Biophysical data

Prep

Load packages

library(sf)
library(tmap)
library(RColorBrewer)
library(raster)
library(rgdal)

Load study area

Load study area and other relevant spatial objects created when prepping the pinch-point polygons.

load("1_data/manual/study_area.rdata")

# load clipped road data
load("1_data/manual/v_road_clip.rdata")

# load polygon representing North Central Region of Saskatchewan region of the ribbon of green
load("1_data/manual/nscr.rdata")

Habitat data

Load environmental Sensitivity data, project to the project crs, and clip to the study area.

ACIMS

ACIMS<-st_read("1_data/external/Environmental_Sensitivity_Data/ACIMS/ACIMS.shp")
st_crs(ACIMS)
# NAD83 / Alberta 3TM ref merid 114 W 
ACIMS_clip<-st_intersection(ACIMS, study_area)

save(ACIMS_clip, file="1_data/manual/ACIMS_clip.rData")

# Visualize layer
m1<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(ACIMS_clip)+
    tm_fill(col="SCOMNAME", palette = "Dark2", contrast = c(0.26, 1),alpha = .3, n= nrow(ACIMS_clip), title="Common name")+
    tm_borders(col = "#636363")+
  tm_layout(legend.outside = FALSE, legend.text.size = .6, legend.bg.color="white", legend.frame=TRUE, legend.frame.lwd=.8)
m1

tmap_save(m1, "4_output/maps/ACIMS_map.png", outer.margins=c(0,0,0,0))
ACIMS layer.

Figure 2.10: ACIMS layer.

Attributes
EO_ID EO_NUM ECODE S_RANK SNAME SCOMNAME LAST_OBS_D EAST_10TM NORTH_10TM DIRECTIONS
1 1851 2 IILEP73020 S2 Poanes hobomok Hobomok Skipper 1999-06-26 594776.4 5930884 McKinnon Ravine, Edmonton
2 3660 3 NBMUS2N040 S1S2 Entodon concinnus moss 1989-06-12 598379.7 5929785 North Saskatchewan River, S bank of; Edmonton; High Level Bridge, just W of.
3 4450 4 NBMUS6F020 S1S2 Rhodobryum ontariense Ontario Rhodobryum moss 1974-10-02 600955.6 5929308 Edmonton; Mill Creek Ravine, E side of; 89th Avenue, at.
5 6734 10 PDAPI1K060 S3 Osmorhiza longistylis smooth sweet cicely 1999-06-18 599449.5 5929445 Edmonton; Queen Elizabeth Park.
7 7612 13 PDASTEH022 S3 Doellingeria umbellata var. pubens flat-topped white aster 1952-08-16 597658.2 5929529 Edmonton; University of Alberta.
16 16511 17 PDAPI1K060 S3 Osmorhiza longistylis smooth sweet cicely 2002-07-29 601132.1 5932106 Edmonton, Latta Bridge at 91 Street and Jasper Avenue

FWMIS

FWMIS<-st_read("1_data/external/Environmental_Sensitivity_Data/FWMIS/FWMIS.shp")
st_crs(FWMIS)
# NAD83 / Alberta 3TM ref merid 114 W 
FWMIS_clip<-st_intersection(FWMIS, study_area)

save(FWMIS_clip, file="1_data/manual/FWMIS_clip.rData")

# Visualize layer
m2<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(FWMIS_clip)+
    tm_symbols(size=.2, col="#ef3b2c", shape=21)+
  tm_layout(legend.show=FALSE)
m2

tmap_save(m2, "4_output/maps/FWMIS_map.png", outer.margins=c(0,0,0,0))
Locations of FWMIS species surveys.

Figure 2.11: Locations of FWMIS species surveys.

Attributes
Inventory Inventor_1 Survey_Typ Survey_Cre Latitude Longitude UTM_Eastin UTM_Northi UTM_Meridi ATS_SEC ATS_TWP ATS_RGE ATS_MER Observatio Species_Co Species__1 Age_Group Gender Species_To or_Abundan Health_Des Cause_of_D Sample_Com Feature_De
4246 15978 Edmonton Occurrence Reports, 2012 Random Observation - Wildlife LISA MATTHIAS 53.51604 -113.5468 331141.9 5932696 -111 (Zone 12) 25 52 25 4 2012-05-02 WTSP WHITE-THROATED SPARROW Reproductively Mature / Adult M 1 NA Alive and Well NA NA NA
4247 15978 Edmonton Occurrence Reports, 2012 Random Observation - Wildlife LISA MATTHIAS 53.51604 -113.5468 331141.9 5932696 -111 (Zone 12) 25 52 25 4 2012-05-02 HETH HERMIT THRUSH Reproductively Mature / Adult M 1 NA Alive and Well NA NA NA
4248 15978 Edmonton Occurrence Reports, 2012 Random Observation - Wildlife LISA MATTHIAS 53.51604 -113.5468 331141.9 5932696 -111 (Zone 12) 25 52 25 4 2012-05-02 PIWO PILEATED WOODPECKER Reproductively Mature / Adult U 1 NA Alive and Well NA NA NA
4249 15978 Edmonton Occurrence Reports, 2012 Random Observation - Wildlife LISA MATTHIAS 53.51604 -113.5468 331141.9 5932696 -111 (Zone 12) 25 52 25 4 2012-05-02 FRGU FRANKLIN’S GULL Reproductively Mature / Adult U 0 1000+ Alive and Well NA NA NA
4250 15978 Edmonton Occurrence Reports, 2012 Random Observation - Wildlife LISA MATTHIAS 53.51604 -113.5468 331141.9 5932696 -111 (Zone 12) 25 52 25 4 2012-05-02 CAGO CANADA GOOSE Reproductively Mature / Adult M 1 NA Alive and Well NA NA NA
4251 15978 Edmonton Occurrence Reports, 2012 Random Observation - Wildlife LISA MATTHIAS 53.51604 -113.5468 331141.9 5932696 -111 (Zone 12) 25 52 25 4 2012-05-02 CAGO CANADA GOOSE Reproductively Mature / Adult F 1 NA Alive and Well NA NA NA

