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We have found 1,228 datasets for the keyword "73 m". You can continue exploring the search results in the list below.
Datasets: 106,156
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1,228 Datasets, Page 1 of 123
Level curves
Level curves with an equidistance of 1 m derived from a lidar survey conducted in 2024.attributes:ID - Unique IDSubtype - Master (1) or secondary (2) level curve SCORE - Elevation value (m) The High Resolution Digital Elevation Model (m) product The High Resolution Digital Elevation Model (HRDM) product is available on the Open Government website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Marine Conservation Targets (MCT) - Camera surveys of the subtidal flora of Nova Scotia and Southwest New Brunswick 2022-2023
To assess the current distribution of kelp beds and other macroalgae in Nova Scotia and Southwest New Brunswick, subtidal drop camera surveys were performed from 2022-2023 at 140 sites. For each site, a GoPro HERO 10 camera was towed along a deep (7-12m) and shallow (3-5m) depth contour until 20 images were acquired per depth. Where possible, species were identified from photos, with particular care given to kelps (defined here as orders Laminariales and Tilopteridales) and fucoids (order Fucales). Crust-forming algae was not counted. Percent cover was calculated using a 10x10 point grid overlaid on each image and recording the dominant cover type at each point. The depth (in meters) of each photo after correcting for tide height ranged from ~0.5m to ~12m. Depths were corrected to chart datum (lowest astronomical tide) using tide predictions from the nearest tide station, taken from tides.gc.ca. Sampling was performed between July and October. Cite this data as: Krumhansl K, Brooks C, Lowen B, DiBacco C, (2025). Camera Surveys of the Subtidal Flora of Nova Scotia and Southwest New Brunswick 2022-2023. Version 1.7. Fisheries and Oceans Canada. Samplingevent dataset. https://ipt.iobis.org/obiscanada/resource?r=camera_surveys_of_the_subtidal_flora_of_nova_scotia_2022-2023&v=1.7For additional information please see:Krumhansl K.A., Brooks C.M., Lowen B., O’Brien J., Wong M., DiBacco C. Loss, resilience and recovery of kelp forests in a region of rapid ocean warming. Annals of Botany 2024 Mar 8; 133(1):73-92. Brooks C.M., Krumhansl K.A. 2023. First record of the Asian Antithamnion sparsum Tokida, 1932 (Ceramiales, Rhodophyta) in Nova Scotia, Canada. BioInvasions Records 12(3):745-725.
Structural Culverts - 25k
The purpose of this dataset is to provide structural culvert locations along highways . The definition of a Structural Culvert is a culvert with span of 2 metres or greater. Drainage culverts have a diameter less than 2 metres and are not included in this dataset.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)
Waterbodies - 250k - Canvec
Hydro Features is composed of the network of Canadian surface waters. Hydro Features entities are: Watercourse, Water Linear Flow, Hydro Obstacle (falls, rapids\...), Waterbody (lake, watercourse\...), Permanent Snow and Ice, Water Well, and Spring. CanVec is a digital cartographic reference product of Natural Resources Canada (NRCan). It originates from the best available data sources covering Canadian territory, offers quality topographical information in vector format, and complies with international geomatics standards. CanVec is a multi-source product coming mainly from the National Topographic Data Base (NTDB), the Mapping the North process conducted by the Canada Center for Mapping and Earth Observation (CCMEO), the Atlas of Canada data, the GeoBase initiative, and the data update using satellite imagery coverage (e.g. Landsat 7, Spot, Radarsat, etc.).Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)
Land Cover - 50k - Canvec
Land Features entities are: Island, Shoreline, Wooded Area, Saturated soil, Landform Feature (esker, sand\...), and Cut Line. CanVec is a digital cartographic reference product of Natural Resources Canada (NRCan). It originates from the best available data sources covering Canadian territory, offers quality topographical information in vector format, and complies with international geomatics standards. CanVec is a multi-source product coming mainly from the National Topographic Data Base (NTDB), the Mapping the North process conducted by the Canada Center for Mapping and Earth Observation (CCMEO), the Atlas of Canada data, the GeoBase initiative, and the data update using satellite imagery coverage (e.g. Landsat 7, Spot, Radarsat, etc.).Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)
Land Cover - 250k - Canvec
Land Features entities are: Island, Shoreline, Wooded Area, Saturated soil, Landform Feature (esker, sand\...), and Cut Line. CanVec is a digital cartographic reference product of Natural Resources Canada (NRCan). It originates from the best available data sources covering Canadian territory, offers quality topographical information in vector format, and complies with international geomatics standards. CanVec is a multi-source product coming mainly from the National Topographic Data Base (NTDB), the Mapping the North process conducted by the Canada Center for Mapping and Earth Observation (CCMEO), the Atlas of Canada data, the GeoBase initiative, and the data update using satellite imagery coverage (e.g. Landsat 7, Spot, Radarsat, etc.).Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)
FRI: Height (Lorey's mean)
Height is an expression of the average height (m) of dominant and co-dominant trees of the leading species in the stand, expressed as Lorey’s mean height (LRY_HT). Available here as a height raster (GeoTIF) with a 20 m pixel resolution.Download: Here The Saskatchewan Ministry of Environment, Forest Service Branch, has developed a forest resource inventory (FRI) which meets a variety of strategic and operational planning information needs for the boreal plains. Such needs include information on the general land cover, terrain, and growing stock (height, diameter, basal area, timber volume and stem density) within the provincial forest and adjacent forest fringe. This inventory provides spatially explicit information as 10 m or 20 m raster grids and as vectors polygons for relatively homogeneous forest stands or naturally non-forested areas with a 0.5 ha minimum area and a 2.0 ha median area. Lorey's mean tree height (LRY_HT) is an expression of the average tree height (m) of dominant and co-dominant trees of the leading species in the stand whereby individual trees are weighted in proportion to their basal area. LRY_HT is available here as a color-mapped 16-bit unsigned integer raster grid in GeoTIFF format with a 20 m pixel resolution. An ArcGIS Pro layer file (*.lyrx) is supplied for viewing LRY_HT data in the following 5 m categories. Domain: [NULL, 0…35]. RANGE LABEL RED GREEN BLUE 0 <= LRY_HT < 3 0 NA NA NA 3 <= LRY_HT < 8 5 63 81 181 8 <= LRY_HT < 13 10 72 144 114 13 <= LRY_HT < 18 15 136 195 73 18 <= LRY_HT < 23 20 255 235 59 23 <= LRY_HT < 28 25 255 180 20 28 <= LRY_HT < 33 30 251 124 18 33 <= LRY_HT <= 35 35 244 67 54 For more information, see the Forest Inventory Standard of the Saskatchewan Environmental Code, Forest Inventory Chapter.
Clay percentage (%) - Soil Landscape Grids of Canada, 100m
Predicted clay percentage (%) at a defined depth range (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm).
Silt percentage (%) - Soil Landscape Grids of Canada, 100m
Predicted silt percentage (%) at a defined depth range (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm).
Bay of Fundy Sea Scallop Commercial Size Abundance Data
This dataset represents abundance data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey. Data is binned into 5-mm shell height bins, is prorated to an 800 m tow length and 17.5 feet (5.334 m) drag width (i.e., representing an area swept of 4267 m2), and was collected using unlined dredge gear. Each row represents a tow and contains information such as tow date, cruise name, gear type, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Commercial Size Abundance Data. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ecc09d98-56ed-4a27-ad62-5c3714a1d9b4
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