Geospatial forest inventory dataset updated for depletions, such as harvesting, and projected annually for growth. Sample attributes in this dataset include: age, species, volume, height. The Vegetation Resources Inventory (VRI) spatial datasets describe both where a vegetation resource (ie timber volume, tree species) is located and how much of a given resource is within an inventory unit. Suggested citation: Forest Analysis and Inventory Branch (2024). VRI - 2024 - Forest Vegetation Composite Rank 1 Layer (R1). British Columbia Data Catalogue. https://catalogue.data.gov.bc.ca/dataset/2ebb35d8-c82f-4a17-9c96-612ac3532d55

The Forest Analysis and Inventory Branch (FAIB) is responsible for coordinating and managing data collection and analyses from a range of different ground sampling programs that collect data on ground plots. This layer shows ground plots from the PSP and VRI programs. **Vegetation Resource Inventory (VRI):** ground samples primarily used to audit and verify key inventory attributes estimated during photo interpretation. These samples are not protected because they will not be revisited. **Permanent Sample Plots (PSP):** subjectively located fixed-area permanent plots, valued for their long-term re-measurement data to support development of growth-and-yield models in unmanaged stands across a range of stand and ecosystem types. Actual GPS coordinates are provided as protection is necessary. - Active PSPs = plot and buffer are protected from harvesting - Inactive PSPs = not protected from harvesting

Seral stage assessment for the Cariboo Region to support the [Cariboo Chilcotin Land Use Plan (CCLUP)](https://www2.gov.bc.ca/gov/content/industry/crown-land-water/land-use-planning/regions/cariboo/cariboochilcotin-rlup). This assessment is based on [Vegetated Resource Information (VRI)](https://catalogue.data.gov.bc.ca/dataset/6ba30649-14cd-44ad-a11f-794feed39f40) data, and uses the CCLUP [Productive Forest Land Base](https://catalogue.data.gov.bc.ca/dataset/0cfa7f53-272d-47d4-83df-95b4edd75460) as the assessment landbase. Last updated 2026-02-06, based on 2024 VRI (Vegetation Resource Inventory) data. Spatial data and PDF reports and for this and previous seral stage assessments are available for download under "Data and Resources" on the right side of this page. Use the **BC Geographic Warehouse Custom Download** link to download the most recent seral stage assessment data. Web map service and KML files of the most recent seral stage assessment are also available through links on the right. Previous assessments are listed by year; spatial data is available in zipped fgdb format for these.

Fire maintained ecosystem restoration for the Rocky Mountain Forest District. The data was provided by MOFR/Interior Reforestation and compiled based on the various sources including VRI, BEC, TSR2 Algorithm 2003, etc.

The Northeast BC VRI Old Forest (NEBC_VRI_OLD_FOREST_PY) is a value-added product derived from the 2023 vintage of the annually updated Forest Vegetation Composite Polygons and Rank1 Layer (VRI) that represents forest stands 140 years and older. This data was originally published in the [BC Energy Regulator (BCER) Data Centre](https://www.bc-er.ca/data-reports/data-centre/) and listed in the BC Data Catalogue with permission from BCER on "as is" basis. Available for download/access through the [BC Energy Regulator (BCER) Open Data Portal](https://data-bc-er.opendata.arcgis.com/datasets/3a6629d370944e56a5a250f15d723e52_1/about) as CSV, Shapefile, GeoJSON, KML, File Geodatabase, Feature Service.

Dominant Species Map 2015The data represent dominant tree species for British Columbia forests in 2015, are based upon Landsat data and modeling, with results mapped at 30 m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The map was generated with the Random Forests classifier that used predictor variables derived from Landsat time series including surface reflectance, land cover, forest disturbance, and forest structure, and ancillary variables describing the topography and position. Training and validation samples were derived from the Vegetation Resources Inventory (VRI), from a pool of polygons with homogeneous internal conditions and with low discrepancies with the remotely sensed predictions. Local models were applied over 100x100 km tiles that considered training samples from the 5x5 neighbouring tiles to avoid edge effects. An overall accuracy of 72% was found for the species which occupy 80% of the forested areas. Satellite data and modeling have demonstrated the capacity for up-to-date, wall-to-wall, forest attribute maps at sub-stand level for British Columbia, Canada.BC Species Likelihood 2015The tree species class membership likelihood distribution data included in this product focused on the province of British Columbia, based upon Landsat data and modeling, with results mapped at 30 m spatial resolution. The data represent tree species class membership likelihood in 2015. The map was generated with the Random Forests classifier that used predictor variables derived from Landsat time series including surface reflectance, land cover, forest disturbance, and forest structure, and ancillary variables describing the topography and position. Training and validation samples were derived from the Vegetation Resources Inventory (VRI) selecting from a stratified pool of polygons with homogeneous internal conditions and with low discrepancies when related to remotely sensed information. Local models were applied over 100x100 km tiles that, to avoid edge effects, considered training samples from the 5x5 neighbouring tiles. An overall accuracy of 72% was found for the species which occupy 80% of the forested areas. As an element of the mapping process, we also obtain the votes received for each class by the Random Forest models. The votes can be understood as analogous to class membership likelihoods, providing enriched information on land cover class uncertainty for use in modeling. Tree species class membership likelihoods lower than 5% have been masked and converted to zero.When using this data, please cite as: Shang, C., Coops, N.C., Wulder, M.A., White, J.C., Hermosilla, T., 2020. Update and spatial extension of strategic forest inventories using time series remote sensing and modeling. International Journal of Applied Earth Observation and Geoinformation 84, 101956. DOI: 10.1016/j.jag.2019.101956 ( Shang et al. 2020).

All the evaluation units of the graphic matrix of the City of Rouyn-Noranda.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Regional Deterministic Air Quality Analysis (RDAQA) is an objective analysis of surface pollutants that combines numerical forecasts from the Regional Air Quality Deterministic Prediction System (RAQDPS) with hourly observations from various monitoring networks in North America, including the Canadian measurement networks operated by the provinces, territories and certain cities, as well as the various American networks in the context of the AIRNow program administered by US/EPA (US Environmental Protection Agency). RDAQA analysis provides the best description of current air quality conditions, and is used to inform the public, meteorologists in the various Environment and Climate Change Canada forecasting offices, Health Canada and other users about the distribution of air pollutants near the ground, and the performance of forecasting models. Each hour, a preliminary product is available approximately one hour after the observation measurement time, while final and Firework products are available approximately two hours after the measurement time. The preliminary and final products contain analysis of the chemical constituents O3, SO2, NO, NO2, PM2.5 (fine particles with diameters of 2.5 micrometers or less) and PM10 (coarse particles with diameters of 10 micrometers or less), while the Firework product contains analysis of PM2.5 and PM10.

The RFI identifies areas of land and water encircling a recreation feature or combination of features that support, or have the potential to support, one or more recreation activities. These areas are rated for their significance or importance to recreation and for their sensitivity to alteration

Facilities are an oil and gas activity, defined in the Energy Resources Activities Act as a system of vessels, piping, valves, tanks and other equipment used to gather, process, measure, store or dispose of petroleum, natural gas, water or a substance referred to in paragraph (d) or (e) of the definition of pipeline. This dataset contains point features for proposed applications collected through the BC Energy Regulator's Application Management System (AMS). This dataset is updated nightly.