{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T06:20:57Z","timestamp":1782195657865,"version":"3.54.5"},"reference-count":46,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,2,24]],"date-time":"2017-02-24T00:00:00Z","timestamp":1487894400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Static geosensor networks are comprised of stations with sensor devices providing data relevant for monitoring environmental phenomena in their geographic perimeter. Although early warning systems for disaster management rely on data retrieved from these networks, some limitations exist, largely in terms of insufficient coverage and low density. Crowdsourcing user-generated data is emerging as a working methodology for retrieving real-time data in disaster situations, reducing the aforementioned limitations, and augmenting with real-time data generated voluntarily by nearby citizens. This paper explores the use of crowdsourced user-generated sensor weather data from mobile devices for the creation of a unified and densified geosensor network. Different scenario experiments are adapted, in which weather data are collected using smartphone sensors, integrated with the development of a stabilization algorithm, for determining the user-generated weather data reliability and usability. Showcasing this methodology on a large data volume, a spatiotemporal algorithm was developed for filtering on-line user-generated weather data retrieved from WeatherSignal, and used for simulation and assessment of densifying the static geosensor weather network of Israel. Geostatistical results obtained proved that, although user-generated weather data show small discrepancies when compared to authoritative data, with considerations they can be used alongside authoritative data, producing a densified and augmented weather map that is detailed and continuous.<\/jats:p>","DOI":"10.3390\/ijgi6030061","type":"journal-article","created":{"date-parts":[[2017,2,24]],"date-time":"2017-02-24T11:19:50Z","timestamp":1487935190000},"page":"61","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Crowdsourcing User-Generated Mobile Sensor Weather Data for Densifying Static Geosensor Networks"],"prefix":"10.3390","volume":"6","author":[{"given":"Shay","family":"Sosko","sequence":"first","affiliation":[{"name":"Mapping and Geo-Information Engineering, The Technion, Haifa 3200003, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5639-8009","authenticated-orcid":false,"given":"Sagi","family":"Dalyot","sequence":"additional","affiliation":[{"name":"Mapping and Geo-Information Engineering, The Technion, Haifa 3200003, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,2,24]]},"reference":[{"key":"ref_1","unstructured":"Liu, J.W.S., Chu, E.T.H., and Tsai, P.H. A Framework for Fusion of Symbiotic Human Sensor and Physical Sensor Data. Available online: http:\/\/www.iis.sinica.edu.tw\/page\/library\/TechReport\/tr2012\/tr12007.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1080\/17538941003759255","article-title":"Crowdsourcing Geographic Information for disaster response: A research frontier","volume":"3","author":"Goodchild","year":"2010","journal-title":"Int. J. Digit. Earth"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1177\/0165551512437638","article-title":"Towards an integrated crowdsourcing definition","volume":"38","year":"2012","journal-title":"J. Inf. Sci."},{"key":"ref_4","unstructured":"NOAA (2012). The USHCN Version 2 Serial Monthly Datasets, Available online: https:\/\/www.ncdc.noaa.gov\/oa\/climate\/research\/ushcn\/."},{"key":"ref_5","unstructured":"National Research Council Improving Disaster Management: The Role of IT in Mitigation, Preparedness, Response, and Recovery. Available online: https:\/\/www.nap.edu\/read\/11824\/chapter\/3."},{"key":"ref_6","first-page":"332","article-title":"Volunteered geographic information: The nature and motivation of producers","volume":"4","author":"Coleman","year":"2009","journal-title":"Int. J. Spat. Data Infrastruct. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1038\/466685a","article-title":"Citizen science: People power","volume":"466","author":"Hand","year":"2010","journal-title":"Nature"},{"key":"ref_8","unstructured":"Starbird, K. (2011, January 7\u201312). Digital volunteerism during disaster: Crowdsourcing information processing. Proceedings of the Conference on Human Factors in Computing Systems, Vancouver, BC, Canada."