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Ana Beatriz Oliveira - One of the best experts on this subject based on the ideXlab platform.

Dechristian França Barbieri - One of the best experts on this subject based on the ideXlab platform.

Divya Srinivasan - One of the best experts on this subject based on the ideXlab platform.

Svend Erik Mathiassen - One of the best experts on this subject based on the ideXlab platform.

Hailemariam Temesgen - One of the best experts on this subject based on the ideXlab platform.

  • Comparison of stratified and non-stratified most similar neighbour imputation for estimating Stand Tables
    Forestry, 2008
    Co-Authors: Bianca N.i. Eskelson, Hailemariam Temesgen, Tara M. Barrett
    Abstract:

    Summary Many growth and yield simulators require a Stand table or tree-list to set the initial condition for projections in time. Most similar neighbour (MSN) approaches can be used for estimating Stand Tables from information commonly available on forest cover maps (e.g. height, volume, per cent canopy cover and species composition). Simulations were used to compare MSN (using an entire database) with two stratifi ed MSN approaches. The fi rst stratifi ed MSN approach used species composition to partition the population into two inventory type strata, while the second stratifi ed MSN approach used average Stand age to partition the data into two Stand development stages (strata). The MSN approach was used within the whole population and within each stratum to select a reference Stand and to impute the ground variables of the reference Stand to each target Stand. Observed vs estimated Stand Tables were then compared for the stratifi ed and non-stratifi ed simulations. The imputation within a stratum did not result in better estimates than using the MSN approach within the whole population. Possible reasons for poor performance of stratifi ed MSN are provided.

  • Imputing tree-lists from aerial attributes for complex Stands of south-eastern British Columbia
    Forest Ecology and Management, 2003
    Co-Authors: Hailemariam Temesgen, Valerie Lemay, K.l Froese, Peter L. Marshall
    Abstract:

    The nearest neighbor, k-nearest neighbors, distance-weighted k-nearest neighbor, and class-weighted k-nearest neighbor imputation methods were compared for accuracy in estimating tree-lists (list of species and diameter for each tree) from aerial attributes for complex Stands, with up to nine species and a wide range of sizes, in south-eastern British Columbia, Canada. For the four imputation methods, the most similar neighbor distance metric was used, and three neighbors were used for the k-nearest neighbor methods. Ground variables used to represent the tree-list included the number of trees per hectare by species, ranges of diameter by species, and basal area per hectare. Aerial variables included species composition, crown closure (%), elevation, biogeoclimatic ecosystem classification (BEC) zones, height, age, and site class. Sample data were divided, and the imputation methods were compared for accuracy using observed and estimated species composition, Stand Tables, basal area, and volume per hectare. Also, the imputed tree-list was used to predict yield using a Stand level growth model, and this predicted yield was compared to the yield obtained using the actual tree-list. Of the four approaches used, the nearest neighbor was marginally better, but the methods that averaged the three nearest neighbors were somewhat better for the distribution of stems per hectare by diameter for the more sparse hardwood species. Of the three averaging methods, weighting by similarity of the species composition and the BEC zone provided better results. In using the estimated trees lists in a growth and yield model, the average volumes were reasonable at the beginning and end of the period for all methods. However, the volumes for a particular Stand could be quite different than that obtained for an observed tree-list.

  • Estimating Stand Tables from Aerial Attributes: a Comparison of Parametric Prediction and Most Similar Neighbour Methods
    Scandinavian Journal of Forest Research, 2003
    Co-Authors: Hailemariam Temesgen
    Abstract:

    Parameter prediction and the most similar neighbour (MSN) approaches were compared to estimate Stand Tables from aerial information. The study was based on 50 Stands in the south-eastern interior of British Columbia, Canada. In the parametric prediction approach, Stand Tables were estimated from aerial attributes and three percentile points (16.7, 63 and 97%) of the diameter distribution. In the MSN analysis, Stand Tables were estimated from the MSN Stand that was selected using 13 ground and 22 aerial variables. The accuracy of these approaches was evaluated by comparing the observed and estimated species composition, Stand Tables and volume per hectare. While the parametric prediction approach is easier and flexible to apply, the MSN approach provided reasonable projections, lower bias and lower root mean square error.