Pub Date : 2023-05-17DOI: 10.5311/josis.2023.26.254
T. Etherington
Mapping the extent of spatial objects from point samples is a fundamental process in geographical analysis. Computational geometry methods are commonly used, and one method that has been proposed is the alpha-shape as it is insensitive to both bias and errors that are common in crowdsourced geographic data and big geographic data more generally. However, many spatial objects are uncertain in nature, with vague boundaries that are not well represented by the current use of discrete alpha-shapes. Fuzzy alpha-shapes are presented as a highly generic and adaptable methodology that can produce maps of spatial objects that recognise the vague and uncertain nature of many geographies. A series of virtual geography experiments demonstrate that fuzzy alpha-shapes avoid the need for binary thresholds, create a model that better represents the uncertain boundaries of some spatial objects, while also retaining the robustness to errors and bias that motivated the original use of alpha-shapes for mapping spatial objects.
{"title":"Mapping uncertain spatial object extents from point samples using fuzzy alpha-shapes","authors":"T. Etherington","doi":"10.5311/josis.2023.26.254","DOIUrl":"https://doi.org/10.5311/josis.2023.26.254","url":null,"abstract":"Mapping the extent of spatial objects from point samples is a fundamental process in geographical analysis. Computational geometry methods are commonly used, and one method that has been proposed is the alpha-shape as it is insensitive to both bias and errors that are common in crowdsourced geographic data and big geographic data more generally. However, many spatial objects are uncertain in nature, with vague boundaries that are not well represented by the current use of discrete alpha-shapes. Fuzzy alpha-shapes are presented as a highly generic and adaptable methodology that can produce maps of spatial objects that recognise the vague and uncertain nature of many geographies. A series of virtual geography experiments demonstrate that fuzzy alpha-shapes avoid the need for binary thresholds, create a model that better represents the uncertain boundaries of some spatial objects, while also retaining the robustness to errors and bias that motivated the original use of alpha-shapes for mapping spatial objects.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46426162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.5311/josis.2023.26.221
T. Hashem, M. Duckham, Mahathir Monjur, F. Islam
We introduce a representative dissimilar path (RDP) query, a novel type of path query in road networks. The k representative paths (RPs) between a source and a destination locations have k smallest costs for a feature (e.g., length, number of road intersections, or straightness). Given x features and k, an RDP query returns a set of paths for a source-destination pair such that the path set includes at least one of the k RPs for every feature, and the path set's similarity score is minimized. We formulate a novel measure to quantify the similarity of a set of paths. Considering different road features and incorporating the novel similarity measure in the computation of RDPs allow us to accommodate the human movement dynamics between two locations in an effective way. Finding the RDPs is a computational challenge because an RDP query requires computing the RPs for multiple features and then finding the RDPs from an exponential number of path combinations. We develop an efficient solution to answer RDP queries. The underlying ideas behind the efficiency of our algorithms are the refinement of the search space, finding the RPs for multiple features with a single search, and exploiting both the lower and upper bounds of the path set's similarity score while identifying the RDPs. We show the efficacy of the RDP query and the efficiency of our solution to answer the RDP query in extensive experiments using real datasets.
