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Oil and Gas Applications of Remote Sensing and UAV Systems
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Oil and Gas Applications of Remote Sensing and UAV Systems

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (30 September 2017) | Viewed by 9666

Special Issue Editor

Dr. Bahram Salehi

E-Mail Website
Guest Editor
C-CORE&Cross Appointed Professor Faculty of Engineering and Applied Science, Memorial University of Newfoundland, Captain Robert A. Bartlett Building, Morrissey Road, St. John's, NL A1B 3X5, Canada
Interests: image processing; photogrammetry; optical and SAR remote sensing

Special Issue Information

Dear Colleagues,

Recent advances in Earth observation (EO) sensors, including space-borne high-resolution multispectral, polarimetric synthetic aperture radar (SAR) and unmanned aerial vehicles (UAV), have brought increasing attention to applications of data acquired by such sensors for environmental, energy and natural resource mapping and monitoring. For years, oil and gas as a major source of energy and natural resources has been explored in both maritime and terrestrial environments. Extraction and transportation (pipelines) of oil/gas can cause extensive environmental changes on both sea and land ecosystems. Remote sensing has been and is being utilized as a timely and cost-effective tool to detect and monitor such changes.

This Special Issue shall explore new trends in algorithm development, image processing and applications of remote sensing and UAV systems in mapping and environmental monitoring related to oil and gas activities. This special issue considers applications in both maritime and terrestrial environments. Topics include, but are not limited to:
-    Detection of terrestrial oil and wastewater spills and their effects on ecosystems, such as forest, wetlands, etc.
-    Maritime oil spill contamination detection and extent mapping
-    Combination of EO, UAV and Electromagnetic Survey (EM) data for monitoring oil/gas related activities
-    Subsidence detection caused by oil and gas exploration in terrestrial areas using InSAR technologies
-    Mapping of oil/gas exploration caused linear (e.g., seismic lines) and areal (e.g., well site) disturbances  
-    Oil spill detection in sea ice
-    UAV pipeline and corridor mapping

Dr. Bahram Salehi, P. Eng
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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4235 KiB  
Article
Exploratory Data Analysis of Synthetic Aperture Radar (SAR) Measurements to Distinguish the Sea Surface Expressions of Naturally-Occurring Oil Seeps from Human-Related Oil Spills in Campeche Bay (Gulf of Mexico)
by Gustavo De Araújo Carvalho, Peter J. Minnett, Fernando Pellon De Miranda, Luiz Landau and Eduardo Tavares Paes
ISPRS Int. J. Geo-Inf. 2017, 6(12), 379; https://doi.org/10.3390/ijgi6120379 - 06 Dec 2017
Cited by 13 | Viewed by 4822
Abstract
An Exploratory Data Analysis (EDA) aims to use Synthetic Aperture Radar (SAR) measurements for discriminating between two oil slick types observed on the sea surface: naturally-occurring oil seeps versus human-related oil spills—the use of satellite sensors for this task is poorly documented in [...] Read more.
An Exploratory Data Analysis (EDA) aims to use Synthetic Aperture Radar (SAR) measurements for discriminating between two oil slick types observed on the sea surface: naturally-occurring oil seeps versus human-related oil spills—the use of satellite sensors for this task is poorly documented in scientific literature. A long-term RADARSAT dataset (2008–2012) is exploited to investigate oil slicks in Campeche Bay (Gulf of Mexico). Simple Classification Algorithms to distinguish the oil slick type are designed based on standard multivariate data analysis techniques. Various attributes of geometry, shape, and dimension that describe the oil slick Size Information are combined with SAR-derived backscatter coefficients—sigma-(σo), beta-(βo), and gamma-(γo) naught. The combination of several of these characteristics is capable of distinguishing the oil slick type with ~70% of overall accuracy, however, the sole and simple use of two specific oil slick’s Size Information (i.e., area and perimeter) is equally capable of distinguishing seeps from spills. The data mining exercise of our EDA promotes a novel idea bridging petroleum pollution and remote sensing research, thus paving the way to further investigate the satellite synoptic view to express geophysical differences between seeped and spilled oil observed on the sea surface for systematic use. Full article
(This article belongs to the Special Issue Oil and Gas Applications of Remote Sensing and UAV Systems)
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11657 KiB  
Article
A New Endmember Preprocessing Method for the Hyperspectral Unmixing of Imagery Containing Marine Oil Spills
by Can Cui, Ying Li, Bingxin Liu and Guannan Li
ISPRS Int. J. Geo-Inf. 2017, 6(9), 286; https://doi.org/10.3390/ijgi6090286 - 08 Sep 2017
Cited by 10 | Viewed by 4234
Abstract
The current methods that use hyperspectral remote sensing imagery to extract and monitor marine oil spills are quite popular. However, the automatic extraction of endmembers from hyperspectral imagery remains a challenge. This paper proposes a data field-spectral preprocessing (DSPP) algorithm for endmember extraction. [...] Read more.
The current methods that use hyperspectral remote sensing imagery to extract and monitor marine oil spills are quite popular. However, the automatic extraction of endmembers from hyperspectral imagery remains a challenge. This paper proposes a data field-spectral preprocessing (DSPP) algorithm for endmember extraction. The method first derives a set of extreme points from the data field of an image. At the same time, it identifies a set of spectrally pure points in the spectral space. Finally, the preprocessing algorithm fuses the data field with the spectral calculation to generate a new subset of endmember candidates for the following endmember extraction. The processing time is greatly shortened by directly using endmember extraction algorithms. The proposed algorithm provides accurate endmember detection, including the detection of anomalous endmembers. Therefore, it has a greater accuracy, stronger noise resistance, and is less time-consuming. Using both synthetic hyperspectral images and real airborne hyperspectral images, we utilized the proposed preprocessing algorithm in combination with several endmember extraction algorithms to compare the proposed algorithm with the existing endmember extraction preprocessing algorithms. The experimental results show that the proposed method can effectively extract marine oil spill data. Full article
(This article belongs to the Special Issue Oil and Gas Applications of Remote Sensing and UAV Systems)
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