DOI: 10.5281/zenodo.16689280
title: Spatial covariates for 45 cities included in the UWIN camera trap network

description: Overall data structure description:

    


File
Spatial Layer
Source(s)
file type


ESA_WorldCover.zip
cropland, forest, lakes, oceans
ESA WorldCover, HydroLAKES, Natural Earth
raster


Census_data.zip
bachelor_degree, graduate_degree, income, white_race(non-minority)
USA and CAN census data
vector


GHL.zip
BUILT_C (2018), BUILT_S (2018 (10m), 2015 (100m)), BUILT_V (2020), BUILT_POP (1975 & 2020), SMOD (1975, 2000, 2020, 2025)
Global Human Settlement
raster


Climate.zip
Degrees under 0 (DD), Summer Precipitation (MSP), relative humidity (RH), Atmospheric temperature (TD) for years 2019-2023 and a mean across those 5 years.
Climate NA
raster


Biomes_and_Ecoregions.zip
Biomes and Ecoregions across all three levels
US Environmental Protection Agency
vector


SLOPE.zip
elevation, slope, terrain_roughness (TRIriley)
Shuttle Radar Topography Mission (SRTM)
raster


roads_lines.zip
OSM roads (all types as in the OSM manuscript) and rivers
OpenStreetMap
vector




NDVI.zip

NDVI estimated from Landsat images
Landsat 8/9
raster


envelopes_all_cities.zip
catalogue of cities included, names, codes and locations
vector


IUCN.zip
species richness, species presence, and rarity-weighted species-richness
IUCN
raster, vector




 

Layer specific information:

        


File
Spatial Layer
Source file 
Source webpage
File type
Resolution
Projection (EPSG)
script
countries


ESA_WorldCover.zip
cropland
ESA WorldCover
DATA | WORLDCOVER
raster
0.0083
4326
 
All


ESA_WorldCover.zip
forest
ESA WorldCover
DATA | WORLDCOVER
raster
0.0083
4326
 
All


ESA_WorldCover.zip
lakes
HydroLAKES
HydroLAKES
vector
NA
4326
 
All


ESA_WorldCover.zip
oceans
Natural Earth
Natural Earth - Free vector and raster map data at 1:10m, 1:50m, and 1:110m scales
vector
NA
4326
 
All


Census_data.zip
Number of bachelor degrees
USA and CAN census data
https://walker-data.com/tidycensus/;  https://mountainmath.github.io/cancensus/index.html
vector
NA
4269
 
USA and Canada


Census_data.zip
Number of graduate degrees
USA census data
https://walker-data.com/tidycensus/;  https://mountainmath.github.io/cancensus/index.html
vector
NA
4269
 
USA


Census_data.zip
Median Income
USA and CAN census data
https://walker-data.com/tidycensus/;  https://mountainmath.github.io/cancensus/index.html
vector
NA
4269
 
USA and Canada


Census_data.zip
Number of non-minority individuals (white)
USA and CAN census data
https://walker-data.com/tidycensus/;  https://mountainmath.github.io/cancensus/index.html
vector
NA
4269
 
USA and Canada


GHL.zip
Building components 2018
GHS_BUILT_C_MSZ_E2018_GLOBE_R2023A_54009_10_V1_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
10
9001
 
All


GHL.zip
Built Surface Area 2018
GHS_BUILT_S_E2018_GLOBE_R2023A_54009_10_V1_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
10
9001
 
All


GHL.zip
Built Surface Area 2025
GHS_BUILT_S_E2025_GLOBE_R2023A_54009_100_V1_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
100
9001
 
All


GHL.zip
Built Volume 2020
GHS_BUILT_V_E2020_GLOBE_R2023A_54009_100_V1_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
100
9001
 
All


GHL.zip
Population density 1975
GHS_POP_E1975_GLOBE_R2023A_54009_100_V1_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
100
9001
 
All


GHL.zip
Population density 2020
GHS_POP_E2020_GLOBE_R2023A_54009_100_V1_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
100
9001
 
All


GHL.zip
Urbanization degree 1975
GHS_SMOD_E1975_GLOBE_R2023A_54009_1000_V2_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
1000
9001
 
All


GHL.zip
Urbanization degree 2000
GHS_SMOD_E2000_GLOBE_R2023A_54009_1000_V2_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
1000
9001
 
All


GHL.zip
Urbanization degree 2020
GHS_SMOD_E2020_GLOBE_R2023A_54009_1000_V2_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
1000
9001
 
All


GHL.zip
Urbanization degree 2025
GHS_SMOD_E2025_GLOBE_R2023A_54009_1000_V2_0
Global Human Settlement - Visualisations of the GHSL datasets - European Commission
raster
1000
9001
 
All


Climate.zip
Degrees under 0 (DD) years 2019-2023 and a mean across those 5 years.
PRISM through ClimateNA 
Home Page - ClimateNA
raster
0.0083
4326
 
All


Climate.zip
Summer Precipitation (MSP) years 2019-2023 and a mean across those 5 years.
PRISM through ClimateNA 
Home Page - ClimateNA
raster
0.0083
4326
 
All


Climate.zip
Relative humidity (RH) years 2019-2023 and a mean across those 5 years.
PRISM through ClimateNA 
Home Page - ClimateNA
raster
0.0083
4326
 
All


Climate.zip
Atmospheric temperature (TD) for years 2019-2023 and a mean across those 5 years.
PRISM through ClimateNA
Home Page - ClimateNA
raster
0.0083
4326
 
All


Biomes_and_Ecoregions.zip
Biomes and Ecoregions across all three levels
US Environmental Protection Agency
Ecoregions of North America | US EPA
vector
NA
4326
 
