Subject(s): Earth and Environmental Sciences / Format: Shapefile - Geodisy Search Results

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1. Dataset for: Recoupling the Livestock Nutrient Economy: A Path forward for Water Quality Improvement (1 of 3)

Werenka, Alexander. Optimization methods were used to evaluate the feasibility of transporting manure for spreading on cropland to meet established nutrient requiremen... University of Waterloo Dataverse.

2. Dataset for: Recoupling the Livestock Nutrient Economy: A Path forward for Water Quality Improvement (2 of 3)

Werenka, Alexander. Optimization methods were used to evaluate the feasibility of transporting manure for spreading on cropland to meet established nutrient requiremen... University of Waterloo Dataverse.

3. Dataset for: Recoupling the Livestock Nutrient Economy: A Path forward for Water Quality Improvement (3 of 3)

Werenka, Alexander. Optimization methods were used to evaluate the feasibility of transporting manure for spreading on cropland to meet established nutrient requiremen... University of Waterloo Dataverse.

4. Don Valley Historical Mapping Project (01 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

5. Don Valley Historical Mapping Project (02 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

6. Don Valley Historical Mapping Project (03 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

7. Don Valley Historical Mapping Project (04 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

8. Don Valley Historical Mapping Project (05 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

9. Don Valley Historical Mapping Project (06 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

10. Don Valley Historical Mapping Project (07 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

11. Don Valley Historical Mapping Project (08 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

12. Don Valley Historical Mapping Project (09 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

13. Don Valley Historical Mapping Project (10 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

14. Don Valley Historical Mapping Project (11 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

15. Don Valley Historical Mapping Project (12 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

16. Don Valley Historical Mapping Project (13 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

17. Don Valley Historical Mapping Project (14 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

18. Don Valley Historical Mapping Project (15 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

19. Don Valley Historical Mapping Project (16 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

20. Don Valley Historical Mapping Project (17 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

21. Don Valley Historical Mapping Project (18 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

22. Don Valley Historical Mapping Project (19 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

23. Don Valley Historical Mapping Project (20 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

24. Don Valley Historical Mapping Project (21 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

25. Don Valley Historical Mapping Project (22 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

26. Don Valley Historical Mapping Project (23 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

27. Don Valley Historical Mapping Project (24 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

28. Don Valley Historical Mapping Project (25 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

29. Don Valley Historical Mapping Project (26 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

30. Don Valley Historical Mapping Project (27 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

31. Don Valley Historical Mapping Project (28 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

32. Don Valley Historical Mapping Project (29 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

33. Don Valley Historical Mapping Project (30 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

34. Don Valley Historical Mapping Project (31 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

35. Don Valley Historical Mapping Project (32 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

36. Don Valley Historical Mapping Project (33 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

37. Don Valley Historical Mapping Project (34 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

38. Don Valley Historical Mapping Project (35 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

39. Don Valley Historical Mapping Project (36 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

40. Don Valley Historical Mapping Project (37 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

41. Don Valley Historical Mapping Project (38 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

42. Don Valley Historical Mapping Project (39 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

43. Don Valley Historical Mapping Project (40 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

44. Don Valley Historical Mapping Project (41 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

45. Don Valley Historical Mapping Project (42 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

46. Don Valley Historical Mapping Project (43 of 43)

Fortin, Marcel and Jennifer Bonnell. Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials... University of Toronto Dataverse.

47. FRAGSTATS DATABASE: Showcasing relationships between neighborhood design and Wellbeing Toronto indicators

Shaker, Richard. A research study across the 140 neighborhood‐landscapes (streetscapes) of Toronto was presented through three main intentions. Its foundational goa... Ryerson University Dataverse.

48. GIS files for Boat Harbour Fish Survey (1 of 8)

Hoover, Zachary. Shp, files and kmz files for the watercourses, cross basin transects and shore transects used in a fish survey of Boat Harbour, Fall 2019. shp. fil... Cape Breton University Dataverse.

