Special Issue "Place-Based Research in GIScience and Geoinformatics"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 August 2018)

Special Issue Editors

Guest Editor
Prof. Dr. Thomas Blaschke

Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria
Website | E-Mail
Fax: +43 662 8044 182
Interests: GIS; remote sensing; spatial analysis and GIS-based spatial decision support systems; object-based image processing, real time sensing – including ‘people as sensors’ approaches, spatial analysis at ‘the human scale’; human-environment interaction
Guest Editor
Dr. Song Gao

Department of Geography, University of Wisconsin, Madison, WI 53796, USA
Website | E-Mail
Interests: Place-based GIS, Geospatial Semantics, Spatiotemporal Big Data Analytics and Modelling

Special Issue Information

Dear Colleagues,

Space and place are two fundamental concepts in geography, and more broadly in the social sciences, the humanities, and information science. Space is more abstract, while the notion of place is more tangible to humans. Place names and the semantics of places described in natural languages, rather than coordinates (i.e., longitude and latitude) and geometries, are pervasive in human discourse, documents, and social media while location needs to be specified. Moreover, digital gazetteers (dictionaries of places) play a central role for geocoding and interlinking other information. With the increasing availability of user-generated content, social media and geo-social network data, and human digital trajectories generated from GPS devices or smart phones and so on, these new sources provide researchers with great opportunities to study the semantics and computational representations of places, and individuals’ observations, experiences, and exposures to ambient environments, as well as associated human-place interactions.

GIS has arrived at everybody’s desktop, or smartphone, respectively. Many of the underlying geometric operations have been established over the last forty years or so. Of course, real-time applications, augmented reality or indoor navigation are more recent challenges. Still, one of the major challenges is to use spatial information in a way as humans do. This may include place names and functions for places. While the English language clearly differentiates between ‘space’ and ‘place’, the situation is different in some other languages, such as German.

Although place-based investigations into human phenomena have been widely conducted in the humanities and social sciences over the last decades, this notion has only recently transgressed into Geographic Information Science (GIScience). The broad umbrella term for place-centered analyses in GIScience has been informally defined as place-based GIS, which comprises research branches from automated computational place modeling on one end of the spectrum, to theoretical discussions, as for instance in critical GIS on the other end. Central to all research branches concerned with place-based GIS is the notion of placing the individual at the focal point of the investigation, in order to assess human-environment relationships. This requires the formalization of place, which poses a significant research challenge on several levels. The first challenge lies in finding an unambiguous definition of place, in order to subsequently be able to translate it into formalized binary code, which computers and GISs can handle. This formalization poses the next challenge, due to the inherent vagueness and subjectiveness of human data. The last challenge is in ensuring the transferability of results, which requires large samples of highly subjective data. Another important characteristic in place-based GIS is the development of place-based operations or analysis functionalities in analogy to their spatial counterparts. The challenge lies in transforming traditional GIS operations such as spatial buffers and joins, or developing completely new ones, in order to deal with the hierarchical and other semantic structures of places.

This Special Issue invites original contributions that tackle the handling of place and which may address the meaning of place in GIScience research. Articles may determine what is special about place and how place is handled in GIScience, Geoinformatics and in neighboring disciplines. Research may contribute to the overarching questions how place can be adequately addressed and handled with established GIScience methods. What methodologies and methods from other disciplines (e.g., computer science, linguistics, etc.) must be considered in order to sufficiently account for place-based analyses. We encourage contributions which help to conflate findings from emerging research, in an attempt to position place-based GIS within the broader framework of GIScience.

We welcome submissions from diverse disciplines, including Environmental Psychology, Linguistics, Urban Planning, Spatial Economics, Geographic Information Science, Spatial Cognition, Human-Computer Interaction, Data Science, Smart City, Big Data, Health and Place, and others.

Prof. Thomas Blaschke
Dr. Song Gao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Place vs. Space
  • Placenames
  • Vague and subjective information
  • Place semantics
  • Ontologies and epistemologies of place
  • Place cognition
  • Gazetteers
  • Natural language computing
  • Human-place interactions
  • Mixed methods approaches
  • Human digital trajectories
  • Giscience

Published Papers (10 papers)

