Geomatica最新文献_第3页

NRCan’s Compliance Program for high accuracy, GNSS services: ensuring compatibility with the Canadian Spatial Reference System NRCan的高精度GNSS服务合规计划:确保与加拿大空间参考系统的兼容性

Geomatica Pub Date : 2018-12-01 DOI: 10.1139/GEOMAT-2019-0001

J. Bond, B. Donahue, M. Craymer, G. Banham

{"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":null,"pages":null},"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}

引用次数: 0

Space, time, and disease on social media: a case study of dengue fever in China 社交媒体上的空间、时间和疾病:以中国登革热为例

Geomatica Pub Date : 2018-12-01 DOI: 10.1139/GEOMAT-2018-0016

Junfang Gong, Shengwen Li, J. Lee, J. Lee

{"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":null,"pages":null},"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}

引用次数: 0

A GIS-based Multi-Criteria Decision Analysis Approach for Public School Site Selection in Surabaya Indonesia 基于GIS的印尼泗水公立学校选址多准则决策分析方法

Geomatica Pub Date : 2018-11-15 DOI: 10.1139/geomatica-2018-0017

D. H. Prasetyo, J. Mohamad, R. Fauzi

引用次数: 0

Pedestrian network information extraction based on VGI 基于VGI的行人网络信息提取

Geomatica Pub Date : 2018-09-01 DOI: 10.1139/GEOMAT-2018-0006

Xue-tong Xie, Guojian Ou

引用次数: 3

A GIS-based multi-criteria decision analysis approach for public school site selection in Surabaya, Indonesia 基于gis的印尼泗水公立学校选址的多标准决策分析方法

Geomatica Pub Date : 2018-09-01 DOI: 10.1139/GEOMAT-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/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":null,"pages":null},"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}

引用次数: 13

A cyclic self-learning Chinese word segmentation for the geoscience domain 地球科学领域的循环自学习中文分词

Geomatica Pub Date : 2018-07-30 DOI: 10.1139/GEOMAT-2018-0007

Qinjun Qiu, Zhong Xie, Liang Wu

{"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":null,"pages":null},"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}

引用次数: 19

Revue des descripteurs tridimensionnels (3D) pour la catégorisation des nuages de points acquis avec un système LiDAR de télémétrie mobile 用移动遥测激光雷达系统对点云进行分类的三维描述符综述

Geomatica Pub Date : 2018-07-18 DOI: 10.1139/GEOMAT-2018-0001

S. Daniel

引用次数: 1

Research on ontology for geospatial Web services 地理空间Web服务的本体研究

Geomatica Pub Date : 2018-06-01 DOI: 10.1139/GEOMAT-2018-0018

J. Bi, J. Brodeur, Jiankun Guo, Xingxing Wang

引用次数: 0

Survey-as-process: meanders or oxbows? 调查即过程:曲折还是牛轭?

Geomatica Pub Date : 2018-06-01 DOI: 10.1139/GEOMAT-2018-0003

Steven Rogers, B. Ballantyne, E. Tompkins

引用次数: 0