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Analysis Tool

Software

Licensing

Required Extension

Ouput

Aggregate Multidimensional Raster

ArcPro 2.5

Basic/Standard/Advanced

Image or Spatial Analyst

CRF

Find Argument Statistics

ArcPro 2.5

Basic/Standard/Advanced

Image Analyst

CRF

Generate Multidimensional Anomaly

ArcPro 2.5

Basic/Standard/Advanced

Image or Spatial Analyst

CRF

Generate Trend Raster

ArcPro 2.5

Basic/Standard/Advanced

Image Analyst

CRF

Predict Using Trend Raster

ArcPro 2.5

Basic/Standard/Advanced

Image Analyst

CRF

Build Multidimensional Info

ArcPro 2.5

Standard/Advanced

None

Mosaic

Build Multidimensional Transpose

ArcPro 2.5

Basic/Standard/Advanced

None

CRF

Make Multidimensional Raster Layer

ArcPro 2.5

Basic/Standard/Advanced

None

CRF

Make oPeNDAP OPeNDAP Raster Layer

ArcPro 2.5

Basic/Standard/Advanced

None

Raster

Select by Dimension

ArcPro 2.5

Basic/Standard/Advanced

None

Raster

Subset Mutidimensional Raster

ArcPro 2.5

Basic/Standard/Advanced

None

Raster

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  • Cloud Raster Format is optimized for writing and reading files and accesses large chunks of data from a large volume of raster data. CRF allows for storing multidimensional datacubes  which contain muiltiple multiple dimensions and many variables in a single efficient data structure.
  • Local Raster Functions are supported with multidimensional raster data. For example, a user can combine temperature data CRF with your relative humidity CRF to create a multidimensional heat index layer by using the heat index raster function. There are over a 100 available raster functions available.
  • Image Analyst is requred required to create the input CRF file via Generate Trend Raster. Prediction using Trend would be very beneficial to NASA sciences for predicting variables of interest at a specific location and future time.
  • Tools need to be used in certain order for you to be able to get to the end result which may be learning curve for ordinary user. Use of ArcGIS Notebooks could streamline the workflows for users to run their analysis and focus on the outputs for their research.
  • Both the ‘Build Multidimensional’ tool and ‘Build Multidimensional Transpose’ tool are easy to use for creating and accessing large scientific multidimensional datasets in a crf format and for slicing along scpecifc specifc dimensions resulting in optimized performance.
  • Scripting for multidimensional raster analysis is now available through arcpy API.
  • Map Algebra can be used with multidimensional data for calculating new ouputs outputs as derivitives deritives of initial variable of interest.
  • Temporal Profile feature allows for quick visualization of multidimensional data as various graphs and charts over time, at specific locations, and different variables of interest, which can be used for comparison and or investigating other variables that influence each other.

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Pros

Cons

Cloud Raster Format is optimized for writing and reading  files and accesses large chunks of data from a large volume of raster data. CRF allows for storing multidimensional datacubes  data cubes  which contain muiltiple multiple dimensions and many variables in a single efficient data structure.

Image Analyst is requred required to create the input CRF file via Generate Trend Raster. Prediction using Trend would be very beneficial to NASA sciences for predicting variables of interest at a specific location and future time.

Local Raster Functions are supported with multidimensional raster data. For example, a user can combine temperature data CRF with your relative humidity CRF to create a multidimensional heat index layer by using the heat index raster function. There are over a 100 available raster functions available.

Tools need to be used in certain order for you to be able to get to the end result which may be learning curve for ordinary user. Use of ArcGIS Notebooks could streamline the workflows for users to run their analysis and focus on the outputs for their research.

Both the ‘Build Multidimensional’ tool and ‘Build Multidimensional Transpose’ tool are easy to use for creating and accessing large scientific multidimensional datasets in a crf CRF format and for slicing along scpecifc specific dimensions resulting in optimized performance.

Temporal Profile feature allows for quick visualization of multidimensional data as various graphs and charts over time, at specific locations, and different variables of interest, however limited on varierty variety of different charts.  

 

Scripting for multidimensional raster analysis is now available through arcpy API.

 

Map Algebra can be used with multidimensional data for calculating new ouputs outputs as derivitives derivatives of initial variable of interest.

 

 

 

 

 

 

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