Edmonton sampling plots

tsp_psp<-st_read("1_data/external/TSP_PSP_Access_Database/PLOT_LOCATIONS_PLS_DATA_3TM.shp")
st_crs(tsp_psp)

#clip to study area 
tsp_psp_clip<-st_intersection(tsp_psp, study_area)

save(tsp_psp_clip, file="1_data/manual/tsp_psp_clip.rData")

# look at attributes
tsp_psp_tbl<-head(as.data.frame(tsp_psp_clip))
save(tsp_psp_tbl, file="images/tables/tsp_psp_tbl.rData")


# Visualize layer
m16<-
tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(tsp_psp_clip)+
    tm_symbols(size=.2, col="#ef3b2c", shape=21)+
  tm_layout(legend.show=FALSE)
m16

tmap_save(m16, "4_output/maps/tsp_psp_map.png", outer.margins=c(0,0,0,0))
Edmonton sample plot locations.

Figure 2.12: Edmonton sample plot locations.

Attributes
TYPE PLOT MEAS YEAR MONTH DAY CREW ZONE EASTING NORTHING MAPCODE SLOPE ASPECT TOPO SURFACE SUBSURF M CC HT S1 P1 S2 P2 S3 P3 S4 P4 S5 P5 uM uHT uS1 uP1 uS2 uP2 uS3 uP3 uS4 uP4 uS5 uP5 PIONEER SERAL SNAGS CWD FWD MOIST NUT ORGDEPTH MINTEXT ORGTEXT HORIZON DRAIN PARENT PCOM STRUCT LFHCOMP EROSION BARESOIL WEEDCOV WEEDDEN NEW_PSP geometry
33 TSP 53 1 2015 6 10 JN 12 336836 5935903 2B 60 200 MS 3 2 NA NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA NA 0 0 0 2 B 0 LS NA BM R F 15 18 8 1 1 1 1 NA 35610.89, 5934996.70
35 TSP 57 1 2015 9 2 JN 12 329927 5935320 5C 60 180 T 4 3 M C 10 AW 9 PB 1 NA 0 NA 0 NA 0 M 6 MM 7 AW 3 NA 0 NA 0 NA 0 SE XS 5 10 10 5 C 0 SL NA AH-5 BHJ-20 MW A 15 18 14 5 3 5 5 NA 28732.76, 5934123.31
41 TSP 67 1 2015 9 10 JN 12 336406 5936764 5C 5 160 T 4 4 M A 8 AW 10 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 SE XS 10 10 10 5 D 0 L NA AH-30 MW A 15 27 8 3 3 1 1 NA 35145.02, 5935838.81
42 TSP 68 1 2015 6 10 JN 12 336836 5936054 2B 60 180 MS 3 0 NA NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA NA 0 0 0 3 C 0 SIL NA AHJ-10-BM R F 15 0 8 3 3 1 1 NA 35604.53, 5935147.56
43 TSP 69 1 2015 9 2 JN 12 329931 5935335 3C 70 180 US 4 2 NA NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA NA 90 25 5 3 D 0 SIL NA AH-25 MB 5 W A 10 27 8 3 1 0 0 NA 28736.13, 5934138.46
44 TSP 70 1 2015 9 2 JN 12 329790 5935405 3C 40 180 MS 4 1 NA NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA 0 NA NA 0 0 0 0 NA 0 NA NA NA NA NA 10 18 8 3 0 0 0 NA 28592.31, 5934202.46

Slope and aspect

Slope

#slope<-raster("1_data/external/Environmental_Sensitivity_Data/Slope/Slope_3_8_16_45_RGB.tif")
slope<-raster("1_data/external/Edmonton_slope_aspect_in_degrees/slope")
slope<-projectRaster(slope, crs=crs(study_area))

slope_clip<-crop(slope, study_area)
hist(aspect_clip)

writeRaster(slope_clip, filename="1_data/manual/slope_clip", format='GTiff', overwrite=TRUE)
save(slope_clip, file="1_data/manual/slope_clip.rData")

m4<-
  tm_shape(slope_clip)+
    tm_raster(palette = c("white", "#00441b"),
      title = "Slope",
              contrast = c(0,.8),
              style = "cont")+
  tm_layout(legend.outside = FALSE, 
            legend.text.size = .8, 
            legend.bg.color="white", 
            legend.frame=TRUE,
            legend.title.size=1, 
            legend.frame.lwd=.8,
            )
m4

tmap_save(m4, "4_output/maps/slope_map.png", outer.margins=c(0,0,0,0))
Slope.

Figure 2.13: Slope.

