| Characteristics | Data source | |
|---|---|---|
| Response or edited | Imputed | |
| % | ||
| Sales of goods manufactured | 91.0 | 9.0 |
| Raw materials and components | 84.5 | 15.5 |
| Goods / work in process | 86.4 | 13.6 |
| Finished goods manufactured | 83.1 | 16.9 |
| Unfilled Orders | 92.2 | 7.8 |
| Capacity utilization rates | 78.3 | 21.7 |
1. Indicate which type of corporation this report covers.
2. Is the reporting entity part of a Canadian consolidation?
3. Does this reporting entity have investments in partnerships or joint ventures?
4. Indicate the accounting standard used to complete this questionnaire.
5. Indicate the currency used to complete this survey.
6. What are the start and end dates of this enterprise's reporting period for the quarter ending:
From: YYYY-MM-DD to YYYY-MM-DD
7. Report your assets
8. Report your liabilities.
9. Report your equity.
10. What period does this income statement cover?
From: YYYY-MM-DD to YYYY-MM-DD
11. Report your revenue.
12. Report your expenses.
13. Report your income.
14. Report other disclosures.
15. Allocate the changes to selected assets and liabilities.
Catalogue number: Catalogue number: 89200005
Issue number: 2020005
Release date: February 17, 2020
QGIS Demo 5
(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Demo 5 - Exploring the Attribute Table and Layer Properties Box of Vector Data")
Following up from interacting with datasets in the Map Canvas, today we'll explore additional information and parameters found in the Attribute Table and Layer Properties Box. The Attribute Table contains additional variables for analyzing and visualizing vector data, while the Layer Properties box contains tabs that summarize information and provide additional functions. We'll quickly summarize some of the key tabs, their content and use, which we'll cover in detail in later demos.
So to open the Attribute Table of a layer, we can left-click it in the Layers panel and select the Attribute table icon, or right-click the layer and select Open Attribute Table.
So within the table, each column reports an additional variable tied to the vector dataset. These are referred to as fields within GIS, whereas each row corresponds to a specific feature or geometry within the canvas.
Using the tabs on the left-hand side we can select features. With an individual feature selected, we can right-click and Zoom to the Feature, and if we still couldn't see it we could also flash the feature. In this case we can't see our feature as it's hidden by our Census Subdivision layer.
Like the Interactive Selection tools, we can use Shift and Control to select multiple features. Using shift to select features within a range and Ctrl to add individual features. In conjunction, selecting features both within and between ranges. We could also then zoom to our selection. So as you can see, when features are selected in the Attribute Table they are also highlighted in the Canvas and vice-versa – highlighted in yellow in the Canvas and blue in the Attribute Table.
To sort a field, ascending or descending we can left-click once or twice on the field name as needed. This can help select features by specific criteria of interest such as selecting all features within a particular province in this case. We can then also zoom once more and using the Invert feature selection, we can switch the selection of features.
To move selections to the top of the attribute table, we can click the Move Selection to Top icon. So now if we add any additional features to our selection they are by default loaded at the top of the table. We could also copy our information and paste it into an external spreadsheet editor for further analysis.
Expanding the Show All Features dropdown, we could apply a field filter, selecting the field to filter by and specific criteria to use in filtering the table. Subsequently, the only remaining entries are those that satisfy the entered criteria, in this case Province name being Manitoba.
If we want a dynamic representation of our attribute features based on the scale and extent, we can apply a Show Features Visible on Map. Now if we change the scale or change the location, our table is filtered accordingly.
To enable additional tools we can enable the editor. This enables us to add or delete features, as well as add and delete fields. We can also click on an individual cell's content to edit its information, or for a selection of features we can use the Update Field Bar, specifying the field to update and the new attributes to update to – in this case clicking Update Selected. If we wanted to retain these changes we can save them, but in this case – since we want to keep our attribute table uniform - we'll just discard the changes and clear our selection.
To open the Layer Properties box of a layer we can right-click it and select Properties or simply double-left click within the Layers Panel.
The Layer Properties box contains various tabs which both summarize information and provide additional functions.
The Information tab summarizes the spatial characteristics as well as some of the attribute information within a dataset.
In the Source Tab we can rename a layer as we did with the Census Subdivisions. We can also use the Query Builder to filter features. However, this would filter the geometries of the layer in the Canvas as opposed to the table when using the Field Filter earlier.