{"title":"Representative dissimilar path queries: accommodating human movement dynamics in road networks","authors":"T. Hashem, M. Duckham, Mahathir Monjur, F. Islam","doi":"10.5311/josis.2023.26.221","DOIUrl":"https://doi.org/10.5311/josis.2023.26.221","url":null,"abstract":"We introduce a representative dissimilar path (RDP) query, a novel type of path query in road networks. The k representative paths (RPs) between a source and a destination locations have k smallest costs for a feature (e.g., length, number of road intersections, or straightness). Given x features and k, an RDP query returns a set of paths for a source-destination pair such that the path set includes at least one of the k RPs for every feature, and the path set's similarity score is minimized. We formulate a novel measure to quantify the similarity of a set of paths. Considering different road features and incorporating the novel similarity measure in the computation of RDPs allow us to accommodate the human movement dynamics between two locations in an effective way. Finding the RDPs is a computational challenge because an RDP query requires computing the RPs for multiple features and then finding the RDPs from an exponential number of path combinations. We develop an efficient solution to answer RDP queries. The underlying ideas behind the efficiency of our algorithms are the refinement of the search space, finding the RPs for multiple features with a single search, and exploiting both the lower and upper bounds of the path set's similarity score while identifying the RDPs. We show the efficacy of the RDP query and the efficiency of our solution to answer the RDP query in extensive experiments using real datasets.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42596974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.5311/josis.2023.26.240
Éric Guilbert, Francis Lessard, N. Perreault, S. Jutras
The surface network is an application of the Morse-Smale complex to digital terrain models connecting ridges and thalwegs of the terrain in a planar, undirected graph. Although it provides a topological structure embedding critical elements of the terrain, its application to morphological analysis and hydrology remains limited mainly because the drainage network is the most relevant structure for analysis and it cannot be derived from the surface network. The drainage network is a directed, hierarchical graph formed by streams. Ridges of the surface network are not equivalent to drainage divides, which are not contained in the drainage network, and there is no direct association between thalwegs and streams. Therefore, this paper proposes to extend the surface network into a new structure that also embeds the drainage network. This is done by (1) revising the definition of ridges so that they include drainage divides and (2) assigning a flow direction to each thalweg, taking into account spurious depressions to avoid flow interruption. We show that this extended surface network can be used to compute the flow accumulation and different hydrographic features such as drainage basins and the Strahler order. The drainage network extracted from the extended surface network is compared to drainage networks computed with the traditional D8 approach in three case studies. Differences remain minor and are mainly due to the elevation inaccuracy in flat or slightly convex areas. Hence, the extended surface network provides a richer data structure allowing the use of a common topological data structure in both terrain analysis and hydrology.
{"title":"Surface network and drainage network: towards a common data structure","authors":"Éric Guilbert, Francis Lessard, N. Perreault, S. Jutras","doi":"10.5311/josis.2023.26.240","DOIUrl":"https://doi.org/10.5311/josis.2023.26.240","url":null,"abstract":"The surface network is an application of the Morse-Smale complex to digital terrain models connecting ridges and thalwegs of the terrain in a planar, undirected graph. Although it provides a topological structure embedding critical elements of the terrain, its application to morphological analysis and hydrology remains limited mainly because the drainage network is the most relevant structure for analysis and it cannot be derived from the surface network. The drainage network is a directed, hierarchical graph formed by streams. Ridges of the surface network are not equivalent to drainage divides, which are not contained in the drainage network, and there is no direct association between thalwegs and streams. Therefore, this paper proposes to extend the surface network into a new structure that also embeds the drainage network. This is done by (1) revising the definition of ridges so that they include drainage divides and (2) assigning a flow direction to each thalweg, taking into account spurious depressions to avoid flow interruption. We show that this extended surface network can be used to compute the flow accumulation and different hydrographic features such as drainage basins and the Strahler order. The drainage network extracted from the extended surface network is compared to drainage networks computed with the traditional D8 approach in three case studies. Differences remain minor and are mainly due to the elevation inaccuracy in flat or slightly convex areas. Hence, the extended surface network provides a richer data structure allowing the use of a common topological data structure in both terrain analysis and hydrology.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41896900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.5311/josis.2023.26.256
Axel Forsch, Johannes Oehrlein, Benjamin Niedermann, J. Haunert
The optimal path between two vertices in a graph depends on the optimization objective, which is often defined as a weighted sum of multiple criteria. When integrating two criteria, their relative importance is expressed with a balance factor α. We present a new approach for inferring α from trajectories. The core of our approach is a compression algorithm that requires a graph G representing a transportation network, two edge costs modeling routing criteria, and a path P in G representing the trajectory. It yields a minimum subsequence S of the sequence of vertices of P and a balance factor α, such that the path P can be fully reconstructed from S, G, its edge costs, and α. By minimizing the size of S over α, we learn the balance factor that corresponds best to the user's routing preferences. In an evaluation with crowd-sourced cycling trajectories, we weigh the usage of official signposted cycle routes against other routes. More than 50% of the trajectories can be segmented into five optimal sub-paths or less. Almost 40% of the trajectories indicate that the cyclist is willing to take a detour of 50% over the geodesic shortest path to use an official cycle path.
