Rule-based classification

In addition to supervised and unsupervised classification algorithms, with Object Analyst you can also create a custom rule to assign class membership to segments. By creating a custom rule, as an analyst you can select the criteria that determines membership of a sample in a class based on your understanding of the domain, data, or both.

You can use various tools or assessments to better understand the data and processes, but the decision on membership of a class is human-made. You can then create a classification rule by using the available attributes and your understanding of the data and the application domain. The knowledge to construct a classification rule comes from existing understanding, which you then translate into an equation. Effective construction of a rule relies on exploring your data and onscreen interpretation of the image and the segments.

Object Analyst can define and apply a classification rule that you have created on segments classified already or on unclassified segments. The prerequisite is the attribute calculation of each segment. After algorithmic classification, you can either remove a class for some or all segments, or change the membership of certain segments in a class to improve the overall accuracy of the classification.

Another scenario is when no algorithmic classification is performed and you want to assign certain segments to a class based on criteria you specify. You can create an attribute field in a vector layer to store the class information and create a rule by using the available calculated attributes.