The following four tabs are for visualization. We'll explore the Symbology and Labels tab in an upcoming demo, where we can apply different symbology styles to visualize fields within the attribute table, as well as differing labelling schemes. We can create Diagrams with the attribute information and, when enabled, also apply 3D visualizations.
The Source Fields tab provides more information on the Field Names, Types and additional parameters and with editor enabled we can add or delete a field, as well as rename a field.
So the Joins tab enables you to link datasets together – tables or vectors, by a field with common entries. The tab specifically works for one-to-one joins. So for example, here we could join the Census division and Subdivision layers using the unique Census Division identifier field. If we want to remove our join, simply select it and click the minus icon.
The final tab I'd like to cover is the rendering tab where we can apply a scale-dependent visibility, defining the minimum and maximum scale at which a dataset should begin or suspend rendering. We can set the scale from the drop-downs or set it to the current map canvas scale by clicking on this icon. This is helpful for large or highly detailed datasets that take a long time to render. Now, clicking OK, if we zoom in – our layer remains visible, but zooming out beyond the specified scale, you can see rendering is suspended.
Congratulations everyone! Today you've learned key skills in exploring, selecting and filtering features within the attribute table, performing simple edits and the use of some tabs within the Layer Properties box. In the next demo, we'll cover procedures for creating vector datasets, which includes delineating features and populating their attributes.
(The words: "For comments or questions about this video, GIS tools or other Statistics Canada products or services, please contact us: statcan.sisagrequestssrsrequetesag.statcan@canada.ca" appear on screen.)
(Canada wordmark appears.)
Catalogue number: Catalogue number: 89200005
Issue number: 2020004
Release date: February 17, 2020
QGIS Demo 4
(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Demo 4 - Interacting with data in the Map Canvas")
Now that we have learned to load and order our datasets in QGIS, let’s explore some tools for interacting with them in the Map Canvas, particularly those found on the Map Navigation and Attribute toolbars. The skills covered today will provide skills for changing and saving the extent, as well as identifying and selecting features from layers in the Map Canvas.
So picking up where we left off…
The Map Navigation toolbar contains tools for changing the scale of the Canvas. By default the Pan Map tool is engaged. Simply left-click and drag the Canvas in the direction of interest.
The Zoom Tools operate similarly, left-click and drag across the area you’d like to zoom to. Depending upon the size of the box that’s drawn determines how much the scale changes. So if we draw a large box the change is negligible, whereas a smaller box the change is much more substantial. Alternatively you can use the scroll-bar of your mouse, scrolling backward and forward to zoom out and in respectively.
If we want to return to the extent of all active layers in the Panel we can use the Zoom to Full tool – helpful when we can’t find a particular dataset or if we just want to return to the full extent.
The Zoom to Layer tool is useful when the extents of loaded datasets differ
and works on the selected layer in the Layers Panel. Applying it to the road segments layer, it zooms to Manitoba, the area for which we downloaded the dataset.
The Zoom Last and Next tools are effectively the Undo and Redo of changes in the Canvas, enabling us to scroll through our previous zooms.
If you are going to be focussing on one area quite a lot for analysis or visualization, you can add a Spatial Bookmark and provide the bookmark with a name. Then if we were to close the Panel and zoom to another area in the map canvas, we can reopen the Panel, select the bookmark and the zoom icon to return to the saved extent.
Just before moving on to the Attribute Toolbar lets discuss grouping layers. We can use the Shift and Control keys to create a selection of layers, then right-click and hit Group Selected. This has many applications such as grouping thematically related layers, preparing mapping groups or organizing datasets such as toggling off many layers at once. Within the group, individual layers can be toggled off and on as normal. We can also right-click to Move a layer out of the Group or drag and drop – as desired.
Now on to the Attribute toolbar – which as the name suggests contains various tools for selecting, editing and examining the attributes of active layers in the Layers Panel. Today we’ll use the Interactive Selection and Identify tools, which default to the selected layer in the Layers Panel.
So with the Census Division layer selected, we can zoom in and left-click to select individual features. We can also drag across to select multiple features. Using Control we can add and remove individual features, or remove a selection of features. Alternatively we can use Shift to add many features to the selection. We can click the Deselect Icon on the toolbar to remove the selection.
