• EXPERIENCE THE BENEFITS


    OF RUNNING ANALYTICS



    AT SCALE

Enterprise Solutions

For more than four decades, L3Harris Geospatial has developed scientifically-proven solutions using cutting-edge technologies. A key part of this has been creating rigorous, customizable, and out-of-the-box analytics to process nearly any type of geospatial data.

Out of the Box and Custom Solutions

As the geospatial analytics leader, many customers have turned to us to create enterprise solutions as a key part of their business growth strategy. We have the skills and experience to help your organization transition from desktop to scalable and planet-scale data processing applications. We are here to make your life easier and enable more collaboration and efficiency, the ability to process all of your available data, and get the answers you need.

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On-premises Solutions

We know how hard it can be to transition from desktop processing to the cloud. We went through these growing pains ourselves and have helped many customers on this journey. A great first step to enterprise processing is deploying automated workflows to local servers.

How can we help?

Considerations for an on-premises solution:

  Data is sensitive
  Analytics are protected
  Data is too large to move to the cloud

Our on-premises solution provide you with:

  Full control of the process
  Custom workflow creation in ENVI®
  Processing on large data sets
  Rapid R&D or algorithm development
  Easy deployment


Easily build custom workflows with the ENVI Modeler and deploy anywhere

If you don’t have experience creating front-end applications and want a simple way to run processing at a larger scale than your desktop, ENVI is the perfect solution! The ENVI Modeler enables you to perform batch processing and create custom, reusable workflows without writing a single line of code. Your workflows can be deployed to our server technologies and you can use ENVI as a client to manage and run remote processing.


Examples of on-premises solutions:

  • Scenario 1

    Jerome collects hyperspectral UAV data that can be terabytes (TB) in size, so he uses servers with optimized drives and local processing to get the answers he needs.

    Scenario 2

    Javier works for the government and their data is classified so they are required to use local, on-premises processing that is disconnected from the outside world.

    Scenario 3

    Danielle's company invested in servers optimized for CPU processing and wants to use on-premises hardware. This solution is ideal for scaling and processing her SAR data.

Automated, Cloud-based Analytics

Our enterprise solutions enable you to completely automate the generation of geospatial products and provides you with the ability to scale if, and when, demand grows.

You may need automated, cloud-based analytics if you:

  Are only interested in cloud-hosted solutions instead of local or on-premises
  Want access to scalable infrastructure
  Have data that lives in the cloud

Important things to consider when getting started:

DATA

DATA

We can connect to nearly any source of imagery. Our technology supports nearly 200 file formats and sensors.

ANALYTICS

ANALYTICS

It is easy to take desktop workflows into the cloud. We make it seamless to create and re-use workflows in different processing environments, including cross-platform.

OUTPUT

OUTPUT

We understand that you likely have different requirements for the final products of each of your workflows. We include common formats for GeoTIFF, NITF, ENVI formatted files, Shapefiles, GeoJSON, and more. Our solutions delivery team also has all the tools needed to ensure your workflows generate the products you need.

HOSTING

HOSTING

Not interested in managing or hosting your own infrastructure? We have our own dedicated, auto-scaling, cloud-hosted solution that you can programmatically access for all of your data processing needs.

 

Examples of cloud-based solutions:

  • Scenario 1

    Remote sensing expert Andy wants to run his deep learning model when Sentinel 2 data is available in AWS.

    Scenario 2

    Becky has a simple workflow that prepares her data for analysis by doing radiometric calibration and atmospheric correction. Her workflow is fully automated and uses Azure Blob Storage to auto-detect when new data needs to be processed.

    Scenario 3

    Lewis manages the IT infrastructure for a data science team. Instead of hosting their own infrastructure in the cloud, they use L3Harris Geospatial’s hosted platform to process all of their data programmatically.

Full-scale Enterprise Applications

We know that no single solution is suitable for every customer. That is why we have architected our enterprise solutions so that we can put the components together like puzzle pieces to solve specific problems. If our other enterprise solutions don’t fit your needs, take a look at our custom, full-scale enterprise applications. Do you need a user-interface for solving a specific workflow or problem or want a way for your users to visualize or interact with data inputs and outputs? L3Harris geospatial can help you with full-scale enterprise solutions.

This could fit your needs if:

  You need more than headless, automated processing
  A user-interface or web application is required
  You need a data catalog to store inputs and outputs for later use

Our full-scale solutions provide you with:

  Web applications for selecting inputs and visualizing outputs
  Store processing outputs in data catalogs
  Advanced visualization of imagery, point clouds, and video datasets
  Automated processing with user workflow to QA/QC results

For many of our customers, these solutions come together to create:

Examples of full-scale enterprise solutions:

 

Scenario 1

Leonard’s organization wants to detect flooded areas using Sentinel 1 SAR data. For this application, analysts pick the area of interest and manually initiate the processing. They need a web application that allows them to: discover data, specify an area of interest (AOI), run automated processing in the cloud for their AOI, and visualize the results.

How can we help?

 
 

Scenario 2

Claire manages a regional district for her state’s Department of Transportation. In order to get a better understanding of how weather affects traffic, her organization uses Helios to tap into their large network of traffic cameras. Using the ground-weather information from Helios, they add a new layer of intelligence to driving conditions and better approximate traffic flow when combined with routing technology.

How can we help?

 
 

Scenario 3

Anita uses the ENVI Deep Learning module to find icebergs and monitor the calving rate of remote glaciers. Their application is connected to a data catalog, which allows users to specify an area of interest (AOI) and automatically extract icebergs as new data enters the system. The scientists then have the ability to sign into a web application and visualize iceberg locations on a map along with the source imagery.

How can we help?

 

From Data and Imagery to Insights and Answers

Let’s find a solution that meets your project requirements. Contact us. Let’s get started today!