Add multidimensional data to your map
In this lesson, you will use multidimensional sea surface temperature data to identify coral reefs that may experience bleaching events. Multidimensional datasets allow you to investigate how a variable changes through time or space. Today, you will investigate changes in sea surface temperature through time.
- Go to Sample NetCDF data for Multidimensional Analysis.
- Click Download.
Depending on your web browser, you may be prompted to choose a file location before you begin the download. Most browsers download to your computer's Downloads folder by default.
- Extract the contents of the MultidimensionalAnalysis_SampleDataset.zip file to a location of your choice (for example, C:\CoralBleaching).
The data packaged for this lesson comes from the NCAR Research Data Archive. It is a netCDF file included in the Climate Forecast System Reanalysis (CFSR) product and contains 35 years of monthly sea surface temperature data with a spatial resolution of 0.5 degrees.
- Open ArcGIS Pro. (Ensure that you have ArcGIS Pro 2.5 or later installed on your computer.)
If you don't have ArcGIS Pro or an ArcGIS account, you can sign up for an ArcGIS free trial.
When ArcGIS Pro opens, it contains a list of blank project templates under the New heading. If you have created a project before, it will include a list of recent projects under the Open heading.
- Under New, click Map.
The Map template can be used to create a project containing a 2D map with the Topographic basemap included.
- In the Create a New Project window, for Name, type CoralBleaching.
- Ensure that Create a new folder for this project is checked, then click OK.
Click and hold the left mouse button to drag and pan the map. Hold the right mouse button to zoom in and out or use the mouse scroll wheel. To rotate the view in the map, hold the V key and use the mouse to alter direction.
Since you will be working with sea surface temperature data and not with land-based data, it is appropriate to update the basemap.
- On the ribbon, in the Map tab, in the Layer group, click the Basemap button, then select Light Gray Canvas.
The source data used in this lesson is in a multidimensional Network Common Data Form (netCDF). The netCDF format is commonly used to store and manage multidimensional scientific data such as sea surface temperature.
You will add the sea surface temperature data to your map as a multidimensional raster. Multidimensional rasters can be added using the Add Multidimensional Raster Layer tool.
- On the ribbon, on the Map tab, in the Layer group, click the Add Data drop-down menu, then select Multidimensional Raster Layer.
- In the Add Multidimensional Raster Layers pane, for Output Configuration, use the drop-down menu and select Multidimensional Raster.
- In the Add Multidimensional Raster Layers pane, for Input File, Mosaic Dataset or Image Service, use the drop-down menu and select Import Variables From File.
- In the Import variables from NetCDF, GRIB or HDF files pane, browse, locate, and select the CFSR_sst.nc netCDF file, then click OK.
Once you have specified the multidimensional raster for analysis, you can select variables to include. In this case, the source data contains only a sea surface temperature (cfsrsst) variable.
- For Select Variables, check the cfsrsst check box, then click OK.
The Sea Surface Temperature data contained in the netCDF file is displayed on the map with temperature displayed in degrees Kelvin.
- On the ribbon, on the Map tab, in the Navigate group, click the full extent button to recenter the map.
The current projection applied to the map does not allow for suitable comparison of size between regions. Before continuing with analysis, it is appropriate to update the projection to an equal area projection that will better represent the relative size of areas where coral bleaching events may occur.
- In the Contents pane, right-click Map, then select Properties.
The Map Properties pane appears.
- In the Map Properties pane, click Coordinate Systems.
- In the Search window, type Behrmann.
- Expand Projected Coordinate System, then expand World and select Behrmann (world).
- Click OK to update and apply the Behrmann (world) equal area projection.
With an equal area projection, you can compare the relative size of regions identified in your analyses.
The CFSR_sst.nc layer in the Contents pane represents sea surface temperature in degrees Kelvin. It would be helpful to update the layer properties to reflect this information.
- If necessary, expand the CFSR_sst.nc layer.