All


SLOPE.zip
elevation
Shuttle Radar Topography Mission (SRTM)
Shuttle Radar Topography Mission (SRTM) | NASA Earthdata
raster
0.0083
4326
 
All


SLOPE.zip
slope
Shuttle Radar Topography Mission (SRTM)
Shuttle Radar Topography Mission (SRTM) | NASA Earthdata
raster
0.0083
4326
 
All


SLOPE.zip
terrain_roughness (TRIriley)
Shuttle Radar Topography Mission (SRTM)
Shuttle Radar Topography Mission (SRTM) | NASA Earthdata
raster
0.0083
4326
 
All


roads_lines.zip
OSM roads (all types as in the OSM manuscript) and rivers
OpenStreetMap
OpenStreetMap; Leveraging Open‐Source Geographic Databases to Enhance the Representation of Landscape Heterogeneity in Ecological Models - Gelmi‐Candusso - 2024 - Ecology and Evolution - Wiley Online Library
vector
NA
4326
 
All




NDVI.zip

NDVI estimated from Landsat images
see Landsat_tiles_acros_cities.csv
EarthExplorer
raster
30
32617 (variable UTM Zone so last two digits wil follow UTM Zone of Landsat Image)
All


envelopes_all_cities.zip
catalogue of cities included, names, codes and locations
UWIN mean LatLong across sites + Buffer defined by UWIN partners
Urban Wildlife Network
vector
NA
4326
 
All


IUCN.zip
species richness
IUCN
IUCN Red List of Threatened Species
raster
NA
9001
 
All


IUCN.zip
species presence
IUCN
IUCN Red List of Threatened Species
vector
NA
4326
 
All


IUCN.zip
rarity-weighted species-richness
IUCN
IUCN Red List of Threatened Species
raster
30000
9001
 
All




 

Github with scripts used to generate layers

tgelmi-candusso/spatial_covariates_for_UWIN: Spatial covariates extracted across 45 cities incuded in UWIN Camera Trap Network

 

Cities included:

    


city_code
city
State/Province
Country
Lon
Lat
buffer_m


edal
Edmonton, AB
Alberta
Canada
-113.493
53.52685
10


caab
Calgary, AB
Alberta
Canada
-114.089
51.02825
30


baar
Bariloche, Ar
Rio Negro
Argentina
-71.3628
-41.122
5


phaz
Phoenix, AZ
Arizona
USA
-112.091
33.53858
25


lrar
Little Rock, AR
Arkansas
USA
-92.3362
34.72394
10


vaca
Vancouver, BC
British Columbia
Canada
-123.124
49.25769
10


baca
Bay Area, CA
California
USA
-122.301
37.87136
20


lbca
Long Beach, CA
California
USA
-118.156
33.78808
10


paca
Pasadena, CA
California
USA
-118.132
34.1844
10


poca
Pomona, CA
California
USA
-117.77
34.06568
10


sdca
San Diego, CA
California
USA
-117.108
32.82431
5


safa
San Francisco, CA
California
USA
-122.728
37.78614
10


deco
Denver, CO
Colorado
USA
-104.854
39.76503
30


foco2
Fort Collins, CO
Colorado
USA
-105.07
40.55614
20


poor
Portland, OR
Oregon
USA
-122.654
45.5434
30


sewa
Seattle, WA
Washington
USA
-122.343
47.60814
35


scut
Salt Lake City, UT
Utah
USA
-111.921
40.77747
35


tawa
Tacoma, WA
Washington
USA
-122.455
47.24359
35


mela
Metro LA
California
USA
-118.19
33.99968
40


wide
Wilmington, DE
Denver
USA
-75.5296
39.73062
15


naca
Washington D.C.
Maryland
USA
-77.0146
38.89406
30


safl
Sanford, FL
Florida
USA
-81.2751
28.78417
20


ahga
Athens, GA
Georgia
USA
-83.3892
33.94382
5


atga
Atlanta, GA
Georgia
USA
-84.4202
33.76751
35


frge
Freiburg, DE
Baden-Württemberg
Germany
7.796468
47.98747
10


chil
Chicago, IL
Illinois
USA
-87.7332
41.83463
46


inin
Indianapolis, IN
Indiana
USA
-86.133
39.78016
20


deio
Des Moines, IA
Iowa
USA
-93.6014
41.56947
20


ioio
Iowa City, IA
Iowa
USA
-91.5408
41.64772
15


boma
Boston, MA
Massachusetts
USA
-70.9977
42.31336
35


jams
Jackson, MS
Mississippi
USA
-90.1966
32.30426
45


slmo
Saint Louis, MO
Missouri
USA
-90.242
38.65315
30


manh
Manchester, NH
New Hampshire
USA
-71.4447
42.97188
55


nyny
New York, NY
New York
USA
-73.0246
40.92768
5


rony
Rochester, NY
New York
USA
-77.617
43.18567
20


syny
Syracuse, NY
New York
USA
-76.1395
43.03529
18


cloh
Cleveland, OH
Ohio
USA
-81.7058
41.49771
10


stok
Stillwater, OK
Oklahoma
USA
-97.0825
36.14178
2


toon
Toronto, ON
Ontario
Canada
-79.3762
43.71792
10


sasa
Saskatoon, SK
Saskatchewan
Canada
-106.664
52.15071
10


autx
Austin, TX
Texas
USA
-97.7487
30.30754
20


dftx
Fort Worth, TX
Texas
USA
-97.3128
32.80077
25


hote
Houston, TX
Texas
USA
-95.4614
29.82447
21


mawi
Madison, WI
Wisconsin
USA
-89.4019
43.08527
10


anma
Andasibe, Madagascar
Toamasina
Madagascar
48.42209
-18.9199
5