{"title":"Inferring routing preferences from user-generated trajectories using a compression criterion","authors":"Axel Forsch, Johannes Oehrlein, Benjamin Niedermann, J. Haunert","doi":"10.5311/josis.2023.26.256","DOIUrl":"https://doi.org/10.5311/josis.2023.26.256","url":null,"abstract":"The optimal path between two vertices in a graph depends on the optimization objective, which is often defined as a weighted sum of multiple criteria. When integrating two criteria, their relative importance is expressed with a balance factor α. We present a new approach for inferring α from trajectories. The core of our approach is a compression algorithm that requires a graph G representing a transportation network, two edge costs modeling routing criteria, and a path P in G representing the trajectory. It yields a minimum subsequence S of the sequence of vertices of P and a balance factor α, such that the path P can be fully reconstructed from S, G, its edge costs, and α. By minimizing the size of S over α, we learn the balance factor that corresponds best to the user's routing preferences. In an evaluation with crowd-sourced cycling trajectories, we weigh the usage of official signposted cycle routes against other routes. More than 50% of the trajectories can be segmented into five optimal sub-paths or less. Almost 40% of the trajectories indicate that the cyclist is willing to take a detour of 50% over the geodesic shortest path to use an official cycle path.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70769779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-20DOI: 10.5311/josis.2022.25.204
Ljiljana Šerić, Marina Tavra, I. Racetin, Antonia Ivanda
Coordinating and managing teams searching for missing persons in wilderness areas is challenging. Local terrain characteristics and environmental conditions strongly influence how searchers accomplish their search tasks. When making decisions, searchers consult various maps of the area. In this paper we proposed a methodology for mapping characteristics of the area that influence user behavior when walking the area, and define a walkability model of the terrain. We define walkability as a measure of how fast a person can walk through terrain. The observed walking speed depends on factors such as the fitness and motivation of a person walking through the terrain, as well as on assistive features and the configuration of the terrain. In our method, walkability is predicted only as a feature of terrain configuration. We used singular value decomposition (SVD) to transform datasets to extract latent features of the terrain and users from multiple Global Positioning System (GPS) trails. We define the walkability measure as a latent component of walking speed, which is a function of terrain features. Finally, we use a polynomial regression algorithm to build a model for predicting terrain walkability based on remote sensing imagery from the Sentinel-2 mission. The application of the proposed model is demonstrated in the Kozjak mountain region in the Republic of Croatia.
{"title":"Modeling walkability by remote sensing as latent walking speed extracted from multiple digital trail maps","authors":"Ljiljana Šerić, Marina Tavra, I. Racetin, Antonia Ivanda","doi":"10.5311/josis.2022.25.204","DOIUrl":"https://doi.org/10.5311/josis.2022.25.204","url":null,"abstract":"Coordinating and managing teams searching for missing persons in wilderness areas is challenging. Local terrain characteristics and environmental conditions strongly influence how searchers accomplish their search tasks. When making decisions, searchers consult various maps of the area. In this paper we proposed a methodology for mapping characteristics of the area that influence user behavior when walking the area, and define a walkability model of the terrain. We define walkability as a measure of how fast a person can walk through terrain. The observed walking speed depends on factors such as the fitness and motivation of a person walking through the terrain, as well as on assistive features and the configuration of the terrain. In our method, walkability is predicted only as a feature of terrain configuration. We used singular value decomposition (SVD) to transform datasets to extract latent features of the terrain and users from multiple Global Positioning System (GPS) trails. We define the walkability measure as a latent component of walking speed, which is a function of terrain features. Finally, we use a polynomial regression algorithm to build a model for predicting terrain walkability based on remote sensing imagery from the Sentinel-2 mission. The application of the proposed model is demonstrated in the Kozjak mountain region in the Republic of Croatia.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42433243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-20DOI: 10.5311/josis.2022.25.164
M. Soares, F. Fonseca, R. Ramos
