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Modelling tropical palm distributions – an integrated GIS and Bayesian approach

Lookup NU author(s): Wiske Rotinsulu, Dr David Fairbairn, Dr Meredith Williams


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Biodiversity erosion is identified as the main threat to the survival of many palm species in North Sulawesi, Indonesia. Poor knowledge of the Sulawesi palm taxonomy, distribution and conservation status is major concern for sustainability management. The existing traditional method (i.e. ground survey) for estimating species distribution is costly and time consuming. It also cannot keep pace with the rate of land-use change over large areas and provide complete coverage to large spatial scales. Remote sensing coupled with GIS can provide a solution to address spatial data management issues. This study aims to develop a GIS-based predictive model of native palm distributions utilising habitat characteristics and other environmental data derived from local observations, herbarium collections and satellite imagery. Three months of intensive fieldwork was carried out in spring/summer 2004 to collect ground truth data for image processing, and palm species data. This poster will present initial findings of this study. Integrated with GIS, a Bayesian approach to decision making will be used as an inductive modelling process for spatial analysis of patterns within native palm distributions. Predictor data sets consisting of possible contributing parameters are combined using the conditional probabilities within Bayes’ theorem. Inputs to the theorem are compared with attributes of a range of variables. This provides a measure of quality of the study area for the environmental data set being considered. Preliminary results suggest that land cover, topographic features and infrastructure are the most significant variables which influence the distribution of the native palm of Sulawesi.

Publication metadata

Author(s): Rotinsulu W, Fairbairn D, Williams M

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Unknown

Conference Name: Annual Conference of the Remote Sensing and Photogrammetry Society

Year of Conference: 2004