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Research

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Open AccessArticle Place and City: Toward Urban Intelligence
ISPRS Int. J. Geo-Inf. 2018, 7(9), 346; https://doi.org/10.3390/ijgi7090346
Received: 17 July 2018 / Revised: 11 August 2018 / Accepted: 20 August 2018 / Published: 23 August 2018
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Abstract
Place, as a concept, is subject to a lively, ongoing discussion involving different disciplines. However, most of these discussions approach the issue without a geographic perspective, which is the natural habitat of a place. This study contributes to this discourse through the exploratory
[...] Read more.
Place, as a concept, is subject to a lively, ongoing discussion involving different disciplines. However, most of these discussions approach the issue without a geographic perspective, which is the natural habitat of a place. This study contributes to this discourse through the exploratory examination of urban intelligence utilizing the geographical relationship between sense of place and social capital at the collective and individual level. Using spatial data collected through a web map-based survey, we perform an exhaustive examination of the spatial relationship between sense of place and social capital. We found a significant association between sense of place and social capital from a spatial point of view. Sense of place and social capital spatial dimensions obtain a non-disjoint relationship for approximately half of the participants and a spatial clustering when they are aggregated. This research offers a new exploratory perspective for place studies in the context of cities, and simultaneously attempts to depict a platial–social network based on sense of place and social capital, which cities currently lack. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessFeature PaperArticle A Graph Database Model for Knowledge Extracted from Place Descriptions
ISPRS Int. J. Geo-Inf. 2018, 7(6), 221; https://doi.org/10.3390/ijgi7060221
Received: 15 April 2018 / Revised: 3 June 2018 / Accepted: 13 June 2018 / Published: 15 June 2018
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Abstract
Everyday place descriptions provide a rich source of knowledge about places and their relative locations. This research proposes a place graph model for modelling this spatial, non-spatial, and contextual knowledge from place descriptions. The model extends a prior place graph, and overcomes a
[...] Read more.
Everyday place descriptions provide a rich source of knowledge about places and their relative locations. This research proposes a place graph model for modelling this spatial, non-spatial, and contextual knowledge from place descriptions. The model extends a prior place graph, and overcomes a number of limitations. The model is implemented using a graph database, and a management system has also been developed that allows operations including querying, mapping, and visualizing the stored knowledge in an extended place graph. Then three experimental tasks, namely georeferencing, reasoning, and querying, are selected to demonstrate the superiority of the extended model. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessArticle Deep Belief Networks Based Toponym Recognition for Chinese Text
ISPRS Int. J. Geo-Inf. 2018, 7(6), 217; https://doi.org/10.3390/ijgi7060217
Received: 20 April 2018 / Revised: 21 May 2018 / Accepted: 12 June 2018 / Published: 14 June 2018
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Abstract
In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is
[...] Read more.
In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is the foundation of mining this useful geo-referenced information by identifying words as toponyms in text. In this paper, we propose an adapted toponym recognition approach based on deep belief network (DBN) by exploring two key issues: word representation and model interpretation. A Skip-Gram model is used in the word representation process to represent words with contextual information that are ignored by current word representation models. We then determine the core hyper-parameters of the DBN model by illustrating the relationship between the performance and the hyper-parameters, e.g., vector dimensionality, DBN structures and probability thresholds. The experiments evaluate the performance of the Skip-Gram model implemented by the Word2Vec open-source tool, determine stable hyper-parameters and compare our approach with a conditional random field (CRF) based approach. The experimental results show that the DBN model outperforms the CRF model with smaller corpus. When the corpus size is large enough, their statistical metrics become approaching. However, their recognition results express differences and complementarity on different kinds of toponyms. More importantly, combining their results can directly improve the performance of toponym recognition relative to their individual performances. It seems that the scale of the corpus has an obvious effect on the performance of toponym recognition. Generally, there is no adequate tagged corpus on specific toponym recognition tasks, especially in the era of Big Data. In conclusion, we believe that the DBN-based approach is a promising and powerful method to extract geo-referenced information from text in the future. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessArticle Enhancing Location-Related Hydrogeological Knowledge
ISPRS Int. J. Geo-Inf. 2018, 7(4), 132; https://doi.org/10.3390/ijgi7040132
Received: 29 January 2018 / Revised: 19 March 2018 / Accepted: 22 March 2018 / Published: 24 March 2018
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Abstract
We analyzed the corpus of three geoscientific journals to investigate if there are enough locational references in research articles to apply a geographical search method, such as the example of New Zealand. Based on all available abstracts and all freely available papers of
[...] Read more.
We analyzed the corpus of three geoscientific journals to investigate if there are enough locational references in research articles to apply a geographical search method, such as the example of New Zealand. Based on all available abstracts and all freely available papers of the “New Zealand Journal of Geology and Geophysics”, the “New Zealand Journal of Marine and Freshwater Research”, and the “Journal of Hydrology, New Zealand”, we searched title, abstracts, and full texts for place name occurrences that match records from the official Land Information New Zealand (LINZ) gazetteer. We generated ISO standard compliant metadata records for each article including the spatial references and made them available in a public catalogue service. This catalogue can be queried for articles based on authors, titles, keywords, topics, and spatial reference. We visualize the results in a map to show which area the research articles are about, and how much and how densely geographic space is described through these geoscientific research articles by mapping mentioned place names by their geographic locations. We outlined the methodology and technical framework for the geo-referencing of the journal articles and the platform design for this knowledge inventory. The results indicate that the use of well-crafted abstracts for journal articles with carefully chosen place names of relevance for the article provides a guideline for geographically referencing unstructured information like journal articles and reports in order to make such resources discoverable through geographical queries. Lastly, this approach can actively support integrated holistic assessment of water resources and support decision making. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessArticle Using Spatial Semantics and Interactions to Identify Urban Functional Regions
ISPRS Int. J. Geo-Inf. 2018, 7(4), 130; https://doi.org/10.3390/ijgi7040130
Received: 9 February 2018 / Revised: 14 March 2018 / Accepted: 22 March 2018 / Published: 23 March 2018
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Abstract
The spatial structures of cities have changed dramatically with rapid socio-economic development in ways that are not well understood. To support urban structural analysis and rational planning, we propose a framework to identify urban functional regions and quantitatively explore the intensity of the
[...] Read more.
