Potential Effects of Contaminants on Fraser River Sockeye Salmon

Appendix 4. Data Treatment and MethodologyA4.1 Treatment <strong>of</strong> Spatial DataSpatial data were obtained from multiple sources in various formats. To standardizethe spatial data into a consistent format, data were converted into ESRI7 shapefilesand projected using the North American Datum (NAD) 1983 BC Environment Alberscoordinate system. Due to the lack <strong>of</strong> data availability and, in some cases, difficultyacquiring spatial data, a variety <strong>of</strong> data mining and data creation techniques wereimplemented. This included, but was not limited to, using Google Earth to generategeographic representations, geo-referencing figures from existing reports, and plottingfacilities and land-use activities from coordinates presented in tabular data. In somecircumstances, only the mailing address <strong>of</strong> the facility was available. In this situation,Google Earth was utilized to obtain the spatial coordinates <strong>of</strong> the facility andsubsequently plotted in ESRI7 ArcMapJ.Many <strong>of</strong> the spatial datasets required formatting and conversion in order to accuratelyand efficiently use the data, information, and maps. Sources <strong>of</strong> spatial data includedscientific and grey-literature, published reports, Micros<strong>of</strong>t Access databases, Micros<strong>of</strong>tExcel spreadsheets, ESRI7 ArcMapJ shapefiles, online mapping tools, and textdescriptions. Spatial datasets, which required unique handling, are described below.RESULTS-Openings Spatial DatabaseThe RESULTS-Openings spatial database was acquired through GeoBC=s DataDiscovery Service and was used to identify predominant tree species and tosummarize and display harvesting activities within the Fraser River Basin in thefollowing time periods: APre-1990" (1960-1990 inclusive) and APost-1990".To achieve these results, the polygons provided in the RESULTS-Openings databasewere overlaid and intersected with the area <strong>of</strong> interest boundaries to extract therelevant information. Micros<strong>of</strong>t Access was then used to classify the data into theAPre-1990" and APost-1990" time periods. In order to do this, the DN1_CompDate (thefirst disturbance completion date) and DN2_CompDate (the second disturbancecompletion date) fields were used in several queries. To achieve the desired results,the following rules were used:$ All DN1_CompDate years falling between 1960 and 1990(inclusive) were classified as APre-1990".$ All DN1_CompDate years occurring after 1990 were classified asAPost-1990".$ All DN2_CompDate years falling between 1960 and 1990(inclusive) where DN1_CompDate field was blank were classifiedas APre-1990".A-30