In this data recipe, learn how to create a time-enabled multidimensional mosaic dataset using GeoTIFF/Cloud Optimized GeoTIFF (COG) files in the GIS desktop program ArcGIS Pro. It also guides users through the process of combing multiple GeoTIFF files into a mosaic, and covers how to perform data prep, add data to the mosaic, build multidimensional info, and set mosaic properties. Mosaic datasets can be used in data analysis and visualizations.

The data used in this recipe comes from NASA’s ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). If you’d like to follow along, you can download these data by clicking the following links: data download link 1, data download link 2, and data download link 3. 

If you’d like to watch a video tutorial for this content, you can find it at NASA Earthdata’s YouTube channel. 

Note: An Earthdata Login account is needed to download these data. View this tutorial to learn how to create an account. 

Step 1: Create a File Geodatabase

1. Open ArcGIS Pro and create or open a project.
2. In the Catalog Pane, right-click on a folder where you want to store your geodatabase.
3. Select New > File Geodatabase.
4. Name your geodatabase (e.g., ecostress.gdb). 

Step 2: Create the Mosaic Dataset

1. In the Catalog Pane, right-click your new geodatabase.
2. Select New > Mosaic Dataset.
3. In the Create Mosaic Dataset tool:
   1. Enter a Name (e.g., LST).
   2. Choose an appropriate Coordinate System (e.g., WGS 1984 or your dataset’s projection).
4. Click Run. 

Step 4: Add and Populate the StdTime Field 

1. In the Contents Pane, right-click your mosaic dataset and select Open Table.
2. In the attribute table, click the Add Field button (on the toolbar).
3. In the Add Field dialog:
   1. Name the field StdTime.
   2. Set the Data Type to Date.
   3. Click OK to create the field.
4. Populate the StdTime field.
5. Open the table and select Calculate Field tool. Then, set the following:
   1. Field Name = “StdTime.”
   2. For the Expression field, use: “format_date(!Name!)”
   3. For the code block, use Python function to extract time from the filename (example below).
   4. Then click Run.

import re 

         timestamp_str = match.group(1) 

         # Convert to datetime object 

         dt = datetime.strptime(timestamp_str, "%Y%m%dT%H%M%S") 

         # Return the formatted date as a string 

         return dt.strftime("%Y-%m-%d %H:%M:%S") 

    else: 

         return None # Return None if no valid timestamp is found