Hydrocarbon microseepage mapping using signature based target detection techniques

Alatan, Abdullah Aydın
In this paper, we compare the conventional methods in hydrocarbon seepage anomalies with the signature based detection algorithms. The Crosta technique [1] is selected as a basement in the experimental comparisons for the conventional approach. The Crosta technique utilizes the characteristic bands of the searched target for principal component transformation in order to determine the components characterizing the target in interest. Desired Target Detection and Classification Algorithm (DTDCA), Spectral Matched Filter (SMF), and Normalized Correlation (NC) are employed for signature based target detection. Signature based target detection algorithms are applied to the whole spectrum benefiting from the information stored in all spectral bands. The selected methods are applied to a multispectral Advanced SpaceBorne Thermal Emission and Radiometer (ASTER) image of the study region, with an atmospheric correction prior to the realization of the algorithms. ASTER provides multispectral bands covering visible, short wave, and thermal infrared region, which serves as a useful tool for the interpretation of the areas with hydrocarbon anomalies. The exploration area is selected as Gemrik Anticline which is located in South East Anatolia, Adiyaman, Bozova Oil Field, where microseeps can be observed with almost no vegetation cover. The spectral signatures collected with Analytical Spectral Devices Inc. (ASD) spectrometer from the reference valley [2] have been utilized as an input to the signature based detection algorithms. The experiments have indicated that DTDCA and MF outperforms the Crosta technique by locating the microseepage patterns along the mitigation pathways with a better contrast. On the other hand, NC has not been able to map the searched target with a visible distinction. It is concluded that the signature based algorithms can be more effective than the conventional methods for the detection of microseepage induced anomalies.


Signature Based Vegetation Detection on Hyperspectral Images
Özdemir, Okan Bilge; Soydan, Hilal; Çetin, Yasemin; Düzgün, Hafize Şebnem (2015-05-19)
In this study, the contribution of utilizing hyperspectral unmixing algorithms on signature based target detection algorithms is studied. Spectral Angle Mapper (SAM), Spectral Matched Filter (SMF) and Adaptive Cosine Estimator (ACE) algorithms are selected as target detection methods and the performance change related to the target spectral acquisition is evaluated. The spectral signature of the desired target, corn, is acquired from ASD hyperspectral library as well as from the hypespectral unmixing endmem...
Özdemir, Okan Bilge; Soydan, Hilal; Çetin, Yasemin; Duzgun, Sebnem (2016-07-15)
This paper presents a vegetation detection application with semi-supervised target detection using hyperspectral unmixing and segmentation algorithms. The method firstly compares the known target spectral signature from a generic source such as a spectral library with each pixel of hyperspectral data cube employing Spectral Angle Mapper (SAM) algorithm. The pixel(s) with the best match are assumed to be the most likely target vegetation locations. The regions around these potential target locations are furt...
Identification of hydrocarbon microseepage induced alterations with spectral target detection and unmixing algorithms
Soydan, Hilal; Koz, Alper; Düzgün, Hafize Şebnem (2019-02-01)
Hydrocarbon micro and macro seeps alter chemical and mineral composition of the Earth's surface, providing prospects for detection with remote sensing tools. There have been several studies focusing on mapping these anomalies by utilizing ever evolving multispectral and hyperspectral imaging instruments, which has proven their capacity for mapping both hydrocarbons and hydrocarbon-induced alterations so far. These studies broadly comprise of methods like calculating band ratios, spectral angle mapping, spec...
Oil Spill Determination with Hyperspectral Imagery: A Comparative Study
Soydan, Hilal; Koz, Alper; Düzgün, Hafize Şebnem; Alatan, Abdullah Aydın (2015-05-19)
Hyperspectral target detection methods have until now progressed mainly on two paths in remote sensing research. The first approach, anomaly detection methods, use the difference of a local region with respect to its neighborhood to analyze the image without using any prior information of the searched target. The second approach on the other hand uses a previously obtained signature of the target, which uniquely represents the target's reflection characteristics with respect to the spectral wavelengths. The...
Çalışkan, Akın; BATI, Emrecan; Koz, Alper; Alatan, Abdullah Aydın (2016-07-15)
Using the spectral signature of a target by means of matching the signature with the pixels of an acquired hyperspectral image has been proven as an effective way of classifying hyperspectral pixels in most of the proposed methods in hyperspectral image analysis. A disadvantage of these methods is however to use only the spectral characteristics of pixels for detection while ignoring the spatial relations between the neighbouring pixels. In this paper, we propose a hyperspectral target detection method whic...
Citation Formats
H. SOYDAN, A. KOZ, H. Ş. DÜZGÜN, and A. A. Alatan, “Hydrocarbon microseepage mapping using signature based target detection techniques,” presented at the 15th SPIE Conference on Earth Resources and Environmental Remote Sensing/GIS Applications VI, Toulouse, FRANCE, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39998.