Feature Extraction

In GIS (Geographic Information System) processing, feature extraction is the process of identifying and extracting specific geographic features or attributes from a dataset, such as buildings, roads, rivers, or land use types.

Feature extraction involves analyzing and processing spatial data to identify and isolate specific features of interest. This can be done through a variety of techniques, such as image analysis, object-based image analysis, or manual digitizing.

Once features are extracted, they can be further analyzed and used for a variety of applications, such as mapping, modeling, or spatial analysis. Feature extraction is an important step in GIS processing, as it enables users to effectively analyze and visualize spatial data in a meaningful way.

Workflow of Feature Extraction 

The workflow of feature extraction involves the following steps: 

● Dividing an image into segments.

● Computing various attributes for the segments.

● Creating several new classes.

● Interactively assigning segments (called training samples) to each class.

●Classifying the entire image with a K Nearest Neighbor (KNN), Support Vector Machine (SVM), or Principal Components Analysis (PCA) supervised classification method, based on your training samples.

● Exporting the classes to a shapefile or classification image.

Feiyan Remote Sensing is a professional provider of feature extraction service. If you need help on extracting specific geographic features or attributes from a certain dataset, please contact us for further information of feature extraction.