Aspect

#aspect<-raster("1_data/external/Environmental_Sensitivity_Data/Slope/Aspect_RGB_(2).tif")
aspect<-raster("1_data/external/Edmonton_slope_aspect_in_degrees/aspect")
aspect<-projectRaster(aspect, crs=crs(study_area))

aspect_clip<-crop(aspect, study_area)
hist(aspect_clip)

#save
writeRaster(aspect_clip, filename="1_data/manual/aspect_clip", format='GTiff', overwrite=TRUE)

save(aspect_clip, file="1_data/manual/aspect_clip.rData")

m5<-
  tm_shape(aspect_clip)+
    tm_raster(palette= c("white", "#023858"),
              title = "Aspect",
              contrast = c(0,.8))+
  tm_layout(legend.outside = FALSE, 
            legend.text.size = .8, 
            legend.bg.color="white", 
            legend.frame=TRUE,
            legend.title.size=1, 
            legend.frame.lwd=.8,
            )
m5

tmap_save(m5, "4_output/maps/aspect_map.png", outer.margins=c(0,0,0,0))
Aspect.

Figure 2.14: Aspect.

Canopy

Natural

can_natural<-raster("1_data/external/Canopy_Cover_2020/All_Classes_Natural.tif")
#st_crs(can_natural)

can_natural_clip<-crop(can_natural, study_area)

writeRaster(can_natural_clip, filename="1_data/manual/can_natural_clip", format='GTiff')
save(can_natural_clip, file="1_data/manual/can_natural_clip.rData")

m18<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#f0f0f0")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.7)+
    tm_borders(col = "#969696")+
  tm_shape(can_natural_clip)+
    tm_raster(palette="Greens",
              style = "cont",
              title = "Natural canopy height",
              contrast = c(.1,1))+
  tm_layout(legend.outside = FALSE, 
            legend.text.size = .8, 
            legend.bg.color="white", 
            legend.frame=TRUE,
            legend.title.size=1, 
            legend.frame.lwd=.8,
            )
m18

tmap_save(m18, "4_output/maps/can_natural_map.png", outer.margins=c(0,0,0,0))
Natural canopy.

Figure 2.15: Natural canopy.

Naturalized

can_naturalized<-raster("1_data/external/Canopy_Cover_2020/All_Classes_Naturalized.tif")
st_crs(can_naturalized)

can_naturalized_clip<-crop(can_naturalized, study_area)

save(can_naturalized_clip, file="1_data/manual/can_naturalized_clip.rData")

m19<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#f0f0f0")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.7)+
    tm_borders(col = "#969696")+
  tm_shape(can_naturalized_clip)+
    tm_raster(palette="Greens",
              title = "Naturalized canopy height",
              style = "cont",
              contrast = c(.1 ,1),
              )+
  tm_layout(legend.outside = FALSE, 
            legend.text.size = .8, 
            legend.bg.color="white", 
            legend.frame=TRUE,
            legend.title.size=1, 
            legend.frame.lwd=.8,
            )
m19

tmap_save(m19, "4_output/maps/can_naturalized_map.png", outer.margins=c(0,0,0,0))
Naturalized canopy.

Figure 2.16: Naturalized canopy.

Ornamental

can_ornamental<-raster("1_data/external/Canopy_Cover_2020/All_Classes_Ornamental.tif")
#st_crs(can_ornamental)

can_ornamental_clip<-crop(can_ornamental, study_area)

save(can_ornamental_clip, file="1_data/manual/can_ornamental_clip.rData")


m20<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#f0f0f0")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.7)+
    tm_borders(col = "#969696")+
  tm_shape(can_ornamental_clip)+
    tm_raster(palette="Greens",
              title = "Ornamental canopy height",
              style="cont",
              contrast = c(.1,1)
              )+
  tm_layout(legend.outside = FALSE, 
            legend.text.size = .8, 
            legend.bg.color="white", 
            legend.frame=TRUE,
            legend.title.size=1, 
            legend.frame.lwd=.8,
            )
m20

tmap_save(m20, "4_output/maps/can_ornamental_map.png", outer.margins=c(0,0,0,0))
Ornamental canopy.

Figure 2.17: Ornamental canopy.

Canopy polygons

Polygons with veg classes derived from canopy rasters.

# Layer was clipped to the study area in ArcGIS due to it's size
can_poly_clip<-st_read("1_data/manual/can_poly_arc_clip.shp")
st_crs(can_poly_clip)

save(can_poly_clip, file="1_data/manual/can_poly_clip.rData")

m21<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.7)+
    tm_borders(col = "#636363")+
  tm_shape(can_poly_clip)+
    tm_fill(col="Class", palette = "Dark2", contrast = c(0.26, 1),alpha = 1, title="Vegetation class")+
    #tm_borders(col = "#636363")
  tm_layout(legend.outside = FALSE, legend.text.size = .8, legend.bg.color="white", legend.frame=TRUE,legend.title.size=1, legend.frame.lwd=.8)
m21

tmap_save(m21, "4_output/maps/can_poly_map.png", outer.margins=c(0,0,0,0))
Canopy polygons.

Figure 2.18: Canopy polygons.