A historical center can be defined as the oldest part of a city where a significant part of the building stock dates back to the early stages of urban growth. Historical centers often contain special urban fabrics with unique, historic, social and cultural identity. Owing to this, they have been subject to special urban planning interventions in order not only to protect the existing urban fabric and its originality, but also to revert depopulation and built deterioration processes aiming to make these old centers attractive and functional again. However, in the inter-urban domain, there is a deficit of spatial planning research, and the delimitation of historical centers is a topic that has been under explored. This paper describes a morphological approach for delimiting the historical center of Guarda, Portugal. Methodologically, the work uses building stock-age data from eight periods between <1919 to 2011 and is supported by both statistical and spatial analysis. Statistically, the urban evolution of the city was analyzed through threshold values and five novel building indexes. Spatially, the work involved disaggregated GIS analysis to map the evolution of built-up areas and to identify the consolidated urban areas. A sensitivity analysis was also performed to assess the influence of some parameters on the obtained boundary. Results indicated that the historical center of Guarda was consolidated in the 1960s and, since then, has been relatively unchanged. The obtained boundary shows a suitable spatial adjustment considering the consolidated urban area and the official boundary included in the Urban Rehabilitation Area.
{"title":"A quantitative spatial methodology for delimiting historical centers - an application in Guarda, Portugal","authors":"M. Soares, F. Fonseca, R. Ramos","doi":"10.5311/josis.2022.25.164","DOIUrl":"https://doi.org/10.5311/josis.2022.25.164","url":null,"abstract":"A historical center can be defined as the oldest part of a city where a significant part of the building stock dates back to the early stages of urban growth. Historical centers often contain special urban fabrics with unique, historic, social and cultural identity. Owing to this, they have been subject to special urban planning interventions in order not only to protect the existing urban fabric and its originality, but also to revert depopulation and built deterioration processes aiming to make these old centers attractive and functional again. However, in the inter-urban domain, there is a deficit of spatial planning research, and the delimitation of historical centers is a topic that has been under explored. This paper describes a morphological approach for delimiting the historical center of Guarda, Portugal. Methodologically, the work uses building stock-age data from eight periods between <1919 to 2011 and is supported by both statistical and spatial analysis. Statistically, the urban evolution of the city was analyzed through threshold values and five novel building indexes. Spatially, the work involved disaggregated GIS analysis to map the evolution of built-up areas and to identify the consolidated urban areas. A sensitivity analysis was also performed to assess the influence of some parameters on the obtained boundary. Results indicated that the historical center of Guarda was consolidated in the 1960s and, since then, has been relatively unchanged. The obtained boundary shows a suitable spatial adjustment considering the consolidated urban area and the official boundary included in the Urban Rehabilitation Area. ","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45073801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-20DOI: 10.5311/josis.2022.25.174
S. Dlamini, S. Tesfamichael, G. Weir-Smith, T. Mokhele
There is limited consensus among researchers on whether the spatial distribution of environmental perceptions and place attachment is influenced by socio-economic factors. This study aimed to determine if environmental perceptions and place attachment concepts in our study area (within Gauteng province, South Africa) showed specific spatial patterns. Hot spot, cluster-outlier analysis, and geographically weighted regression (GWR) were used to depict the spatial patterns of environmental perceptions and place attachment. Results showed a pattern where the central, generally affluent wards of the province hold more positive environmental perceptions and place attachment than those in the periphery. This is in line with dependency and other models that associate lower socio-economic status with lower levels of environmental awareness but is incongruent with other findings that have associated lower socio-economic status with pro-environmental behaviour being more prominent. Geographically weighted regression results revealed the combined importance of numbers of people with above-average income, college-level education, age below 50 years, female proportion, formal dwelling residence and African race in explaining the numbers of people with positive views on place attachment and environmental perceptions. Further, the GWR modelling allowed for the spatial dependence of the relationship between place attachment and environmental perceptions on the one hand and socio-economic factors on the other. These results have significant implications for environmental sustainability, planning and policy formulation in the province.
