrating Local Ecology And Human Dimensions To Understand A Tidally Dynamic Ecosystem In Downeast Maine, Gabriella Marafino
Integrating Local Ecology And Human Dimensions To Understand A Tidally Dynamic Ecosystem In Downeast Maine, Gabriella Marafino
Electronic Theses and Dissertations
Coastal community resilience requires connecting people with useful information that reflects their needs and interests and empowers them to make informed marine resource decisions. In this thesis, I explore how to effectively integrate disparate data from different disciplines and sources to make information more useful and usable at federal, state, tribal, and local levels in order to support more holistic and integrated management. To accomplish this, I draw on different types of knowledge and approaches, including Western science, local ecological knowledge, traditional ecological knowledge, and citizen science, to incorporate the social perspective and community values for holistic marine resource management. …
A Hidden Markov Model For Matching Spatial Networks, Benoit Costes, Julien Perret
A Hidden Markov Model For Matching Spatial Networks, Benoit Costes, Julien Perret
Journal of Spatial Information Science
Datasets of the same geographic space at different scales and temporalities are increasingly abundant, paving the way for new scientific research. These datasets require data integration, which implies linking homologous entities in a process called data matching that remains a challenging task, despite a quite substantial literature, because of data imperfections and heterogeneities. In this paper, we present an approach for matching spatial networks based on a hidden Markov model (HMM) that takes full benefit of the underlying topology of networks. The approach is assessed using four heterogeneous datasets (streets, roads, railway, and hydrographic networks), showing that the HMM algorithm …
Evaluating Existing Manually Constructed Natural Landscape Classification With A Machine Learning-Based Approach, Rok Ciglic, Erik Strumbelj, Rok Cesnovar, Mauro Hrvatin, Drago Perko
Evaluating Existing Manually Constructed Natural Landscape Classification With A Machine Learning-Based Approach, Rok Ciglic, Erik Strumbelj, Rok Cesnovar, Mauro Hrvatin, Drago Perko
Journal of Spatial Information Science
Some landscape classifications officially determine financial obligations; thus, they must be objective and precise. We presume it is possible to quantitatively evaluate existing manually constructed classifications and correct them if necessary. One option for achieving this goal is a machine learning method. With (re)modeling of the landscape classification and an explanation of its structure, we can add quantitative proof to its original (qualitative) description. The main objectives of the paper are to evaluate the consistency of the existing manually constructed natural landscape classification with a machine learning-based approach and to test the newly developed general black-box explanation method in order …
Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko
Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko
Journal of Spatial Information Science
In a typical data collection process, a surveyed spatial object is annotated upon creation, and is classified based on its attributes. This annotation can also be guided by textual definitions of objects. However, interpretations of such definitions may differ among people, and thus result in subjective and inconsistent classification of objects. This problem becomes even more pronounced if the cultural and linguistic differences are considered. As a solution, this paper investigates the role of topology as the defining characteristic of a class of spatial objects. We propose a data mining approach based on frequent itemset mining to learn patterns in …
Considering The Non-Programming Geographer's Perspective When Designing Extracurricular Introductory Computer Programming Workshops, Thomas R Etherington
Considering The Non-Programming Geographer's Perspective When Designing Extracurricular Introductory Computer Programming Workshops, Thomas R Etherington
Journal of Spatial Information Science
Computer programming is becoming an increasingly important scientific skill, but geographers are not necessarily receiving this training as part of their formal education. While there are efforts to promote and support extracurricular introductory computer programming workshops, there remain questions about how best to deliver these workshops. Therefore, as part of a recent introductory programming extracurricular workshop I organized for non-programing geographers, I tried to understand more about their perceptions of computer programming. I identify that one of the most important aspects for geographers to learn to computer program is to have training that is domain specific to ensure that the …
Towards Harmonizing Property Measurement Standards, Abdullah Kara, Volkan Çağdaş, Ümit Işıkdağ, Bülent Onur Turan
Towards Harmonizing Property Measurement Standards, Abdullah Kara, Volkan Çağdaş, Ümit Işıkdağ, Bülent Onur Turan
Journal of Spatial Information Science
Area and volume values of buildings and building parts have been used in many applications including taxation, valuation and land use planning. Many countries maintain a national standard for representing the measurements of floor areas in buildings. The national standards generally use similar basis for measuring building floor areas, in fact, areas specified in national standards often have semantic differences. Therefore, a number of international standards have been developed for harmonizing floor area measurements; however, they also have differences. This study aims at harmonizing the floor areas defined in the international property measurement standards by revealing the semantic relations between …
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.
Hyper-Local Geographically Weighted Regression: Extending Gwr Through Local Model Selection And Local Bandwidth Optimization, Alexis Comber, Yunqiang Wang, Yihe Lü, Xingchang Zhang, Paul Harris
Hyper-Local Geographically Weighted Regression: Extending Gwr Through Local Model Selection And Local Bandwidth Optimization, Alexis Comber, Yunqiang Wang, Yihe Lü, Xingchang Zhang, Paul Harris
Journal of Spatial Information Science
Geographically weighted regression (GWR) is an inherently exploratory technique for examining process non-stationarity in data relationships. This paper develops and applies a hyper-local GWR which extends such investigations further. The hyper-local GWR simultaneously optimizes both local model selection (which covariates to include in each local regression) and local kernel bandwidth specification (how much data should be included locally). These are evaluated using a measure of model fit. The hyper-local GWR approach evaluates different kernel bandwidths at each location and selects the most parsimonious local regression model. By allowing models and bandwidths to vary locally, this approach extends and refines the …
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 …
Towards Place-Based Exploration Of Instagram: Using Co-Design To Develop An Interdisciplinary Geovisualization Prototype, Catherine Emma Jones, Daniele Guido, Marta Severo
Towards Place-Based Exploration Of Instagram: Using Co-Design To Develop An Interdisciplinary Geovisualization Prototype, Catherine Emma Jones, Daniele Guido, Marta Severo
Journal of Spatial Information Science
An abundance of geographic information is hidden within texts and multimedia objects that has the potential to enrich our knowledge about the relationship between people and places. One such example is the geographic information embedded within user-generated content collected and curated by the social media giants. Such geographic data can be encoded either explicitly as geotags or implicitly as geographical references expressed as texts that comprise part of a title or image caption. To use such data for knowledge building there is a need for new mapping interfaces. These interfaces should support both data integration and visualization, and geographical exploration …