49. GIS files for Boat Harbour Fish Survey (2 of 8)

Hoover, Zachary. Shp, files and kmz files for the watercourses, cross basin transects and shore transects used in a fish survey of Boat Harbour, Fall 2019. shp. fil... Cape Breton University Dataverse.

50. GIS files for Boat Harbour Fish Survey (3 of 8)

Hoover, Zachary. Shp, files and kmz files for the watercourses, cross basin transects and shore transects used in a fish survey of Boat Harbour, Fall 2019. shp. fil... Cape Breton University Dataverse.

51. GIS files for Boat Harbour Fish Survey (4 of 8)

Hoover, Zachary. Shp, files and kmz files for the watercourses, cross basin transects and shore transects used in a fish survey of Boat Harbour, Fall 2019. shp. fil... Cape Breton University Dataverse.

52. GIS files for Boat Harbour Fish Survey (5 of 8)

Hoover, Zachary. Shp, files and kmz files for the watercourses, cross basin transects and shore transects used in a fish survey of Boat Harbour, Fall 2019. shp. fil... Cape Breton University Dataverse.

53. GIS files for Boat Harbour Fish Survey (6 of 8)

Hoover, Zachary. Shp, files and kmz files for the watercourses, cross basin transects and shore transects used in a fish survey of Boat Harbour, Fall 2019. shp. fil... Cape Breton University Dataverse.

54. GIS files for Boat Harbour Fish Survey (7 of 8)

Hoover, Zachary. Shp, files and kmz files for the watercourses, cross basin transects and shore transects used in a fish survey of Boat Harbour, Fall 2019. shp. fil... Cape Breton University Dataverse.

55. GIS files for Boat Harbour Fish Survey (8 of 8)

Hoover, Zachary. Shp, files and kmz files for the watercourses, cross basin transects and shore transects used in a fish survey of Boat Harbour, Fall 2019. shp. fil... Cape Breton University Dataverse.

56. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (01 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

57. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (02 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

58. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (03 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

59. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (04 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

60. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (05 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

61. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (06 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

62. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (07 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

63. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (08 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

64. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (09 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

65. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (10 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

66. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (11 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

67. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (12 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

68. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (13 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

69. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (14 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

70. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (15 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

71. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (16 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

72. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (17 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

73. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (18 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

74. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (19 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

75. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (20 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

76. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (21 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

77. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (22 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

78. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (23 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

79. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (24 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

80. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (25 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

81. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (26 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

82. Historic Ontario Road, Rail, Municipality, County and District Shapefiles (27 of 27)

Penfound, Elissa and Vaz, Eric. Historic Maps of southern Ontario, between the years 1800-1970, were collected from oldmapsonline.org to measure for land use and land cover change... Ryerson University Dataverse.

83. How does vegetation fragmentation affect urban carbon stock in City of Vancouver, Canada

Li, Derek. Urban vegetation acts as an extremely important carbon stock to store carbon. Although many studies have investigated the relationship between urba... UBC Dataverse.

84. Light Detection and Ranging (LiDAR)-based Forest Inventory and Land Classification Map 2020 of the University of British Columbia (UBC) Vancouver Campus (1 of 4)

Shao, Yifei. As urban forest provides ecological, social, and economic values to the residents, forest inventory can monitor forest health. Based on the land cl... UBC Dataverse.

85. Light Detection and Ranging (LiDAR)-based Forest Inventory and Land Classification Map 2020 of the University of British Columbia (UBC) Vancouver Campus (2 of 4)

Shao, Yifei. As urban forest provides ecological, social, and economic values to the residents, forest inventory can monitor forest health. Based on the land cl... UBC Dataverse.

86. Modelling the Potential Impacts of Climate Change on Arboreal Diversity of the University of British Columbia Vancouver Campus from 2050 to 2080 (1 of 4)

Liang, Chris. Climate change poses a considerable risk to forest diversity in urban communities. The University of British Columbia (UBC) seeks to identify vulne... UBC Dataverse.

87. Modelling the Potential Impacts of Climate Change on Arboreal Diversity of the University of British Columbia Vancouver Campus from 2050 to 2080 (2 of 4)

Liang, Chris. Climate change poses a considerable risk to forest diversity in urban communities. The University of British Columbia (UBC) seeks to identify vulne... UBC Dataverse.

