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We have found 1,585 datasets for the keyword "point cloud". You can continue exploring the search results in the list below.
Datasets: 104,192
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1,585 Datasets, Page 1 of 159
LiDAR Point Clouds - CanElevation Series
The LiDAR Point Clouds is a product that is part of the CanElevation Series created to support the National Elevation Data Strategy implemented by NRCan.This product contains point clouds from various airborne LiDAR acquisition projects conducted in Canada. These airborne LiDAR acquisition projects may have been conducted by NRCan or by various partners. The LiDAR point cloud data is licensed under an open government license and has been incorporated into the National Elevation Data Strategy.Point cloud files are distributed by LiDAR acquisition project without integration between projects.The point cloud files are distributed using the compressed .LAZ / Cloud Optimized Point Cloud (COPC) format. The COPC open format is an octree reorganization of the data inside a .LAZ 1.4 file. It allows efficient use and visualization rendering via HTTP calls (e.g. via the web), while offering the capabilities specific to the compressed .LAZ format which is already well established in the industry. Point cloud files are therefore both downloadable for local use and viewable via URL links from a cloud computing environment.The reference system used for all point clouds in the product is NAD83(CSRS), epoch 2010. The projection used is the UTM projection with the corresponding zone. Elevations are orthometric and expressed in reference to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013).
Ontario Raw Point Cloud (Imagery-Derived)
The Ontario Raw Point Cloud (Imagery-Derived) is elevation point cloud data created from aerial photography from the Geospatial Ontario (GEO) imagery program. It was created using a pixel-autocorrelation process based on aerial photography collected by the imagery contractor for the GEO imagery program. The dataset consists of overlapping tiles in LAZ format and is 6.29 terabytes in size. Tiles are overlapping because the pixel-autocorrelation process extracts elevation values from overlapping stereo photo strips. No classification has been applied to the point cloud, however they are encoded with colour (RGB) values from the source photography. This data is for geospatial tech specialists, and is used by government, municipalities, conservation authorities and the private sector for land use planning and environmental analysis. __Related data__ For a product in non-overlapping tiles with a ground classification applied, see the [Ontario Classified Point Cloud (Imagery-Derived)](https://geohub.lio.gov.on.ca/datasets/febf17330adb4100a22738e1684b5feb). Raster derivatives have been created from the point clouds for some imagery projects. These products may meet your needs and are available for direct download. For a representation of bare earth, see [Ontario Digital Elevation Model (Imagery-Derived)](https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-elevation-model-imagery-derived/about). For a model representing all surface features, see the [Ontario Digital Surface Model (Imagery-Derived)](https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-surface-model-imagery-derived/about).
Ontario Classified Point Cloud (Imagery-Derived)
The Ontario Classified Point Cloud (Imagery-Derived) is a classified elevation point cloud based on aerial photography. The point cloud is structured in non-overlapping 1 km by 1 km tiles in a compressed format. The following classification codes are applied to the data: * unclassified * ground * low noise This data is for geospatial tech specialists, and is used by government, municipalities, conservation authorities and the private sector for land use planning and environmental analysis. __Related data:__ Raster derivatives have been created from the point clouds for some imagery projects. These products may meet your needs and are available for direct download. For a representation of bare earth, see the [Ontario Digital Elevation Model (Imagery-Derived)]( https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-elevation-model-imagery-derived/about). For a model representing all surface features, see the [Ontario Digital Surface Model (Imagery-Derived)]( https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-surface-model-imagery-derived/about).
Ontario Classified Point Cloud (Lidar-Derived)
The Ontario Point Cloud (Lidar-Derived) consists of points containing elevation and intensity information derived from returns collected by an airborne topographic lidar sensor. The point cloud is structured into non-overlapping 1 km by 1 km tiles in LAZ format. The following classification codes are applied to the data: * unclassified * ground * water * high noise * low noise This dataset is a compilation of lidar data from multiple acquisition projects, so specifications, parameters, accuracy and sensors may vary by project. This data is for geospatial tech specialists, and is used by government, municipalities, conservation authorities and the private sector for land use planning and environmental analysis. __Related data:__ Raster derivatives have been created from the point clouds. These products may meet your needs and are available for direct download. For a representation of bare earth, see the [Ontario Digital Terrain Model (Lidar-Derived)]( https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-terrain-model-lidar-derived/about). For a model representing all surface features, see the [Ontario Digital Surface Model (Lidar-Derived)](https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-surface-model-lidar-derived/about).
Oil and Gas Well Surface Hole Location Applications
Applications for the surface location of a well associated with oil and gas activity. This dataset contains point features for proposed applications collected through the BC Energy Regulator's Application Management System (AMS). This dataset is updated nightly
Video Flightline Points
VIDEO FLIGHT POINTS are a specific GPS spatial point recorded during the video taping of the shoreline. They are represented by a specific latitude and longitude taken at a specific date and time. They are associated with a specific VIDEO SEGMENT and link to online Youtube video of the recorded flight.
[ARCHIVED] Nova Scotia Lidar Point Cloud Ground Classified Lockeport 2013
[ARCHIVED] This dataset has been archived as it is no longer able to be provided in this manner. For a more current version of this elevation dataset, please refer to https://nsgi.novascotia.ca/datalocator/elevation/ to access the current catalogue of available elevation products. Elevation data (LiDAR) was captured for a select group of 1:2000 scale map sheets covering the Town of Lockeport. This LiDAR data has had all ground points classified thereby providing a bare earth profile for the project area. The nominal point spacing of the returns is 1 point per metre. The area collected is a total of five 1:2000 scale map sheet windows for a total coverage of approximately 14 square kilometres.
Lidar Data
Lidar point cloud data with classifications – unclassified (1), ground (2), low vegetation (3), medium vegetation (4), high vegetation (5), buildings (6), low point - noise (7), reserved – model keypoint (8), high noise (18).
[ARCHIVED] Nova Scotia Lidar Point Cloud All Hits Hantsport 2013
[ARCHIVED] This dataset has been archived as it is no longer able to be provided in this manner. For a more current version of this elevation dataset, please refer to https://nsgi.novascotia.ca/datalocator/elevation/ to access the current catalogue of available elevation products. Elevation data (LiDAR) was captured for a select group of 1:2000 scale map sheets covering the Town of Hantsport. This LiDAR data has not been classified and is a raw data record of all the returns from the LiDAR sensor. The nominal point spacing of the returns is 1 point per metre. The area collected is a total of six 1:2000 scale map sheet windows for a total coverage of approximately 17 square kilometres.
Lidar Download Map
Lidar point cloud data with classifications – unclassified (1), ground (2), low vegetation (3), medium vegetation (4), high vegetation (5), buildings (6), low point - noise (7), reserved – model keypoint (8), high noise (18).
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