Citizen Science and Geospatial Capacity Building

• Autore: Kocaman Sultan
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (202 p.)
• Soggetto topico: Research and information: general
• Soggetto non controllato: biases; citizen science; CitSci; CMIP; community-based geoportal; community-based monitoring; crowdsourced data quality; crowdsourced earth observation product; crowdsourcing; data contribution activities; data quality; disaster mitigation; earthquake; eBird; geospatial capacity building; GeoWeb; habitat suitability; Indian monsoon; intensity mapping; Jacobin cuckoo; knowledge sharing; machine learning; Maxent; outdoor air pollution; participatory GIS; participatory toponyms; public participation; range expansion; remote sensing; social media; spatial and temporal patterns; spatial data infrastructure (SDI); spatial kriging; spatiotemporal bias; species distribution model; symptom mapping; volunteered geographic information; volunteered geographic information (VGI); water quality; web application; WorldClim
• Persona (resp. second.): SaranSameer; DurmazMurat; KumarA; KocamanSultan
• Sommario/riassunto: This book is a collection of the articles published the Special Issue of ISPRS International Journal of Geo-Information on "Citizen Science and Geospatial Capacity Building". The articles cover a wide range of topics regarding the applications of citizen science from a geospatial technology perspective. Several applications show the importance of Citizen Science (CitSci) and volunteered geographic information (VGI) in various stages of geodata collection, processing, analysis and visualization; and for demonstrating the capabilities, which are covered in the book. Particular emphasis is given to various problems encountered in the CitSci and VGI projects with a geospatial aspect, such as platform, tool and interface design, ontology development, spatial analysis and data quality assessment. The book also points out the needs and future research directions in these subjects, such as; (a) data quality issues especially in the light of big data; (b) ontology studies for geospatial data suited for diverse user backgrounds, data integration, and sharing; (c) development of machine learning and artificial intelligence based online tools for pattern recognition and object identification using existing repositories of CitSci and VGI projects; and (d) open science and open data practices for increasing the efficiency, decreasing the redundancy, and acknowledgement of all stakeholders.
• Titolo autorizzato: Citizen Science and Geospatial Capacity Building
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910576876503321
• Lo trovi qui: Univ. Federico II