- Click and select Value, then click Value again to enable editing.
- For Value, type Sea Surface Temperature (degrees Kelvin), then press Enter.
The layer properties are updated and you are ready to continue with your analysis.
- Save the project.
Visualize multidimensional data
The next step in your coral reef analysis is to investigate your data. Multidimensional data contains several layers of information stacked on top of each other into a cube. The stacked layers can represent data from different depths or height, or as in this example, time.
The sea surface temperature dataset used in this lesson consists of monthly temperature observations from 1980 to 2015, in which each month can effectively be seen as its own layer. To view the monthly time slices of your dataset, you will use the tools in the Multidimensional tab.
- In the Contents pane, click CFSR_sst.nc to select the layer.
The Multidimensional ribbon and tools are only active when a multidimensional layer is selected.
The Multidimensional tab on the ribbon updates to display the Raster Layer tab grouping the Appearance, Data, and Multidimensional tabs.
- On the ribbon, click and activate the Multidimensional tab and review the data exploration, analysis, and data management tools.
In addition, the tab contains various data exploration, analysis, and data management tools.
- In the Current Display Slice group, verify that Variable is set to cfsrsst.
- On the ribbon, click the Multidimensional tab, in the Current Display Slice group, click the StdTime drop-down menu and review the monthly time slices represented in the CFSR_sst.nc layer.
Time is formatted as year, month, and day.
Time slices represent monthly sea surface temperature observations, and individual time slices can be displayed by selecting them in the drop-down menu; in addition, they can be viewed sequentially as an animation.
- In the Current Display Slice group, locate and click the Play button to the right of the StdTime drop-down menu.
The Play button is both the start and stop; click once to start, click a second time to stop.
The display sequentially steps through the time slices of the dataset and updates the layer in the map, thereby animating monthly observations.
Next, you will use the multidimensional trend analysis tools to predict sea surface temperature changes through time and space.
Generate trends and forecast sea surface temperature
Generate a temporal profile
The ArcGIS Pro multidimensional geoprocessing tools simplify working with multidimensional data and make processing and exploration quick and straightforward. Next, you will use the multidimensional geoprocessing tools to investigate your data and run a trend analysis.
- In the Map, in the Contents pane, ensure that CFSR_sst.nc_cfsrsst is selected.
The original layer name in the Contents pane reflects the variable selected to represent the Multidimensional extent.
One way to review and explore multidimensional data is with a temporal profile chart. Using the CFSR_sst.nc_cfsrsst layer, the temporal profile chart will display a graph with time on the x-axis, and the sea surface temperature on the y-axis.
- On the ribbon, on the Multidimensional tab, in the Analysis group, click Temporal Profile .
A new chart is generated and the Chart and Chart Properties panes appear.
- Reposition and dock the Chart pane below the map and the Chart Properties pane to the right of the map.
The temporal profile chart allows you to define an area of interest using points, lines, or polygons. The chart will then plot values through time for the area of interest only.
- In the Chart Properties pane, click and select the Point area of interest tool.
- On the map, with the point tool active, click a location within the area of interest you have identified. You may want to consider a location with high coral diversity situated between Australia and Indonesia.
Your location and temporal profile may differ based on the area of interest identified.
The Change in cfsrsst over StdTime temporal profile updates to display monthly sea surface temperatures from 1980 to 2015 for the location selected. In the chart, observe the cyclical pattern and variation in the monthly temporal profile, reflecting the seasonal variation in sea surface temperatures at the location.
In the chart, you can modify the binning interval (how the data is grouped together and averaged) to observe longer average temperature fluctuations such as yearly.
- In the Chart Properties pane, for Time binning options and Interval size, click the calendar button and update the interval to 1 years.
The chart updates to display yearly sea surface temperature variations as a result of the change in binning interval.
