Spatial statistical analysis of tree deaths using airborne digital imagery |
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| Institution: | 1. adixen Vacuum Products: 98, Avenue de Brogny-BP 2069, 74009 Annecy Cedex, France;2. Université Lyon 1, CNRS, UMR 5256 IRCELYON: 2, avenue Albert Einstein, 69626 Villeurbanne Cedex, France;1. School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland;2. Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland;1. Nugaal University, Lasanod, Somalia;2. Laboratorio de Investigación y Análisis, Instituto Gemológico Español (IGE & Minas), Alenza 1, 28003 Madrid, Spain;3. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Avda. Complutense 40, 28040 Madrid, Spain |
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| Abstract: | High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics). |
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| Keywords: | Covariate effect Kernel estimation Morphological image analysis Partial residual Spatial point pattern Tree location detection Point process Logistic regression Leverage Influence |
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