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Our aim at UP42 is to provide the building blocks for powerful geospatial products while enabling you to work with your own components, wherever desired. The introduction of our new import data blocks, developed in collaboration with Aspectum makes this aim a reality. UP42 users are now able to bring DIMAP or GeoTIFF files from their Google Cloud Storage or AWS buckets into UP42 for processing with our wide selection of pre-processing, statistical, and machine learning capabilities.

You can now simply authenticate your Google Cloud or AWS environment, search within your bucket by filename, geographic location, or time, and process your data with an UP42 workflow.

Key features

  • Access data from Google Cloud or AWS
  • Import DIMAP or GeoTIFF data
  • Secure authentication environment
  • Process data in the UI or via the Python SDK

How does it work?

Import Data (DIMAP) Block

Our custom data blocks make it as easy as possible to utilize your own data within the UP42 platform and build powerful solutions based on that data. Whether you use Google Cloud or AWS and whether you’re working with DIMAP or GeoTIFF data, it can be integrated into an UP42 workflow in a matter of minutes.

Set up your authenticated environment

Create Environment

Environments in UP42 are secure mechanisms for you to provide access details for AWS, Google Cloud, or even your own dedicated storage system. For AWS, you simply set up an environment with variables for your Access Key ID and Secret Access Key. For Google Cloud, you provide the full JSON string of your Google Application Credentials. You can learn more about UP42 environments in our docs.

Build your workflow

Workflow

Once you’ve set up your secure environment, you can build a workflow in UP42 leveraging either the Import Data (DIMAP) or Import Data (GeoTIFF). Simply add the block to your workflow, specify your environment, and choose your processing capabilities.

Select or search for image

With our import data blocks, we provide two options for you to access data. Firstly, you can specify a specific image via scene ideas. Alternatively, you can search by geographic location or time, optionally limited by subfolder within the AWS or Google Cloud bucket. These variables are specified within your job parameters.

Job Parameters

For example, here’s an example set of parameters for accessing GeoTIFF data within a Google Cloud bucket, accessing a specific image using filenames and within a subfolder using prefix:

{ 
  "geotiff-custom:1": {
    "cloud_provider": "gcs", 
    "bucket_name": "mosaic-geotiff-data", 
    "prefix": "europe/portugal/", 
    "filenames": [“mosaic.tif”],
  } 
}

Here’s an example set of parameters for accessing data within an AWS bucket, searching via time and area of interest (AOI):

{ 
  "dimap-custom:1": {
    "cloud_provider": "aws", 
    "bucket_name": "spot-dimap-data", 
    "bbox": [ 13.351818, 52.501907, 13.379109, 52.510788], 
    "time": "2019-01-01T00:00:00+00:00/2020-12-31T23:59:59+00:00", 
    "limit": 4, "max_cloud_cover": 20 
  } 
}

For more information on the available parameters, review the documentation for the Import Data (DIMAP) or Import Data (GeoTIFF).

Process your data

Once you’ve set up your environment and set your parameters, you can choose any compatible processing block, from preprocessing to machine learning algorithms. You can even create a custom processing block to leverage your own algorithms and process your analytics workflow on UP42’s scalable infrastructure.

Get started

Start building workflows, utilizing your own data, by signing up with UP42. We’ll even give you 10,000 credits to spend on processing your custom data!

To find out more about how to use our custom data blocks, check out the DIMAP or GeoTIFF import blocks in the UP42 marketplace.

Nathan Davis avatar

Nathan Davis

Product Marketing Manager

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