TY - BOOK ID - 133873635 TI - Citizen Science and Geospatial Capacity Building AU - Kocaman, Sultan AU - Saran, Sameer AU - Durmaz, Murat AU - Kumar, A. PY - 2022 PB - Basel MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Research & information: general KW - participatory toponyms KW - knowledge sharing KW - public participation KW - citizen science KW - geospatial capacity building KW - volunteered geographic information KW - social media KW - spatiotemporal bias KW - CitSci KW - earthquake KW - intensity mapping KW - disaster mitigation KW - spatial kriging KW - volunteered geographic information (VGI) KW - data contribution activities KW - spatial and temporal patterns KW - biases KW - eBird KW - community-based geoportal KW - crowdsourced earth observation product KW - remote sensing KW - spatial data infrastructure (SDI) KW - crowdsourced data quality KW - GeoWeb KW - outdoor air pollution KW - symptom mapping KW - data quality KW - web application KW - water quality KW - community-based monitoring KW - machine learning KW - Indian monsoon KW - Jacobin cuckoo KW - Maxent KW - species distribution model KW - habitat suitability KW - range expansion KW - WorldClim KW - CMIP KW - crowdsourcing KW - participatory GIS UR - https://www.unicat.be/uniCat?func=search&query=sysid:133873635 AB - 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. ER -