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The aim of this study was to improve HIA methods for air pollution studies in situations where exposures can be estimated using GIS with high spatial resolution and dispersion modeling approaches.
Some methods such as IslandViewer and MobileHomeFinder are dedicated to predict genomic islands (GIs) with high stringency.
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This study is an attempt to analyze by GIS the areas with higher landscape value in the impact assessment of dam constructions in the case of Seyhan-Köprü Hydroelectric Dam project proposal.
With high resolution, high quality GIS data increasingly available to local communities, they are now in a position to guide local management of watershed N by targeting upland source controls and by identifying landscape sinks for protection and/or restoration.
This GIS predictive modelling allowed to identify different areas with high archaeological potential.
Using geographic information system (GIS -based spatial statistics, this analysis identified areas with hiGIS -basedcespatialmale breastatisticsthis should be emphanalysisn future cancer preventidentifiedntrol.
Using GIS-based spatial statistics, we investigated the spatial distribution of HFRS cases and identified counties with high endemic HFRS and clustering patterns.
This is particularly important here as low resolution GIS data is unlikely to correlate well with the response variables from our plot network as many plots (with high variance [58]) may fall within a single cell [59].
This is particularly important here as low resolution GIS data is unlikely to correlate well with the response variables from our plot network as many plots (with high variance [ 58]) may fall within a single cell [ 59].
Another GIS study examined the spatial distribution of sarcomas and non-Hodgkin lymphomas around a municipal solid waste incinerator with high emission levels of PCDD/Fs, identifying highly significant clusters around the incinerator (Viel et al. 2000).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com