This research aims to develop a comprehensive geospatial method for visualizing GIS based 3-D landscape visualizations in flood prone tourism towns and geospatial web applications containing multimedia information.
In this paper we develop a robust geospatial method for defining and mapping the WUI in the Alpine environment, where most interactions between infrastructures and wildland vegetation concern the fire ignition through human activities, whereas no significant threats exist for infrastructures due to contact with burning vegetation.
I have a background in geospatial methods and I have used geospatial data in my research.
Therefore, the aim of this paper is to provide an overview of geospatial methods applied in unintentional injury epidemiological studies.
As data is scarce for a city-regional perspective, we combine geospatial methods for an automatic identification of building types from topographic data and maps, for measuring multi-modal accessibility and for small scale demographic analysis.
It also provides an example of how geospatial methods and variables may be used in understanding the ecology of human WNV risk for other areas.
Over the past 15 years, there appears to have been an increasing application of geospatial methods for investigating unintentional injuries, demonstrated by the growing number of published studies using these methods, particularly since 2008.
Though there is an increase in popularity of predictive modelling for assessing the geographical distribution of species, there is still a clear gap on explaining geospatial methods to derive the presence/absence of species in terms of geospatial extent besides the ambiguity of robust models.
Geospatial methods have a long history of use in public health, including for epidemiological research (Auchincloss et al. 2012; Lawson 2001).
Geospatial methods play an important role in understanding the influence of complex social environments on injury outcomes that will help to develop population level injury prevention strategies (Bell and Schuurman 2010).
The aim of this review has been to provide an overview of the types of geospatial methods applied to unintentional injury epidemiological studies.
