Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling [dataset]

dc.contributor.authorStoy, Paul C.
dc.contributor.authorQuaife, Tristan
dc.date.accessioned2015-05-19T17:55:16Z
dc.date.available2015-05-19T17:55:16Z
dc.date.issued2015-05
dc.description.abstractMATLAB code to perform two-dimensional Tikhonov Regularization (2DTR). Subheaders refer to MATLAB function names. A simulated landscape with a Lagrange multiplier gamma = 10^.85, a mean value of 0.54, and a variance of 0.009 can be generated using: [Rgamma] = doDisaggExperiment(rand(64), 10^.85, 0.009, 0.54 ). The Stoy Lab adheres to an open data policy. Data collected by the Stoy Lab are free to anyone to use with two caveats: 1. Coauthorship may be requested if intellectual input is provided. Intellectual input is defined in this case as an analysis that is critical to outcomes that could not otherwise be performed. 2. Graduate students operate the towers and analyze the data. They must be given the opportunity to be coauthors on your work. Please email paul dot stoy at gmail dot com with any questions.en_US
dc.identifier.citationStoy P, Quaife T (2015) Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling [dataset]. Montana State University ScholarWorks. http://doi.org/10.15788/M21598
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/9022
dc.publisherMontana State University ScholarWorks
dc.relation.ispartofhttp://doi.org/10.1371/journal.pone.0128935
dc.titleProbabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling [dataset]en_US
dc.typeDataseten_US
mus.identifier.categoryLife Sciences & Earth Sciencesen_US
mus.identifier.doihttp://doi.org/10.15788/M21598
mus.relation.collegeCollege of Agricultureen_US
mus.relation.departmentLand Resources & Environmental Sciences.en_US
mus.relation.universityMontana State Universityen_US

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