Investigating the capability of WorldView-3 superspectral data for direct hydrocarbon detection

Abstract

CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOThe recently launched WorldView-3 (WV-3) satellite is a high spatial resolution instrument with eight multispectral bands in the visible and near-infrared and an additional eight bands in the short-wave infrared (SWIR). Three of the SWIR bands, including bands 9, 12, and 16 (centered at 1210, 1730, and 2330. nm) respectively overlap with diagnostic absorption features of hydrocarbons (HCs) at 1200, 1700, and 2300. nm. This paper aims to investigate the capability of this superspectral instrument for direct HC detection. For this purpose, we have conducted several simulation experiments using multiple datasets comprising (i) spectral libraries of different HCs measured in the laboratory, (ii) close-range hyperspectral imagery of a well-known tar-sand sample acquired with a sisuCHEMA imaging system, and (iii) far-range ProSpecTIR hyperspectral imagery collected over twelve simulated HC-shows. These datasets were convolved to the spectral resolution of WV-3 and analyzed using a variety of spectral processing techniques. The absorption features of HCs manifest themselves in all cases albeit with varying intensity. The effect of a series of parameters on the detectability of the HCs was also scrutinized; these included background geology, spectral mixing, HC type, endmember set, spatial resolution, noise level, and topography. We demonstrate that the HC absorption feature in WV-3's band 12, accompanied by shoulders sustained at bands 11 and 13 (centered at 1660 and 2165. nm), is resilient enough and persist under various conditions. Potential applications of these finding include hydrocarbon exploration in frontier basins and environmental monitoring. © 2015 Elsevier Inc.The recently launched WorldView-3 (WV-3) satellite is a high spatial resolution instrument with eight multispectral bands in the visible and near-infrared and an additional eight bands in the short-wave infrared (SWIR). Three of the SWIR bands, including bands 9, 12, and 16 (centered at 1210, 1730, and 2330. nm) respectively overlap with diagnostic absorption features of hydrocarbons (HCs) at 1200, 1700, and 2300. nm. This paper aims to investigate the capability of this superspectral instrument for direct HC detection. For this purpose, we have conducted several simulation experiments using multiple datasets comprising (i) spectral libraries of different HCs measured in the laboratory, (ii) close-range hyperspectral imagery of a well-known tar-sand sample acquired with a sisuCHEMA imaging system, and (iii) far-range ProSpecTIR hyperspectral imagery collected over twelve simulated HC-shows. These datasets were convolved to the spectral resolution of WV-3 and analyzed using a variety of spectral processing techniques. The absorption features of HCs manifest themselves in all cases albeit with varying intensity. The effect of a series of parameters on the detectability of the HCs was also scrutinized; these included background geology, spectral mixing, HC type, endmember set, spatial resolution, noise level, and topography. We demonstrate that the HC absorption feature in WV-3's band 12, accompanied by shoulders sustained at bands 11 and 13 (centered at 1660 and 2165. nm), is resilient enough and persist under various conditions. Potential applications of these finding include hydrocarbon exploration in frontier basins and environmental monitoring173162173CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOsem informaçãoBoardman, J.W., Kruse, F.A., Green, R.O., Mapping target signatures via partial unmixing of AVIRIS data (1995), pp. 23-26. , In, Summaries, Fifth JPL Airborne Earth Science Workshop : JPL Publication 95-1Brekke, C., Solberg, A.H.S., Oil spill detection by satellite remote sensing (2005) Remote Sensing of Environment, 95, pp. 1-13Brown, R.A., Hydrocarbon pollution detection and quantification using hyperspectral remote sensing and geophysics (2009) Institute for Geo-Information Science and Earth Observation (ITC), p. 83. , International Institute for Geo-Information Science and Earth ObservationEnschede, The NetherlandsCarvalho Junior, O.A., Menezes, P.R., Spectral Correlation Mapper (SCM): an improvement on the Spectral Angle Mapper (SAM) (2000) Proceedings of the Tenth JPL Airborne Earth Science Workshop, pp. 65-74. , JPL Publication 00-18Clark, R.N., Curchin, J.M., Hoefen, T.M., Swayze, G.A., Reflectance spectroscopy of organic compounds: 1. Alkanes (2009) Journal of Geophysical Research, Planets, 114, p. 19Clark, R.N., Swayze, G.A., Leifer, I., Livo, K.E., Kokaly, R., Hoefen, T., A method for quantitative mapping of