Classify areas by degree of urbanization

In 2020, the United Nations (UN) endorsed the Degree of Urbanization method to classify urban and rural areas around the world. Urbanization typically provides greater access to amenities and opportunities, while creating challenges such as increased air pollution and crime. Understanding urbanization in a standardized way helps officials monitor and report a country or region's progress toward the UN's Sustainable Development Goals (SDGs), adopted in 2015 as a call to action to end poverty and protect the planet.

In this tutorial, you'll classify the Pacific island of New Caledonia by its degree of urbanization. First, you'll create a population grid, which measures population using spatial units of uniform shape and size. You'll convert this population grid into a degree of urbanization grid, which classifies those spatial units as urban or rural based on population criteria. Last, you'll use the degree of urbanization grid to classify New Caledonia's territorial units as urban or rural.

This workflow can be repeated for any country or territory with population data and a built-up surface raster. During the workflow, you'll learn how to access a built-up surface raster for almost any location around the world, allowing you to apply the workflow to your own population data.

This tutorial was last tested on August 29, 2023, using ArcGIS Pro 3.1. If you're using a different version of ArcGIS Pro, you may encounter different functionality and results.

Requirements

• ArcGIS Pro (see options for software access)
• GHS-DEGURBA Toolkit
• MATLAB Runtime 9.9 or higher

Create a population grid

A population grid is a raster layer made up of pixels of uniform shape and size, with information about the number of people who live in each pixel. These grids are helpful for understanding population distribution and density and can assist governments in making informed decisions about resource allocation and planning. They are also an essential first step for determining an area's degree of urbanization.

First, you'll download the data for the tutorial. You'll also download and install a suite of open tools developed and used by the European Commission for standardized analysis of urbanization. Then, you'll run a tool to create a population grid for New Caledonia.

Download the data

The data for this tutorial is contained in an ArcGIS Pro project package.

1. Download the New_Caledonia_Degree_of_Urbanization project package.
2. Locate the downloaded file on your computer.

   Note:

   Depending on your web browser, you may have been prompted to choose the file's location before you began the download. Most browsers download to your computer's Downloads folder by default.

3. If you have ArcGIS Pro installed on your machine, double-click New_Caledonia_Degree_of_Urbanization.ppkx to open the project. If prompted, sign in using your licensed ArcGIS account.

   Note:

   If you don't have access to ArcGIS Pro or an ArcGIS organizational account, see options for software access.

   The project contains a map showing New Caledonia, a Pacific island territory under the jurisdiction of France. The map uses the Mollweide (world) equal area projection. It's essential to use an equal area projection for accurate area calculations during analysis.

   

   The project contains two data layers necessary for creating a population grid. Both layers are turned off by default.

4. In the Contents pane, check the box next to NC 2019 Population to turn it on.

   

   The layer appears on the map.

   

   This layer displays the 33 communes in New Caledonia. Communes are similar to townships or municipalities and are a suitable administrative unit for determining urbanization. The smallest available territorial units are the best choice to create a population grid.

5. In the Contents pane, right-click NC 2019 Population and choose Attribute Table.

   

   The layer's attribute table appears. It lists each commune and its population based on the 2019 census. Accurate population data is one of the essential inputs for creating a population grid.

   

6. Close the table. In the Contents pane, turn off NC 2019 Population and turn on GHS Built 2020 NC 100.tif.

   

   This layer is a built-up surface raster layer covering New Caledonia. It shows where there are built-up (generally, human-made) structures. Dark pixels are places without structures, while light pixels are places with structures.

   The greatest cluster of light pixels is in the southwest of the island, where New Caledonia's capital and most populous city, Nouméa, is located. Places with more people have more built-up surfaces, making a built-up surface raster a good indicator of population density and urbanization.

7. In the Contents pane, right-click GHS Built 2020 NC 100.tif and choose Properties.

   The Layer Properties window appears.

8. In the Layer Properties window, click the Source tab. Expand Raster Information.

   

   This section provides important information to know about the data. The Cell Size X and Cell Size Y are both 100. Additionally, in the Data Source section, the Vertical Units is Meter. This information means that the layer's resolution, or the size of each pixel, is 100 square meters. When performing analysis with raster layers, you should ensure you do not create output layers that have a smaller resolution than your input layer.

