Pub Date : 2018-12-01DOI: 10.1139/GEOMAT-2019-0001
J. Bond, B. Donahue, M. Craymer, G. Banham
There are currently over 700 Global Navigation Satellite System (GNSS) reference stations actively broadcasting corrections (Active Control Stations — ACSs) in Canada. This number has been consistently growing since the early 2000s. In 2009, the federal, provincial, and territorial members of the Canadian Council on Geomatics (CCOG) recognized that consumers of GNSS corrections data had very little ability to verify that service providers were following best practices to ensure the quality of their work. It is common for surveyors to delineate property boundaries or to define the location of civil infrastructure with significant economic value, so being dependent upon another party without quality assurance was perceived as a major risk. Additionally, this new dependence upon commercial ACSs for GNSS corrections posed a threat to the consistency of position values in Canada. To address this concern, CCOG tasked its Canadian Geodetic Reference System Committee (CGRSC) with developing a plan to describe, validate, and provide certification of the GNSS corrections services consumed by industry. This paper summarizes the development of Natural Resources Canada’s (NRCan) Compliance Program for High Accuracy, GNSS Services, and how it can benefit professional surveyors across Canada.
{"title":"NRCan’s Compliance Program for high accuracy, GNSS services: ensuring compatibility with the Canadian Spatial Reference System","authors":"J. Bond, B. Donahue, M. Craymer, G. Banham","doi":"10.1139/GEOMAT-2019-0001","DOIUrl":"https://doi.org/10.1139/GEOMAT-2019-0001","url":null,"abstract":"There are currently over 700 Global Navigation Satellite System (GNSS) reference stations actively broadcasting corrections (Active Control Stations — ACSs) in Canada. This number has been consistently growing since the early 2000s. In 2009, the federal, provincial, and territorial members of the Canadian Council on Geomatics (CCOG) recognized that consumers of GNSS corrections data had very little ability to verify that service providers were following best practices to ensure the quality of their work. It is common for surveyors to delineate property boundaries or to define the location of civil infrastructure with significant economic value, so being dependent upon another party without quality assurance was perceived as a major risk. Additionally, this new dependence upon commercial ACSs for GNSS corrections posed a threat to the consistency of position values in Canada. To address this concern, CCOG tasked its Canadian Geodetic Reference System Committee (CGRSC) with developing a plan to describe, validate, and provide certification of the GNSS corrections services consumed by industry. This paper summarizes the development of Natural Resources Canada’s (NRCan) Compliance Program for High Accuracy, GNSS Services, and how it can benefit professional surveyors across Canada.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2019-0001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45289705","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 : 2018-12-01DOI: 10.1139/GEOMAT-2018-0016
Junfang Gong, Shengwen Li, J. Lee, J. Lee
It is possible to generate real-time and location-by-location data of many types of human dynamic events based on social media information for the awareness of events in public health. Analyzing these events is useful in understanding spatiotemporal trends and patterns of how diseases spread and also provides indications for users’ sentiment about the concerned disease. This article examines the spatial and temporal patterns of social media posts based on the content, attributes, and follower activities of posts on social media. We describe the spatial features of the topic discussed in the posts and the spatial relationship among comments on the posts. We present models for describing the diffusion process of these posts and for exploring their spatiotemporal patterns. Our results suggest that (1) the long-term trends of the topics in users’ views seem to be stable, (2) results from analyzing follower activities of posts are critical in describing the spatial patterns of the posts, and (3) the diffusion process of an event in social media is still similar to that of a traditional information diffusion model. Our findings are useful for understanding social media and social events. The processes we describe in this article suggest a standard form of analysis that can be adopted for extracting spatiotemporal patterns of information diffusion and for data mining in social media posts.
