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13-appendix7.Rmd
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13-appendix7.Rmd
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# Appendix 7: Spatial Processing for Habitat Indicators {#appendix-7 .unnumbered}
| Dataset Name | Filter | Processing | Source | Indicator | Region(s) |
|:--------------|:--------|:------------|:--------|:-----------|:-----------|
| Agriculture Land Dispositions | TENURE_PURPOSE = ‘Agricultural’ –> se type 7 <br> TENURE_PURPOSE = ‘Grazing’ –> se type 6 | 1. Apply filters <br> 2. Assign se_type codes to each filter <br> 3. Union inputs <br> 4. Calculate max_type_code <br> 5. Dissolve on max_type_code <br> 6. Reclassify max_type_code to populate datasource and type (Unknown, Unknown (clearing), Rangeland, Cropland) <br> 7. Intersect with watersheds to calculate % watershed affected by agriculture = agricultural area/total watershed area | GeoYukon | Agriculture | Yukon |
| Baseline Thematic Mapping | PLU_LABEL = ‘Agriculture’ –> se type 5 <br> PLU_LABEL = ‘Range Lands’ –> se type 4 | Same as above | DataBC | Agriculture | BC |
| VRI | NON_PRODUCTIVE_DESCRIPTOR_CD = 'OR' –> se type 3 <br> NON_PRODUCTIVE_DESCRIPTOR_CD = 'C' –> se type 1 | Same as above | DataBC | Agriculture | BC |
| Historical Fire Polygons | FIRE_YEAR >= 1964 (last 60 years) | 1. Apply filters <br> 2. Calculate YEARS_SINCE <br> 3. Merge inputs <br> 4. Union with burn severity polygons <br> 5. Identity with Forest Inventory Zones to identify coastal vs interior <br> 6. Calculate PF_FACTOR_TIME <br> 7. Calculate PF_FACTOR_SEVERITY based on coastal vs interior <br> 8. Calculate PF_FACTOR = PF_FACTOR_TIME * PF_FACTOR_SEVERITY <br> 9. Dissolve on PF_FACTOR <br> 10. Split by PF_FACTOR <br> 11. Union the split feature classes <br> 12. Calculate MAX_PF_FACTOR <br> 13. Dissolve on MAX_PF_FACTOR <br> 14. Intersect with watersheds to calculate % watershed affected by fire = (affected area * pf_factor)/total watershed area | DataBC | Fire | BC |
| Current Fire Polygons | N/A | Same as above | DataBC | Fire | BC |
| Fire History | FIRE_YEAR >= 1964 AND FIRE_YEAR < 9900 (last 60 years) | Same as above | GeoYukon | Fire | Yukon |
| Burn Severity Polygons | N/A | Same as above | DataBC | Fire | BC |
| Forest Inventory Zones | FRST_NVNTE IN ('A', 'B', 'C') (coastal zones) | Same as above | DataBC | Fire | BC |
| Harvested Areas in BC (Consolidated Cutblocks) | HARVEST_YEAR >= 1964 (last 60 years) | 1. Apply filters <br> 2. Calculate YEARS_SINCE_HARVEST <br> 3. Merge inputs <br> 4. Calculate PF_FACTOR <br> 5. Erase reserves <br> 6. Dissolve on PF_FACTOR <br> 7. Split by PF_FACTOR <br> 8. Union <br> 9. Calculate MAX_PF_FACTOR <br> 10. Dissolve on MAX_PF_FACTOR <br> 11. Intersect with watersheds to calculate % watershed affected by forest harvest = (affected area * pf_factor)/total watershed area | DataBC | Harvest | BC |
| Forest Openings | N/A | Same as above | GeoYukon | Harvest | Yukon |
| Historic Silviculture Inventory 50K | HARVEST_START >= timestamp ‘1964-01-01 00:00:00’ (last 60 years) | Same as above | GeoYukon | Harvest | Yukon |
| Logging History on Haida Gwaii 1962 to 2021 | First_Harvest_Year >= 1964 OR Second_Harvest_Year >= 1964 (last 60 years) | Same as above | Gowgaia Institute | Harvest | Haida Gwaii |
