Leveraging Machine Learning to Extend Ontology-Driven Geographic Object-Based Image Analysis (O-GEOBIA): A Case Study in Forest-Type Mapping

Leveraging Machine Learning to Extend Ontology-Driven Geographic Object-Based Image Analysis (O-GEOBIA): A Case Study in Forest-Type Mapping

Ontology-driven Geographic Object-Based Image Analysis (O-GEOBIA) contributes to the identification of meaningful objects. In fusing data from multiple sensors, the number of feature variables is increased and object identification becomes a challenging task. We propose a methodological contribution...

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Bibliographic Details
Main Authors: Sachit Rajbhandari, Jagannath Aryal, Jon Osborn, Arko Lucieer, Robert Musk
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Remote Sensing
Subjects:
GEOBIA
rule-based classification
ontology
machine learning
random forests
rules extraction
variogram
semantic similarities
semantic variogram
Online Access:http://www.mdpi.com/2072-4292/11/5/503

Internet

http://www.mdpi.com/2072-4292/11/5/503

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