If we expand the drop-down there are alternative selection options:
Select by Polygon is helpful for selecting irregular shaped features. We can left-click to add individual vertices and right-click to complete the polygon.
There is also Select by Radius, where we can zoom in, left-click a point of interest and left-click again when satisfied with the radius. Alternatively, we can specify the radius value in the top-right corner.
The Identify tool operates in a similar fashion. We can click an individual feature, and as we can see the Identify Panel returns information on both the geometry and attributes of the identified feature. Similar to the Interactive Selection tools we can drag across to identify multiple features and use the Collapse and Expand All icons to rapidly examine their attributes. Re-enabling the Census Subdivision layer, we can right-click and select Identify All. Here we returned two division features and six census subdivision features.
The same options from the interactive selection tool are available in the Identify tool by expanding the drop-down icon in top-centre of the Panel. Additionally we can change the Mode to alter which layers features are returned by the tool. Changing from Current to Top-Down will identify from all active layers. So re-enabling our grouped layers and creating a small selection in Northern Ontario we’ve identified a few features within the hydrological layer and ultimately returned features from three separate layers.
To remove the identified features click the Clear Results icon within the Identify Panel.
So that summarizes some of the basic tools for changing the extent and scale of the map canvas as well as interacting with vector datasets in the map canvas. In the next demo we will explore additional information found within the Attribute table and Layer Properties box of vector datasets.
(Canada wordmark appears.)
Catalogue number: Catalogue number: 89200005
Issue number: 2020003
Release date: February 17, 2020
QGIS Demo 3
(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Demo 3 - Loading and Ordering Spatial Data in QGIS")
Hello everyone! So now that we've downloaded QGIS and spatial data, today we'll learn how to load and order datasets of different geometry types in QGIS, and save the Project for later use. For the demonstration we'll use several datasets that we downloaded in the previous video, covering the main geometry types of vector data: points, lines & polygons.
So the first step is to open QGIS Desktop from a desktop shortcut or from the start-bar.
And the first thing well do is pin QGIS to the taskbar since we will be using it frequently in subsequent training videos.
When you open QGIS for the first time it looks like this.
To load spatial data into QGIS, they are added from the Browser panel, in to the Layers panel, and also visualized in the Map Canvas.
So the first thing we need to do is expand the folders to find where we downloaded our spatial datasets to in the previous video. So I'll expand the Home folder and the Documents folder to find the GeospatialData folder.
Since it's the first time we're locating this folder, we'll right-click and add it as a favourite, which adds it to our favourites drop-down at the top, which will help us load datasets more quickly and easily in the future.
To see the available layers just continue expanding the folders, and within the Intro Demo folder there are 4 shapefiles and 2 geodatabase files.
So to load datasets in it is quite simple, you can just double-left click or drag-and-drop from the Browser to the Layers panel.
These procedures can also be applied to geodatabase files, you just need to expand the folder to see the available layers first. For Grain Elevators there is only one, so just double left-click, while for Transport Features there are many, but for the purpose of the demo we'll use the Road Segments layer.
Finally we will load in our two census boundary files into the layers panel.
Don't worry if the colours of your files differ from those in this video. QGIS assigns a single random colour when vector datasets are loaded.
So within the Layers Panel, individual layers can be toggled off and back on again, as well as renamed. So here I'll just rename the Census Subdivisions file with a more intuitive name.
Despite having loaded the six layers into the Layers Panel, we can only see one within the Map Canvas. This is because the order within the Layers Panel affects the order that they are rendered in the Map Canvas.
So in general points are placed above lines, which themselves are placed above polygons. For vectors of the same geometry type it is important to think about their position in the landscape relative to one another – so do rivers flow over roads, or do roads tend to get built over rivers? Well often roads are built over rivers, so we'll just switch their order in the Layers Panel. And similarly, the Lakes and Rivers polygon, as a land-cover feature we'll place it above the census boundary files.
So now if we zoom in we can see that all of our layers are visible in the Map Canvas.
The final component of the video I'd like to discuss today is saving the project for later use. This will save the order of layers in the Layers Panel, any visualizations styles such as labels or colours as well as any joins– all procedures that we'll discuss in later demos. So navigate to the Project Toolbar and click on the Save Icon. In general we want to store the project in the same location as the spatial data, and provide it with an intuitive filename, like Loading and Ordering Spatial Data.