By observing and exploring the temporal profile, you have a sense of the sea surface temperature variations in the data. Using additional multidimensional tools, you can begin to analyze the trends that exist in the data, which, in turn, will be helpful in predicting which locations will experience warming. Using these predicted sea surface temperatures, you will be able to complete a statistical analysis that will allow you to identify regions at risk of coral bleaching.
- Close the Chart and Chart Properties panes after exploring various locations on the map and modifying the binning interval.
Closing the chart does not remove it from the project; it is accessible as an item in the Contents pane.
- Save the project.
Calculate trends and predict sea surface temperature
Using historical sea surface temperature data and analyzing trends helps identify areas where steady and marked warming or cooling patterns are currently observed. These trends can then be used to predict ocean temperature changes, thus allowing you to identify additional locations that will be affected. Since coral reefs with rich biodiversity are highly concentrated in the region around Australia and Indonesia, you will limit analysis to this area.
- On the ribbon, on the Map tab, in the Navigate group, click the Go To XY button.
Using the Go To XY navigation pane, in the lower left of the map, you can center the map by entering a Long and Lat value.
- In the Go To XY navigation pane, enter the following coordinates to identify your study area and center the map:
- For Long, type 127 E.
- For Lat, type 10 S.
- Press Enter.
Coordinates may also be entered as Long: 127 and Lat: -10.
- In the map, for Scale, type 42500000 and press Enter to zoom in on the study area.
The map changes scales and displays the analysis region. Be sure not to modify the current map extent.
The current map extent represents the region where you will focus your analysis. This region represents a critical part of the local and global coral ecosystems and is severely threatened by coral bleaching.
It does not make sense to try to explore a smaller region or a specific reef, as the spatial resolution of the source data is 0.5 degrees, which means that each pixel represents an area of about 55 square kilometers or 34 square miles.
- On the ribbon, on the Multidimensional tab, in the Analysis group, click Trend.
In the Generate Trend Raster pane, identify the Parameters and Environment tabs.
- In the Generate Trend Raster pane, on the Parameters tab, do the following:
- For Input Multidimensional Raster, select CFSR_sst.nc_cfsrsst.
- For Output Multidimensional Raster, type CFSR_sst_GenerateTrend.crf.
- For Dimension, select StdTime.
- For Variables, select cfsrsst.
- For Trend Line Type, select Harmonic.
- For Frequency/Polynomial Order, type 1.
- Ensure that Ignore NoData remains checked.
The Generate Trend Raster tool creates the Output Multidimensional Raster in the Cloud Raster Format (.crf). The .crf format is optimized for cloud-based processing and analytics and can also be displayed and processed in ArcGIS Pro.
- In the Generate Trend Raster pane, click the Environments tab.
Because this dataset is quite large and processing may take several minutes, you will apply a processing extent to limit the analysis to the region around Australia and Indonesia. Due to the spatial resolution of the data, it does not make sense to identify a smaller region.
Updating environment settings in a geoprocessing tool overrides the default analysis and output settings associated with the project.
- On the Environments tab, for Processing Extent, click the Extent drop-down menu and select Current Display Extent.
The analysis processing extent min and max values update to those of the current map extent.
- In the Generate Trend Raster tool, click Run.
Depending on the processing speed of your computer, the tool may take several minutes to execute.
The Generate Trend Raster tool processes the input CFSR_sst.nc_cfsrsst netCDFfile and creates the output CFSR_sst_GenerateTrend.crf Cloud Raster Format file, which is then added as a layer to the map.
- In the Contents pane, uncheck CFSR_sst.nc_cfsrsst to turn it off.
The map displays the sea surface temperature trend layer (CFSR_sst_GenerateTrend.crf ).
- In the map, explore the CFSR_sst_GenerateTrend.crf layer.
Purple regions are areas that are getting warmer. Green areas are getting colder. As you can see, most of the area within your map is getting warmer over time. You can now use this trend analysis result to predict sea surface temperatures.