Attributes
Class Shape_Leng Shape_Area
Grass 95 142.50
Grass 56 94.00
Grass 22 20.25
Grass 53 133.25
Grass 70 87.50
Grass 49 63.00

uPLVI

UPLVI<-st_read("1_data/external/2018_uPLVI/COE_2018_uPLVI_RES_UPDATE_DRAFTv3.shp")

st_crs(UPLVI)

UPLVI_clip<-st_intersection(st_make_valid(UPLVI), study_area)

save(UPLVI_clip, file="1_data/manual/UPLVI_clip.rData")

#UPLVI_clip$Value<-as.factor(UPLVI_clip$Value)

m17<-
  tm_shape(UPLVI_clip)+
    tm_fill(col="LANDCLAS1", palette = "Dark2", contrast = c(0.26, 1),alpha = 1, title="Land Classification", labels = c("Developed","Modified", "Natural", "Naturally Wooded", "Naturally Non-Wooded"))+
  tm_shape(v_road_clip)+tm_lines(col="white", lwd=1)+
  #tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.7)+
    tm_borders(col = "#636363")+
    #tm_borders(col = "#636363")
  tm_layout(legend.outside = FALSE, legend.text.size = .8, legend.bg.color="white", legend.frame=TRUE,legend.title.size=1, legend.frame.lwd=.8)
m17

tmap_save(m17, "4_output/maps/UPLVI_map.png", outer.margins=c(0,0,0,0))
Urban Primary Land and Vegetation Inventory (uPLVI).

Figure 2.19: Urban Primary Land and Vegetation Inventory (uPLVI).

Attributes
POLY_NUM AREAHA NSR PRIMECLAS1 LANDCLAS1 STYPE1 STYPEPER1 MOISTURE1 NUTRIENT1 ECOUNIT1 ECOLABEL1 STND1 STNDLABEL1 DCLASS1 CON1 LSPP1 PSERAL1 SSERAL1 DIST1 DISTPER1 DISTYEAR1 WETLAND1 PRIMECLAS2 LANDCLAS2 STYPE2 STYPEPER2 MOISTURE2 NUTRIENT2 ECOUNIT2 ECOLABEL2 STND2 STNDLABEL2 DCLASS2 CON2 LSPP2 PSERAL2 SSERAL2 DIST2 DISTPER2 DISTYEAR2 WETLAND2 PRIMECLAS3 LANDCLAS3 STYPE3 STYPEPER3 MOISTURE3 NUTRIENT3 ECOUNIT3 ECOLABEL3 STND3 STNDLABEL3 DCLASS3 CON3 LSPP3 PSERAL3 SSERAL3 DIST3 DISTPER3 DISTYEAR3 WETLAND3
6925 6925 0.0844 CP NVE DEV BPC 10 0 NA Z ANTH NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA
6928 6928 0.3326 CP VEG MOD NG 8 0 NA Z ANTH NA NA NA 0 NA NA NA NA 0 0 NA VEG MOD TT 2 0 NA Z ANTH NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA
6929 6929 1.6579 CP NVE NAT EMS 10 1 B A UNSTABLE NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA
6932 6932 1.4119 CP NVE DEV ECS 10 0 NA Z ANTH NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA
6933 6933 5.9448 CP NVE DEV ECS 8 0 NA Z ANTH NA NA NA 0 NA NA NA NA 0 0 NA VEG MOD TT 2 0 NA Z ANTH NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA
6934 6934 0.7534 CP NVE DEV BPC 10 0 NA Z ANTH NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA NA NA NA 0 0 NA NA NA NA NA NA 0 NA NA NA NA 0 0 NA

DEM

DEM<-raster("1_data/external/CoE_DEM_2019/Edmonton_05m.tif")
st_crs(DEM)

DEM_clip<-crop(DEM, study_area)

save(DEM_clip, file="1_data/manual/DEM_clip.rData")


m22<-
  tm_shape(DEM_clip)+
    tm_raster(palette="YlOrBr",
              title = "DEM",
              style="cont",
              drop.levels = TRUE,
              contrast = c(0,1),
              alpha = .9
              )+
  tm_layout(legend.outside = FALSE, 
            legend.text.size = .8, 
            legend.bg.color="white", 
            legend.frame=TRUE,
            legend.title.size=1, 
            legend.frame.lwd=.8,
            )
m22

tmap_save(m22, "4_output/maps/DEM_map.png", outer.margins=c(0,0,0,0))
Digital elevation model.

Figure 2.20: Digital elevation model.

Parks infrastructure

Bridges

bridges<-st_read("1_data/external/Parks_Infrastructure/Copy_of_Parks_BRIDGES.shp")
st_crs(bridges)
bridges<-st_transform(bridges, crs = st_crs(3776))

# NAD83 / Alberta 3TM ref merid 114 W 
bridges_clip<-st_intersection(bridges, study_area)

save(bridges_clip, file="1_data/manual/bridges_clip.rData")

# Visualize layer
m8<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(bridges_clip)+
    tm_symbols(size=.2, col="#ef3b2c", shape=21)+
  tm_layout(legend.show=FALSE)
m8

tmap_save(m8, "4_output/maps/bridges_map.png", outer.margins=c(0,0,0,0))
Bridge locations.

Figure 2.21: Bridge locations.

