Random forest in remote sensing: A review of applications and future directions

• Published in: ISPRS journal of photogrammetry and remote sensing Vol. 114; pp. 24 - 31
• Main Authors: Belgiu, Mariana, Drăguţ, Lucian
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.04.2016
• Subjects: Classification; Classifiers; Communities; data analysis; decision support systems; Decision trees; Ensemble classifier; Feature selection; hyperspectral imagery; photogrammetry; Random forest; Remote sensing; Review; Sampling; Seasons; Supervised classifier; Training; Feature selection; Random forest; Supervised classifier; Review; Ensemble classifier

A random forest (RF) classifier is an ensemble classifier that produces multiple decision trees, using a randomly selected subset of training samples and variables. This classifier has become popular within the remote sensing community due to the accuracy of its classifications. The overall objectiv...