A Hierarchical Multiscale Super-Pixel-Based Classification Method for Extracting Urban Impervious Surface Using Deep Residual Network From WorldView-2 and LiDAR Data

A Hierarchical Multiscale Super-Pixel-Based Classification Method for Extracting Urban Impervious Surface Using Deep Residual Network From WorldView-2 and LiDAR Data

High-resolution optical imagery can provide detailed information of urban land objects for impervious surface extraction, while airborne light detection and ranging (LiDAR) data can provide height features of land objects. Therefore, synergistic use of high-resolution imagery and LiDAR data is consi...

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Bibliographic Details
Main Authors: Mengfan Wu, Xiangwei Zhao, Zhongchang Sun, Huadong Guo
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep residual network
impervious surface
light detection and ranging (LiDAR)
multiscale
Spatial Pyramid Pooling (SPP-net)
super pixel
Online Access:https://ieeexplore.ieee.org/document/8600363/

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