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Towards modelling bird migration using environment variables: A case study of Barnacle Geese, Branta leucopsis

Kalra, Mohit (2009) Towards modelling bird migration using environment variables: A case study of Barnacle Geese, Branta leucopsis.

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Abstract:The observation data of bird migration offers the potential to understand spatiotemporal movement of birds. However, it is not easy to link such data to dynamical models of movement (Patterson, et al., 2008). This study used Geese data for developing spatiotemporal model in the context of geographical information system (GIS) for increasing the understanding about bird migration. The three main objectives of the research were to identify the criteria to use as an input in model building and to increase the understanding about bird migration, model the possible locations of migrants using criteria identified previously and lastly evaluate the models performance. The developed model is based on expert information (literature based) using two different approaches, Boolean logic and Weighted Index Overlay (WIO) methods. Using the Boolean approach two different models varying based on number of input parameters were developed. We used Global Weather Forecast Model (GWF) data for six environmental variables: atmospheric air temperature, surface observations, cloud cover, precipitation, wind speed and direction. In the WIO method Analytical hierarchical process (AHP) process was applied for calculating the weights for all six variables. The weights were multiplied with corresponding layers after assigning the membership function using fuzzy logic technique. An attempt was also made for validating the Boolean models performance using independent data set. Though, the validation of model is not highly accurate due to the uncertainty in the satellite tracking data. The test based on the kappa statistics reflected that the model performance was below average in both the cases. The poor performance of model may be explained by the uncertainty in the tracking data, upper and lower limit of thresholds and due to the discrete properties of environmental variables. The weighted index overlay model with continuous data may give better results, full validation can be part of future investigation. The study revealed that bird migration model involves consideration of just more than applying Boolean and weighted overlay functions. Additional inputs may be added such as distance from the adjacent suitable pixels within the layer and the accumulation of values of parameters of interest with time rather than simply overlapping different layers of geographical information. Keywords: Spatiotemporal, Migrants, Boolean logic, Weighted index, Global Weather Forecast Model, Analytical hierarchical process
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
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