Multidimensional Raster Predictive Model

Zach Torres
Zach Torres

October 17, 2022

Multidimensional Raster Predictive Model

This project utilized multidimensional data to assess change across various times in sea surface temperatures. I used the dataset to analyze historical trends and predict future outcomes.

My workflow is described below:

  1. Add data with the Multidimensional Raster Layer dialog
  2. Configure the raster layer to view different slices of the data
  3. Analyze changes over time with a Temporal Profile Chart in the Multidimensional tab.
  4. Use trend line in the chart
  5. Use the Generate Trend Raster tool to create an estimated temperature trend for each pixel over the entire time series.
  6. Set the trend type to Harmonic to account for seasonal changes.
  7. Use the output of the previous tool in the Predict Using Trend Raster tool to predict future values based on the trend raster.
  8. Calculate anomalies with the Generate Multidimensional Anomaly tool to find spatial regions with the greatest difference from the mean surface temperature.
  9. Run the Find Argument Statistics tool to measure duration of exposure to specified temperature thresholds.
  10. Classify symbology of the output layer to two classes and adjust display slices to reveal differences across time in sea surface temperatures that cause coral reef bleaching.

Data provided by Esri.

Tools used

ArcGIS ProCharts

Plug-ins used

Find Argument StatisticsGenerate Multidimensional AnomalyGenerate Trend RasterPredict Using Trend Raster


Anomaly ModelingChartsPrediction ModelingTrend Modeling

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