LiDAR data was collected using LSI's proprietary Helix LiDAR system - Novatel GPS and SPANS inertial unit, coupled to a Riegl Q560 digital waveform ranging laser and mounted in a Cessna 185 aircraft. LiDAR was collected at 600m AGL, and a ground speed of 160km/h. Original data was in an ASCII XYZ coordinate format.

__LiDAR__ (__Li__ght __D__etection __A__nd __R__anging) is a modern survey method that produces three-dimensional spatial information in the form of a data point cloud. LiDAR is an active remote sensing system; it produces its own energy to acquire information, versus passive systems, like cameras, that only receive energy. LiDAR systems are made up of a scanner, which is a laser transmitter and receiver; a GNSS (GPS) receiver; and an inertial navigation system (INS). These instruments are mounted to an aircraft. The laser scanner transmits near-infrared light to the ground. The light reflects off the ground and returns to the scanner. The scanner measures the time interval and intensity of the reflected signals. This information is integrated with the positional information provided by the GNSS and INS to create a three-dimensional point cloud representing the surface. A LiDAR system can record millions of points per second, resulting in high spatial resolution, which allows for differentiation of many fine terrain features. Point clouds collected with LiDAR can be used to create three-dimensional representations of the Earth’s surface, such as Digital Elevation Models (DEMs) and Digital Surface Models (DSMs). DEMs model the elevation of the ground without objects on the surface, and DSMs model ground elevations as well as surface objects such as trees and buildings. LidarBC's **Open LiDAR Data Portal** (see link under Resources) is an initiative to provide **open** public access to LiDAR and associated datasets collected by the Government of British Columbia. The data in the portal is released as Open Data under the [**Open Government Licence – British Columbia**](https://www2.gov.bc.ca/gov/content/data/open-data/open-government-licence-bc) (OGL-BC). Four Government of British Columbia business areas and one department of the Government of Canada make LiDAR data available through the portal: * [**GeoBC**](https://www2.gov.bc.ca/gov/content/data/about-data-management/geobc) * [**Emergency Management and Climate Readiness**](https://www2.gov.bc.ca/gov/content/safety/emergency-management) (EMCR) * [**BC Timber Sales**](https://www2.gov.bc.ca/gov/content/industry/forestry/bc-timber-sales) (BCTS) * [**Forest Analysis and Inventory Branch**](https://www2.gov.bc.ca/gov/content/industry/forestry/managing-our-forest-resources/forest-inventory) (FAIB) * [**Natural Resources Canada**](https://www.nrcan.gc.ca/home) (NRCan) GeoBC is the provincial branch that oversees and manages LidarBC’s Open LiDAR Data Portal, including storage, distribution, maintenance, and updates. Please direct questions to **LiDAR@gov.bc.ca**.

Location and contact information for Pacific Recreational Fishery Salmon Head Recovery Depots.The sport fishing community has an important role in the recovery of coded-wire tags found in Coho and Chinook. A coded-wire tag is a 1mm piece of wire that is laser etched with a unique number. Tags are injected into the nose cartilage of juvenile salmon prior to ocean migration. Annually, Canada and the United States tag over 50 million juvenile salmon. Fisheries and Oceans Canada applies about 5.5 million tags, using about 5.5 kilometres of wire. Anglers can recognize the presence of a coded-wire tag because of the missing adipose fin (located on the dorsal surface of the salmon). If you have caught an adipose fin clipped Coho and Chinook, it is a simple matter of removing the head from the fish, completing a sport head label and then submitting the head to a Sport Head Recovery Depot in the area. It is just as important to turn in heads from terminal or freshwater sites as it is from marine areas. Even though anglers fishing close to hatcheries can be fairly certain of the origin of their catch, data will not be recorded unless the heads from fin-clipped recoveries are turned in. Without the data, the health of the stock and the value of the resource to anglers could be underestimated.

A lidar dataset (*light detection and ranging*) is a collection of 3D points represented in the form of a point cloud, generated from laser surveys (airborne).Remote sensing by airborne laser or lidar refers to a remote sensing or optical measurement technology based on the analysis of the properties of laser light returned to its emitter. The coordinates of the lidar points correspond to the precise positions where the laser pulses emitted by the lidar sensor have been reflected by objects or surfaces. In other words, each lidar spot represents a specific location where the light beam touched a surface and returned to the sensor. These coordinates are expressed in three dimensions (X, Y, Z) and make it possible to create very detailed and accurate representations of the terrain.In particular, lidar data allows:* to generate, among other things, numerical terrain (DTM) and surface (MNS) models;* to visualize the territory in perspective;* to perform three-dimensional spatial analyses for various needs, including: * the identification of areas potentially exposed to landslides and bank erosion; * landslide modeling; * the production of by-products and analyses of forest sectors; * the delimitation of flood zones.These datasets are the result of various intergovernmental collaborations, in particular with several ministries of the Government of Quebec, as well as with the federal government and the municipal sector. The geographic coverage corresponds to the information available on the download map and will be improved according to the availability of new data. In most cases, the data shown on this map corresponds to classified data. In the absence of classified data, but in the presence of raw data, it is the latter that will be presented on the map. Users of [*Open Forest*] (https://www.foretouverte.gouv.qc.ca/?pos=@-69.01196,50.56983&ctx=_telechargement&layers=236id,0v,38z;275id,272pid,1v,6z&groups=272id,T%C3%A9l%C3%A9chargement%20-%20Lidar%20(nuages%20de%20points)t,5z,1v,1e) can also download this data on this platform. **This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Forest Elevation(Ht) Mean 2015Mean height of lidar first returns (m). Represents the mean canopy height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018) Wulder et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest Basal Area 2015Cross-sectional area of tree stems at breast height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The sum of the cross-sectional area (i.e. basal area) of each tree in square metres in a plot, divided by the area of the plot (units = m2ha). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest Percent Above Mean 2015Percentage of first returns above the mean height (%). It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Represents the canopy cover above mean canopy height. Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest Percentage Above 2m 2015Percentage of first returns above 2 m (%). Represents canopy cover. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest 95th Percentile Elevation(Ht) 201595th percentile of first returns height (m). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest Lorey's Height 2015Lorey's mean height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Average height of trees weighted by their basal area (m). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011