Appendix 7: Spatial Processing for Habitat Indicators
Dataset Name | Filter | Processing | Source | Indicator | Region(s) |
---|---|---|---|---|---|
Agriculture Land Dispositions | TENURE_PURPOSE = ‘Agricultural’ –> se type 7 TENURE_PURPOSE = ‘Grazing’ –> se type 6 |
1. Apply filters 2. Assign se_type codes to each filter 3. Union inputs 4. Calculate max_type_code 5. Dissolve on max_type_code 6. Reclassify max_type_code to populate datasource and type (Unknown, Unknown (clearing), Rangeland, Cropland) 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 PLU_LABEL = ‘Range Lands’ –> se type 4 |
Same as above | DataBC | Agriculture | BC |
VRI | NON_PRODUCTIVE_DESCRIPTOR_CD = ‘OR’ –> se type 3 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 2. Calculate YEARS_SINCE 3. Merge inputs 4. Union with burn severity polygons 5. Identity with Forest Inventory Zones to identify coastal vs interior 6. Calculate PF_FACTOR_TIME 7. Calculate PF_FACTOR_SEVERITY based on coastal vs interior 8. Calculate PF_FACTOR = PF_FACTOR_TIME * PF_FACTOR_SEVERITY 9. Dissolve on PF_FACTOR 10. Split by PF_FACTOR 11. Union the split feature classes 12. Calculate MAX_PF_FACTOR 13. Dissolve on MAX_PF_FACTOR 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 2. Calculate YEARS_SINCE_HARVEST 3. Merge inputs 4. Calculate PF_FACTOR 5. Erase reserves 6. Dissolve on PF_FACTOR 7. Split by PF_FACTOR 8. Union 9. Calculate MAX_PF_FACTOR 10. Dissolve on MAX_PF_FACTOR 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 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 2. Union with VRI dead layer 3. Calculate YEARS_SINCE_PEST 4. Calculate PF_FACTOR_TIME 5. Calculate PF_STAND_PCT_DEAD (either from the midpoint of the severity mortality range or VRI stand_percentage_dead, whichever is greater) 6. Calculate PF_FACTOR_SEVERITY (if severity is moderate = 0.5; if severity is severe or very severe = 1) 8. Calculate PF_FACTOR = PF_FACTOR_TIME * PF_FACTOR_SEVERITY * PF_STAND_PCT_DEAD/100 9. Count overlapping features 10. Join overlapping features 11. Summarize MAX_PF_FACTOR 12. Join MAX_PF_FACTOR back to planarized features 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 2. Add and calculate standardized fields: se_source, se_type, commodity_d, names, status_d 3. Append BC points into one feature class 4. Convert Yukon polygons to points (inside = true) 5. Append Yukon gravel points with step 3 output 6. Append BC points (step 3) with Yukon points (step 5) 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 2. Buffer Yukon road network by 30m 3. Erase forest resource roads that are within the 30m buffers 4. Merge Yukon road network with output of step 3 5. Erase BC from step 4 (some Yukon roads overlap with BC) 6. Pairwise dissolve step 5 7. Merge YT (step 6) with BC dissolved roads (step 1) 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 2. Merge YEC_Power_Lines, YEC_Power_Distribution_Lines, Utilities_Line_50k (Transmission line) 3. Buffer step 2 power lines by 12.5m then dissolve -> power lines 4. Merge pipeline_1 and Utilities_Line_50K (pipeline) 5. Buffer step 4 pipelines by 25m then dissolve -> oil and gas infrastructure 6. Buffer track_segment_1 by 10m then merge with runways_25k and dissolve -> rail and airport 7. Merge rail and airport (step 6), oil and gas infrastructure (step 5), power lines (step 3) with urban (LCC landcover) 8. Add and calculate standardized fields: DISTRB_CD, DISTRB_GRP |
Government of Canada | Urban & Industrial | Yukon |
Utilities_Line_50k | “FEATURE” = ‘Transmission line’ “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_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_1 | N/A | Same as above | Natural Resources Canada | Urban & Industrial | Yukon |