Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks

Li, Hao and Ghamisi, Pedram and Soergel, Uwe and Zhu, Xiao Xiang (2018) Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks. Remote Sensing (10), pp. 1649-1668. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs10101649. ISSN 2072-4292.

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Official URL: https://www.mdpi.com/2072-4292/10/10/1649

Item URL in elib:

https://elib.dlr.de/122440/

Document Type:

Article

Title:

Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Li, Hao	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Ghamisi, Pedram	DLR-IMF/TUM-LMF	UNSPECIFIED	UNSPECIFIED
Soergel, Uwe	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Zhu, Xiao Xiang	DLR-IMF/TUM-LMF	UNSPECIFIED	UNSPECIFIED

Date:

2018

Journal or Publication Title:

Remote Sensing

Refereed publication:

Yes

Open Access:

Yes

Gold Open Access:

Yes

In SCOPUS:

Yes

In ISI Web of Science:

Yes

DOI:

10.3390/rs10101649

Page Range:

pp. 1649-1668

Publisher:

Multidisciplinary Digital Publishing Institute (MDPI)

ISSN:

2072-4292

Status:

Published

Keywords:

Feature Extraction, sentinel-1, local climate zones, lcz

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Space

HGF - Program Themes:

Earth Observation

DLR - Research area:

Raumfahrt

DLR - Program:

R EO - Earth Observation

DLR - Research theme (Project):

R - Vorhaben hochauflösende Fernerkundungsverfahren (old)

Location:

Oberpfaffenhofen

Institutes and Institutions:

Remote Sensing Technology Institute > EO Data Science

Deposited By:

Häberle, Matthias

Deposited On:

20 Nov 2018 10:43

Last Modified:

14 Dec 2019 04:26

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