The spatial structures of cities have changed dramatically with rapid socio-economic development in ways that are not well understood. To support urban structural analysis and rational planning, we propose a framework to identify urban functional regions and quantitatively explore the intensity of the interactions between them, thus increasing the understanding of urban structures. A method for the identification of functional regions via spatial semantics is proposed, which involves two steps: (1) the study area is classified into three types of functional regions using taxi origin/destination (O/D) flows; and (2) the spatial semantics for the three types of functional regions are demonstrated based on point-of-interest (POI) categories. To validate the existence of urban functional regions, we explored the intensity of interactions quantitatively between them. A case study using POI data and taxi trajectory data from Beijing validates the proposed framework. The results show that the proposed framework can be used to identify urban functional regions and promotes an enhanced understanding of urban structures. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessArticle Mining Individual Similarity by Assessing Interactions with Personally Significant Places from GPS Trajectories
ISPRS Int. J. Geo-Inf. 2018, 7(3), 126; https://doi.org/10.3390/ijgi7030126
Received: 29 January 2018 / Revised: 16 March 2018 / Accepted: 17 March 2018 / Published: 19 March 2018
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Abstract
Human mobility is closely associated with places. Due to advancements in GPS devices and related sensor technologies, an unprecedented amount of tracking data has been generated in recent years, thus providing a new way to investigate the interactions between individuals and places, which
[...] Read more.
Human mobility is closely associated with places. Due to advancements in GPS devices and related sensor technologies, an unprecedented amount of tracking data has been generated in recent years, thus providing a new way to investigate the interactions between individuals and places, which are vital for depicting individuals’ characteristics. In this paper, we propose a framework for mining individual similarity based on long-term trajectory data. In contrast to most existing studies, which have focused on the sequential properties of individuals’ visits to public places, this paper emphasizes the essential role of the spatio-temporal interactions between individuals and their personally significant places. Specifically, rather than merely using public geographic databases, which include only public places and lack personal meanings, we attempt to interpret the semantics of places that are significant to individuals from the perspectives of personal behavior. Next, we propose a new individual similarity measurement that incorporates both the spatio-temporal and semantic properties of individuals’ visits to significant places. By experimenting on real-world GPS datasets, we demonstrate that our approach is more capable of distinguishing individuals and characterizing individual features than the previous methods. Additionally, we show that our approach can be used to effectively measure individual similarity and to aggregate individuals into meaningful subgroups. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessArticle An Improved Identification Code for City Components Based on Discrete Global Grid System
ISPRS Int. J. Geo-Inf. 2017, 6(12), 381; https://doi.org/10.3390/ijgi6120381
Received: 12 October 2017 / Revised: 14 November 2017 / Accepted: 22 November 2017 / Published: 23 November 2017
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Abstract
City components are important elements of a city, and their identification plays a key role in digital city management. Various identification codes have been proposed by different departments and systems over the years, however, their application has been partly hindered by the lack
[...] Read more.
City components are important elements of a city, and their identification plays a key role in digital city management. Various identification codes have been proposed by different departments and systems over the years, however, their application has been partly hindered by the lack of a unified coding framework. The use of a code identifying a city component for unified management and geospatial computation across systems is still problematic. In this paper, we put forward an improved identification code for city components based on the discrete global grid system (DGGS). According to their spatial location, city components were identified with one-dimensional integer codes. The results illustrated that this identification code could express the location information of city components explicitly, as well as indicate the spatial distance relationship and the spatial direction relationship between different components. The experiment showed that this code performed better than traditional codes in data query and geospatial computation. Therefore, we concluded that this improved identification code was conducive to the more efficient management of city components, and hence might be used to improve digital city management. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessArticle Understanding the Functionality of Human Activity Hotspots from Their Scaling Pattern Using Trajectory Data
ISPRS Int. J. Geo-Inf. 2017, 6(11), 341; https://doi.org/10.3390/ijgi6110341
Received: 2 September 2017 / Revised: 26 October 2017 / Accepted: 2 November 2017 / Published: 5 November 2017
Cited by 2 | PDF Full-text (2964 KB) | HTML Full-text | XML Full-text
Abstract
Human activity hotspots are the clusters of activity locations in space and time, and a better understanding of their functionality would be useful for urban land use planning and transportation. In this article, using trajectory data, we aim to infer the functionality of
[...] Read more.
Human activity hotspots are the clusters of activity locations in space and time, and a better understanding of their functionality would be useful for urban land use planning and transportation. In this article, using trajectory data, we aim to infer the functionality of human activity hotspots from their scaling pattern in a reliable way. Specifically, a large number of stopping locations are extracted from trajectory data, which are then aggregated into activity hotspots. Activity hotspots are found to display scaling patterns in terms of the sublinear scaling relationships between the number of stopping locations and the number of points of interest (POIs), which indicates economies of scale of human interactions with urban land use. Importantly, this scaling pattern remains stable over time. This finding inspires us to devise an allometric ruler to identify the activity hotspots, whose functionality could be reliably estimated using the stopping locations. Thereafter, a novel Bayesian inference model is proposed to infer their urban functionality, which examines the spatial and temporal information of stopping locations covering 75 days. Experimental results suggest that the functionality of identified activity hotspots are reliably inferred by stopping locations, such as the railway station. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Open AccessArticle The Local Colocation Patterns of Crime and Land-Use Features in Wuhan, China
ISPRS Int. J. Geo-Inf. 2017, 6(10), 307; https://doi.org/10.3390/ijgi6100307
Received: 22 August 2017 / Revised: 25 September 2017 / Accepted: 16 October 2017 / Published: 17 October 2017
Cited by 3 | PDF Full-text (1915 KB) | HTML Full-text | XML Full-text
Abstract
Most studies of spatial colocation patterns of crime and land-use features in geographical information science and environmental criminology employ global measures, potentially obscuring spatial inhomogeneity. This study investigated the relationships of three types of crime with 22 types of land-use in Wuhan, China.
[...] Read more.
Most studies of spatial colocation patterns of crime and land-use features in geographical information science and environmental criminology employ global measures, potentially obscuring spatial inhomogeneity. This study investigated the relationships of three types of crime with 22 types of land-use in Wuhan, China. First, global colocation patterns were examined. Then, local colocation patterns were examined based on the recently-proposed local colocation quotient, followed by a detailed comparison of the results. Different types of crimes were encouraged or discouraged by different types of land-use features with varying intensity, and the local colocation patterns demonstrated spatial inhomogeneity. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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Review