So that concludes the procedures for loading datasets into QGIS from the Browser to the Layers Panel, which will work for most spatial data, and how to order them in the layers panel for their visualization in the Map Canvas. Additionally, we learned how to save our project and the specific properties that are retained. Stay tuned for the next demo, where we will explore some of the tools on the Map Navigation and Attribute toolbars for interacting with these datasets in the Map Canvas.
(Canada wordmark appears.)
Catalogue number: Catalogue number: 89200005
Issue number: 2020002
Release date: February 17, 2020
QGIS Demo 2b
(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Demo 2b - Downloading Spatial Datasets from Open Maps")
So now that we have a better understanding of spatial data let's go to the Open Maps website and download some datasets to use in QGIS. Specifically we'll download 3 datasets, then using the skills from the video you can isolate and download the remaining files shown at the end of the video.
Open Maps is the integrated federal archive for spatial data making it a one-stop-shop for downloading thematically diverse datasets – from broad to highly specific content, which should enable most processes or features of interest to be examined. It is important to note that not all datasets are inherently spatial, but most have traits that enable their integration and use in GIS.
To begin searching for datasets scroll down the main page, and click the Open Maps link.
This brings us to a page with a search-bar where we can search specific datasets. The first one we'll look for is the Transport Features released by Natural Resources Canada as part of their CanVEC catalogue.
So the search results appear as such with a hyperlinked title to the main dataset page, a description of its content, the organization associated with its release and the file formats for the different components of the dataset.
At the moment datasets must be downloaded individually.
At the top right of the page are Search Filters to help refine the results. We'll apply two to find our dataset right now. Scrolling down to the Format Filter we'll check the FGDB box since we are looking for a File Geodatabase. In the Organization filter we'll click on Natural Resources Canada.
So we can click on the title to bring us to the main page of the dataset. The Resource Type column indicates the different components of the dataset, such as web services, classification guide or the main dataset itself,
in this case provided in Shapefile or File Geodatabase format. The file formats of spatial datasets and supporting information are varied between entries.
So to download the dataset we'll click the Access tab beside FGDB. This brings us to the main index page which hosts the available datasets. All are listed as Canvec - followed by abbreviations for the scale and geographic location and all are part of the Transport series. So national datasets vary in resolution from 1 in 1 million to 1 in 15 million, whereas provincially subset datasets vary in resolution from 1 in 50,000 to 1 in 250,000.
In general, you should use the dataset that matches your intended scale of analysis and visualization. So using the finest resolution data for a national examination of transport features or using the coarsest resolution for local assessment would both be inappropriate.
We'll download the 1 in 50,000 dataset for Manitoba.
Closing the index page, now I'd like to quickly show the classification guide. Classification guides contain information to help interpret and use a dataset. In the Catalogue drop-down we'll select Transport – the dataset we downloaded. It defaulted to 1 in 50,000 so we can just scroll down to a layer of interest. And within the table, we can expand a field we'd like more information on. So expanding the Road Class drop-down it provides the numeric IDs within the Attribute table, as well as the corresponding class and a detailed description of each class. We'll use this guide in a later demo to help classify our road segments.
So now we can close up the page and hit back. The first thing we'll do is remove the filters we applied earlier so they don't impact our next search results.
The next dataset we'll look for is the Annual Crop Inventory, a thematic raster released by Agriculture and Agri-Food Canada. This is a great resource for local assessments of crop variations both spatially and over time within Canada.
So scrolling down we can see each entry associated with a particular year, and then further down there is one without a designated year. We'll click on this link.
Once on the main page we'll scroll past the web-mapping services
until we reach the main components of the dataset. We'll download the Classifications Guide, to help us interpret the crop classes associated with the different numeric values.
If we wanted more information on the sources and methodology used to create the dataset we can access the metadata guide. In this case providing us information on the remote sensing datasets, methodologies, as well as the resolution and some accuracy assessments.
Now to access the main dataset, we'll click on the Access tab beside GeoTIF.
As we can see, the entire time-series is listed on this one integrated index, which would make for quicker downloading of a time-series than were we to click on the individual links in the original search results. We'll select 2017, and once again download the subset dataset for Manitoba.
