• TECHNOLOGY WHITEPAPERS

L3Harris Geospatial whitepapers feature detailed technical information about how product and services have been developed and used across industries to empower you to understand the world around you.



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Using UAV Imagery and Deep Learning for Wind Turbine Inspection

12/12/2018

Presented at Wind Europe Summit 2018

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Custom Workflows for Detecting Hydrocarbon Microseepage in Remote Sensing Imagery

12/12/2018

Presented at the GRSG Oil and Gas Workshop – Boulder, Colorado – July 11-12, 2018.

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Building GeoServices for CloudEO Store Using ENVI®

12/8/2017

This whitepaper illustrates how the development of GeoServices is realized through an ENVI Task. This is... more »

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Vegetation Analysis: Using...

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ENVI Orthorectification Module

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Point Cloud Based Change Detection: An Automated Approach for Cloud-based Services

Point Cloud Based Change Detection: An Automated Approach for Cloud-based Services

12/12/2018

Presented at the EGU General Assembly 2016 – Vienna, Austria – April 17-22, 2016

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Application of Softmax Regression and its Validation for Spectral-Based Land Cover Mapping

Application of Softmax Regression and its Validation for Spectral-Based Land Cover Mapping

12/12/2018

Presented at the ISPRS Hannover Workshop 2017 – Hannover, Germany – June 6-9, 2017.

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Building GeoServices for CloudEO Store Using ENVI®

Building GeoServices for CloudEO Store Using ENVI®

12/8/2017

This whitepaper illustrates how the development of GeoServices is realized through an ENVI Task. This is done without the necessity of other technologies or the development of other components.

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Harris Deep Learning Technology

Harris Deep Learning Technology

9/6/2017

Learn how Harris Geospatial Solutions uses deep learning technology to solve real-world problems.

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Using ENVI for Agriculture Research  |  Optical Remote Sensing of Sugarcane Development

Using ENVI for Agriculture Research | Optical Remote Sensing of Sugarcane Development

6/28/2017

Remote sensing is an effective tool for monitoring crop health and development when extensive field studies are not feasible. Using remote sensing to monitor development stages throughout the growing season (also called phenology) can help provide better estimates of productivity, yield forecasts, and biomass.

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