CNN-Enhanced Heterogeneous Graph Convolutional Network: Inferring Land Use from Land Cover with a Case Study of Park Segmentation

CNN-Enhanced Heterogeneous Graph Convolutional Network: Inferring Land Use from Land Cover with a Case Study of Park Segmentation

Land use segmentation is a fundamental yet challenging task in remote sensing. Most current methods mainly take images as input and sometimes cannot achieve satisfactory results due to limited information. Inspired by the inherent relations between land cover and land use, we investigate land use se...

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Bibliographic Details
Main Authors: Zhi-Qiang Liu, Ping Tang, Weixiong Zhang, Zheng Zhang
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Remote Sensing
Subjects:
land use
semantic segmentation
heterogeneous graph
graph convolutional network (GCN)
Online Access:https://www.mdpi.com/2072-4292/14/19/5027

Internet

https://www.mdpi.com/2072-4292/14/19/5027

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