About: Christoph Perger

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An Entity of Type : wikibase:Item, within Data Space : wikidata.demo.openlinksw.com associated with source document(s)

ORCID 0000-0002-7206-4148

Attributes	Values
rdf:type	Item
description	연구원 (ko) 研究者 (ja) araştırmacı (tr) wetenschapper (nl) дослідник (uk) эрдэмтэн (mn) изилдөөчү (ky) 研究者 (zh) ORCID 0000-0002-7206-4148 (en)
rdfs:label	Christoph Perger (en) Christoph Perger (nl)
skos:prefLabel	Christoph Perger (en) Christoph Perger (nl)
name	Christoph Perger (en) Christoph Perger (nl)
given name	wds:Q74543582-91465B9E-3BE7-43AD-A534-1A6ACC14D0F6
given name	Christoph
instance of	wds:Q74543582-f1efe152-4187-a546-e362-c3236e867cd9
instance of	Homo sapiens
occupation	wds:Q74543582-0D56B2D7-945A-48FD-8DF5-37CD0E493A55
employer	wds:Q74543582-38F8934B-89AA-432B-A644-7EEE2C129284 wds:Q74543582-EEBE9AC6-3E4E-4845-85F9-D8DAF7B854F9
VIAF ID	wds:Q74543582-63f573f6-2033-4cce-92e3-c6fb733993ab
GND ID	wds:Q74543582-8c85512d-ebd2-4774-b240-aad2e1d95b1c
DBLP author ID	wds:Q74543582-B3197356-94B5-4489-9929-64995DF13A33
educated at	wds:Q74543582-ECB195BB-5217-4F8D-A489-2E2EEEAF3E61 wds:Q74543582-EFBF6803-78F4-45B7-B70C-F87953F85044
VIAF ID	http://viaf.org/viaf/160251788
GND ID	https://d-nb.info/gnd/142781681
DBLP author ID	https://dblp.org/pid/60/9764.rdf
occupation	researcher
employer	United Nations International Institute for Applied Systems Analysis
VIAF ID	160251788
GND ID	142781681
DBLP author ID	60/9764
educated at	University of Applied Sciences Wiener Neustadt
ORCID iD	wds:Q74543582-d50d5634-48a4-f6a6-ff65-f77baf64cbcd
ORCID iD	https://orcid.org/0000-0002-7206-4148
ORCID iD	0000-0002-7206-4148
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q74543582
is author of	Mapping global cropland and field size Comparing the quality of crowdsourced data contributed by expert and non-experts Developing a community-based worldwide urban morphology and materials database (WUDAPT) using remote sensing and crowdsourcing for improved urban climate modelling Building a hybrid land cover map with crowdsourcing and geographically weighted regression Development of a global hybrid forest mask through the synergy of remote sensing, crowdsourcing and FAO statistics Using control data to determine the reliability of volunteered geographic information about land cover Cropland for sub-Saharan Africa: A synergistic approach using five land cover data sets Assessing quality of volunteer crowdsourcing contributions: lessons from the Cropland Capture game Geo-Wiki: An online platform for improving global land cover Downgrading recent estimates of land available for biofuel production. Crowdsourcing In-Situ Data on Land Cover and Land Use Using Gamification and Mobile Technology The Forest Observation System, building a global reference dataset for remote sensing of forest biomass A global dataset of crowdsourced land cover and land use reference data Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki Increasing the Accuracy of Crowdsourced Information on Land Cover via a Voting Procedure Weighted by Information Inferred from the Contributed Data Geography Geo-Wiki in the Classroom: Using Crowdsourcing to Enhance Geographical Teaching LACO-Wiki: A New Online Land Cover Validation Tool Demonstrated Using GlobeLand30 for Kenya A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform. Assessing and Improving the Reliability of Volunteered Land Cover Reference Data Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania
is author of	wds:Q57655780-DB1C8A32-B6AC-44B0-B31D-C674BA27198C wds:Q58394005-92D44337-D0CB-4CB1-A1A7-FBDA60E867B1 wds:Q73168993-0C8D330E-2C94-4B0E-B9A3-5B177F0C3E93 wds:Q30000785-274618CA-036A-4F60-A420-270289A45CDC wds:Q73186558-379591D6-C167-4BAD-9D37-80CB2FDC5BFC wds:Q66692894-3EB39C91-CBD5-47E7-B74F-193E9A9BC73B wds:Q36400315-94A08AA3-9F94-4DBC-92DA-FF1481613923 wds:Q56805037-9DBDCF70-EFBC-4515-8EFC-18F9ADE7B730 wds:Q90640091-C903983A-2E71-4221-A5A2-507FEBB4CEC3 wds:Q41498398-A07A8D66-B707-42FA-9C09-A7F85F62AEA9 wds:Q60400664-B3FDFD15-ECEA-4480-9B2D-18764DC32C18 wds:Q114363855-CBE73836-A0DA-47D4-97FF-B326DA29FE97 wds:Q58417780-641AFF4C-B371-4DC1-AD4B-CE62AB43B4DD wds:Q73141971-3CD5F59C-2F95-487D-A4BA-C8A1066AAB30 wds:Q42163752-351DC893-68FA-444D-A582-50B501F538FA wds:Q45949909-AA16D8DA-83A9-48AA-BC17-FA7E22E1A8DC wds:Q57879112-AFADF4F0-777B-4A93-B6C2-E49DAE207842 wds:Q58068475-8d880ff7-4ddd-66fe-c819-9100476fb1ac wds:Q57879050-232BCCB7-8EC0-4761-9ED5-9E5F3BF94099 wds:Q97681994-2599552C-DFD5-43FA-9A10-16D72A376906

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