Concommittant with an increasing trend towards the ecological classification of forest land in British Columbia is the need for more detailed vegetation inventories and larger mapping scales. Although existing classification schemes (biogeoclimatic, provincial biophysical and habitat type classification) usually present a useful initial stratification of broad zonal vegetation patterns, they seldom provide, or were intended to provide a classification suitable for detailed vegetation inventory and mapping in a particular study area. In most instances, primary vegetation data must be collected and classified at a level of detail compatible with the scale of mapping and the variability of the vegetation landscape. Limited access and steep mountainous terrain are additional problems contributing to the acquisition, classification, interpretation and mapping of vegetation at large scales.
Dissimilarity Analysis is a numerical classification analysis programmed and studied by the provincial government as a means to stratify large volumes of vegetation data in a relatively objective and efficient manner. As a divisive-polythetic classification strategy it demonstrates several advantages over other numerical analyses. Although it is now used as a routine analysis by the provincial biophysical survey, it has not yet been thoroughly evaluated or formally presented with regard to its suitability for vegetation classification and mapping on an operational basis.
This study investigated four related questions: a. What methods can be employed for detailed vegetation mapping (scale 1:15,840) in mountainous terrain with limited access? b. What is the value of Dissimilarity Analysis for the classification of vegetation in primary survey? c. What is the predictive capability of the pretyping (prestratification) approach developed for vegetation mapping? d. What is the reliability of the vegetation maps. The study was divided into two separate but related investigations: the operational classification and mapping of vegetation in two small mountainous watersheds and a detailed systematic sampling study of two representative areas within one of the watersheds to assess the vegetation mapping procedure and map reliability.
A detailed vegetation mapping procedure was developed which utilized permanent physiographic landscape features directly observable or inferred from black and white stereo aerial photographs (scale 1:15,840), macro and meso physiognomic vegetation features, a simple concept relating the above features to the available moisture for vegetation, and information about existing vegetation (e.g. forest cover maps; concepts and maps of vegetation zonation).
Dissimilarity Analysis was found to be an objective and efficient method of vegetation stratification by reducing personal bias and ensuring an optimum and consistent utilization of the available information in the data set. It was felt to be an appropriate technique for stratifying primary vegetation data since it maximizes differences between groups, defines limits to classes and facilitates the formation of a hierarchical identification procedure.
It was concluded that the vegetation pretyping approach developed for operational mapping provided a methodical, preliminary stratification of the landscape upon which improved mapping criteria could be added to better predict present vegetation condition.
A quantitative assessment of map reliability in two representative areas of one of the watersheds resulted in a value of 79% relative to an independent chance of agreement of 6.2% and an optimum chance of agreement of 29%. It was felt that these values were representative of the map reliability in the remainder of the watershed. / Forestry, Faculty of / Graduate
| Identifer | oai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/21123 |
| Date | January 1978 |
| Creators | Jones, Richard Keith |
| Source Sets | University of British Columbia |
| Language | English |
| Detected Language | English |
| Type | Text, Thesis/Dissertation |
| Rights | For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
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