Using volunteered geographic information (VGI) in design-based statistical inference for area estimation and accuracy assessment of land cover

15247 12 83891 3 235897 document 83891 VGI_DB_Inference_R1_Final.pdf application/pdf 82468563d979ceab62078c6108dec479 MD5 696370 2018-04-27 11:33:41 https://pure.iiasa.ac.at/id/eprint/15247/1/VGI_DB_Inference_R1_Final.pdf 15247 1 1 application/pdf text en public cc_by_nc_nd_4

VGI_DB_Inference_R1_Final.pdf

accepted 83896 2 235905 document 83896 lightbox.jpg image/png 166812eec8fdafb11d7b97055277a4d3 MD5 44307 2018-04-27 11:34:38 https://pure.iiasa.ac.at/id/eprint/15247/2/lightbox.jpg 15247 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en staffonly

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/83891 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/83891 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/83891 archive 353 disk0/00/01/52/47 2018-04-27 08:52:46 2021-08-27 17:30:17 2018-04-27 08:52:46 article show Stehman S.V. Fonte C.C. Foody G.M. See L. 8571 0000-0002-2665-7065 Using volunteered geographic information (VGI) in design-based statistical inference for area estimation and accuracy assessment of land cover pub prog_esm Probability sampling; External validity; Pseudo-weights; Data quality; Model-based inference; Volunteered geographic information (VGI); Crowdsourcing Volunteered Geographic Information (VGI) offers a potentially inexpensive source of reference data for estimating area and assessing map accuracy in the context of remote-sensing based land-cover monitoring. The quality of observations from VGI and the typical lack of an underlying probability sampling design raise concerns regarding use of VGI in widely-applied design-based statistical inference. This article focuses on the fundamental issue of sampling design used to acquire VGI. Design-based inference requires the sample data to be obtained via a probability sampling design. Options for incorporating VGI within design-based inference include: 1) directing volunteers to obtain data for locations selected by a probability sampling design; 2) treating VGI data as a “certainty stratum” and augmenting the VGI with data obtained from a probability sample; and 3) using VGI to create an auxiliary variable that is then used in a model-assisted estimator to reduce the standard error of an estimate produced from a probability sample. The latter two options can be implemented using VGI data that were obtained from a non-probability sampling design, but require additional sample data to be acquired via a probability sampling design. If the only data available are VGI obtained from a non-probability sample, properties of design-based inference that are ensured by probability sampling must be replaced by assumptions that may be difficult to verify. For example, pseudo-estimation weights can be constructed that mimic weights used in stratified sampling estimators. However, accuracy and area estimates produced using these pseudo-weights still require the VGI data to be representative of the full population, a property known as “external validity”. Because design-based inference requires a probability sampling design, directing volunteers to locations specified by a probability sampling design is the most straightforward option for use of VGI in design-based inference. Combining VGI from a non-probability sample with data from a probability sample using the certainty stratum approach or the model-assisted approach are viable alternatives that meet the conditions required for design-based inference and use the VGI data to advantage to reduce standard errors. 2018-06 published Elsevier 10.1016/j.rse.2018.04.014 276 public Remote Sensing of Environment 212 47-59 TRUE 1879-0704 Harnessing the power of crowdsourcing to improve land cover and land-use information (CROWDLAND, FP7 617754) A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring (LANDSENSE, H2020 689812) FALSE yes info:eu-repo/grantAgreement/EC/FP7/617754/EU//CROWDLAND; info:eu-repo/grantAgreement/EC/H2020/689812/EU//LANDSENSE; info:eu-repo/semantics/article info:eu-repo/semantics/embargoedAccess