eCognition Developer is a powerful development environment for object-based image analysis. It is used in earth sciences to develop rule sets (or applications for eCognition Architect) for the automatic analysis of remote sensing data.
eCognition Developer can be applied for all common remote sensing tasks such as vegetation mapping, feature extraction, change detection and object recognition. The object-based approach facilitates analysis of all common data sources, such as medium to high resolution satellite data, high to very high resolution aerial photography, lidar, radar and even hyperspectral data.
Superior Object Based Image Analysis Tools and Algorithms
eCognition Developer offers a comprehensive collection of algorithms tailored to the different aspects of image analysis. The user can choose from a variety of segmentation algorithms such as multiresolution segmentation, quad tree or chessboard. The scope of classification algorithms range from sample-based nearest neighbor, fuzzy logic membership function or specialized context-driven analysis. Layer operation algorithms allow pixel based filters such as slope, aspect, edge extraction or user defined layer arithmetics to be applied.
The graphical user interface flexibly displays any source of image data. Simple drag and drop functionality enables users without any programming skills to quickly develop rule sets and applications for standard analysis. Advanced users can leverage powerful tools to tackle even the most advanced tasks.
After setting up an application in eCognition Architect, it can be stored and applied to a vast amount of images by extending the eCognition installation with eCognition Server. This enables the image analysis process to be fully automated while providing extensive scalability through the service-oriented architecture.
The included SDK allows the core capabilities of eCognition Developer to be extended by adding algorithms, object features, data drivers and more. In this way, custom segmentations, classifiers, layer operations or object features can be added to the software.
In the data loading step, data can be imported in arbitrary combinations. Different resolutions are supported as well as differing sensor types. Image segmentation derives the homogeneous image regions that provide the base layer for the following analysis steps.
Analysis can be implemented based on conditions, samples or a combination of both. Through context analysis, features that are not identifiable solely based on spectral or textural
attributes can be extracted.
The extracted features can be exported in raster or vector format allowing smooth integration into GIS workflows. Rule sets and applications developed for one task can be reused over large areas, effectively automating image analysis.
To find out more, download the eCognition Developer Quickstart Package