{"title":"Spatial pattern of environmental perception and place attachment in a diverse socio-economic context: the case of Gauteng province, South Africa","authors":"S. Dlamini, S. Tesfamichael, G. Weir-Smith, T. Mokhele","doi":"10.5311/josis.2022.25.174","DOIUrl":"https://doi.org/10.5311/josis.2022.25.174","url":null,"abstract":"There is limited consensus among researchers on whether the spatial distribution of environmental perceptions and place attachment is influenced by socio-economic factors. This study aimed to determine if environmental perceptions and place attachment concepts in our study area (within Gauteng province, South Africa) showed specific spatial patterns. Hot spot, cluster-outlier analysis, and geographically weighted regression (GWR) were used to depict the spatial patterns of environmental perceptions and place attachment. Results showed a pattern where the central, generally affluent wards of the province hold more positive environmental perceptions and place attachment than those in the periphery. This is in line with dependency and other models that associate lower socio-economic status with lower levels of environmental awareness but is incongruent with other findings that have associated lower socio-economic status with pro-environmental behaviour being more prominent. Geographically weighted regression results revealed the combined importance of numbers of people with above-average income, college-level education, age below 50 years, female proportion, formal dwelling residence and African race in explaining the numbers of people with positive views on place attachment and environmental perceptions. Further, the GWR modelling allowed for the spatial dependence of the relationship between place attachment and environmental perceptions on the one hand and socio-economic factors on the other. These results have significant implications for environmental sustainability, planning and policy formulation in the province.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48632182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-20DOI: 10.5311/josis.2022.25.166
M. Tennekes, Y. Gootzen
Mobile network operator (MNO) data are a rich data source for various topics in official statistics, such as present population, mobility, migration, and tourism. Estimating the geographic location of mobile devices is an essential step for statistical inference. Most studies use Voronoi tessellation for this, which is based on the assumption that mobile devices are always connected to the nearest radio cell. We propose an alternative location estimation method following a Bayesian approach and using a physical model for the received signal strength. Our Bayesian framework allows for different modules of prior knowledge about where devices are expected to be, and different modules for the likelihood of connection given a geographic location. We discuss and compare the use of several prior modules, including one that is based on land use. For the likelihood module we propose a signal strength model using radio cell properties such as antenna height, propagation direction, and power. Using Bayes' rule, we derive a posterior probability distribution that is an estimate of the geographic location, which can be used for further statistical inference. We describe the method and provide illustrations of a fictional example that resembles a real-world situation. The method has been implemented in the R packages mobloc and mobvis, which are briefly described.
{"title":"Bayesian location estimation of mobile devices using a signal strength model","authors":"M. Tennekes, Y. Gootzen","doi":"10.5311/josis.2022.25.166","DOIUrl":"https://doi.org/10.5311/josis.2022.25.166","url":null,"abstract":"Mobile network operator (MNO) data are a rich data source for various topics in official statistics, such as present population, mobility, migration, and tourism. Estimating the geographic location of mobile devices is an essential step for statistical inference. Most studies use Voronoi tessellation for this, which is based on the assumption that mobile devices are always connected to the nearest radio cell. We propose an alternative location estimation method following a Bayesian approach and using a physical model for the received signal strength. Our Bayesian framework allows for different modules of prior knowledge about where devices are expected to be, and different modules for the likelihood of connection given a geographic location. We discuss and compare the use of several prior modules, including one that is based on land use. For the likelihood module we propose a signal strength model using radio cell properties such as antenna height, propagation direction, and power. Using Bayes' rule, we derive a posterior probability distribution that is an estimate of the geographic location, which can be used for further statistical inference. We describe the method and provide illustrations of a fictional example that resembles a real-world situation. The method has been implemented in the R packages mobloc and mobvis, which are briefly described.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47613278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.5311/josis.2022.24.199
S. Ray, B. Nickerson