9. Close the Layer Properties pane. In the Contents pane, turn off GHS Built 2020 NC 100.tif.

   You've explored the two layers necessary for creating a population grid. Though the study area of this tutorial is New Caledonia, this workflow can be performed for any area as long as you have the following datasets:

   • A shapefile (typically a polygon shapefile, although a point shapefile can be used too) containing census data about population for the area of interest.
   • A built-up surface or volume raster corresponding to the same area.

   Note:

   You can download a free built-up surface raster for nearly any populated location in the world at the Global Human Settlement Layer (GHSL) download page. By combining this layer with census data for your area of interest, you can complete this workflow for any location in the world.

Download the tools

Next, you'll download and install the suite of free tools developed by the European Commission for applying the degree of urbanization method.

1. Go to the GHSL tools download page.

   This page contains download links for four degree of urbanization tools. You can download the tools separately or as a group. In this tutorial, you'll use three of the four tools, so you'll download the entire toolkit as a group.

   Note:

   It is recommended that you read through the end user license agreement linked on the page before downloading and using the tools.

2. In the GHS-DEGURBA Toolkit section, under Select the version and the type of installation and click download, for Version, choose ArcGIS. For Installation type, choose Online.
3. Click Download GHS_DEGURBA_Toolkit ArcGIS toolbox online.

   Note:

   The download is 333 MB and may take a few minutes.

4. Once the download completes, locate the downloaded file on your computer. Double-click GHS_DEGURBA_Toolkit_arcgis_toolbox_installer.

   A wizard appears to guide you through the installation process.

5. Follow the wizard's instructions. Make note of where the tools will be installed and perform the installation.

   Note:

   The installation may take several minutes.

6. When the installation is completed, click Finish.

   Next, you'll add the downloaded suite of tools to ArcGIS Pro.

7. In ArcGIS Pro, in the Catalog pane, right-click Toolboxes and choose Add Toolbox.

   

8. In the Add Toolbox window, browse to the location where you installed the tools and open the GHS DEGURBA Toolkit ArcGIS Toolbox folder. Open the application folder and select GHS_Tools.pyt.

   

9. Click OK. In the Catalog pane, expand Toolboxes.

   The toolbox is listed alongside the project's default toolbox.

10. Expand GHS_Tools.pyt.

    

    The toolbox contains four tools, three of which you'll use in this workflow (you won't use GHS Population Warp). The GHS Population To Grid tool (GHS-POP2G) is the one you'll use to create a population grid.

11. On the Quick Access Toolbar, click the Save Project button to save the project.

    

Run the population grid tool

You'll run the GHS Population To Grid tool to convert your polygon census data and built-up surface raster into a population grid. This grid will convey key information about the distribution of people across your study area.

When census data is organized based on territorial units, such as the communes of the NC 2019 Population layer, the GHS Population To Grid tool can combine the reported population with the geographic distribution of population informed by the built-up surface raster.

Note:

For the tools to run, you must have MATLAB Runtime 9.9 or later. You can download the latest version of MATLAB Runtime from the MATLAB Compiler. After installing the latest version, save the project and restart ArcGIS Pro before running the tool.

1. In the Catalog pane, under GHS_Tools.pyt, double-click GHS Population To Grid.

   The tool opens in the Geoprocessing pane. Like most geoprocessing tools, you'll set parameters to ensure the tool runs the way you want. First, you'll determine the output workspace, where output datasets will be saved.

2. For Output workspace, click the Browse button.

   

   You'll browse to the default project folder and use it as the output workspace.

3. In the Output workspace window, under Project, click Folders. Select New_Caledonia_Degree_of_Urbanization.

   

4. Click OK.
5. Confirm that Output projection is set to World_Mollweide and Output cell size is set to 1000.

   The default output projection is World_Mollweide, the same projection as the project. This projection is an equal area projection, making it ideal for any area-based calculations, so you'll leave it unchanged.

   The default output cell size is 1000. When you explored your built-up surface raster, you learned it had a cell size of 100 square meters. It's important that your output cell size is not smaller than the cell size of your input raster, because there is no way for the tool to add detail that isn't in the original dataset. Because 1000 is larger than 100, it's an appropriate cell size. You could change the cell size to be 100 to match the input layer, but it's not necessary. A cell size of 1000 square meters, or 1 square kilometer, meets international standards for population grids.