| Results Inventory (for reserves) | ((RES_CD IN ('G') and STK_ST_CD = 'MAT' and UPDATE_YR >= 2012) OR (RES_CD IN ('G') and STK_ST_CD = 'MAT' and RES_OBJ_CD = 'WTR') OR (RES_CD IN ('G') and STK_ST_CD in ('NP', 'MAT','IMM','RES') and STK_TP_CD in ('NAT', 'FOR', 'BR')) OR STK_ST_CD in ('L', 'M', 'R', 'S')) AND GEOM_YN = 'Y' | 1. Apply filters <br> 2. Dissolve | DataBC | Harvest | BC |
| Pest Infestation Polygons | PEST_SEVERITY_CODE IN ('V', 'S', 'M') AND PEST_SPECIES_CODE NOT LIKE 'A%' AND PEST_SPECIES_CODE NOT LIKE 'N%' AND PEST_SPECIES_CODE NOT LIKE 'T%' AND PEST_SPECIES_CODE NOT LIKE 'V%' AND CAPTURE_YEAR >= 1964 (last 60 years) | 1. Apply filters <br> 2. Union with VRI dead layer <br> 3. Calculate YEARS_SINCE_PEST <br> 4. Calculate PF_FACTOR_TIME <br> 5. Calculate PF_STAND_PCT_DEAD (either from the midpoint of the severity mortality range or VRI stand_percentage_dead, whichever is greater) <br> 6. Calculate PF_FACTOR_SEVERITY (if severity is moderate = 0.5; if severity is severe or very severe = 1) <br> 8. Calculate PF_FACTOR = PF_FACTOR_TIME * PF_FACTOR_SEVERITY * PF_STAND_PCT_DEAD/100 <br> 9. Count overlapping features <br> 10. Join overlapping features <br> 11. Summarize MAX_PF_FACTOR <br> 12. Join MAX_PF_FACTOR back to planarized features <br> 13. Intersect with watersheds | DataBC | Insects | BC |
| Forest Health Overview | SEVERITY_CODE IN ('V', 'VS') AND DISTURBANCE_CODE NOT LIKE 'A%' AND DISTURBANCE_CODE NOT LIKE 'N%' AND DISTURBANCE_CODE NOT LIKE 'T%' AND DISTURBANCE_CODE NOT LIKE 'V%' AND SURVEY_YEAR >= 1964 (last 60 years) | Same as above | GeoYukon | Insects | Yukon |
| VRI Dead Layer | EARLIEST_NONLOGGING_DIST_TYPE LIKE 'I%' AND EARLIEST_NONLOGGING_DIST_DATE IS NOT NULL | Stand percentage dead used where greater than the midpoint of the severity rating range (from pest infestation polygons layer) | DataBC | Insects | BC |
| Minfile Inventory Database | STATUS_DS IN ('Developed Prospect', 'Producer', 'Past Producer') | 1. Apply filters <br> 2. Add and calculate standardized fields: se_source, se_type, commodity_d, names, status_d <br> 3. Append BC points into one feature class <br> 4. Convert Yukon polygons to points (inside = true) <br> 5. Append Yukon gravel points with step 3 output <br> 6. Append BC points (step 3) with Yukon points (step 5) <br> 7. Intersect with watersheds to calculate number of mines per km2 | DataBC | Mines | BC |
| Minfile Production Database | Spatial selection – features that do not intersect selected features from inventory dataset (row above) | Same as above | DataBC | Mines | BC |
| BC Aggregate Inventory Private Pits (2004) | N/A | Same as above | British Columbia Geological Survey MapPlace | Mines | BC |
| Quartz Land Use Permits 50K | N/A | Same as above | GeoYukon | Mines | Yukon |
| Quartz Mining Licences 50K | N/A | Same as above | GeoYukon | Mines | Yukon |
| Quartz Leases 50K | N/A | Same as above | GeoYukon | Mines | Yukon |
| Mineral Claims Polygon Surveyed | N/A | Same as above | GeoYukon | Mines | Yukon |
| Coal Leases 50K | N/A | Same as above | GeoYukon | Mines | Yukon |
| Coal Exploration Licenses 50K | N/A | Same as above | GeoYukon | Mines | Yukon |
