Tutorials - Overview

The following tutorials give you an introduction on how to apply eCognition's new features to specific question formulations. All material is designed for self-study.

Audience

The contents are intended for beginners or for users familiar with eCognition who would like to learn more about building complex rule sets.

Requirements

To perform these guided tours or tutorials, you will need:

Tutorials

Tutorials and data are available in the Library of the eCognition Knowlege-Base - they give you a basic introduction analyzing a very simple schematic image. The key concepts are the segmentation and distinction of image objects showing how to build a first rule set.

A nice start to learn eCognition is our webinar for beginners that you can find here (1h 15 min):
eCognition-for-Beginners

 

Or take a look at these short videos (3-10 min) where you learn basic steps in eCognition:

Getting Started 1 of 4: Create a project

Getting Started 2 of 4: First dynamic classification

Getting Started 3 of 4: Improve your objects

Getting Started 4 of 4: Export your results

 

Videos for first steps using Deep Learning - Convolutional neural networks - CNN :

Deep Learning 1 of 4: Introduction and Set-up

Deep Learning 2 of 4: Creating Samples

Deep Learning 3 of 4: Create / Train / Save CNN

Deep Learning 4 of 4: Apply CNN with OBIA

 

Load convolutional neural network - load external CNN model

Apply instance segmentation - external instance segmentation model

Videos and Webinars

Follow our movies about various eCognition topics for beginners up to advanced users including eCognition deconstructed videos, detailed webinars and short technical support videos on eCognition tv.

Our eCognition videos explain theory, algorithm and use cases around these and more topics:

Accuracy Assessment workflow - introduction to accuracy assessment

Assign class by thematic layer - how to classify image objects based on a thematic layer

Apply instance segmentation - Deep Learning - how to apply an external Instance Segmentation model

Automatic Threshold - compute a threshold that can be used in segmentation

Assign class - assign classes to image objects based on single or multiple thresholds

Assign Layer Alias - learn how to assign a layer alias to an image or thematic layer

Batch processing with eCognition - Batch processing using eCognition developer and server

Calculate Random Number - creates a random value feature (can be used to split samples for calibration and validation)

Change Detection using multi-temporal NDVI - apply a NDVI change detection classification

Change Detection with Maps - use maps to perform a change detection

Chessboard Segmentation - how Chessboard Segmentation works

Compute statistical value - how to perform a statistical operation on the feature distribution within a domain and stores the result in a process variable operations

Contrast Split Segmentation - create image objects based on contrast in one layer

Convert to sub-objects - split all image objects of a domain into its sub-objects

Create & convert & remove thematic layers - how to work with vector layers

Customized Import - how to create customized import routines

Delete layer - how to delete image layers, point clouds & vectors from your project - usage of 'delete layer algorithm'

Distance Map Algorithm - calculate the distance to objects of a certain class

DSM, DTM & nDSM - how to create elevation information in eCognition

Export Vector Layer - export objects as vectors in different formats (shp, FileGDB, Geojson)

Fill pixel values - learn how to fill in raster regions and apply interpolation methods

Find Domain Extrema - find minimum or maximum values for a feature in a certain area

Grow Region - growing regions and objects

Hillshade calculation - algorithm that applies a hillshade layer

Image object fusion - learn how to grow and merge objects

Index Layer Calculation - algorithm that calculates different indices (NDVI and more)

Layer Arithmetics - how to calculate raster layer indices

Load convolutional neural network - Deep Learning - how to load an external CNN model

Majority Vote (Feature) - how to apply the majority vote features Majority vote area & Majority vote count

Median filter - how to filter raster images and create a new temporary raster layer

Merge Region - merging regions and objects

Morphology - how to use the 'morphology algorithm' to smooth image objects by pixel-based opening or closing operations

Multiresolution Segmentation - create image objects using Multiresolution Segmentation

Multi-threshold segmentation - how to apply the algorithm Multi-threshold segmentation

NDSM Layer Calculation - algorithm that calculates nDSM based on DSM and DTM

Pixel-Based Object Resizing I - how to use pixel-based object resizing part I

Pixel-Based Object Resizing II - how to use pixel-based object resizing part II

Principal Component Analysis - learn how to apply PCA

Rasterize Point Cloud - algorithm that rasterizes point clouds

Remove Objects - how to remove objects

Sobel operator filter - learn how to apply this filter

Startrails example for arrays and variables and layer arithmetics

Supervised classification - how to apply a supervised classification

Thematic Layer Operation Algorithms Alterations: Buffering & Dissolve - thematic layer algorithms

Thematic Layer Operation Algorithms: Create / Convert / Remove - thematic layer algorithms

Unsupervised Classification - how to apply the algorithm - former cluster analysis algorithm

Update Region algorithm - how to work with regions

Vector Orthogonalization - algorithm that creates generalized rectangular vectors

Vector-based segmentation - algorithm to create image objects based on a vector layer

Watershed segmentation - explains how the watershed segmentation works

Working with Regions - how to use the region concept

Working with IOL hierarchies - image object levels and their application

 

The following webinars explain eCognition and applications in more detail:

Agricultural Field Boundary Delineation with Multi Temporal Sentinel 2 Imagery
Automated Extraction of Geospatial Information for Humanitarian Action Support
Broad Scale Automated Mapping of Shallow Benthic Habitats in the Caribbean using Planet Dove Imagery
Coral Reef and Seagrass Habitat Mapping using Object Based Analysis
Data Fusion Approaches to Tree Canopy Change Detection
Deep Learning - How to analyze large sonar data sets with machine learning
Deep Learning - Mapping of Rock Glaciers
Deep Learning - UAVs and Precision Agriculture
eCognition algorithms for complex agricultural Goals
eCognition Developer for Beginners
eCognition for License Administrators
eCognition Server
eCognition Version 10
eCognition Version 10.1
Image Object Refinement Techniques
Land Register Automation
Mapping - GIS Maps of Louisiana's Dynamic Wetlands
Mapping of Louisiana's Wetlands
Natural Disaster Mapping for Hurricane Harvey with Trimble eCognition
Object based Landslide Assessment in Site Specific Scale
Point Cloud - LiDAR Point Cloud Quality Control
Point Cloud - OBIA Point Cloud Analytics
Template Matching - Counting Features with Template Matching
Timber Cruising with eCognition
Time Series Image Data as Frames in eCognition
Vegetation Analysis in Feeder Corridors with YellowScan & Trimble

 

See also our 'Oldies but Goldies' videos:

OBIA made easy
eCognition Introduction
eCognition Essentials Introduction
Pixels are not the answer
Benefits of rule sets within eCognition Developer

Installation videos

Download and Installation of the eCognition Developer Software
Install License Manager and activate Licenses
Online activation
Check License Administrator
Online return
Offline activation
Offline return
License borrowing
eCognition GRID Installation