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).

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).

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).

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).

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product.Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases.

Highway Reference Point is a visibly recognizable feature used to describe and identify a point on the Highway (i.e., a reference point abstracted on the Highway and defined by a physical landmark such as an intersection). HRP Landmarks are used in order to provide reference points relating to inventory item data

Named point features (both fresh and marine) such as points of land, etc. Point names included as an attribute

The maximum temperature layer shows the modeled maximum temperature [°C] at a height of 100 m above ground level, at each grid point, over the three year period from January 1, 2008 to December 31, 2010. Values are presented in bins with ranges of 1.5 °C each. Further details including data for individual years can be obtained by clicking on the dot representing the grid point location.

The wind speed layer shows the modeled wind speed [m/s] at a height of 100 m above ground level, at each grid point, averaged over the three year period from January 1, 2008 to December 31, 2010. Values are presented in bins with ranges of 0.5 m/s each. Further details including data at different heights, and for individual years, can be obtained by clicking on the dot representing the grid point location.

The minimum temperature layer shows the modeled minimum temperature [°C] at a height of 100 m above ground level, at each grid point, over the three year period from January 1, 2008 to December 31, 2010. Values are presented in bins with ranges of 1.5 °C each. Further details including data for individual years can be obtained by clicking on the dot representing the grid point location.