6. Confirm that Use population polygons is checked.

   Your input population layer, NC 2019 Population, is a polygon layer, so this option is appropriate.

   Note:

   If your population data used a point layer, you would check Use population points and uncheck Use population polygons. If running this workflow using your own data, be sure to check the option that is most appropriate.

   Next, you'll add the population polygon layer.

7. For Population (polygons) layer, click the Browse button.
8. In the Population (polygons) layer window, under Project, click Folders. Open New_Caledonia_Degree_of_Urbanization, commondata, and new_caledonia_degree_of_urbanization1.
9. Select NC_2019_Population.shp.

   

   Note:

   The input population layer must be a shapefile. If your population data is a file geodatabase feature class, you can convert it to a shapefile using the Feature Class To Shapefile geoprocessing tool.

10. Click OK.

    You'll set the field that contains population data. When you looked at the attribute table, there was only one population field.

11. For Population (polygons) count field, choose populati_1.

    For this tutorial, you won't set the Population (polygons) stepwise group field. This optional parameter can group census units based on larger administrative boundaries or other criteria. For instance, one of the fields in the population layer's attribute table showed the province of each commune. You could set that field for this parameter to group population by province. This parameter is useful for managing large datasets and optimizing computational efficiency.

12. For Built-up raster, choose GHS Built 2020 NC 100.tif.

    The Built-up MINIMUM value and Built-up MAXIMUM value values correspond to the minimum and maximum values in the built-up surface raster. You can confirm they are correct by comparing them to the minimum and maximum values for the built-up surface raster in the Contents pane.

13. If necessary, set Built-up MINIMUM value to 0 and Built-up MAXIMUM value to 9040.
14. Confirm that Multicore is checked.

    This parameter adjusts software settings for computational efficiency. All parameters have now been set.

    

15. Click Run.

    Note:

    If the tool fails, it's possible you do not have the latest version of MATLAB Runtime installed. You can download the latest version from the MATLAB Compiler. After installing the latest version, save the project and restart ArcGIS Pro before running the tool again. To quickly set the tool parameters after restarting, click the Analysis tab on the ribbon and click the History button. In the History pane, double-click GHS Population To Grid to reopen the tool with the same parameters as before.

    The tool runs. When it finishes, no output is added to the map. You'll add it yourself.

16. In the Catalog pane, expand Folders and expand New_Caledonia_Degree_of_Urbanization. Right-click New_Caledonia_Degree_of_Urbanization and choose Refresh.

    The folder refreshes, showing the new files you created using the tool.

17. Right-click GHS-POP2G_1000m.tif and choose Add To Current Map.

    

18. If the Calculate statistics for GHS-POP2G_1000m.tif window appears, click Yes.

    The population grid is added to the map.

    

Symbolize the population grid

By default, the population grid doesn't show much; only the area around Nouméa has any visible difference. You'll symbolize the population grid to better see the distribution of population.

1. In the Contents pane, right-click GHS-POP2G_1000m.tif and choose Symbology.

   

2. In the Symbology pane, confirm that Primary symbology is set to Stretch.
3. For Stretch type, choose Minimum Maximum.

   

4. Check Edit min/max values. Set the maximum value to 1500.

   

   Next, you'll add a mask to the data so that values of 0 are transparent. This way, only locations where people live will be displayed on the map.

5. In the lower part of the pane, click the Mask tab. Check Display background value and confirm 0 is set as the value.

   

   The map adjusts, displaying data only where people live.

   

6. Close the Symbology pane. On the map, zoom in to a populated location.

   

   Each pixel covers a square kilometer. Light-colored pixels have a higher population, while dark-colored pixels have a smaller population. Areas with no pixels have no people at all.

   In the example image, which is zoomed to the capital of Nouméa, there is a large cluster of white pixels, indicating high population density. This distribution makes sense for the island's most populous city. Outside the city, there are darker pixels, suggesting more rural areas. Most of the areas with no people are mountainous regions that can be difficult for human habitation.

7. Zoom back out to the full extent of the data.
8. Save the project.

Using census data and a built-up surface raster, you've created a population grid, which shows you the number of people who live within units of standard shape and size. Next, you'll use this population grid to determine degree of urbanization.

