Pub Date : 2021-04-01DOI: 10.22224/gistbok/2021.2.8
T. Meyer
{"title":"Earth's Shape, Sea Level, and the Geoid","authors":"T. Meyer","doi":"10.22224/gistbok/2021.2.8","DOIUrl":"https://doi.org/10.22224/gistbok/2021.2.8","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127339640","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 : 2021-04-01DOI: 10.22224/gistbok/2021.2.9
J. Hamerlinck, L. Ramasubramanian
{"title":"GIS&T and Public Policy","authors":"J. Hamerlinck, L. Ramasubramanian","doi":"10.22224/gistbok/2021.2.9","DOIUrl":"https://doi.org/10.22224/gistbok/2021.2.9","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"475 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115287310","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 : 2021-01-01DOI: 10.22224/gistbok/2021.1.1
Guiming Zhang
{"title":"Volunteered Geographic Information","authors":"Guiming Zhang","doi":"10.22224/gistbok/2021.1.1","DOIUrl":"https://doi.org/10.22224/gistbok/2021.1.1","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132280005","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 : 2021-01-01DOI: 10.22224/gistbok/2021.1.8
Aileen R. Buckley, Jon A. Kimerling
{"title":"Map Reading","authors":"Aileen R. Buckley, Jon A. Kimerling","doi":"10.22224/gistbok/2021.1.8","DOIUrl":"https://doi.org/10.22224/gistbok/2021.1.8","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"106 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134196156","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 : 2021-01-01DOI: 10.22224/gistbok/2021.1.13
B. Buttenfield, Georgios Charisoulis
{"title":"Cartographic Modeling","authors":"B. Buttenfield, Georgios Charisoulis","doi":"10.22224/gistbok/2021.1.13","DOIUrl":"https://doi.org/10.22224/gistbok/2021.1.13","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124812109","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 : 2020-10-01DOI: 10.22224/gistbok/2020.4.6
Andrzej Rutkowski
{"title":"GIS&T and Libraries, Archives, and Museums","authors":"Andrzej Rutkowski","doi":"10.22224/gistbok/2020.4.6","DOIUrl":"https://doi.org/10.22224/gistbok/2020.4.6","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124889901","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 : 2020-10-01DOI: 10.22224/gistbok/2020.4.5
Jamal Golmohammadi, Yiqun Xie, Jayant Gupta, Majid Farhadloo, Y. Li, Jiannan Cai, Samantha Detor, Abigail Roh, S. Shekhar
: The goal of spatial data mining is to discover potentially useful, interesting, and non-trivial patterns from spatial data-sets (e.g., GPS trajectory of smartphones). Spatial data mining is societally important having applications in public health, public safety, climate science, etc. For example, in epidemiology, spatial data mining helps to find areas with a high concentration of disease incidents to manage disease outbreaks. Computational methods are needed to discover spatial patterns since the volume and velocity of spatial data exceed the ability of human experts to analyze it. Spatial data has unique characteristics like spatial autocorrelation and spatial heterogeneity which violate the i.i.d (Independent and Identically Distributed) assumption of traditional statistic and data mining methods. Therefore, using traditional methods may miss patterns or may yield spurious patterns, which are costly in societal applications. Further, there are additional challenges such as MAUP (Modifiable Areal Unit Problem) as illustrated by a recent court case debating gerrymandering in elections. In this article, we discuss tools and computational methods of spatial data mining, focusing on the primary spatial pattern families: hotspot detection, colocation detection, spatial prediction, and spatial outlier detection. Hotspot detection methods use domain information to accurately model more active and high-density areas. Colocation detection methods find objects whose instances are in proximity to each other in a location. Spatial prediction approaches explicitly model the neighborhood relationship of locations to predict target variables from input features. Finally, spatial outlier detection methods find data that differ from their neighbors. Lastly, we describe future research and trends in spatial data mining.
{"title":"An Introduction to Spatial Data Mining","authors":"Jamal Golmohammadi, Yiqun Xie, Jayant Gupta, Majid Farhadloo, Y. Li, Jiannan Cai, Samantha Detor, Abigail Roh, S. Shekhar","doi":"10.22224/gistbok/2020.4.5","DOIUrl":"https://doi.org/10.22224/gistbok/2020.4.5","url":null,"abstract":": The goal of spatial data mining is to discover potentially useful, interesting, and non-trivial patterns from spatial data-sets (e.g., GPS trajectory of smartphones). Spatial data mining is societally important having applications in public health, public safety, climate science, etc. For example, in epidemiology, spatial data mining helps to find areas with a high concentration of disease incidents to manage disease outbreaks. Computational methods are needed to discover spatial patterns since the volume and velocity of spatial data exceed the ability of human experts to analyze it. Spatial data has unique characteristics like spatial autocorrelation and spatial heterogeneity which violate the i.i.d (Independent and Identically Distributed) assumption of traditional statistic and data mining methods. Therefore, using traditional methods may miss patterns or may yield spurious patterns, which are costly in societal applications. Further, there are additional challenges such as MAUP (Modifiable Areal Unit Problem) as illustrated by a recent court case debating gerrymandering in elections. In this article, we discuss tools and computational methods of spatial data mining, focusing on the primary spatial pattern families: hotspot detection, colocation detection, spatial prediction, and spatial outlier detection. Hotspot detection methods use domain information to accurately model more active and high-density areas. Colocation detection methods find objects whose instances are in proximity to each other in a location. Spatial prediction approaches explicitly model the neighborhood relationship of locations to predict target variables from input features. Finally, spatial outlier detection methods find data that differ from their neighbors. Lastly, we describe future research and trends in spatial data mining.","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123004745","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 : 2020-07-01DOI: 10.5040/9781509916511.ch-005
X. Gong, Xining Yang
{"title":"Social Media Platforms","authors":"X. Gong, Xining Yang","doi":"10.5040/9781509916511.ch-005","DOIUrl":"https://doi.org/10.5040/9781509916511.ch-005","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122749061","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 : 2020-07-01DOI: 10.22224/gistbok/2020.3.7
M. Yuan
{"title":"Relationships between Space and Time","authors":"M. Yuan","doi":"10.22224/gistbok/2020.3.7","DOIUrl":"https://doi.org/10.22224/gistbok/2020.3.7","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116428844","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 : 2020-04-01DOI: 10.22224/gistbok/2020.2.1
Jochen Albrecht
{"title":"Philosophical Perspectives","authors":"Jochen Albrecht","doi":"10.22224/gistbok/2020.2.1","DOIUrl":"https://doi.org/10.22224/gistbok/2020.2.1","url":null,"abstract":"","PeriodicalId":325401,"journal":{"name":"Geographic Information Science & Technology Body of Knowledge","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127515658","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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