The map displays bedrock formations at or near the surface of the land, on the sea floor above the continental crust that forms the Canadian landmass, and oceanic crust surrounding the landmass. The bedrock units are grouped and coloured according to geological age and composition. The colours of offshore units and oceanic crust are paler and more generalized than those on land, although the constituent units offshore are still easily discernible from their dashed boundaries. This colour design, coupled with the use of a white buffer zone at the coast allows the coastline of Canada to be readily distinguished and still show the grand geological architecture of the Canadian landmass.The map also shows major faults that have disrupted the Earth's crust, onshore and offshore, and a variety of special geological features such as kimberlite pipes, which locally contain diamonds, impact structures suspected to have been caused by meteorites, and extinct and active spreading centres in the surrounding oceans.

The 2010 AAFC Land Use is a culmination and curated metaanalysis of several high-quality spatial datasets produced between 1990 and 2021 using a variety of methods by teams of researchers as techniques and capabilities have evolved. The information from the input datasets was consolidated and embedded within each 30m x 30m pixel to create consolidated pixel histories, resulting in thousands of unique combinations of evidence ready for careful consideration. Informed by many sources of high-quality evidence and visual observation of imagery in Google Earth, we apply an incremental strategy to develop a coherent best current understanding of what has happened in each pixel through the time series.

Industrial sectors.attributs:ID - Unique identifierName - Industrial park name**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

STR - Facilities and structures (structure)Man-made construction. For example, resources describing buildings, museums, churches, schools, hospitals, factories, housing, monuments, and towers.

Major buildings and municipal services.attributes:ID - unique identifierSubtype - Item subtypeName - Building or department name**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The spatial representation for an Inventory Region or Compartment. Established by the Resource Inventory Branch, Inventory Regions are large drainages encompassing groups of small drainages also known as compartments. These were once used for planning purposes, similar to the current Planning Cells. They are now maintained in the files as reference for many administration boundaries

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).**

All land uses in the planning and development planrevised by the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

“Automatically Extracted Buildings” is a raw digital product in vector format created by NRCan. The feature classes of this product delineate polygonal building footprints automatically extracted from airborne Lidar data, high-resolution optical imagery or other sources.The first feature class, Automatically Extracted Buildings by acquisition source, contains building footprints delivered according to the spatial extent of each source dataset used for extraction. When the spatial extents of acquisition sources overlap, footprints for the same building may therefore be duplicated in this class.The second feature class, Optimized Buildings Layer, is an assembled and harmonized layer derived from the buildings by acquisition source. Its objective is to provide a unique representation of each building footprint by removing duplicates and resolving overlaps between sources.

The 2005 AAFC Land Use is a culmination and curated metaanalysis of several high-quality spatial datasets produced between 1990 and 2021 using a variety of methods by teams of researchers as techniques and capabilities have evolved. The information from the input datasets was consolidated and embedded within each 30m x 30m pixel to create consolidated pixel histories, resulting in thousands of unique combinations of evidence ready for careful consideration. Informed by many sources of high-quality evidence and visual observation of imagery in Google Earth, we apply an incremental strategy to develop a coherent best current understanding of what has happened in each pixel through the time series.