Now the final dataset we'll look for is the land-cover circa 2000 file. So look-up land-cover within the Search Bar and hit search. With 271 returned records, we'll once again scroll down to the format filter, expand it and in the expanded options we'll select shapefile.
Once again it's our first returned result so we'll click the hyperlinked title. On the main page we'll scroll-down and click on the shapefile dataset.
Once again this is a subset dataset, but less intuitive than the provincially subset datasets we just downloaded. However, it is in the National Topographic System, a common referencing system for federal spatial data. So just look up NTS Index Canada in a new tab, and click the Open Canada link to access the reference guide which will help us isolate the files that correspond with our area of interest. There are a variety of formats we could use to find the files of interest, but for now we'll use the .pdf file and click on the prairies. This is how the system appears. Each areas is referenced by a large number and – zooming in – they are also subset by specific letters. So if we wanted to download the land-cover for Winnipeg we could download 62 G, H, I and J. Closing up the Reference Guide and returning to the main data index page for the dataset, scroll down to 62 and then select G, H, I and J. This system is also used for the Digital Elevation Model datasets in Table 1.
I'd also like to quickly discuss downloading the Statistics Canada Census Boundary files, which were accessed from Statistics Canada's website. So look up Statistics Canada Boundary Files in a webpage and click on the on the link. There are two styles of boundary files. There is the cartographic boundary file, which include shorelines, islands and other land-components and are best are used for visualization of data. And the Digital boundary file in which there is one feature for each corresponding boundary. These are best suited for processing and analysis.
Now that we know of the two different styles, we can click on the 2016 link to access the most recent boundary files. So we can select the specific style and level of interest. We'll start by downloading the digital boundary file for Census Divisions, clicking on Continue and then selecting the hyperlinked text to access the dataset. Then we can access the Census Subdivision Cartographic file, selecting the corresponding level and style, clicking on continue at the bottom of the page and the zipped dataset link on the next page. So repeat these procedures as necessary to download the remaining boundary files and styles, as well as the Lakes and Rivers Polygon and Rivers line datasets shown in the table at the end of the video.
While we are here we will also download the table datasets listed in Table 1.
First we'll download the Population and Dwelling Highlight Tables. So click on Data, and look up Highlight. The first returned result is the compiled highlight tables from the 2016 census. Listed are the various highlight tables, ours is on Page 2 and we'll click on the Population and Dwelling Count highlights. We'll then download the complete geographic level by clicking on the CSV/TAB hyperlink in which we can then download the Census Divisions, Subdivisions and Tracts.
The next table dataset we'll look for is the Farms Classified by Total Farm Capital table. Much like Open Maps there are various filters we can apply to help isolate the dataset, so let's add an Agriculture filter and search Farm Capital. Scrolling down it is around the 8th result, so once found click on the hyperlinked title. On the main page it has provided the dataset by default for Canada. We can click on the Add/Remove Data tab to change the geography levels, as well as the reference period, and choose the variables we want to download.
So let's expand the Geography levels to show how to select different boundary levels. To download a complete geographic level we can use the boxes at the top – clicking on the box furthest to the right to download the finest resolution at the subdivision level or in this case we'll select the Census Agricultural Regions– the third box. We could also expand and select a specific area of interest within the drop-downs, clicking all or on an individual feature. Re-enabling we'll just select all Agricultural Regions and toggle Canada off.
Then we can go over to our variables. In this case, by default all the variables are enabled – which is not always the case so it is always good to verify and select the variables that are of interest to you. If a dataset has been collected over multiple census periods, you can specify the Reference period to include in the table from the drop-downs here.
And the Customizable Layout tab lets you format the dataset according to your particular use of interest. For us we'll simply change the Geography from Columns to Rows.
Then we'll click Apply. Once the formatting has been applied to the table below we can select Download Options. We'll Download As Displayed to retain the formatting specified. If we were to Download the Entire Table it would remove those formatting specifications.
The final procedure I'd like to discuss is extracting our datasets to a common folder. In GIS it is best practice to store all your datasets in one common directory. So we'll expand the Documents and create a new folder called GeospatialData. Within this folder we can use additional subdirectories be organized by project or theme to help organize your files. Before hitting extract, we will copy the directory so we can paste it when repeating the procedure with other downloaded datasets. Repeat with the remaining files.
