Vai al contenuto principale della pagina

GeoHumanities 2018 : proceedings of the 2nd ACM SIGSPATIAL Workshop on Geospatial Humanities (GeoHumanities-2018) : Nov 6th, 2018, Seattle, Washington, USA / / editors, Patricia Murrieta-Flores, Bruno Martins ; Association for Computing Machinery-Digital Library, contributor



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Titolo: GeoHumanities 2018 : proceedings of the 2nd ACM SIGSPATIAL Workshop on Geospatial Humanities (GeoHumanities-2018) : Nov 6th, 2018, Seattle, Washington, USA / / editors, Patricia Murrieta-Flores, Bruno Martins ; Association for Computing Machinery-Digital Library, contributor Visualizza cluster
Pubblicazione: New York NY : , : ACM, , 2018
Descrizione fisica: 1 online resource (38 pages) : illustrations
Disciplina: 001.302854
Soggetto topico: Digital humanities
Geographic information systems - Social aspects
Human geography - Data processing
Machine learning - Social aspects
Persona (resp. second.): Murrieta-FloresPatricia
MartinsBruno
Sommario/riassunto: Scholars in the humanities have long paid attention to spatial theory and cartographic outputs. Moreover, in recent years, new technologies and methods have lead to the emergence of a field that is now commonly known as the Spatial Humanities. Methods from the standard toolset of geographic information systems (e.g., computation of viewsheds and zones of influence, least-cost path analysis, mass-preserving areal weighting and dasymetric mapping, terrain classification according to land coverage or land use, different types of thematic cartography techniques, etc.) have been successfully employed to analyze the geographies of human cultures, both past and present, and to address research questions posed by humanities-based fields. However, many challenges persist in the application of more recent technical developments in the geographical information sciences, which have been showcased in venues such as ACM SIGSPATIAL (e.g., high performance computing methods for analyzing increasingly larger datasets, intelligent techniques based on machine learning for developing and tuning models making use of multiple sources of auxiliary data, the usage of volunteered geographical information to complement traditional data sources, or methods from the geo- spatial semantic web to ease interoperability across datasets and services).
Titolo autorizzato: GeoHumanities 2018  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910375692003321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: ACM international conference proceedings series.