Jump to: Research

Open AccessReview Revisiting the Role of Place in Geographic Information Science
ISPRS Int. J. Geo-Inf. 2018, 7(9), 364; https://doi.org/10.3390/ijgi7090364
Received: 29 May 2018 / Revised: 31 August 2018 / Accepted: 3 September 2018 / Published: 5 September 2018
PDF Full-text (1561 KB) | HTML Full-text | XML Full-text
Abstract
Although place-based investigations into human phenomena have been widely conducted in the social sciences over the last decades, this notion has only recently transgressed into Geographic Information Science (GIScience). Such a place-based GIS comprises research from computational place modeling on one end of
[...] Read more.
Although place-based investigations into human phenomena have been widely conducted in the social sciences over the last decades, this notion has only recently transgressed into Geographic Information Science (GIScience). Such a place-based GIS comprises research from computational place modeling on one end of the spectrum, to purely theoretical discussions on the other end. Central to all research that is concerned with place-based GIS is the notion of placing the individual at the center of the investigation, in order to assess human-environment relationships. This requires the formalization of place, which poses a number of challenges. The first challenge is unambiguously defining place, to subsequently be able to translate it into binary code, which computers and geographic information systems can handle. This formalization poses the next challenge, due to the inherent vagueness and subjectivity of human data. The last challenge is ensuring the transferability of results, requiring large samples of subjective data. In this paper, we re-examine the meaning of place in GIScience from a 2018 perspective, determine what is special about place, and how place is handled both in GIScience and in neighboring disciplines. We, therefore, adopt the view that space is a purely geographic notion, reflecting the dimensions of height, depth, and width in which all things occur and move, while place reflects the subjective human perception of segments of space based on context and experience. Our main research questions are whether place is or should be a significant (sub)topic in GIScience, whether it can be adequately addressed and handled with established GIScience methods, and, if not, which other disciplines must be considered to sufficiently account for place-based analyses. Our aim is to conflate findings from a vast and dynamic field in an attempt to position place-based GIS within the broader framework of GIScience. Full article
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
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