thick oil spills using imaging spectroscopy (2010) U.S. Geological Survey Open-File Report Number 2010-1167, p. 51Cloutis, E.A., Spectral reflectance properties of hydrocarbons: remote-sensing implications (1989) Science, 245, pp. 165-168Crowley, J.K., Brickey, D.W., Rowan, L.C., Airborne imaging spectrometer data of the Ruby mountains, Montana: mineral discrimination using relative absorption band-depth images (1989) Remote Sensing of Environment, 29, pp. 121-134WorldView-3 datasheet, , https://www.digitalglobe.com/sites/default/files/DG_WorldView3_DS_forWeb_0.pdf, URL:, (In)Donkor, K.K., Kratochvil, B., Thompson, G.R., Analysis of Athabasca oil sand by near-infrared-diffuse reflectance spectroscopy (1995) Analyst, 120, pp. 2713-2717Ellis, J.M., Davis, H.H., Zamudio, J.A., Exploring for onshore oil seepas with hyperspectral imaging (2001) Oil and Gas Journal, 99, pp. 49-58Elvidge, C.D., Visible and near infrared reflectance characteristics of dry plant materials (1990) International Journal of Remote Sensing, 11, pp. 1775-1795Feng, J., Rivard, B., Sánchez-Azofeifa, A., The topographic normalization of hyperspectral data: implications for the selection of spectral end members and lithologic mapping (2003) Remote Sensing of Environment, 85, pp. 221-231Fingas, M., Brown, C.E., Oil spill remote sensing (2014) Handbook of Oil Spill Science and Technology, pp. 311-356. , John Wiley & Sons, IncHörig, B., Kühn, F., Oschütz, F., Lehmann, F., HyMap hyperspectral remote sensing to detect hydrocarbons (2001) International Journal of Remote Sensing, 22, pp. 1413-1422Jha, M., Levy, J., Gao, Y., Advances in remote sensing for oil spill disaster management: state-of-the-art sensors technology for oil spill surveillance (2008) Sensors, 8, p. 236Kallevik, H., Kvalheim, O.M., Sjöblom, J., Quantitative determination of asphaltenes and resins in solution by means of near-infrared spectroscopy. Correlations to emulsion stability (2000) Journal of Colloid and Interface Science, 225, pp. 494-504Kokaly, R.F., Couvillion, B.R., Holloway, J.M., Roberts, D.A., Ustin, S.L., Peterson, S.H., Piazza, S.C., Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes (2013) Remote Sensing of Environment, 129, pp. 210-230Kruse, F., Perry, S., Mineral mapping using simulated Worldview-3 short-wave-infrared imagery (2013) Remote Sensing, 5, pp. 2688-2703Kühn, F., Oppermann, K., Hörig, B., Hydrocarbon Index - an algorithm for hyperspectral detection of hydrocarbons (2004) International Journal of Remote Sensing, 25, pp. 2467-2473Lammoglia, T., Souza Filho, C., Spectroscopic characterization of oils yielded from Brazilian offshore basins: potential applications of remote sensing (2011) Remote Sensing of Environment, 115, pp. 2525-2535Lammoglia, T., Souza Filho, C., Mapping and characterization of the API gravity of offshore hydrocarbon seepages using multispectral ASTER data (2012) Remote Sensing of Environment, 123, pp. 381-389Leifer, I., Lehr, W.J., Simecek-Beatty, D., Bradley, E., Clark, R., Dennison, P., Wozencraft, J., State of the art satellite and airborne marine oil spill remote sensing: application to the BP Deepwater Horizon oil spill (2012) Remote Sensing of Environment, 124, pp. 185-209Macgregor, D.S., Relationships between seepage, tectonics and subsurface petroleum reserves (1993) Marine and Petroleum Geology, 10, pp. 606-619Mishra, D.R., Cho, H.J., Ghosh, S., Fox, A., Downs, C., Merani, P.B.T., Mishra, S., Post-spill state of the marsh: remote estimation of the ecological impact of the Gulf of Mexico oil spill on Louisiana Salt Marshes (2012) Remote Sensing of Environment, 118, pp. 176-185Prelat, A., Gunaratne, S., Huebner, L., Freeman, C., Cook, A., Soriano, C., Airborne hyperspectral detection of natural offshore and onshore hydrocarbon seeps (2013) Hydrocarbon Seepage: From Source to Surface, pp. 171-182. , American Association of Petroleum Geologists, Tulsa, OK, U.S.A. F. Aminzadeh, T.B. Berge, D.L. Connolly (Eds.)Rodger, A., Laukamp, C., Haest, M., Cudahy, T., A simple quadratic method of absorption feature wavelength estimation in continuum removed spectra (2012) Remote Sensing of Environment, 118, pp. 273-283Shaw, R.C., Kratochvil, B., Near-infrared diffuse reflectance analysis of Athabasca oil sand (1990) Analytical Chemistry, 62, pp. 167-174Van Der Meer, F., Van Dijk, P., Van Der Werff, H., Yang, H., Remote sensing and petroleum seepage: a review and case study (2002) Terra Nova, 14, pp. 1-17van der Werff, H., Knowledge based remote sensing of complex objects recognition of spectral and spatial patterns resulting from natural hydrocarbon (2006) International Institute for Geo-Information Science and Earth Observation (ITC), p. 138. , (Enschede, The Netherlands

    Similar works