Geospatial Services Framework (GSF) is deployed in the enterprise and makes powerful analytics, and the information they provide, available across an organization. Better access to information results in better and more confident decision making. GSF is elastic and easily scales up or down to meet demands and is cloud and data agnostic. This means GSF easily installs within existing infrastructure and takes advantage of the data assets an organization has already invested in.

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Customizing GSF with Node.js

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Customizing the Geospatial Services Framework with Node.js


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Analytics Without Limits


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Data Agnostic

GSF is a flexible framework that can input and analyze virtually any remotely sensed data. Organizations that have already made investments in commercially available data from L3Harris, DigitalGlobe, Airbus, etc. including LiDAR, multispectral/hyperspectral imagery, or SAR can easily use those existing data within GSF. Additionally, organizations can upload their own data gathered from other sources such as drones or UAV.

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Analytics at Scale

GSF uses the full power of cloud and enterprise architecture and can quickly run automated analytics on existing data stores or new and incoming data. Available analytics include L3Harris’ advanced machine learning capabilities, algorithms an organization is already using, and any of the powerful analytics available within ENVI software such as feature extraction, classification, object identification, and more.

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Readily Available Results

Results from analytical routines performed within GSF are easily pushed to web clients. Web clients can be tailored according to organizational need and can provide as much, or as little, detail that is needed by end users.

  • Expose task orders to a mobile work force via mobile device to maximize effeciency of working hours
  • Email regular field health reports to farmers so they make better and more informed crop decisions
  • Notify stakeholders when a specific object has been indentified in an area of interest so appropriate follow up actions happen quickly
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L3Harris Geospatial has a legacy of expertise in advanced raster analytics. GSF enables dynamic clustering of these advanced analytical capabilities which means it’s easy to for a GEOINT application to scale up or down to meet the demands of an organization.

rapid application development

In recent years, geospatial has gone main stream as more industries have learned that advanced image analytics can be used to solve business problems. Existing commercial satellite constellations, combined with the advent of small sats and miniaturized sensors for drones, have made data easily accessible. Advances in GPU and cloud technology have put massive compute power into the hands of individuals and organizations large and small. GSF brings together data, geospatial analytics, and compute power to enable the rapid development of applications to solve problems at scale across industries.

Tools to get started

Out of the box, GSF provides the fundamental tools needed to get up and running. Because GSF is modular and built on open source Node.js, it’s easy to replace components or extend functionality through open source communities like npm and GitHub. Upon installation, GSF includes the following tools:


Implements REST-based API which provides HTTP endpoints for initiating jobs, retrieving status and accessing resources.


Maps resources and translates input and output values to appropriate representations such as Amazon S3, GeoServer WCS and ENVI data sources.


Wrap whatever API the engine provides by implementing a JavaScript module that defines tasks and maps them to engine execution.


Allows queues to be defined for specific tasks, jobs and workflows like a high performance route for GPU enabled processing.


Creates and maintains all workspace files for each job which can be distributed across local, shared and cloud enabled workspaces.


Each job references task(s) with required parameters and our job manager submits jobs for processing. Can even be updated to use your job manager.

Cloud Ready Deployment

Organizations that have existing cloud capabilities can take advantage of provided GSF code that enables quick deployment into existing Amazon Web Services (AWS), Microsoft Azure, and Google Cloud environments. Customers building their own cloud capabilities can also take advantage of the same code to easily include GSF functionality in their cloud.

Fast Start Program

The Fast Start program is a 3-day service in which a L3Harris Geospatial engineer will work onsite to perform an installation. Installation includes an evaluation of the current state of an organization’s project, a basic installation and configuration to get GSF up and running, deployment of solutions into the desired infrastructure, and guidance on analysis workflows and best practices.

From Data and Imagery to Insights and Answers

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