- On the ribbon, on the Multidimensional tab, in the Analysis group, click Predict.
The Predict Using Trend Raster tool opens.
The Predict Using Trend Raster tool uses the trend result to generate a new multidimensional dataset that predicts weekly sea surface temperatures, in this case, until January 1, 2022.
- In the Predict Using Trend Raster pane, do the following:
- For Input Multidimensional Raster, select CFSR_sst_GenerateTrend.crf.
- For Output Multidimensional Raster, type CFSR_sst_Predict.crf.
- For Variables, select cfsrsst.
- For Dimension Definition, select By interval.
- For Start, type 2011-01-01T00:00:00.
- For End, type 2022-01-01T00:00:00.
- For Value Interval, type 1.
- For Unit, select Weeks.
- Click Run.
The Predict Using Trend Raster tool executes and adds a predicted sea surface temperature trend layer to the map.
The CFSR_sst_Predict.crf layer is added to the map, but may not initially display. Consider refreshing the map and unchecking the Layer Cache in the CFSR_sst_Predict.crf layer properties.
- In the Contents pane, uncheck the CFSR_sst_GenerateTrend.crf layer to turn it off.
- In the map, investigate and explore the CFSR_sst_Predict.crf layer.
The layer displays weekly predicted sea surface temperatures from January 2011 through December 2021.
- On the ribbon, click the Multidimensional tab, in the Current Display Slice group, click the StdTime drop-down menu to review the time slices available in the CFSR_sst_Predict.crf layer.
The current predicted sea surface temperature map is not as useful for answering questions about where coral bleaching events are likely to occur. However, you can use the predicted weekly temperatures and additional multidimensional geoprocessing tools to identify anomalies and pinpoint areas most likely to experience bleaching events.
- In the map, investigate and explore the CFSR_sst_Predict.crf layer and various time slices.
- Save the project.
Predict where coral bleaching events will occur
Coral bleaching events occur when reefs are exposed to elevated water temperatures for long periods of time. Now that you have used trend analysis to create your predicted sea surface temperatures for the time ending in 2021, you can analyze the prediction data to find locations where water temperatures remain warm for extended periods of time.
- On the ribbon, on the Multidimensional tab, in the Analysis group, click Anomaly.
The Generate Multidimensional Anomaly tool opens.
- In the Generate Multidimensional Anomaly pane, do the following:
- For Input Multidimensional Raster, select CFSR_sst_Predict.crf.
- For Output Multidimensional Raster, type CFSR_sst_Predict_GenerateAnom.crf.
- For Variables, select cfsrsst.
- For Anomaly Calculation Method, select Difference From Mean.
- For Mean Calculation Interval, select Recurring weekly.
- Ensure that Ignore NoData is checked.
- Click Run.
The Generate Multidimensional Anomaly tool executes and adds the CFSR_sst_GenerateAnom.crf layer to the map. The layer identifies anomalies by comparing the monthly average water temperature at each location to the overall average sea surface temperature.
- In the Contents pane, uncheck the CFSR_sst_Predict.crf layer to turn it off.
- In the map, investigate and explore the CFSR_sst_GenerateAnom.crf layer.
In the CFSR_sst_GenerateAnom.crf dataset, each layer represents one month, from January 2011 through December 2021.
Areas in blue have temperatures below the average, while areas in yellow and red have temperatures above the average.
Next, you will explore the time steps that are included in your anomaly dataset. You can now use this anomaly data to determine which locations are likely to experience coral bleaching events through January 2022.
- Click the StdTime drop-down menu and review several time slices for the CFSR_sst_GenerateAnom.crf layer.
To determine where and when certain conditions occur, for example, maximum temperature, you can use the Find Argument Statistics tool.
- On the Multidimensional tab, in the Analysis group, click the down arrow on the tool gallery, then locate and click Find Argument Statistics.