Attributes
ID EFFECTIVE_ EFFECTIVE1 BRIDGE_NUM NAME TYPE MATERIAL OWNER MAINTAINER CONTRIBUTE LIFE_EXPEC INITIAL_VA HANDRAIL HYPERLINK FIELD_NOTE OBSERVATIO LTT_FEATUR LTT_STATUS LTT_CURREN SNOW_CLEAR geometry
17 995 2010-01-01 NA 160 Riverside G.C. Bikeway Tres. Br. Minor Pedestrian Wood Parks Parks Unknown NA NA Double NA NA NA 160 NA 0 N/A 36041.22, 36069.09, 36095.42, 5935465.10, 5935480.56, 5935492.93
18 501405 2014-07-10 NA 0 NA Boardwalk Wood Parks Parks Unknown NA NA None NA NA NA 1274 NA 0 N/A 36506.88, 36509.58, 5936521.16, 5936521.81
19 477700 2014-06-09 NA 426 Fulton Creek Pedestrian Bridge Minor Pedestrian Wood and Metal Parks Parks Unknown NA NA Double NA NA NA 1209 NA 0 N/A 37149.69, 37158.40, 5934966.84, 5934978.27
20 477699 2014-06-04 NA 216 C.C. Park - Capilano Footbridge Minor Pedestrian Wood Parks Parks Unknown NA NA Double NA NA NA 1208 NA 0 N/A 37516.24, 37524.54, 5936100.95, 5936107.45
33 1088 2010-01-01 NA 0 SL Boardwalk Wood Parks Parks Unknown NA NA Double NA NA NA 81 NA 0 N/A 35833.02, 35829.87, 5931319.07, 5931321.17
34 1049 2010-01-01 NA 0 SL Boardwalk Wood Parks Parks Unknown NA NA None NA NA NA 47 NA 0 N/A 35819.30, 35823.76, 5931329.27, 5931331.74

Picnic Sites

picnic<-st_read("1_data/external/Parks_Infrastructure/Copy_of_PICNIC_SITES.shp")
st_crs(picnic)
picnic<-st_transform(picnic, crs = st_crs(3776))

# NAD83 / Alberta 3TM ref merid 114 W 
picnic_clip<-st_intersection(picnic, study_area)

save(picnic_clip, file="1_data/manual/picnic_clip.rData")

# Visualize layer
m9<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(picnic_clip)+
    tm_symbols(size=.2, col="#ef3b2c", shape=21)+
  tm_layout(legend.show=FALSE)
m9

tmap_save(m9, "4_output/maps/picnic_map.png", outer.margins=c(0,0,0,0))
Picnic sites.

Figure 2.22: Picnic sites.

Attributes
ID EFFECTIVE_ EFFECTIVE1 OWNER MAINTAINER BOOKABLE SITE_NUMBE SEASONAL HYPERLINK OBSERVATIO FIELD_NOTE LTT_FEATUR LTT_STATUS LTT_CURREN
8 141 2017-07-28 NA Parks Parks Yes 2 N/A NA Sheltered NA 141 NA 0
9 143 2017-07-28 NA Parks Parks Yes 3 N/A NA Sheltered NA 143 NA 0
10 144 2017-07-28 NA Parks Parks Yes 4 N/A NA Sheltered NA 144 NA 0
11 142 2017-07-28 NA Parks Parks Yes 1 N/A NA Sheltered NA 142 NA 0
12 145 2017-07-28 NA Parks Parks Yes 5 N/A NA Sheltered NA 145 NA 0
13 146 2017-07-28 NA Parks Parks Yes 6 N/A NA Sheltered NA 146 NA 0

Playgrounds

playgrounds<-st_read("1_data/external/Parks_Infrastructure/Copy_of_Playgrounds.shp")
st_crs(playgrounds)
playgrounds<-st_transform(playgrounds, crs = st_crs(3776))

# NAD83 / Alberta 3TM ref merid 114 W 
playgrounds_clip<-st_intersection(playgrounds, study_area)

save(playgrounds_clip, file="1_data/manual/playgrounds_clip.rData")

# Visualize layer
m10<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(playgrounds_clip)+
    tm_symbols(size=.2, col="#ef3b2c", shape=21)+
  tm_layout(legend.show=FALSE)
m10

tmap_save(m10, "4_output/maps/playgrounds_map.png", outer.margins=c(0,0,0,0))
Playgrounds sites.

Figure 2.23: Playgrounds sites.

Attributes
ID EFFECTIVE_ EFFECTIVE1 NAME PLAYGROUND ADDRESS MANUFACTUR SURFACE_TY TYPE OWNER MAINTAINER CONTRIBUTE LIFE_EXPEC INITIAL_VA HYPERLINK FIELD_NOTE OBSERVATIO LTT_FEATUR LTT_STATUS LTT_CURREN SUB_TYPE USER_CATEG ACCESSIBIL REDEVELOPM
13 508107 2012-09-01 NA Highlands Spray Park 3628 11333 62 Street NW Vortex Concrete Spray Deck Parks Parks Unknown NA NA NA NA Updated Start date to Retrofit year 2012 NA 0 Unknown Unknown Wheelchair Accessible NA
14 12297 1954-12-31 NA Highlands 56 11333 62 Street NW Sunshine, Landscape Structures Sand Playground Parks Parks Unknown NA NA NA NA Senior 258 NA 0 Unknown Unknown Unknown 1994-12-31
18 12376 1998-12-31 NA Virginia Park School 387 7324 109 Avenue NW Sunshine Pour In Place Rubber, Sand Playground Parks Parks Unknown NA NA NA NA Junior; NOT Wheelchair Accessible, as per PLG Team Leader 27 NA 0 Unknown Unknown Unknown 1998-12-31
19 12252 1990-12-31 NA Bellevue School 16 11515 71 Street NW Big Toy, Landscape Sand Playground Parks Parks Unknown NA NA NA NA NA 158 NA 0 Unknown Unknown Unknown 1990-12-31
20 464949 1963-12-31 NA Borden Park 390 7405 - 112 Avenue NW GameTime Engineered Wood Fibre Playground Parks Parks Parks NA NA NA NA NA 1710 NA 0 Unknown Unknown Wheelchair Accessible 2012-12-31
21 464947 1963-12-31 NA Borden Park 390 7405 - 112 Avenue NW GameTime Engineered Wood Fibre Playground Parks Parks Parks NA NA NA NA NA 1708 NA 0 Unknown Unknown Wheelchair Accessible 2012-12-31

Sports fields

sports_fields<-st_read("1_data/external/Parks_Infrastructure/Copy_of_SPORTS_FIELDS.shp")
st_crs(sports_fields)
sports_fields<-st_transform(sports_fields, crs = st_crs(3776))

# there are some invalid geometries in this spatial layer.
# identify invalid geometries:
valid<-st_is_valid(sports_fields)

#fix by by buffering geometries:
sports_fields<-st_buffer(sports_fields[!is.na(valid),], 0.0)

#clip to study area 
sports_fields_clip<-st_intersection(sports_fields, study_area)

save(sports_fields_clip, file="1_data/manual/sports_fields_clip.rData")


# Visualize layer
m11<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(sports_fields_clip)+
    tm_fill(col="#2ca25f")+
    #tm_symbols(size=.2, col="#ef3b2c", shape=21)+
  tm_layout(legend.show=FALSE)
m11

tmap_save(m11, "4_output/maps/sports_fields_map.png", outer.margins=c(0,0,0,0))
Sports fields in Edmonton.

Figure 2.24: Sports fields in Edmonton.

Attributes
ID EFFECTIVE_ EFFECTIVE1 BOOKABLE SURFACE_MA TYPE OWNER MAINTAINER CONTRIBUTE LIFE_EXPEC INITIAL_VA NAME HYPERLINK LENGTH WIDTH FIELD_NUMB FIXTURE_TY FIXTURE_SI CLASS_FACI IRRIGATION FIELD_NOTE OBSERVATIO LTT_FEATUR LTT_STATUS LTT_CURREN
200 407917 2002-03-06 NA N/A Unknown Rink Community League Community League Unknown NA NA Highlands Community League NA NA NA NA Rink NA NA N/A NA NA 3588 NA 0
201 815462 2020-01-14 NA N/A Unknown Bookable Open Space Parks Parks Unknown NA NA Highlands Urban Village Park NA NA NA 2 NA NA NA N/A NA NA 8843 NA 0
202 815460 2020-01-14 NA N/A Unknown Bookable Open Space Parks Parks Unknown NA NA Highlands Urban Village Park NA NA NA 1 NA NA NA N/A NA NA 8841 NA 0
203 408277 2011-07-07 NA N/A Turf Lawn Bowling Community League Community League Unknown NA NA Highlands Community League NA NA NA NA Lawn Bowling NA NA N/A NA NA 3902 NA 0
204 815461 2020-01-14 NA N/A Unknown Bookable Open Space Parks Parks Unknown NA NA Highlands Urban Village Park NA NA NA 3 NA NA NA N/A NA NA 8842 NA 0
208 549243 2001-09-13 NA N/A Asphalt Tennis Court Community League Community League Unknown NA NA NA \REVFSV01_549243 0 0 NA Tennis NA NA N/A NA From SLIMDBA.PLAY_AREAS 5830 NA 0

Stairs

stairs<-st_read("1_data/external/Parks_Infrastructure/Copy_of_STAIRS.shp")
st_crs(stairs)
stairs<-st_transform(stairs, crs = st_crs(3776))

#clip to study area 
stairs_clip<-st_intersection(stairs, study_area)

save(stairs_clip, file="1_data/manual/stairs_clip.rData")


# Visualize layer
m12<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(stairs_clip)+
    #tm_fill(col="#2ca25f")+
    tm_lines(col="#ef3b2c",
            lwd=6)+
  tm_layout(legend.show=FALSE)
m12

tmap_save(m12, "4_output/maps/stairs_map.png", outer.margins=c(0,0,0,0))
Stairs in Edmonton.

Figure 2.25: Stairs in Edmonton.

Attributes
ID EFFECTIVE_ EFFECTIVE1 NUMBER_OF_ REST_STOPS HAND_RAIL BIKE_RAMP_ MATERIAL TYPE OWNER MAINTAINER CONTRIBUTE LIFE_EXPEC INITIAL_VA FIELD_NOTE OBSERVATIO HYPERLINK LTT_FEATUR LTT_STATUS LTT_CURREN TAG_NUM
24 739001 2019-06-12 NA 21 0 No None Wood Terraced Steps Parks Parks Unknown NA NA NA NA NA 2459 NA 0 NA
25 34718 2010-01-01 NA 181 2 Yes Double Wood Staircase Transportation Transportation Unknown NA NA NA NA NA 157 NA 0 NA
26 750102 2019-09-10 NA 3 0 No None Concrete Staircase Unknown Unknown Unknown NA NA NA NA NA 2706 NA 0 NA
32 34693 2010-01-01 NA 47 0 Yes None Wood Staircase Transportation Transportation Unknown NA NA NA NA NA 67 NA 0 47
33 34694 2010-01-01 NA 46 0 Yes None Wood Staircase Transportation Transportation Unknown NA NA NA NA NA 68 NA 0 46
34 337126 2012-05-30 NA 6 0 Yes None Concrete Staircase Building and Facilities Maintenance Building and Facilities Maintenance Unknown NA NA NA NA NA 262 NA 0 NA

