Deep learning-based multi-spectral satellite image segmentation for water body detection

Deep learning-based multi-spectral satellite image segmentation for water body detection

Automated water body detection from satellite imagery is a fundamental stage for urban hydrological studies. In recent years, various deep convolutional neural network (DCNN)-based methods have been proposed to segment remote sensing data collected by conventional RGB or multi-spectral imagery for s...

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Bibliographic Details
Main Authors: Kunhao Yuan, Xu Zhuang, Gerald Schaefer, Jianxin Feng, Lin Guan, Hui Fang
Format: Default Article
Published: 2021
Subjects:
Artificial intelligence not elsewhere classified
Physical Geography and Environmental Geoscience
Geomatic Engineering
feature fusion
semantic segmentation
deep convolutional neural networks
water body detection
Multi-spectral remote sensing
Artificial Intelligence and Image Processing
Online Access:https://hdl.handle.net/2134/14999412.v1
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https://hdl.handle.net/2134/14999412.v1

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