Congratulations! From today's demo you've learned foundational skills to navigate the Open Maps Platform, download and take full advantage of the diversity of spatial data it stores. Many of these skills can be extended to accessing datasets from other geospatial archives, such as those hosted by municipal and provincial governments. We also covered the process of extracting and storing datasets in a common directory on your computer, with subdirectories to help organize the different datasets. With this experience you should be able to isolate relevant data and file formats for your own work activities. In the following tutorial we'll cover the procedures for loading and ordering datasets in QGIS.
(Canada wordmark appears.)
Catalogue number: Catalogue number: 89200005
Issue number: 2020001
Release date: February 17, 2020
QGIS Demo 2a
(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Demo 2a - Categories, Sub-Types and Properties of Spatial Data")
Hello everyone. So we've installed QGIS, but have no data to use.
So in today's tutorial we'll cover two items. First we'll expand some definitions, exploring the properties, main categories and subtypes of spatial data. Then we'll discuss procedures for downloading datasets online from Open Maps, which is the integrated federal archive for geospatial data.
The understanding of different spatial data types, their traits and applications in GIS developed in the first part of this video will provide the knowledge and skills to navigate the platform, as well as other online spatial data archives, and download datasets relevant to your own areas of expertise.
So in the previous video we introduced spatial data as data referenced to specific geographic locations through coordinates. Today we'll discuss the three listed properties that make datasets spatial, and explore the main categories of spatial data, vectors and rasters, as well as their characteristics, subtypes and common file formats.
The figure on the right nicely depicts some of the properties and subtypes of these two spatial data categories and their integrated use in capturing complex real-world processes and features.
The first component that makes a dataset spatial is the map projection, which defines how the Earth's 3D surface is transformed to a 2D representation. All projections distort features in some way with differing projections created to preserve certain characteristics such as distance, direction, angle, area, or shape. Projections can be thought of as a light source projecting features onto a 3D shape which is unfurled for a 2D view.
The figure shows the three main projection families which are: Cylindrical, Conical, and Planar.
The geodetic datum is a series of key base-points that define the position of select features, with WGS84 approximating mean sea level. They act as known points which are then used to develop the Coordinate Reference System and link features to the projected surface. There are horizontal and vertical datums, which define the shape and position of features in 2D and 3D space. We'll focus on horizontal datums.
So they have been developed for different scales and locations, from local to global levels. Often there is a trade-off in the area they cover and the accuracy of the fit for the specific area of interest, as is shown in the figure. WGS84 or the World Geodetic Systemis the best fit for the entire world as a whole, while the North American Datumbetter fits its specific location. Datums can also become deprecated with NAD27 being replaced by NAD83.
So Coordinate Reference Systems are comprised of meridians and parallels, or vertical and horizontal lines, which create a gridded network and enable the location of features to be defined anywhere on the projected surface through XY coordinates. There are two main types of coordinate systems: Geographic and Projected.
So, geographic coordinate systems generally cover larger areas with coordinates in angular units like decimal degrees or degrees-minutes-seconds.
Projected Coordinate Systems are derived from geographic ones and generally cover smaller extents, but are designed for planar representation of features. As such projected systems are used for spatial analysis such as overlaying layers or adding spatial measures to a dataset. The coordinates often use linear units such as metres.
The figure shows that the appearance of features can change significantly depending on the applied projection, datum and CRS. When using multiple layers in GIS it is best practice to ensure that these properties are uniform. This is particularly important for analysis using multiple layers, where differing properties can result in erroneous measures, overlays or processing tools failing.
So the first spatial data category we'll discuss is vector data, which is probably more accessible to new GIS users. The QGIS User Manual defines vector data as "table data with geometry".
Vector data is used to depict discrete features using three broad geometry types: points, lines and polygons which are shown in the figures below through rail stations and grain elevators, roads and rivers, and land-cover boundaries respectively. Additional variables - numeric or text - are stored in the attribute table, which can be used for analysis and visualization. Common file formats of vector data include shapefiles and file geodatabases. File geodatabases may contain multiple layers of any geometry type – and in certain cases must be exported to a new layer for editing and analysis. Geopackage, the default format in QGIS, combines elements of these two file formats.