{"title":"Space, time, and disease on social media: a case study of dengue fever in China","authors":"Junfang Gong, Shengwen Li, J. Lee, J. Lee","doi":"10.1139/GEOMAT-2018-0016","DOIUrl":"https://doi.org/10.1139/GEOMAT-2018-0016","url":null,"abstract":"It is possible to generate real-time and location-by-location data of many types of human dynamic events based on social media information for the awareness of events in public health. Analyzing these events is useful in understanding spatiotemporal trends and patterns of how diseases spread and also provides indications for users’ sentiment about the concerned disease. This article examines the spatial and temporal patterns of social media posts based on the content, attributes, and follower activities of posts on social media. We describe the spatial features of the topic discussed in the posts and the spatial relationship among comments on the posts. We present models for describing the diffusion process of these posts and for exploring their spatiotemporal patterns. Our results suggest that (1) the long-term trends of the topics in users’ views seem to be stable, (2) results from analyzing follower activities of posts are critical in describing the spatial patterns of the posts, and (3) the diffusion process of an event in social media is still similar to that of a traditional information diffusion model. Our findings are useful for understanding social media and social events. The processes we describe in this article suggest a standard form of analysis that can be adopted for extracting spatiotemporal patterns of information diffusion and for data mining in social media posts.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2018-0016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45767879","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 : 2018-11-15DOI: 10.1139/geomatica-2018-0017
D. H. Prasetyo, J. Mohamad, R. Fauzi
{"title":"A GIS-based Multi-Criteria Decision Analysis Approach for Public School Site Selection in Surabaya Indonesia","authors":"D. H. Prasetyo, J. Mohamad, R. Fauzi","doi":"10.1139/geomatica-2018-0017","DOIUrl":"https://doi.org/10.1139/geomatica-2018-0017","url":null,"abstract":"","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46477084","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 : 2018-09-01DOI: 10.1139/GEOMAT-2018-0006
Xue-tong Xie, Guojian Ou
Pedestrian network information plays an important role in pedestrian location based service (LBS), and its completeness determines the quality of a pedestrian LBS. This study used volunteered data and BaiduMap to research how to extract pedestrian network information on the basis of pedestrian GPS trajectories. The method extracts human road information by three steps: cleaning track data, extracting the road network, and detecting and analysing the recognised pedestrian road facilities. Once the road network information is extracted, the information regarding road facilities can be obtained, e.g., pedestrian crossings, overpasses, and underground passages. This paper describes a new method for incrementally updating electronic maps.
{"title":"Pedestrian network information extraction based on VGI","authors":"Xue-tong Xie, Guojian Ou","doi":"10.1139/GEOMAT-2018-0006","DOIUrl":"https://doi.org/10.1139/GEOMAT-2018-0006","url":null,"abstract":"Pedestrian network information plays an important role in pedestrian location based service (LBS), and its completeness determines the quality of a pedestrian LBS. This study used volunteered data and BaiduMap to research how to extract pedestrian network information on the basis of pedestrian GPS trajectories. The method extracts human road information by three steps: cleaning track data, extracting the road network, and detecting and analysing the recognised pedestrian road facilities. Once the road network information is extracted, the information regarding road facilities can be obtained, e.g., pedestrian crossings, overpasses, and underground passages. This paper describes a new method for incrementally updating electronic maps.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2018-0006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47629967","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 : 2018-09-01DOI: 10.1139/GEOMAT-2018-0017
D. H. Prasetyo, J. Mohamad, R. Fauzi
Surabaya is one of the old cities of Indonesia and has been inhabited since the Colonial era. It has been continuously growing until today leading to expansion of its area to the south, east, and west. Unfortunately, it has not been supported by the addition of new public schools, particularly at the secondary and high school levels. This research aimed to help the government by determining the suitability level of the whole area of the city for locating a new school and for evaluating current school locations. This research proposed six spatial factors: administration, population, transportation, land-use, student flow, and public preferences. Each factor was represented as raster file built from primary and secondary tabular and spatial data. Each factor then was weighted from the multi-criteria decision analysis step using the analytical hierarchy process method. The results show recommended and non-recommended areas in Surabaya for locating a new school building. This research integrated GIS analysis, web-GIS application, public participation, and MCDA to identify the best solution for this case.
