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Abstract Details
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Activity Number:
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86
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #300874 |
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Title:
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Spatial Statistical Analysis of Changes in Native Vegetation Using Airborne Digital Imagery
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Author(s):
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Ya-Mei Chang*+
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Companies:
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Tamkang University
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Address:
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Department of Statistics, New Taipei City, International, , Taiwan
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Keywords:
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covariate effect ;
kernel estimation ;
morphological image analysis ;
partial residual ;
spatial point pattern ;
tree location detection
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Abstract:
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High resolution airborne imagery of native vegetation on an urban groundwater supply catchment was analysed for environmental monitoring purposes. Our previous work (Wallace, 2008) used semiautomatic methods to detect deaths of individual trees occurring between anniversary dates. In this paper, the locations of living trees were identified using techniques from morphological image analysis. Tree deaths can then be referred to the population density of living trees, permitting a more searching analysis of vegetation changes. Methods of spatial statistics yield estimates of the spatially-varying tree death risk, and show that it is significantly non-uniform. The influence of hydrological variables on tree death rate was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics) including new statistical techniques.
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Authors who are presenting talks have a * after their name.
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