Imputing Mean Annual Change to Estimate Current Forest Attributes Public Deposited

http://ir.library.oregonstate.edu/concern/defaults/g158bh83r

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  • When a temporal trend in forest conditions is present, standard estimates from paneled forest inventories can be biased. Thus methods that use more recent remote sensing data to improve estimates are desired. Paneled inventory data from national forests in Oregon and Washington, U.S.A., were used to explore three nearest neighbor imputation methods to estimate mean annual change of four forest attributes (basal area/ha, stems/ha, volume/ha, biomass/ha). The random Forest imputation method outperformed the other imputation approaches in terms of root mean square error. The imputed mean annual change was used to project all panels to a common point in time by multiplying the mean annual change with the length of the growth period between measurements and adding the change estimate to the previously observed measurements of the four forest attributes. The resulting estimates of the mean of the forest attributes at the current point in time outperformed the estimates obtained from the national standard estimator.
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  • Eskelson, B.N.I., T.M. Barrett, and H. Temesgen. 2009. Imputing Mean Annual Change and Estimating Current Forest Attributes. Silva Fennica. 43(4):649-658.
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  • description.provenance : Approved for entry into archive by Sue Kunda(sue.kunda@oregonstate.edu) on 2012-03-28T01:13:06Z (GMT) No. of bitstreams: 1 Imputing Mean Annual Change and Estimating Current Forest Attributes.pdf: 345930 bytes, checksum: 8170629fae7c74764f3745e8d9d2ff70 (MD5)
  • description.provenance : Made available in DSpace on 2012-03-28T01:13:06Z (GMT). No. of bitstreams: 1 Imputing Mean Annual Change and Estimating Current Forest Attributes.pdf: 345930 bytes, checksum: 8170629fae7c74764f3745e8d9d2ff70 (MD5) Previous issue date: 2009
  • description.provenance : Submitted by Logan Bernart (logan.bernart@gmail.com) on 2012-03-13T00:32:04Z No. of bitstreams: 1 Imputing Mean Annual Change and Estimating Current Forest Attributes.pdf: 345930 bytes, checksum: 8170629fae7c74764f3745e8d9d2ff70 (MD5)

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