elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

Plank, Simon and Mager, Alexander and Schöpfer, Elisabeth (2014) Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis. Remote Sensing, 6, pp. 11977-12004. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs61211977 ISSN 2072-4292

[img] PDF
8MB

Official URL: http://www.mdpi.com/2072-4292/6/12/11977

Abstract

In developing countries, there is a high correlation between the dependence of oil exports and violent conflicts. Furthermore, even in countries which experienced a peaceful development of their oil industry, land use and environmental issues occur. Therefore, an independent monitoring of oil field infrastructure may support problem solving. Earth observation data enables a fast monitoring of large areas which allows comparing the real amount of land used by the oil exploitation and the companies’ contractual obligations. The target feature of this monitoring is the infrastructure of the oil exploitation, oil well pads – rectangular features of bare land covering an area of approximately 50–60 m x 100 m. This article presents an automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR) and an object-based post-classification. The method is developed and tested using dual-polarimetric TerraSAR-X imagery acquired over the Doba basin in south Chad. The advantages of PolSAR are independence of the cloud coverage (vs. optical imagery) and the possibility of detailed land use classification (vs. single-pol SAR). The PolSAR classification uses the polarimetric Wishart probability density function based on the anisotropy/entropy/alpha decomposition. The object-based post-classification refinement, based on properties of the feature targets such as shape and area, increases the user’s accuracy of the methodology by an order of a magnitude. The final achieved user’s and producer’s accuracy is 59–71% in each case (area based accuracy assessment). Considering only the numbers of correctly/falsely detected oil well pads, the user’s and producer’s accuracies increase to even 74–89%. In an iterative training procedure the best suited polarimetric speckle filter and processing parameters of the developed feature extraction procedure are determined. The high transferability of the methodology is proved by an application to a second SAR acquisition.

Item URL in elib:https://elib.dlr.de/92999/
Document Type:Article
Title:Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Plank, Simonsimon.plank (at) dlr.deUNSPECIFIED
Mager, Alexanderalexander.mager (at) dlr.deUNSPECIFIED
Schöpfer, Elisabethelisabeth.schoepfer (at) dlr.deUNSPECIFIED
Date:2 December 2014
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:No
Volume:6
DOI :10.3390/rs61211977
Page Range:pp. 11977-12004
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:SAR polarimetry; object-based image analysis; feature extraction; natural resources; monitoring; oil exploitation
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:04 Dec 2014 14:27
Last Modified:21 Sep 2019 05:05

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.