Create a degree of urbanization grid

You'll build on the population grid to create a degree of urbanization grid, also known as a geospatial settlement classification grid. Based on population density and size thresholds, a degree of urbanization grid classifies 1 square kilometer cells based on the type of settlement they are.

There are two levels of classification. The first level contains only three classes: urban center grid cells, urban cluster grid cells, and rural grid cells. The second level is more granular and contains eight classes: urban center grid cells, dense urban cluster grid cells, semi-dense urban cluster grid cells, suburban or peri-urban grid cells, rural cluster grid cells, low density rural grid cells, very low density rural grid cells, and water grid cells. You'll create grids at both classification levels and compare them.

Run the degree of urbanization grid tool

You'll run the GHS Degree of Urbanisation Grid tool (GHS-DUG) using your population grid and built-up surface raster as inputs. The tool will create output grids at both the first and second level of the degree of urbanization classification. It'll also create tables that contain statistics related to urbanization.

1. In the Catalog pane, expand Toolboxes and GHS_Tools.pyt. Double-click GHS Degree of Urbanisation Grid.

   

   The Geoprocessing pane appears with the tool parameters. First, you'll set the output workspace, like you did when creating the population grid.

2. For Output workspace, click the Browse button.
3. In the Output workspace window, under Project, click Folders. Select New_Caledonia_Degree_of_Urbanization and click OK.

   You'll set your population grid as the input population raster.

4. For Population raster, choose GHS-POP2G_1000m.tif.

   Note:

   For this tool, the input population raster must have a cell size of 1000m, or 1km. It must also be projected in an equal area projection.

   Next, you'll ensure the tool reduces urban center fragmentation using an optional parameter. Doing so causes the tool to include areas with a high concentration of buildings as urban even if the population is low. Some parts of urban areas lack residential housing, but include industrial buildings or other types of structures; these places should still be considered urban. The tool can account for these areas using the built-up surface raster.

5. Check Reduce Urban Centre fragmentation.

   The option to choose a built-up surface raster becomes available.

6. For Built-up raster, choose GHS Built 2020 NC 100.tif.

   Now, the tool will still consider cells that have a population under 1,500 but higher than average built-up surface.

   

   You can use a custom land layer as an additional input. A land layer is a continuous raster with values ranging from 0 for water to 100 for land. A default version of this layer is already available in the tool, but if you have a more specific or customized land layer tailored to your area of interest, you can use it instead by checking Use custom land layer and setting the subsequent Land raster parameter.

   By default, Create output for visualisation is checked. This parameter creates a settlement grid projected according to the specified authority code in the Visualisation output coordinate system authority code parameter. If necessary, you can adjust the code to create an output grid using a projection other than the default Mollweide (world) projection. This output is for visualization only and should not be used for further analysis; all input layers for the GHS-DEGURBA Toolkit tools should be projected in Mollweide.

7. Click Run.

   The tool runs and completes successfully.

Explore the tool outputs

As before, the output layers are not automatically added to the map, so you'll add them.

1. In the Catalog pane, under Folders, right-click New_Caledonia_Degree_of_Urbanization and choose Refresh.

   There are several output files; some are tables, some are shapefiles, and some are raster files.

   

   Many of the output files focus on a specific class, such as dense urban clusters, rural clusters, and so on. Among the files are GHS-DUG_GRID_L1.tif and GHS-DUG_GRID_L2.tif, which contain the degree of urbanization grid at both the first and second level of classification. (In the file names, degree of urbanization is shortened to DUG.) You'll investigate these files first.

2. Right-click GHS-DUG_GRID_L1.tif and choose Add To Current Map. If the Calculate statistics for GHS-DUG_GRID_L1.tif window appears, click Yes.

   

   Level 1 classification contains three classes:

   • Class 1 (Green): Rural areas
   • Class 2 (Orange): Towns and semi-dense areas
   • Class 3 (Red): Cities

   According to this classification, the majority of New Caledonian land surface is rural; the only urban center is the capital, Nouméa, which is surrounded by some urban cluster grid cells. This level of classification can be improved with more detail, so you'll look at the second level of classification.

3. In the Contents pane, right-click GHS-DUG_GRID_L1.tif and choose Remove.
4. In the Catalog pane, right-click GHS-DUG_GRID_L2.tif and choose Add To Current Map. If the Calculate statistics for GHS-DUG_GRID_L2.tif window appears, click Yes.