Trails

trails<-st_read("1_data/external/Trails/Copy_of_TRAILS.shp")
st_crs(trails)
trails<-st_transform(trails, crs = st_crs(3776))

#clip to study area 
trails_clip<-st_intersection(trails, study_area)

save(trails_clip, file="1_data/manual/trails_clip.rData")


# Visualize layer
m15<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
  tm_shape(trails_clip)+
  tm_lines(col="SURFACE_TY",
           palette="Dark2",
           contrast=c(0, 1),
           title.col = "Surface type")+
  tm_layout(
            legend.outside = FALSE, 
            legend.text.size = .6, 
            legend.bg.color="white", 
            legend.frame=TRUE, 
            legend.frame.lwd=.8)

m15

tmap_save(m15, "4_output/maps/trails_map.png", outer.margins=c(0,0,0,0))
Map of trails in Edmonton by surface type.

Figure 2.26: Map of trails in Edmonton by surface type.

Attributes
ID EFFECTIVE_ EFFECTIVE1 NAME SEASONAL SNOW_CLEAR STATUS TYPE SURFACE_TY OWNER MAINTAINER CONTRIBUTE LIFE_EXPEC LENGTH WIDTH DIFFICULTY DESCRIPTIO EQUINE SKI CYCLE FIELD_NOTE OBSERVATIO HYPERLINK LTT_FEATUR LTT_STATUS LTT_CURREN
199 525445 2015-05-26 NA NA N/A No Unknown Maintained Concrete Parks Parks Unknown NA 8.47 2.0 Unknown NA N/A N/A N/A NA NA NA 33511 NA 0
200 400099 2010-01-01 NA NA N/A Yes Unknown Maintained Concrete Parks Parks Unknown NA 9.67 1.5 Unknown NA N/A N/A N/A NA NA NA 21711 NA 0
201 400095 2010-01-01 NA NA N/A Yes Unknown Maintained Asphalt Parks Parks Unknown NA 39.49 1.0 Unknown NA N/A N/A N/A NA NA NA 21707 NA 0
202 525446 2015-05-26 NA NA N/A No Unknown Maintained Asphalt Parks Parks Unknown NA 10.45 1.0 Unknown NA N/A N/A N/A NA NA NA 33512 NA 0
203 525442 2015-05-26 NA NA N/A No Unknown Maintained Asphalt Parks Parks Unknown NA 6.33 1.0 Unknown NA N/A N/A N/A NA NA NA 33508 NA 0
204 398000 2010-01-01 NA NA N/A No Unknown Maintained Concrete Community League Community League Unknown NA NA 1.5 Unknown NA N/A N/A N/A NA NA NA 19612 NA 0

Roads data

Road width and speed

road_ws<-st_read("1_data/external/roads_data/Road_Width_and_Speed/Road_Width_and_Speed.shp")
st_crs(road_ws)
road_ws<-st_transform(road_ws, crs = st_crs(3776))

#clip to study area 
road_ws_clip<-st_intersection(road_ws, study_area)

save(road_ws_clip, file="1_data/manual/road_ws_clip.rData")


# Visualize layer
m13<-
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
  tm_shape(road_ws_clip)+
  tm_lines(col="SPEED",
           palette="Greys",
           contrast=c(0,1),
           title.col="Road speed limit")+
  tm_layout(bg.col="#d9d9d9",
            legend.outside = FALSE, 
            legend.text.size = .6, 
            legend.bg.color="white", 
            legend.frame=TRUE, 
            legend.frame.lwd=.8)

m13

tmap_save(m13, "4_output/maps/road_ws_map.png", outer.margins=c(0,0,0,0))
Edmonton roads colored according to speed limit.

Figure 2.27: Edmonton roads colored according to speed limit.

Attributes
ID STREET CARRIAGEWA TYPE SPECIAL_KE START START_MEAS START_OS END END_MEASUR END_OS LENGTH LANE_POSIT LANE_TYPE LANE_LENGT LANE_WIDTH LANE_AREA LANE_KMS PAVEMENT ROAD_CLASS SPEED
2 20085 107 AVENUE NW EB-S NORMAL N/A GROAT ROAD NW [Northbound] {Exit Ramp}/107 AVENUE NW [Eastbound] {Overpass} 900.2006 0 GROAT ROAD NW [Southbound] {Entrance Ramp}/107 AVENUE NW [Eastbound] {Overpass} 1009.5612 0 109.3606 0000 CenterLine 104 13.0 1545 0.384 Unknown Arterial 50
3 18605 107 AVENUE NW EB-S NORMAL N/A 124 STREET NW 0.0000 0 125 STREET NW 123.3023 0 123.3023 0000 CenterLine 118 9.4 1154 0.304 Composite Arterial 50
4 18604 107 AVENUE NW EB-S NORMAL N/A 125 STREET NW 123.3023 0 126 STREET NW 246.4571 0 123.1548 0000 CenterLine 118 7.9 1100 0.298 Composite Arterial 50
5 18603 107 AVENUE NW EB-S NORMAL N/A 126 STREET NW 246.4571 0 127 STREET NW 365.0756 0 118.6185 0000 CenterLine 114 7.9 1077 0.289 Composite Arterial 50
6 18655 107 AVENUE NW EB-S NORMAL N/A 127 STREET NW 365.0756 0 128 STREET NW 482.4337 0 117.3581 0000 CenterLine 112 7.9 1048 0.282 Composite Arterial 50
7 18654 107 AVENUE NW EB-S NORMAL N/A 128 STREET NW 482.4337 0 129 STREET NW 597.5225 0 115.0888 0000 CenterLine 111 7.9 1040 0.280 Composite Arterial 50

