“Automatically Extracted Buildings” is a raw digital product in vector format created by NRCan.It consists of a single topographical feature class that delineates polygonal building footprints automatically extracted from airborne Lidar data, high-resolution optical imagery or other sources.

The resource management features of the CanVec series include power lines, communication lines, pipelines, valves, petroleum wells, wind-operated devices, transformer stations, ore extraction sites, aggregate extraction sites, peat extraction sites and oil and gas sites.The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.Related Products:[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)

Species characterization by environmental DNA (eDNA) is a method that allows the use of DNA released into the environment by organisms from various sources (secretions, faeces, gametes, tissues, etc.). It is a complementary tool to standard sampling methods for the identification of biodiversity. This project provides a list of invertebrates species whose DNA has been detected in water samples collected at 2018 using the marker COI.The surveys were carried out in the summer of 2018 from August 11 to 14, between Forestville and Godbout (Haute-Côte-Nord). Sampling was carried out between 9-52 meters depth in 40 stations with one sample par station. Two liters of water were filtered through a 1.2 µm fiberglass filter. DNA extractions were performed with the DNeasy Blood and Tissue extraction kit (Qiagen). Negative field, extraction and PCR controls were added at the different stages of the protocol. Libraries at the COI locus were prepared by Genome Quebec and sequenced on an Illumina MiSeq PE250 system. The bioinformatics analysis of the sequences obtained was carried out using an in-house analysis pipeline as reported in Bourret et al. 2022. A first step made it possible to obtain a molecular operational taxonomic unit table (MOTU) using the cutadapt software for the removal of the adapters and the DADA2 R package for the filtration, fusion, chimera removal and data compilation. The MOTUs table was subsequently corrected by taking into account the negative controls, where the number of observations in the latter was removed from the linked samples. Singleton MOTUs have also been removed. Finally, the taxonomic assignments were carried out on the MOTUs using the IDTAXA classifier (present in the DECIPHIER R package) using a training set trained on the COI reference bank for Golf St-Laurent (GSL-rl v1.0, https://github.com/GenomicsMLI-DFO/MLI_GSL-rl) and a threshold of 40. Detections with an “Unreliable due to gaps” category were reported at the genus level only.The file provided includes generic activity information, including site, station name, date, marker type, assignment types used for taxa identification, and a list of taxa or species. The list of taxa has been verified by a biodiversity expert from the Maurice-Lamontagne Institute.This project was funded by Fisheries and Oceans Canada's Coastal Environmental Baseline Data Program under the Oceans Protection Plan. This initiative aims to acquire baseline environmental data that contributes to the characterization of significant coastal areas and supports evidence-based assessments and management decisions to preserve marine ecosystems.Data are also available on SLGO platform : https://doi.org/10.26071/ogsl-cd4c205b-f63b

This model is derived from geological, geophysical and other forms of geodata. Feature extraction used deep learning. Predictive modelling made use of the deep ensemble method. Displayed is a Pan-Canadian probability map of mineral potential of graphite. This map was generated using known graphite deposits and occurrences and their associated features. Higher probability values highlight areas with an increased probability of graphite mineral systems.

This layer comprises all the available water wells in GIN (Yukon, British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Quebec, Nova Scotia and Newfoundland and Labrador) and published through the open data platforms. This layer is a combination of all individual provincial and territorial layers. The original databases are dynamically converted by an automatic process managed by Natural Resources Canada (Groundwater Information Network).

This dataset represents the Environmental and Socio-economic Assessments (ESA) submitted to the Canada Energy Regulator (CER). The CER has made this and other ESAs available through an online search tool called BERDI (Biophysical Socio-Economic Regional Data and Information). Data extraction methodology is available on the BERDI website. Pipelines represented in this layer include a start and end point.

The elevation features of the CanVec series include the elevation contours and elevation points. These entities are used to describe the relief of the Canadian Landmass.The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.Related Products:[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)

The land features of the CanVec series contains landscape features of Canada such as islands, shoreline delineation, wooded areas, saturated soil features, landform features (esker, sand, etc.).The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.Related Products:[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)

This thematic layer shows the location of the wells sampled for pesticides in the context of various studies carried out near certain target crop environments between 1999 and 2024. The data comes from an extraction from the BQMA and, when a report is available on the Department's website, the reader can access it from a link in the information window. Private well sampling stations are grouped by watershed in order to comply with sections 53 and 54 of the Act on access to documents held by public bodies and on the protection of personal information.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The administrative features of the CanVec series include geopolitical regions (international, territorial and provincial) and populated place names.A wide selection of attributes describe the data.The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.Related Products:[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)