Integration of Convolutional Neural Networks and Object-Based Post-Classification Refinement for Land Use and Land Cover Mapping with Optical and SAR Data

Integration of Convolutional Neural Networks and Object-Based Post-Classification Refinement for Land Use and Land Cover Mapping with Optical and SAR Data

Object-based image analysis (OBIA) has been widely used for land use and land cover (LULC) mapping using optical and synthetic aperture radar (SAR) images because it can utilize spatial information, reduce the effect of salt and pepper, and delineate LULC boundaries. With recent advances in machine...

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Bibliographic Details
Main Authors: Shengjie Liu, Zhixin Qi, Xia Li, Anthony Gar-On Yeh
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Remote Sensing
Subjects:
object-based post-classification refinement (OBPR)
convolutional neural network (CNN)
synthetic aperture radar (SAR)
land use and land cover
object-based image analysis (OBIA)
Online Access:https://www.mdpi.com/2072-4292/11/6/690

Internet

https://www.mdpi.com/2072-4292/11/6/690

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