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Trimble eCognition Developer Open Training

June 3 – 5, 2019

event-landing-eCognition
Who should attend?

We recommend participants have a solid understanding of Remote Sensing & GIS.   Familiarity with image analysis is advantageous, but not required.

Duration

Three days
8:30 am – 4:30 pm each day

Cost

$1,195 per student
Beverages and lunch are included and will be provided each day.

When

June 3 – 5, 2019

Where

CSDS Training Center
4823 Auburn Blvd.
Sacramento, CA 95841

Requirements

Each student must bring a laptop with a license of eCognition Developer. Temporary licenses are available for the duration of this course.

Overview

eCognition Developer fundamentals training will be held at the CSDS Training Center from June 3 – 5, 2019.

This three day course covers all the core concepts of OBIA (Object Based Image Analysis) and the fundamental tools and functions required to become a proficient Rule Set developer within eCognition Developer.

The participant is guided through general theory, followed by hands-on exercises designed to emphasize both the how and why of Rule Set development. The goal of this training is to provide attendees with the capabilities to setup an image analysis workflow and the knowledge of when to use which tool to achieve the desired results with their own data.

In addition, we review tools and methods available within the Developer software such as native vector handling and template matching.

Registration

Please register the individual listed below to attend this training.

Theoretical Knowledge Base eCognition

Content

eCognition Developer Fundamentals covers all the core functionalities and methods, from loading data to exporting results. Different sensor types and input data formats are used during the hands-on exercises. Fundamental topics covered include:

  • Introduction to OBIA
  • Loading & viewing data
  • Working with Projects & Workspaces
  • Introduction to “Processes”
  • Core segmentation techniques
  • Image objects as information carriers
  • Fundamental classification techniques
  • Image object refinement algorithms
  • The integration of thematic layers

In addition, the course will introduce tools and algorithms for more complex classification methods and will walk participants through a typical land cover classification analysis:

  • Using customized features
  • Introduction to fuzzy logic & membership functions
  • Supervised classification models
  • Sample dataset creation & handling
  • Manual image object editing
  • Refinement using “remove objects” & “grow region”
  • Rule Set structure & organization
  • Reusing & documenting Rule Sets

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