88. Modelling the Potential Impacts of Climate Change on Arboreal Diversity of the University of British Columbia Vancouver Campus from 2050 to 2080 (3 of 4)

Liang, Chris. Climate change poses a considerable risk to forest diversity in urban communities. The University of British Columbia (UBC) seeks to identify vulne... UBC Dataverse.

89. Modelling the Potential Impacts of Climate Change on Arboreal Diversity of the University of British Columbia Vancouver Campus from 2050 to 2080 (4 of 4)

Liang, Chris. Climate change poses a considerable risk to forest diversity in urban communities. The University of British Columbia (UBC) seeks to identify vulne... UBC Dataverse.

90. Pollinators Habitat Capability Analysis of the University of British Columbia (UBC) Vancouver Campus (1 of 5)

Song, Jia Yi. Pollination is an essential ecosystem service for crop production, where species such as insects and birds help to transfer pollen for plants to re... UBC Dataverse.

91. Pollinators Habitat Capability Analysis of the University of British Columbia (UBC) Vancouver Campus (2 of 5)

Song, Jia Yi. Pollination is an essential ecosystem service for crop production, where species such as insects and birds help to transfer pollen for plants to re... UBC Dataverse.

92. Pollinators Habitat Capability Analysis of the University of British Columbia (UBC) Vancouver Campus (3 of 5)

Song, Jia Yi. Pollination is an essential ecosystem service for crop production, where species such as insects and birds help to transfer pollen for plants to re... UBC Dataverse.

93. Pollinators Habitat Capability Analysis of the University of British Columbia (UBC) Vancouver Campus (4 of 5)

Song, Jia Yi. Pollination is an essential ecosystem service for crop production, where species such as insects and birds help to transfer pollen for plants to re... UBC Dataverse.

94. Pollinators Habitat Capability Analysis of the University of British Columbia (UBC) Vancouver Campus (5 of 5)

Song, Jia Yi. Pollination is an essential ecosystem service for crop production, where species such as insects and birds help to transfer pollen for plants to re... UBC Dataverse.

95. Replication data: mapping and remote sensing of Hul'qumi'num culturally important seaweeds in the Salish Sea

Thom, Brian and Baker, Jack. Drone imagery for Cordova Bay and Porlier Pass Two study sites in the Salish sea were surveyed using Unoccupied Aerial Vehicle (UAV) techniques: ȾE... University of Victoria Dataverse.

96. Spatial distribution of icings (aufeis) in northwestern Canada (1 of 2)

Crites, Hugo. This geospatial point dataset offers information on icing (aufeis) distribution in northwestern Canada (1985-2016). . University of Ottawa Dataverse.

97. Spatial distribution of icings (aufeis) in northwestern Canada (2 of 2)

Crites, Hugo. This geospatial point dataset offers information on icing (aufeis) distribution in northwestern Canada (1985-2016). . University of Ottawa Dataverse.

98. [University of British Columbia Point Grey Campus Lidar], 2005 (1 of 2)

University of British Columbia. Campus and Community Planning. <p>Projection: NAD 83/UTM Zone 10 N (EPSG:26910)</p> <p>Combined DEM produced from ASCII text by UBC Library 15 Oct 2021.</p> <p>Contour shapefile ... Abacus Open Data.

99. [University of British Columbia Point Grey Campus Lidar], 2005 (2 of 2)

University of British Columbia. Campus and Community Planning. <p>Projection: NAD 83/UTM Zone 10 N (EPSG:26910)</p> <p>Combined DEM produced from ASCII text by UBC Library 15 Oct 2021.</p> <p>Contour shapefile ... Abacus Open Data.

100. [University of British Columbia Point Grey Campus Lidar], 2021 (01 of 15)

University of British Columbia. Campus and Community Planning. No control was available to verify the absolute accuracy of the dataset. However, due to a robust trajectory solution and good calibration results,... Abacus Open Data.