International Journal of Advances in Science, Engineering and Technology(IJASEAT)
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  Journal Paper

Paper Title
Visualizing Of Lightning Activity Over The Sydney Region

Abstract
Accurately 16 years of lightning data from the Lightning Imaging Sensor (LIS) was analyzed to determine the spatial distribution of lightning flashes over the Greater Metropolitan Severe Thunderstorm Warning Area (GMSTWA). Primary each detectable lightning event is considered as a key atmospheric factor and thereafter nearly about 2505 lightning observations were combined to form the first “lightning climatology dataset” of a thundery-warned region, with its sprawling suburban area, and a population of nearly 4.8 million. A "climatologically oriented GIS" was intently applied by importing all lightning observations into ArcGIS software, to create appropriate distinct digital layers needed for the subsequent spatial analysis. A range of spatial statistics and pertinent analytic tools mainly for analyzing and mapping of existing spatial patterns among data layers have been applied. Progressively, within a Model Builder setting, a Nearest Neighbor Index (NNI), an Anselin's Local Moran Index and a Kernel Density function were introduced to the applicable personal database. The resulting spatial LIS indexes have established dissimilar spatial patterns, indicating clusters of lightning events statistically significant inside of GMSTW. The concluding outcomes indicate that more than 90% of the flashes occur during October to March with a single peak in the summer from December to January, and a substantial lightning activity in February, indicating a prominent diurnal afternoon peak. Spatial indexes illustrate that the most frequent and energetic lightning events happen over the western parts of the Sydney Metropolitan Area, Hornsby Plateau and mainly over the western elevated parts over the Blue Mountains. Remarkably, less frequent lightning flashes were surprisingly noticed adjacent the coastal areas. Keywords- LIS Data, Climatologically-Oriented GIS, Spatial Indexes, GMSTWA.


Author - Aliakbar Rasouli, Kevin. W. Cheung

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