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1111\/gec3.12213","article-title":"A review of Volunteered Geographic Information for disaster management","volume":"9","author":"Haworth","year":"2015","journal-title":"Geogr. Compass"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.jnca.2011.03.002","article-title":"Taking advantage of collective knowledge in emergency response systems","volume":"35","author":"Vivacqua","year":"2012","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_11","unstructured":"Horita, F.E.A., Degrossi, L.C., Assis, L.F.F.G., Zipf, A., and Porto de Albuquerque, J. (2013, January 15\u201317). The use of volunteered geographic information and crowdsourcing in disaster management: A systematic literature review. Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, IL, USA."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Wiggins, A., and Crowston, K. (2011, January 4\u20137). From conservation to crowdsourcing: A typology of citizen science. Proceedings of the 2011 44th Hawaii International Conference on System Science (HICSS), Kauai, HI, USA.","DOI":"10.1109\/HICSS.2011.207"},{"key":"ref_13","unstructured":"Evangelos, N., Vourvopoulos, A., Langheinrich, M., Campos, P., and Doria, A. (2014, January 13\u201317). Atmos: A hybrid crowdsourcing approach to weather estimation. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication (UbiComp \u201914 Adjunct), Seattle, WA, USA."},{"key":"ref_14","unstructured":"GCOS Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC (2010 Update). Available online: http:\/\/www.wmo.int\/pages\/prog\/gcos\/Publications\/gcos-138.pdf."},{"key":"ref_15","unstructured":"Field, C.B., Barros, V., Stocker, T.F., Qin, D., Dokken, D.J., Ebi, K.L., Mastrandrea, M.D., Mach, K.J., Plattner, G.-K., and Allen, S.K. (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, Cambridge University Press. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1002\/joc.3678","article-title":"Sensors and the city: A review of urban meteorological networks","volume":"33","author":"Muller","year":"2013","journal-title":"Int. J. Climatol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1175\/BAMS-86-8-1069","article-title":"The community collaborative rain, hail, and snow network: Informal education for scientists and citizens","volume":"86","author":"Cifelli","year":"2005","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1002\/wea.2244","article-title":"UK citizen rainfall network: A pilot study","volume":"69","author":"Illingworth","year":"2014","journal-title":"Weather"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1175\/BAMS-D-13-00014.1","article-title":"mPING: Crowd-sourcing weather reports for research","volume":"95","author":"Elmore","year":"2014","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1186\/1476-072X-10-67","article-title":"Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: Trends, OGC standards and application examples","volume":"10","author":"Boulos","year":"2011","journal-title":"Int. J. Health Geogr."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4081","DOI":"10.1002\/grl.50786","article-title":"Crowdsourcing urban air temperatures from smartphone battery temperatures","volume":"40","author":"Overeem","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3185","DOI":"10.1002\/joc.4210","article-title":"Crowdsourcing for climate and atmospheric sciences: Current status and future potential","volume":"35","author":"Muller","year":"2015","journal-title":"Int. J. Climatol."},{"key":"ref_23","unstructured":"Ge, L., Rizos, C., Han, S., and Zebker, H. (2001, January 19\u201322). Mining subsidence monitoring using the combined InSAR and GPS approach. Proceedings of the 10th International Symposium on Deformation Measurements, Anaheim, CA, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1179\/003962608X389997","article-title":"Comparison of four geodetic network densification solutions","volume":"41","author":"Fok","year":"2009","journal-title":"Surv. Rev."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.inffus.2011.08.001","article-title":"Multisensor data fusion: A review of the state-of-the-art","volume":"14","author":"Khaleghi","year":"2013","journal-title":"Inf. Fusion"},{"key":"ref_26","unstructured":"Llinas, J., McNeese, M., and Hall, D.L. (2011). Modeling and Mapping of Human Source Data, Available online: https:\/\/ntrl.ntis.gov\/NTRL\/dashboard\/searchResults\/titleDetail\/ADA546038.xhtml."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Beach, A., Gartrell, M., Xing, X., and Han, R. (2010, January 22\u201323). Fusing mobile, sensor, and social data to fully enable context-aware computing. Proceedings of the Eleventh Workshop on Mobile Computing Systems & Applications, Annapolis, MD, USA.","DOI":"10.1145\/1734583.1734599"},{"key":"ref_28","unstructured":"Schroeder, M.J., and Buck, C.C. Fire Weather: A Guide for Application of Meteorological Information to Forest Fire Control Operations. Available online: http:\/\/digitalcommons.usu.edu\/barkbeetles\/14\/."