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POTENTIAL DISTRIBUTION OF THE TIGER MOSQUITO AEDES ALBOPICTUS IN NORTHERN ITALY DERIVED FROM RECONSTRUCTED MODIS LAND SURFACE TEMPERATURE MAPS
The recent rapid spread of Aedes albopictus, is a major health concern in several European countries. This invasive vector increases the risk of infectious diseases as an outbreak of the tropical Chikungunya disease in Italy proved in 2007. An important environmental factor in the assessment of its distribution is the temperature which can be obtained from daily satellite data. The potential distribution of Ae. albopictus is determined by winter (egg survival), summer, annual mean and autumnal mean temperatures (adult survival), as well as growing degree days (insect development). Unfortunately, satellite temperature maps are regularly incomplete because cloud cover “contaminates” the data, or other pixel drop-outs occur.
We propose an innovative approach for the reconstruction of incomplete time series of daily MODIS Land Surface Temperature (LST) satellite data. The LST map reconstruction was executed by data reprojection prior to the GRASS import, elimination of temperature outliers and reconstruction of the LST datum in areas with no data using GRASS and related tools. For this last procedure, temperature gradient based models were used. Input data points were subsequently interpolated with volumetric splines to obtain complete LST maps. The temperature gradient based models together with elevation map allowed to increase the resolution from 1000m to 200m pixel size. These reconstructed daily LST maps were compared to meteorological temperature measurements in order to assess the quality of the data reconstruction.
As a result, more than 11.000 maps were produced in a parallelized approach on a Linux cluster. By map aggregation, input variables to obtain the potential distribution of Ae. albopictus were generated and eventually integrated with a scoring system to obtain the final map of potential Ae. albopictus distributional areas. The needed software enhancements have been integrated into the GRASS 6.4.0 version.
Markus Neteler - Fondazione Edmund Mach
David Roiz - Fondazione Edmund Mach
Cristina Castellani - Fondazione Edmund Mach
Duccio Rocchini - Fondazione Edmund Mach
Annapaola Rizzoli - Fondazione Edmund Mach