Conversely, raster data often depicts continuous data. There are three broad types: single-band, composite and thematic. Single-band shows variations of a single variable like elevation, slope, precipitation, or Hillshade and Aspect – as shown on the left side of the figure. Composite rasters refer to remotely sensed data like satellite imagery, as shown with the Landsat 8 image, where different bands can be combined for analysis and visualization. Thematic rasters are often used to release land-cover classifications derived from composite imagery, like the Annual Crop Inventory on the right.
Unlike vector data, the visualization of raster data is scale-dependent, varying with its cell or pixel size, which is tied to its spatial resolution. Raster data is strictly numeric with each cell assigned a number, corresponding to variations in a specific variable or attribute.
Rasters are generally in image file formats, the most common formats being GeoTIFs (.tif), and JPEG2000 (.jp2). Raster datasets underscore the finer-grain data that is publically available, with resolutions of 15 to 30 metres being common. We will use a combination of vector and raster datasets throughout the subsequent training materials.
So that concludes the first part of this video, expanding our understanding of the properties that make a dataset spatial and the main categories, subtypes and traits of spatial data. Stay tuned for the second half of this tutorial where we'll show the procedures for navigating and accessing spatial datasets from Open Maps.
(Canada wordmark appears.)
Catalogue number: Catalogue number: 89200005
Issue number: 2019001
Release date: February 17, 2020
QGIS Demo 1
(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Demo 1 - What is GIS, and why use QGIS?")
Hello everyone, I'm Alex Foster and I work as a data analyst at Statistics Canada. As the first video in our series, today I'll introduce what Geographic Information Systems - or GIS for short - are, discuss their relevance and their potential integration in your areas of work and expertise.
There are two items to cover. The first is some definitions and applications of GIS using spatial data. The second is to contextualize why we're using QGIS, an open-source GIS, for the tutorials.
These training materials are targeted for new GIS users with no formal training using GIS. So we'll start with foundational concepts and skills, and build towards more advanced applications and topics throughout. These skills and procedures can then be extended to datasets that are thematically relevant to you. We'll show you how with a few relatively easy steps you can get quite a lot out of GIS, and how you can integrate Statistics Canada and other public datasets to address challenges or tasks faced in your day-to-day work.
Geographic Information Systems, or GIS, are programs that can store, process, combine and visualize spatial data, which is any dataset with coordinate information used to position and render it within GIS.
So if you have ever used a mapping tool or GPS to find the fastest route between locations or looked at weather maps of a storm, shown in the figures below, you've interacted with GIS and geospatial data.
So why use GIS? Well GIS programs are powerful tools for data linking, analysis and visualization, enabling spatial datasets to be overlaid, integrated, and mapped in an interactive and multi-scalar format. As such, GIS is the go-to-tool for disseminating data, and is the industry standard for decision-making – informing disparate topics from targeting social and economic development programs and policies; to optimizing marketing, business and service deliveries; to improving environmental and land-use management practices. GIS has many uses from simple analysis and mapping to highly advanced functions, scripting and modelling. We anticipate most uses of interest to new GIS users can be accomplished in a few easy steps - requiring little effort to get the most out of the data.
In general GIS can visualize multidisciplinary information in an intuitive and accessible format, which can be used to support and enhance documents, or act as a standalone product. You know, much like a picture is worth a thousand words, an interactive map is worth a thousand data tables in terms of interpretability and accessibility.
They can also be used to derive new information through overlaying and combining multiple datasets and variables and take advantage of finer resolution and frequency datasets.
The figure shows two visualizations I created in GIS. On the right is a heat map of traffic collision frequency in Ottawa for 2017 and on the left shows a time-series of the mean monthly temperatures across Manitoba in 2016. Both demonstrate the power of visualizing spatial data to convey information, and were produced using a few simple steps.
So why use QGIS? Well open-source GIS was traditionally restricted to technically trained users. Yet, technological developments have increased the immersion of GIS in our day-to-day lives, and made the software increasingly accessible and usable to new GIS users.
And this is epitomized by QGIS. As an open-source program it is free to download online with underlying codes also provided. It is advantageous as it emphasizes its graphical-user interface, resulting in an intuitive and easy-to-use program. It integrates its own toolset with those from other established open-source GIS such as SAGA and GRASS toolsets, as well as integrating user-created plugins, resulting in diverse functionality. It also has a smaller installation size and computational requirements than other GIS programs. And the significant user-base provides rapid updates, plugins and patches for the program, which in conjunction with online documentation can be consulted to perform or parametrize a variety of functions.