   

   Level 2 classification contains eight classes:

   • Class 10 (Blue): Water grid cells
   • Class 11 (Light Green): Very low-density rural grid cells
   • Class 12 (Green): Low-density rural grid cells
   • Class 13 (Dark Green): Rural cluster grid cells
   • Class 21 (Yellow): Suburban or peri-urban grid cells
   • Class 22 (Brown): Semi-dense urban cluster grid cells
   • Class 23 (Dark Brown): Dense urban cluster grid cells
   • Class 30 (Red): Urban center grid cells

   Note:

   The number for each class appears in the Contents pane.

   As before, Nouméa is the only area classified as an urban center. However, this level of classification indicates several smaller settlement classes throughout New Caledonia.

   You'll learn more about the statistical breakdown of each class by looking at the table that was created alongside the other tool outputs.

5. In the Catalog pane, right-click GHS-DUG_L2_stats.xls and choose Show In File Explorer.

   

   A file browser window appears, showing the location where your output files are saved.

6. If you have Microsoft Excel or another program that can read Microsoft Excel files, open GHS-DUG_L2_stats.xls.

   The spreadsheet shows the total population and area of each class. It also shows the population share, or the percentage of population in each class (expressed as a fraction).

   

   Note:

   Your table may contain different numbers.

   As expected, there is a population of 0 in the uninhabited water bodies, although they comprise the majority of total area. About 13.7 percent of the population lives in very low-density rural grid cells, which also constitute a large amount of area compared to the other populated places. Despite urban center grid cells covering only 56 square kilometers, nearly 28 percent of the total population lives in them—a larger population share than any other class.

7. Close the spreadsheet. In ArcGIS Pro, save the project.

You've used your population grid to create a degree of urbanization grid, allowing you to understand the different classes of settlement in New Caledonia. Next, you'll use the degree of urbanization grid to classify the administrative units of New Caledonia by settlement type.

Classify administrative units

Now that you've created a degree of urbanization grid, you'll classify territorial units. Your starting population data, NC 2019 Population, contains the boundaries for New Caledonia's communes. Using this dataset, you'll create a map that shows the predominant settlement type of each commune. The classification will combine the geography of the commune with the population grid and degree of urbanization grid to determine the type of settlement in which most people in each commune live.

Run the territorial unit classifier

You'll run the GHS Degree of Urbanisation - Territorial Unit Classifier (GHS-DU-TUC) tool using the census data, population grid, and degree of urbanization grid as inputs. This tool can be run using any territorial unit you have data for, whether they're census, administrative, or statistical regions.

1. In the Catalog pane, under GHS_Tools.pyt, double-click GHS Degree of Urbanisation - Territorial Unit Classifier.

   

   The Geoprocessing pane appears with the tool parameters. First, you'll set the output workspace.

2. For Output workspace, click the Browse button.
3. In the Output workspace window, under Project, click Folders. Select New_Caledonia_Degree_of_Urbanization and click OK.

   Next, you'll choose the dataset that contains the territorial units you want to classify. In this case, that dataset is NC 2019 Population.

4. For Territorial Units, click the Browse button.
5. In the Territorial Units window, under Project, click Folders. Double-click New_Caledonia_Degree_of_Urbanization, commondata, and new_caledonia_degree_of_urbanization1.
6. Select NC_2019_Population.shp and click OK.

   The Territorial stepwise group field is optional and can be used to group units into clusters to facilitate computations. For instance, your commune data has a field for provinces; that field could be used to classify provinces. For this workflow, you're only interested in classifying communes, so you'll leave the field unchanged.

   Territorial classification is done by determining the settlement type in which the majority of the population lives for each territorial unit. By default, the tool can estimate the total population of each territorial unit with the population grid. For more accurate results, you can choose the field that contains the population of each territorial unit. In your NC 2019 Population data, the populati_1 field contains the population of each commune.

7. For Territorial population count field, choose populati_1.

   The Territorial cross tabulation field is optional and enables the tool to compare a settlement classification field in the original dataset (for example, a national urban and rural classification) with the settlement classification in the degree of urbanization grid. For instance, if there had already been a field in the NC 2019 Population dataset that designated communes as rural or urban, that field could be used for cross tabulation. No such field exists, so you'll leave this parameter unchanged.