Since coral bleaching events occur when sea surface temperatures are high for long periods of time, you will use the Find Argument Statistics tool to search the predicted sea surface temperature data for times when the sea surface temperature is warm (between 0.1 and 5 degrees above the mean).
The Find Argument Statistics pane appears
- In the Find Argument Statistics pane, do the following:
- For Input Multidimensional of Multiband Raster, select CFSR_sst_Predict_GenerateAnom.crf.
- For Dimension, select StdTime.
- For Variables, select cfsrsst_diff_anomaly.
- For Output Raster, type CFSR_sst_ArgStatistics.crf.
- For Statistics Type, select Duration.
- For Dimension Definition, select Interval Keyword.
- For Keyword Interval, select Yearly.
- For Minimum Value, type 0.1.
- For Maximum Value, type 5.
- Ensure that Ignore NoData is checked.
By setting the Statistics Type to Duration, the Find Argument Statistics tool will report the number of consecutive weeks when the sea surface temperature is elevated for each location, a condition that results in coral bleaching.
- Click Run.
The tool executes and an anomaly layer is added to the map. The layer shows the number of weeks in each year that a location is subjected to sea surface temperatures above the mean.
Use ArcGIS Notebooks for multidimensional geoprocessing: In this lesson, you used the multidimensional geoprocessing tools in ArcGIS Pro to analyze sea surface temperatures and predict coral bleaching events. You can use the same steps and analysis using ArcGIS Notebooks and Python code. For an example of the same analysis using ArcGIS Notebooks, see the Use raster analytics and the Python API to monitor coral bleaching blog article.
- In the Contents pane, uncheck the CFSR_sst_GenerateAnom.crf layer to turn it off.
You are now displaying the argument statistics layer.
- Review time slices for the CFSR_sst_ArgStatistics.crf layer.
- In the map, investigate and explore specific areas in the CFSR_sst_ArgStatistics.crf layer.
In addition, select and display various time slices to gain more insight into which locations are likely to experience coral bleaching.
Light blues through reds represent areas that experience prolonged periods of warming. Regions with longer periods of elevated water temperatures are more likely to experience bleaching events in which the coral reefs die.
- On the Multidimensional tab, in the Current Display Slice group, click the Play button to the right of the StdTime drop-down menu.
The display steps through the time slices of the CFSR_sst_ArgStatistics.crf layer as an animation.
Observe the changes over time as the animation displays time slices.
To stop the animation, click the Play button.
- Save the project.
In this lesson, you predicted coral bleaching events using historical sea surface temperature data and multidimensional data geoprocessing tools. Analyzing your historical sea surface temperature data with the Generate Trend Raster tool allows you to detect changes in the average water temperatures at each location through time. The results from the trend raster then allow you to predict of sea surface temperatures using the Predict Using Trend Raster tool. Anomalously warm water temperatures can be identified with the Generate Multidimensional Anomaly tool, and the duration of those warm periods quantified using the Find Argument Statistics tool. By identifying areas that will experience prolonged periods of warm water temperatures, you can identify locations that are likely to experience coral bleaching events, a phenomenon that causes severe environmental and ecological damage.
To create an alert map for coral reef stations: Build a map to help identify, prioritize, and manage coral reefs. Use the Living Atlas NOAA Coral Reef Watch (CRW) Virtual Stations feature layer and the Zonal Statistics tool (also located on the Multidimensional tab) to identify the number of weeks each reef location is expected to experience elevated water temperatures. This result can be published and shared with protection and management teams using an ArcGIS Operations Dashboard. For an example, see Coral Reefs at Risk of Bleaching.
Multidimensional data is often used in ocean and climate studies. In addition to identifying locations where coral bleaching is likely to occur, similar tools and processes can be used when investigating trends in temperature, precipitation, and ocean salinity. The multidimensional geoprocessing tools used in this lesson can help provide answers to many important questions in the world today. For more ideas, review the following topics: