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Multi‐sensor OBIA methods for conflict research and humanitarian relief applications

Plank, Simon and Aravena Pelizari, Patrick and Spröhnle, Kristin and Bernhard, Eva-Maria and Mager, Alexander and Nitsche, Robin and Martinis, Sandro and Schöpfer, Elisabeth (2014) Multi‐sensor OBIA methods for conflict research and humanitarian relief applications. South-Eastern European Journal of Earth Observation and Geomatics, 3 (2S), pp. 259-262. Aristotle University of Thessaloniki, Greece. ISBN 2241-1224 ISSN 2241-1224

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Official URL: http://ejournals.lib.auth.gr/seejeog

Abstract

Two case studies are presented showing the potential of remote sensing focusing on advanced semi-automated Object-Based Image Analysis (OBIA) methods to support the monitoring of conflict affected areas where traditional field assessments are hampered by security concerns or other hindering factors making field access very difficult. First, the exploitation of natural resources is examined by Synthetic Aperture Radar (SAR) polarimetry. Decomposition of polarimetric SAR data is applied to extract polarimetric parameters which have strong relation to the physical scattering mechanisms of the ground target. Then, a hereon based unsupervised land cover classification is conducted. Next, the result of the aforementioned pixel-based classification is improved by OBIA post-processing procedures. The second method described in this article concentrates on the application of state of the art machine learning techniques in order to provide a generic OBIA approach for the extraction of very small scaled features such as dwellings in Internally Displaced Persons (IDP) or refugee camps. Based on current Very High Resolution (VHR) optical data, a comprehensive set of descriptive attributes is derived comprising spectral, geometrical and relational information in order to characterize the features of interest. In the next step, the target features are identified and specified applying the non-parametric classification algorithm Support Vector Machines (SVM).

Item URL in elib:https://elib.dlr.de/89180/
Document Type:Article
Title:Multi‐sensor OBIA methods for conflict research and humanitarian relief applications
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Plank, Simonsimon.plank (at) dlr.deUNSPECIFIED
Aravena Pelizari, PatrickPatrick.AravenaPelizari (at) dlr.deUNSPECIFIED
Spröhnle, Kristinkristin.sproehnle (at) dlr.deUNSPECIFIED
Bernhard, Eva-MariaEva-Maria.Bernhard (at) dlr.deUNSPECIFIED
Mager, Alexanderalexander.mager (at) dlr.deUNSPECIFIED
Nitsche, Robinrobin.nitsche (at) dlr.deUNSPECIFIED
Martinis, Sandrosandro.martinis (at) dlr.deUNSPECIFIED
Schöpfer, Elisabethelisabeth.schoepfer (at) dlr.deUNSPECIFIED
Date:May 2014
Journal or Publication Title:South-Eastern European Journal of Earth Observation and Geomatics
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:3
Page Range:pp. 259-262
Editors:
EditorsEmail
Gitas, IoannisAristotle University of Thessaloniki
Mallinis, GiorgiosDemocritus University of Thrace
Patias, PetrosAristotle University of Thessaloniki
Stathakis, DimitrisUniversity of Thessaly
Zalidis, GeorgiosInterbalkan Environment Center
Publisher:Aristotle University of Thessaloniki, Greece
Series Name:GEOBIA 2014 Advancements, trends and challenges, 5th Geographic Object-Based Image Analysis Conference, Thessaloniki, Greece, May 21-24, 2014
ISSN:2241-1224
ISBN:2241-1224
Status:Published
Keywords:Feature extraction, machine learning, OBIA, SAR polarimetry
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 Zivile Kriseninformation und Georisiken (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Plank, Simon Manuel
Deposited On:02 Jun 2014 14:46
Last Modified:17 Jul 2015 07:44

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