   Lastly, you'll add the input population raster and degree of urbanization raster.

8. For Population raster, choose GHS-POP2G_1000m.tif. For Degree of Urbanisation raster, choose GHS-DUG_GRID_L2.tif.

   Note:

   If you wanted, you could run the territorial unit classifier using the level 1 classification instead.

   

9. Click Run.

   The tool runs and completes successfully.

Visualize the results

As before, the output layers are not automatically added to the map, so you'll add them.

1. In the Catalog pane, under Folders, right-click New_Caledonia_Degree_of_Urbanization and choose Refresh.

   Several new files appear in the folder. These include two tables with statistics about the classification, four layer files with classification symbology, and a shapefile including the classification itself.

   

2. Right-click NC_2019_Population_GHS-DU-TUC.shp and choose Add To Current Map.

   The layer shows the communes of New Caledonia. Currently, they aren't symbolized, so you can't see the classifications. You'll apply symbology using the layer files that the tool created.

3. In the Contents pane, confirm that NC_2019_Population_GHS-DU-TUC is selected.

   

4. On the ribbon, click the Feature Layer tab. In the Drawing group, click Import.

   

5. In the Import Symbology window, for Symbology Layer, click the Browse button.
6. In the Symbology Layer window, under Project, click Folders. Double-click New_Caledonia_Degree_of_Urbanization.
7. Select GHS-DU-TUC-L2.lyr and click OK.
8. Click OK.

   Each commune is symbolized by its degree of urbanization classification.

   

   In New Caledonia, the only city is the capital, Nouméa. However, there are some other communes where most of the population lives in villages, and one where the population primarily lives in dense towns. Most of the other communes are dispersed rural areas.

   You'll also explore the classification statistics contained in the tables the tool created.

9. In the Catalog pane, right-click NC_2019_Population_GHS-DU-TUC.xlsx and choose Show In File Explorer.
10. In your file explorer, if you have Microsoft Excel or software that can read Excel spreadsheets, open NC_2019_Population_GHS-DU-TUC.xlsx.

    This file shows the population and population share within each type of settlement class for each commune. This data was used to determine the degree of urbanization classification for each commune.

11. Close the spreadsheet. In your file explorer, open NC_2019_Population_GHS-DU-TUC_statistics.xlsx.

    

    These summary statistics break down the total population and the percent of population within each settlement class, both at level 1 classification and level 2 classification.

12. Close the spreadsheet. In ArcGIS Pro, save the project.

In this tutorial, you classified New Caledonia by its degree of urbanization. Degree of urbanization is a framework that standardizes the classification of settlements based on population density and built-up surfaces. By using this classification method, you generated insightful urbanization statistics for the territory and its territorial units.

This workflow can be applied to any population location in the world, at both regional and global levels. Through the analysis of global data, scientists have observed that nearly half of the world's population lives in cities. When towns and semi-dense areas are included, that figure rises to about 76 percent.

The degree of urbanization method is a valuable tool for monitoring and reporting progress toward Sustainable Development Goals. Urbanization directly affects access to amenities, opportunities, goods, and services that enhance human well-being, while also adding challenges such as increased air pollution and crime rates. Using the standardized classification scheme of degree of urbanization, you can compare urbanization in different regions and identify areas requiring critical services based on their population density.

You can find more tutorials in the tutorial gallery.

Acknowledgements

• The population data is shared under the Licence Ouverte 2.0, which allows for reproduction and modification for commercial or noncommercial purposes as long as attribution is given to the original source and its last modified date (April 7, 2020).
• The commune boundary data is shared under the Open Data Commons Open Database License (ODbL), which allows for the creation of derivative products for commercial or noncommercial purposes as long as the original license is included.
• The built-up surface raster is shared under CC BY 4.0. Pesaresi, Martino; Politis, Panagiotis (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) [Dataset] doi: 10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA PID: https://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea
• Global Human Settlement Layer (GHSL) tools © European Union, image from GHSL tools suite available at GHSL tools. Images of the tools displayed with permission.
• World Topographic Map sources: Esri, HERE, Garmin, FAO, NOAA, USGS, OpenStreetMap contributors, and the GIS User Community