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Online Random Forests For Large-Scale Land-Use Classification From Polarimetric SAR Images

Hänsch, Ronny and Hellwich, Olaf (2019) Online Random Forests For Large-Scale Land-Use Classification From Polarimetric SAR Images. In: International Geoscience and Remote Sensing Symposium (IGARSS), pp. 5808-5811. IEEE. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2019-07-28 - 2019-08-02, Yokohama, Japan. DOI: 10.1109/IGARSS.2019.8898021 ISBN 978-1-5386-9154-0 ISSN 2153-7003

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Abstract

The deployment of numerous air- and space-borne remote sensing sensors as well as new data policies led to a tremendous increase of available data. While methods such as neural networks are trained by online or batch processing, i.e. keeping only parts of the data in the memory, other methods such as Random Forests require offline processing, i.e. keeping all data in the memory of the computer. The latter are therefore often trained on a small subset of a larger data set that is hoped to be representative instead of exploiting the information contained in all samples. This paper shows that Random Forests can be trained by batch processing too making their application to large data sets feasible without further constraints. The benefits of this training scheme are illustrated for the use case of land-use classification from PolSAR imagery.

Item URL in elib:https://elib.dlr.de/131039/
Document Type:Conference or Workshop Item (Speech)
Title:Online Random Forests For Large-Scale Land-Use Classification From Polarimetric SAR Images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Hänsch, RonnyRonny.Haensch (at) dlr.dehttps://orcid.org/0000-0002-2936-6765
Hellwich, Olafolaf.hellwich (at) tu-berlin.deUNSPECIFIED
Date:14 November 2019
Journal or Publication Title:International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI :10.1109/IGARSS.2019.8898021
Page Range:pp. 5808-5811
Publisher:IEEE
Series Name:IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
ISSN:2153-7003
ISBN:978-1-5386-9154-0
Status:Published
Keywords:Classification, Random Forest, Batch processing, Online learning
Event Title:IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Event Location:Yokohama, Japan
Event Type:international Conference
Event Dates:2019-07-28 - 2019-08-02
Organizer:IEEE GRSS
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Flugzeug-SAR
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > SAR Technology
Deposited By: Hänsch, Ronny
Deposited On:21 Nov 2019 15:04
Last Modified:12 Jan 2020 15:11

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