ArcGIS Pro

Create Image Cubes from STAC-Enabled Datasets using ArcGIS

When conducting analysis using imagery over a large area and an extended period, the initial step always involves aggregating the data into either an image composite or an image cube with a specified time interval. The support of STAC in ArcGIS Pro 3.2 facilitates working with various STAC-compliant datasets in the cloud, such as the open datasets in AWS or Microsoft Planetary Computer. To optimize the process, you can create a virtual machine in the cloud close to these datasets for direct access and process. If you plan to use data on the Microsoft Planetary Computer, refer to the AMPC solution. This blog guides you through the end-to-end process of creating cloud-free image cubes from STAC-enabled open datasets in the cloud. If you already have the data on your machine, you can skip the first two steps and start from step 3.

Step 1: Create a STAC connection file

Use the STAC Connection wizard to create the STAC connection file by providing the STAC API and the cloud store connections to the datasets within the STAC collection. In this blog, this STAC API was used to access USGS’s Landsat Collection 2 datasets in AWS, as illustrated below:

STAC connection wizard

Notes:

Step 2: Search STAC items

Launch the Search STAC item pane from STAC connection file. Here you can define your search criteria including time, extent, and attribute. In this example we set a time range from 5/15/2022 to 10/15/2022, defined an extent using Oregon state boundary, and applied attribute filter for cloud cover less than 30%. For the details on using STAC in ArcGIS Pro, you can refer to this blog.

Search dialog

Step 3: create a mosaic dataset

To generate a mosaic dataset from the search result, choose the “Add Mosaic Dataset” option, which activates the “Add Raster to Mosaic Dataset” tool. The search result is automatically configured as the input for the tool. Next, select the Landsat 8 raster type and a Multiband template containing the surface reflectance bands along with a QA band. Repeat the same process for Landsat 9 images.

Create mosaic dataset dialog

We now have a mosaic dataset containing 229 scenes.

mosaic dataset footprints

Notes:

If you want to aggregate the images per year to create a multidimensional raster, run the Build Multidimensional Info tool to construct multidimensional information for the mosaic dataset. In this example, the “AcquisitionDate” field was employed as the time dimension, and the “Tag” field was designated for the variable name.

Build mdinfo tool

Step 4: Define processing templates

Creating a cloud-free image cube from the mosaic dataset involves several processes, all of which can be defined using raster functions:

QA mask function chain
The function chain

Save this function as a function template for use in the next step.

Step 5: Generate the image cube

Use Generate Raster From Raster Function tool to apply the aforementioned processing template to the mosaic dataset. Since the input and function parameters are defined in the processing template, no additional parameters are required other than specifying the input processing template and output CRF. Check the “Process as Multidimensional” option if creating a multidimensional raster.

Generate the cube

Below is the cloud free image cube created from Landsat Collection 2 data in AWS.

Landsat image composite

We completed the entire workflow without using a single line of code. However, if you prefer Python-based approach, you can refer to the code provided in this blog.

Check out this blog to see how the resulted image composite gets used in the aboveground biomass prediction.

About the author

Hong is a Principal Software Product Engineer on Esri's raster team, where she has been working since 1999. She has played key roles in the development and leadership of various software products related to imagery and data science throughout her tenure. Currently, her areas of focus include time-series image analysis, multidimensional raster, and altimetry data.

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