New spatio-textual indexing methods are needed to support efficient search and update of the massive amounts of spatially referenced text being generated. Location based services using geo-tagged documents provide valuable ranked recommendations about nearby restaurants, services, sales, emergency events, and visitor attractions. Consequently, top-k spatial keyword search queries (TkSKQ) have received a lot of attention from the research community. Several spatio-textual indexes have been proposed to efficiently support TkSKQ. Some of these indexes support updates based on live document streams, but the ranking schemes employed by them do not simultaneously incorporate temporal relevance, textual similarity and spatial proximity. Moreover, existing approaches have limited or no capability to exploit parallelism with document ingestion and query execution. We present a parallel spatio-textual index, Pastri, to address the aforementioned issues. Pastri can be updated incrementally over real-time spatio-textual document streams. To support temporally relevant ranking of continuously generated document streams, we propose a dynamic ranking scheme. Our approach retrieves the top-k documents that are most temporally relevant at the time of a query execution. We implemented Pastri and we integrate it within a system with a persistent document store and several thread pools to exploit parallelism at various levels. Experimental evaluation involving real-world datasets and synthetic datasets (that we created) demonstrates that our system is able to sustain high document update throughput. Furthermore, Pastri's TkSKQ search performance is one to two orders of magnitude faster than other spatio-textual indexes.
{"title":"Temporally relevant parallel top-k spatial keyword search","authors":"S. Ray, B. Nickerson","doi":"10.5311/josis.2022.24.199","DOIUrl":"https://doi.org/10.5311/josis.2022.24.199","url":null,"abstract":"New spatio-textual indexing methods are needed to support efficient search and update of the massive amounts of spatially referenced text being generated. Location based services using geo-tagged documents provide valuable ranked recommendations about nearby restaurants, services, sales, emergency events, and visitor attractions. Consequently, top-k spatial keyword search queries (TkSKQ) have received a lot of attention from the research community. Several spatio-textual indexes have been proposed to efficiently support TkSKQ. Some of these indexes support updates based on live document streams, but the ranking schemes employed by them do not simultaneously incorporate temporal relevance, textual similarity and spatial proximity. Moreover, existing approaches have limited or no capability to exploit parallelism with document ingestion and query execution. We present a parallel spatio-textual index, Pastri, to address the aforementioned issues. Pastri can be updated incrementally over real-time spatio-textual document streams. To support temporally relevant ranking of continuously generated document streams, we propose a dynamic ranking scheme. Our approach retrieves the top-k documents that are most temporally relevant at the time of a query execution. We implemented Pastri and we integrate it within a system with a persistent document store and several thread pools to exploit parallelism at various levels. Experimental evaluation involving real-world datasets and synthetic datasets (that we created) demonstrates that our system is able to sustain high document update throughput. Furthermore, Pastri's TkSKQ search performance is one to two orders of magnitude faster than other spatio-textual indexes.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44859171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.5311/josis.2022.24.209
T. Tenbrink, A. Williams
Despite the prominence of 'place' notions in human geography and beyond, the language of place is surprisingly poorly understood. Platial research addresses human relations to places beyond the purely (geometric and cognitive) spatial aspects, whose linguistic features are well researched. This paper offers an in-depth case study of platial discourse in English and Welsh, contributing to a better understanding of how people use language to describe their attachment to a place. We asked 72 people to describe three local areas in North Wales in terms of what makes each one special and distinctive, along with further questions. We explore the responses in terms of a range of qualitative linguistic features indicating aspects such as proximity and ownership, identify a range of semantic categories relevant to the notion of place, and offer an exhaustive analysis of how one particularly popular local feature - castles - is referred to in our data. Beyond identifying how the three local areas differ with respect to the platial attachment associated with them, this paper offers lists of keywords for each of the identified platial semantic categories as a basis for future studies in the field. Our findings further suggest that ownership terminology, time references, and spatial inferences frequently characterise expressions of place appreciation, in different ways in English and Welsh.
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