Curb lines

curbs<-st_read("1_data/external/roads_data/Curb_lines/Copy_of_CURB_LINEWORK.shp")
st_crs(curbs)
curbs<-st_transform(curbs, crs = st_crs(3776))


#clip to study area 
curbs_clip<-st_intersection(curbs, study_area)

save(curbs_clip, file="1_data/manual/curbs_clip.rData")


# Visualize layer
m14<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
  tm_shape(curbs_clip)+
  tm_lines(col="TYPE",
           palette="Greys",
           contrast=c(.5, 1),
           title.col="Curb type")+
  tm_layout(
            legend.outside = FALSE, 
            legend.text.size = .6, 
            legend.bg.color="white", 
            legend.frame=TRUE, 
            legend.frame.lwd=.8)

m14

tmap_save(m14, "4_output/maps/curbs_map.png", outer.margins=c(0,0,0,0))
Map of curbs in Edmonton by type.

Figure 2.28: Map of curbs in Edmonton by type.

Attributes
ID MAPSHEET OWNER UTIL FEATURE TYPE FIRST_ID
12767 2677987 9344003 Curbs Base Curb Lines Curb Lines CURB
12768 2677371 9344003 Curbs Base Sidewalks Sidewalks CURB
12769 2677995 9344003 Curbs Base Curb Lines Curb Lines CURB
12770 2677369 9344003 Curbs Base Sidewalks Sidewalks CURB
12771 2677367 9344003 Curbs Base Sidewalks Sidewalks CURB
12772 2677433 9344003 Curbs Base Sidewalks Sidewalks CURB

Cultural and historical resources

CHRP<-st_read("1_data/external/Environmental_Sensitivity_Data/Historical_Resources_Public/AB_Culture_Historic_Resources_Public.shp")
st_crs(CHRP)
# NAD83 / Alberta 3TM ref merid 114 W 
CHRP_clip<-st_intersection(CHRP, study_area)

save(CHRP_clip, file="1_data/manual/CHRP_clip.rData")


# Visualize layer
CHRP_clip$HRV<-as.factor(CHRP_clip$HRV)

m3<-
  tm_shape(v_road_clip)+tm_lines(col="white")+
  tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(CHRP_clip)+
    tm_fill(col="HRV", palette = "Dark2", contrast = c(0.26, 1),alpha = .3, title="Historic Resource Value (HRV)")+
    tm_borders(col = "#636363")+
  tm_layout(legend.outside = FALSE, legend.text.size = .8, legend.bg.color="white", legend.frame=TRUE,legend.title.size=1, legend.frame.lwd=.8)
m3

tmap_save(m3, "4_output/maps/CHRP_map.png", outer.margins=c(0,0,0,0))
Historic Resource Value (HRV) scores in Edmonton.

Figure 2.29: Historic Resource Value (HRV) scores in Edmonton.

Attributes
ATS HRV CATEGORY MER RNG TWP SEC LSD Shape_area Shape_len
112 4-24-52-28-1,2,7-10,12-15 5 a 4 24 52 28 1,2,7-10,12-15 1648926.5 7317.441
113 4-24-52-28-1,2,7-10,13-15 5 p 4 24 52 28 1,2,7-10,13-15 1479182.3 6513.312
114 4-24-52-28-13 5 a, h 4 24 52 28 13 169723.0 1648.392
115 4-24-52-28-1,12,14 2 h 4 24 52 28 1,12,14 169776.1 1648.639
116 4-24-52-28-1,12,14 2 h 4 24 52 28 1,12,14 169744.2 1648.496
117 4-24-52-28-1,12,14 2 h 4 24 52 28 1,12,14 161633.2 1608.147

Cell phone use data

#slope<-raster("1_data/external/Environmental_Sensitivity_Data/cell/cell_3_8_16_45_RGB.tif")
cell<-raster("1_data/external/Visitation_forBrenden_20210625/Visitation_Density_InclRoads_20210625.tif")
cell<-projectRaster(cell, crs=crs(study_area))

plot(cell)
cell_clip<-crop(cell, study_area)
hist(cell)

writeRaster(cell_clip, filename="1_data/manual/cell_clip", format='GTiff', overwrite=TRUE)
save(cell_clip, file="1_data/manual/cell_clip.rData")


m4<-
  #tm_shape(v_road_clip)+tm_lines(col="#636363")+
  #tm_layout(bg.col="#d9d9d9")+
  tm_shape(nscr)+
    tm_fill(col="white", alpha=.4)+
    tm_borders(col = "#636363")+
  tm_shape(cell_clip)+
    tm_raster(palette = c("white", "#f03b20"),
      title = "visitation density",
              contrast = c(0, 1),
              style = "cont",
      alpha = .8)+
  tm_layout(legend.outside = FALSE, 
            legend.text.size = .8, 
            legend.bg.color="white", 
            legend.frame=TRUE,
            legend.title.size=1, 
            legend.frame.lwd=1,
            )
m4

tmap_save(m4, "4_output/maps/cell_map.png", outer.margins=c(0,0,0,0))
Cellphone derived visitation density .

Figure 2.30: Cellphone derived visitation density .