QGIS has been significantly expanded and improved upon with its newest releases.
So let's go and download QGIS. Use the link provided in the video description or search online as I'm doing right now. QGIS link
There are two main options for download on Windows: the OSGEO4W Package and the stand-alone Installers. The first is best suited for advanced users, as it automates updates and avoids duplicating packages used by multiple GIS programs.
We will download the stand-alone installer of which there are two versions. At the time of recording there is v. 3.6 The Most Recent Feature Rich Release and the new long-term release v. 3.4.
To enable the most up-to-date functions and adopt the next generation of QGIS, we will download the newest long-term release – version 3.4 – which was released in February 2019.
For users with other operating systems, the stand-alone installers can be downloaded by expanding the drop-downs below.
Once downloaded, use the default installation settings – hitting Next until Finish.
Once installed, open the QGIS Desktop application from the Start Bar or shortcut. In the pop-up box we will select the Fresh Start, instead of importing settings from QGIS 2.
The download procedures can be reapplied as needed when updating the program.
Stay tuned for the next series of videos, where we will download spatial data, and start to work through a few different procedures - so you can begin to analyze and visualize data within the program, and create products relevant to you. In the next demo we will introduce the common categories and file formats of spatial datasets, as well as procedures for navigating and downloading these datasets from Open Maps, the integrated federal archive for storing and disseminating spatial data.
(Canada wordmark appears.)
Statistics Canada is organized based on a professional services model with multiple service pathways delivered by service entities with functional or portfolio-based service delivery responsibilities. The main organizational units at Statistics Canada are the contact centre, regional offices, subject-matter areas in Ottawa, the media line, and the microdata access network. These organizational units are responsible for managing enquiries and providing services according to the agency's service standards. Within this decentralized structure, each function (subject matter divisions and regional offices) has its own or shared client service unit. Each one is responsible for organizing itself according to the resources available, the volume of requests, the expertise required to respond to requests and the level of knowledge of client service representatives (generalists or experts). The structure requires extensive information exchange between functions to coordinate and route requests based on the required level of expertise.
The Evaluation Division of Statistic Canada's Audit and Evaluation Branch conducted an independent evaluation of the agency's client service delivery. The primary objective of the evaluation was to provide a neutral, evidence-based analysis of the relevance and performance of the organization's client service delivery environment in support of decision making, accountability and improvement. The evaluation was conducted in accordance with the Treasury Board Secretariat's Policy on Results (2016) and Statistics Canada's Risk-Based Audit and Evaluation Plan (2018/2019 to 2022/2023).
The evaluation found that clients of Statistics Canada want fast, reliable, consistent, transparent and professional service at a reasonable cost. While they were satisfied with the professionalism of staff and the quality of the information and services provided, more complex requests (including those for customized products and expert advice) were sometimes challenging. Consistency, transparency, timeliness, communication and cost of services were all areas requiring improvement. The evaluation found some fundamental gaps in the organization: little evidence of an overarching strategy for client service delivery at the agency level, a lack of clarity around roles and responsibilities, inconsistent processes and tools resulting in a fragmented delivery of services, and gaps in corporate governance and leadership.
The evaluation proposed three recommendations:
An agency-wide client service delivery strategy or plan is developed that covers governance and leadership, agency-level objectives, standards including targets, performance measures, roles and responsibilities, and communications. The strategy should focus on creating a more holistic and consistent approach that addresses the various issues highlighted during the evaluation, such as timeliness, transparency, consistency and costs.
The agency's new CRMS is aligned to the strategy in Recommendation 1 and thus supports a more holistic and consistent approach.
The quality and coverage of information in the CRMS are improved, and the awareness among managers about the CRMS is increased.
| Geography | CVs for operating revenue |
|---|---|
| percent | |
| Canada | 1.86 |
| Newfoundland and Labrador | 0.00 |
| Prince Edward Island | 0.00 |
| Nova Scotia | 3.22 |
| New Brunswick | 2.39 |
| Quebec | 3.83 |
| Ontario | 2.99 |
| Manitoba | 2.48 |
| Saskatchewan | 1.06 |
| Alberta | 4.02 |
| British Columbia | 3.61 |
| Yukon | 0.00 |
| Northwest Territories | 0.00 |
| Nunavut | 0.00 |