{"title":"A GIS-based multi-criteria decision analysis approach for public school site selection in Surabaya, Indonesia","authors":"D. H. Prasetyo, J. Mohamad, R. Fauzi","doi":"10.1139/GEOMAT-2018-0017","DOIUrl":"https://doi.org/10.1139/GEOMAT-2018-0017","url":null,"abstract":"Surabaya is one of the old cities of Indonesia and has been inhabited since the Colonial era. It has been continuously growing until today leading to expansion of its area to the south, east, and west. Unfortunately, it has not been supported by the addition of new public schools, particularly at the secondary and high school levels. This research aimed to help the government by determining the suitability level of the whole area of the city for locating a new school and for evaluating current school locations. This research proposed six spatial factors: administration, population, transportation, land-use, student flow, and public preferences. Each factor was represented as raster file built from primary and secondary tabular and spatial data. Each factor then was weighted from the multi-criteria decision analysis step using the analytical hierarchy process method. The results show recommended and non-recommended areas in Surabaya for locating a new school building. This research integrated GIS analysis, web-GIS application, public participation, and MCDA to identify the best solution for this case.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2018-0017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44107502","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 : 2018-07-30DOI: 10.1139/GEOMAT-2018-0007
Qinjun Qiu, Zhong Xie, Liang Wu
Unlike English and other western languages, Chinese does not delimit words using white-spaces. Chinese Word Segmentation (CWS) is the crucial first step towards natural language processing. However, for the geoscience subject domain, the CWS problem remains unresolved with many challenges. Although traditional methods can be used to process geoscience documents, they lack the domain knowledge for massive geoscience documents. Considering the above challenges, this motivated us to build a segmenter specifically for the geoscience domain. Currently, most of the state-of-the-art methods for Chinese word segmentation are based on supervised learning, whose features are mostly extracted from a local context. In this paper, we proposed a framework for sequence learning by incorporating cyclic self-learning corpus training. Following this framework, we build the GeoSegmenter based on the Bi-directional Long Short-Term Memory (Bi-LSTM) network model to perform Chinese word segmentation. It can gain a great advantage through iterations of the training data. Empirical experimental results on geoscience documents and benchmark datasets showed that geological documents can be identified, and it can also recognize the generic documents.
{"title":"A cyclic self-learning Chinese word segmentation for the geoscience domain","authors":"Qinjun Qiu, Zhong Xie, Liang Wu","doi":"10.1139/GEOMAT-2018-0007","DOIUrl":"https://doi.org/10.1139/GEOMAT-2018-0007","url":null,"abstract":"Unlike English and other western languages, Chinese does not delimit words using white-spaces. Chinese Word Segmentation (CWS) is the crucial first step towards natural language processing. However, for the geoscience subject domain, the CWS problem remains unresolved with many challenges. Although traditional methods can be used to process geoscience documents, they lack the domain knowledge for massive geoscience documents. Considering the above challenges, this motivated us to build a segmenter specifically for the geoscience domain. Currently, most of the state-of-the-art methods for Chinese word segmentation are based on supervised learning, whose features are mostly extracted from a local context. In this paper, we proposed a framework for sequence learning by incorporating cyclic self-learning corpus training. Following this framework, we build the GeoSegmenter based on the Bi-directional Long Short-Term Memory (Bi-LSTM) network model to perform Chinese word segmentation. It can gain a great advantage through iterations of the training data. Empirical experimental results on geoscience documents and benchmark datasets showed that geological documents can be identified, and it can also recognize the generic documents.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2018-0007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49132909","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 : 2018-07-18DOI: 10.1139/GEOMAT-2018-0001
S. Daniel
La comprehension de nuage de points LiDAR consiste a reconnaitre les objets qui sont presents dans la scene et a associer des interpretations aux nuages d’objets qui le composent. Les donnees LiDAR acquises en milieu urbain dans des environnements a grande echelle avec des systemes terrestres de telemetrie mobile presentent plusieurs difficultes propres a ce contexte : chevauchement entre les nuages de points, occlusions entre les objets qui ne sont vus que partiellement, variations de la densite des points. Compte tenu de ces difficultes, beaucoup de descripteurs tridimensionnels (3D) proposes dans la litterature pour la classification et la reconnaissance d’objets voient leurs performances se degrader dans ce contexte applicatif, car ils ont souvent ete introduits et evalues avec des jeux de donnees portant sur de petits objets. De plus, il y a un manque de comparaison approfondie entre les descripteurs 3D mis en œuvre dans des environnements a grande echelle ce qui a pour consequence un manque de conna...