| Gravel Pits 25K | N/A | Same as above | GeoYukon | Mines | Yukon |
| BC CEF Integrated Roads | N/A | 1. Pairwise dissolve BC roads <br> 2. Buffer Yukon road network by 30m <br> 3. Erase forest resource roads that are within the 30m buffers <br> 4. Merge Yukon road network with output of step 3 <br> 5. Erase BC from step 4 (some Yukon roads overlap with BC) <br> 6. Pairwise dissolve step 5 <br> 7. Merge YT (step 6) with BC dissolved roads (step 1) <br> 8. Intersect with watersheds to calculate length (km) of roads per km2 | DataBC | Roads | BC |
| Yukon Road Network | N/A | Same as above | GeoYukon | Roads | Yukon |
| Forestry Resource Roads 50K | N/A | Same as above | GeoYukon | Roads | Yukon |
| BC CEF Human Disturbance OGC_Geophysical_1_SLU_raw | N/A | Add and calculate standardized fields: DISTRB_CD, DISTRB_GRP | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance OGC_Infrastructure_1_SLU_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance Power_1_Dams_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance Power_2_Transmission_Lines_GBA_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance Rail_and_Infrastructure_1_Railways_GBA_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance Rail_and_Infrastructure_2_Railways_GBA_NEBC_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance Rail_and_Infrastructure_3_VRI_Airports_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance ROW_1_Surveyed_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance ROW_2_Crown_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance Urban_1_BTM_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| BC CEF Human Disturbance Urban_2_VRI_raw | N/A | Same as above | DataBC | Urban & Industrial | BC |
| Landcover circa 2000 | COVTYPE = 34 Urban | 1. Apply filters <br> 2. Merge YEC_Power_Lines, YEC_Power_Distribution_Lines, Utilities_Line_50k (Transmission line) <br> 3. Buffer step 2 power lines by 12.5m then dissolve -> power lines <br> 4. Merge pipeline_1 and Utilities_Line_50K (pipeline) <br> 5. Buffer step 4 pipelines by 25m then dissolve -> oil and gas infrastructure <br> 6. Buffer track_segment_1 by 10m then merge with runways_25k and dissolve -> rail and airport <br> 7. Merge rail and airport (step 6), oil and gas infrastructure (step 5), power lines (step 3) with urban (LCC landcover) <br> 8. Add and calculate standardized fields: DISTRB_CD, DISTRB_GRP | Government of Canada | Urban & Industrial | Yukon |
| Utilities_Line_50k | "FEATURE" = 'Transmission line' <br> "FEATURE" = 'pipeline' | Same as above | GeoYukon | Urban & Industrial | Yukon |
| YEC_Power_Lines | N/A | Same as above | GeoYukon | Urban & Industrial | Yukon |
| YEC_Power_Distribution_Lines | N/A | Same as above | GeoYukon | Urban & Industrial | Yukon |
| Railroads_50K_Canvec canvec_50K_YT_Transport.gdb\track_segment_1 | N/A | Same as above | GeoYukon | Urban & Industrial | Yukon |
| Runways_25k | N/A | Same as above | GeoYukon | Urban & Industrial | Yukon |
| Canvec Pipelines 50K canvec_50K_YT_Res_MGT.gdb\pipeline_1 | N/A | Same as above | Natural Resources Canada | Urban & Industrial | Yukon |
: Table 7.1: Spatial data processing methods for habitat pressure indicators.