COMPARISON OF SPATIAL INTERPOLATION METHODS FOR ATMOSPHERIC CARBON MONITORING

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dc.contributor.advisorKedem, Benjaminen_US
dc.contributor.authorCasey, Philipen_US
dc.contributor.departmentMathematical Statisticsen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2022-09-20T05:30:29Z
dc.date.available2022-09-20T05:30:29Z
dc.date.issued2022en_US
dc.description.abstractSpatial interpolation is an important tool for prediction of unobserved points in space in the earth and environmental sciences. Three methods for spatial interpolation were atmospheric compared. The first two methods are ordinary kriging and Empirical Bayesian Kriging (EBK). The third method is the Bayesian Transformed Gaussian (BTG) model. The three methods are applied to remotely sensed satellite data of atmospheric carbon dioxide (XCO2) provided by NASA’s Orbiting Carbon Observatory (OCO-2) mission. Cross validation on the data shows that the methods are close in terms of mean squared error (MSE) when applied to XCO2 data.en_US
dc.identifierhttps://doi.org/10.13016/br3r-oatr
dc.identifier.urihttp://hdl.handle.net/1903/29196
dc.language.isoenen_US
dc.subject.pqcontrolledStatisticsen_US
dc.subject.pquncontrolledKrigingen_US
dc.subject.pquncontrolledSpatial Statisticsen_US
dc.subject.pquncontrolledStatisticsen_US
dc.titleCOMPARISON OF SPATIAL INTERPOLATION METHODS FOR ATMOSPHERIC CARBON MONITORINGen_US
dc.typeThesisen_US

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