{"title":"Revue des descripteurs tridimensionnels (3D) pour la catégorisation des nuages de points acquis avec un système LiDAR de télémétrie mobile","authors":"S. Daniel","doi":"10.1139/GEOMAT-2018-0001","DOIUrl":"https://doi.org/10.1139/GEOMAT-2018-0001","url":null,"abstract":"La comprehension de nuage de points LiDAR consiste a reconnaitre les objets qui sont presents dans la scene et a associer des interpretations aux nuages d’objets qui le composent. Les donnees LiDAR acquises en milieu urbain dans des environnements a grande echelle avec des systemes terrestres de telemetrie mobile presentent plusieurs difficultes propres a ce contexte : chevauchement entre les nuages de points, occlusions entre les objets qui ne sont vus que partiellement, variations de la densite des points. Compte tenu de ces difficultes, beaucoup de descripteurs tridimensionnels (3D) proposes dans la litterature pour la classification et la reconnaissance d’objets voient leurs performances se degrader dans ce contexte applicatif, car ils ont souvent ete introduits et evalues avec des jeux de donnees portant sur de petits objets. De plus, il y a un manque de comparaison approfondie entre les descripteurs 3D mis en œuvre dans des environnements a grande echelle ce qui a pour consequence un manque de conna...","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2018-0001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44764824","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 : 2018-06-01DOI: 10.1139/GEOMAT-2018-0018
J. Bi, J. Brodeur, Jiankun Guo, Xingxing Wang
Discovery and access of Web services for geographic information on the Semantic Web has not been addressed yet by the Semantic Web community or by the geographic information community. However, ISO/TC 211 in the ISO Technical Specification ISO/TS 19150-1:2012, Geographic information — Ontology — Part 1: Framework provides a plan to cover this purpose. Recently, ISO/TC 211 approved a new project ISO 19150-4, Geographic information — Ontology — Part 4: Service ontology, for the development of a new ISO standard that deals with Web services for geographic information. This ISO standard has reached the draft international standard stage. This paper aims at providing an overall description of the standard including the ontological framework for geographic information services and a crosswalk with other frameworks for Web services (such as OWL-S, SWSO, WSMO) to support interoperability with them.
{"title":"Research on ontology for geospatial Web services","authors":"J. Bi, J. Brodeur, Jiankun Guo, Xingxing Wang","doi":"10.1139/GEOMAT-2018-0018","DOIUrl":"https://doi.org/10.1139/GEOMAT-2018-0018","url":null,"abstract":"Discovery and access of Web services for geographic information on the Semantic Web has not been addressed yet by the Semantic Web community or by the geographic information community. However, ISO/TC 211 in the ISO Technical Specification ISO/TS 19150-1:2012, Geographic information — Ontology — Part 1: Framework provides a plan to cover this purpose. Recently, ISO/TC 211 approved a new project ISO 19150-4, Geographic information — Ontology — Part 4: Service ontology, for the development of a new ISO standard that deals with Web services for geographic information. This ISO standard has reached the draft international standard stage. This paper aims at providing an overall description of the standard including the ontological framework for geographic information services and a crosswalk with other frameworks for Web services (such as OWL-S, SWSO, WSMO) to support interoperability with them.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2018-0018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41682540","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 : 2018-06-01DOI: 10.1139/GEOMAT-2018-0003
Steven Rogers, B. Ballantyne, E. Tompkins
Land surveying is a process that is more than fieldwork. Survey-as-process includes interplay with existing surveys, with landowners (and others with rights in the land) and with regulators. Proof of concept evidence, theoretical constructs, a Specific Claims Tribunal decision and a First Nations Land Management Act boundary opinion illustrate how survey-as process fits within the larger exercise of re-establishing boundaries.
{"title":"Survey-as-process: meanders or oxbows?","authors":"Steven Rogers, B. Ballantyne, E. Tompkins","doi":"10.1139/GEOMAT-2018-0003","DOIUrl":"https://doi.org/10.1139/GEOMAT-2018-0003","url":null,"abstract":"Land surveying is a process that is more than fieldwork. Survey-as-process includes interplay with existing surveys, with landowners (and others with rights in the land) and with regulators. Proof of concept evidence, theoretical constructs, a Specific Claims Tribunal decision and a First Nations Land Management Act boundary opinion illustrate how survey-as process fits within the larger exercise of re-establishing boundaries.","PeriodicalId":35938,"journal":{"name":"Geomatica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1139/GEOMAT-2018-0003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44985228","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}
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