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"869","DOI":"10.5194\/acp-13-869-2013","article-title":"Aerosol decadal trends\u2014Part 1: In-situ optical measurements at GAW and IMPROVE stations","volume":"13","author":"Collaud","year":"2013","journal-title":"Atmos. Chem. Phys."},{"key":"ref_30","unstructured":"Lawson, B.D., and Armitage, O.B. (2008). Weather Guide for the Canadian System of Forest Fire Danger Rating."},{"key":"ref_31","unstructured":"National Wildfire Coordinating Group Interagency Wildland Fire Weather Station Standards & Guidelines, Available online: https:\/\/www.nwcg.gov\/sites\/default\/files\/products\/pms426-3.pdf."},{"key":"ref_32","unstructured":"International Data Corporation Smartphone OS Market Share, 2016 Q2. Available online: http:\/\/www.idc.com\/prodserv\/smartphone-os-market-share.jsp."},{"key":"ref_33","unstructured":"Nickinson, P. Samsung Galaxy S4 Specs. Available online: http:\/\/www.androidcentral.com\/samsung-galaxy-s4-specs."},{"key":"ref_34","unstructured":"Sensirion Data Sheet SHTC1 Humidity and Temperature Sensor IC for High-Volume Applications. Available online: http:\/\/www.sensirion.com\/fileadmin\/user_upload\/customers\/sensirion\/Dokumente\/Humidity\/Sensirion_Humidity_SHTC1_Datasheet_V3.pdf."},{"key":"ref_35","unstructured":"OpenSignal Sensing Samsung: The Evolution of Sensors in the Galaxy S Series. Available online: http:\/\/opensignal.com\/blog\/category\/weathersignal-2\/."},{"key":"ref_36","unstructured":"World Meteorological Organization Guide to Meteorological Instruments and Methods of Observation. Available online: https:\/\/www.wmo.int\/pages\/prog\/gcos\/documents\/gruanmanuals\/CIMO\/CIMO_Guide-7th_Edition-2008.pdf."},{"key":"ref_37","unstructured":"Israel Meteorological Station (2015). Israel Meteorological Service User Guide for Using Meteorological Data, Available online: http:\/\/www.ims.gov.il\/IMSEng\/CLIMATE."},{"key":"ref_38","unstructured":"Guptill, S.C., and Morisson, J.L. (1995). Elements of Spatial Data Quality, Pergamon."},{"key":"ref_39","unstructured":"Seo, S., and Marsh, G.M. (2006). A Review and Comparison of Methods for Detecting Outliersin Univariate Data Sets, Department of Biostatistics, Graduate School of Public Health."},{"key":"ref_40","unstructured":"Natrella, M., Croarkin, C., Tobias, P., and Filliben, J.J. (2012). NIST\/SEMATECH E-Handbook of Statistical Methods."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1343","DOI":"10.1080\/01621459.1968.10480932","article-title":"A comparative study of various tests for normality","volume":"63","author":"Shapiro","year":"1968","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"59","DOI":"10.2307\/2685263","article-title":"Thirteen ways to look at the correlation coefficient","volume":"42","author":"Rodgers","year":"1988","journal-title":"Am. Stat."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1111\/j.1538-4632.1995.tb00338.x","article-title":"Local indicators of spatial association-LISA","volume":"27","author":"Anselin","year":"1995","journal-title":"Geogr. Anal."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1111\/j.0016-7363.2005.00671.x","article-title":"GeoDa: An introduction to spatial data analysis","volume":"38","author":"Anselin","year":"2006","journal-title":"Geogr. Anal."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"38","DOI":"10.3808\/jei.201100197","article-title":"Comparison of six GIS-based spatial interpolation methods for estimating airtemperature in Western Saudi Arabia","volume":"18","author":"Eldrandaly","year":"2011","journal-title":"J. Environ. Inform."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Hofstra, N., Haylock, M., New, M., Jones, P., and Frei, C. (2008). Comparison of six methods for the interpolation of daily european climate data. J. Geophys. Res. Atmos.","DOI":"10.1029\/2008JD010100"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/3\/61\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:29:07Z","timestamp":1760207347000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/3\/61"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,2,24]]},"references-count":46,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2017,3]]}},"alternative-id":["ijgi6030061"],"URL":"https:\/\/doi.org\/10.3390\/ijgi6030061","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,2,24]]}}}