A generalized flexible sampling model for vegetation survey
A generalized flexible sampling model for vegetation survey
A generalized flexible sampling model for vegetation survey is represented. It consists of a two-stage sampling system, where the primary sampling, carried out by a selected sampling method, provides information which is subsequently used as a criterion to constrain the randomicity of the secondary samples. The vegetational data, consisting of a number of species records taken from separate sample sites, are first analysed by Principal Component Analysis (pc & ) to provide weightings of the individual samples on the component axes. The weightings from the more important axes are used to represent the floristic information present in the samples. The information for all the samples is then represented as a surface for each axis of variation. The level of the surface at the coordinates of each sample represents the information contained in it and the intermediate points are extrapolated in relation to the real data. For the contouring of the surface, the use of both the main and residual values from TrendSurface Analysis (TSA), and a method devised by SHEPARD in which the surface fits the actual values, were all tested. The traditional TSA proved too insensitive for the purpose, but the Shepard method gave satisfactory results; the use of TSA residuals gave comparable results to the latter, but required more computing time. The surfaces derived from each of the main PCA axes are then assembled in a composite differential surface by WOMBLE's differential systematic. The composite surface plotted is used as a criterion for selection of the secondary samples by a system giving a higher probability of sampling to the most variable zones of the vegetation, i. e. the highest zones of the surface. Various facets of the method were tested on four set of vegetational data, two of which were already available, and the other two collected specifically for the purpose. The results were compared with those obtained by traditional sampling methods and proved more
University of Southampton
Caldas, Francisco Barreto
1979
Caldas, Francisco Barreto
Caldas, Francisco Barreto
(1979)
A generalized flexible sampling model for vegetation survey.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
A generalized flexible sampling model for vegetation survey is represented. It consists of a two-stage sampling system, where the primary sampling, carried out by a selected sampling method, provides information which is subsequently used as a criterion to constrain the randomicity of the secondary samples. The vegetational data, consisting of a number of species records taken from separate sample sites, are first analysed by Principal Component Analysis (pc & ) to provide weightings of the individual samples on the component axes. The weightings from the more important axes are used to represent the floristic information present in the samples. The information for all the samples is then represented as a surface for each axis of variation. The level of the surface at the coordinates of each sample represents the information contained in it and the intermediate points are extrapolated in relation to the real data. For the contouring of the surface, the use of both the main and residual values from TrendSurface Analysis (TSA), and a method devised by SHEPARD in which the surface fits the actual values, were all tested. The traditional TSA proved too insensitive for the purpose, but the Shepard method gave satisfactory results; the use of TSA residuals gave comparable results to the latter, but required more computing time. The surfaces derived from each of the main PCA axes are then assembled in a composite differential surface by WOMBLE's differential systematic. The composite surface plotted is used as a criterion for selection of the secondary samples by a system giving a higher probability of sampling to the most variable zones of the vegetation, i. e. the highest zones of the surface. Various facets of the method were tested on four set of vegetational data, two of which were already available, and the other two collected specifically for the purpose. The results were compared with those obtained by traditional sampling methods and proved more
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Published date: 1979
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Local EPrints ID: 462438
URI: http://eprints.soton.ac.uk/id/eprint/462438
PURE UUID: ac5f302f-ea7b-4f4f-a6c4-38fda73f9fb5
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Date deposited: 04 Jul 2022 19:08
Last modified: 04 Jul 2022 19:08
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Author:
Francisco Barreto Caldas
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