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		<isbn>978-85-17-00088-1</isbn>
		<label>59376</label>
		<citationkey>ScafuttoSouz:2017:AvApTr</citationkey>
		<title>Avaliação da aplicação da transformação wavelet e análise de componentes independentes em imagens hiperespectrais no LWIR para a detecção de plumas de metano em regiões continentais</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>1173 KiB</size>
		<author>Scafutto, Rebecca Del Papa Moreira,</author>
		<author>Souza Filho, Carlos Roberto,</author>
		<electronicmailaddress>rebecca.scafutto@gmail.com</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<e-mailaddress>daniela.seki@inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)</conferencename>
		<conferencelocation>Santos</conferencelocation>
		<date>28-31 maio 2017</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>7643-7650</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>Research focused on the detection of methane (CH4) emissions has been gaining attention. Methane is the main component of natural gas and emission rates related to the oil industry comprises a large percentage of the global budget. However, these are still poor explored sources and contributions for methane concentration in the atmosphere from this segment are not well defined. Remote sensing tools have the potential to assist in the detection of fugitive CH4 emissions, which escapes through leaks in the pipeline network or storage tanks in refineries. Large spatial cover combined with high spectral resolution of airborne hyperspectral imaging sensors supports the direct mapping of gas plumes. Here, we process images acquired with the thermal imaging sensor Hytes (NASA) from Kern River Oil Field (California  EUA) with wavelets transformation and Independent Component Analysis (ICA) technique. Preliminary results demonstrate that these techniques can be used for the detection of CH4 sources. The methane plumes from storage tanks were identified and the spectral features of the gas (7.6 - 7.9 µm) highlighted. The methodology study here can be useful for the detection of methane sources related to the oil industry, assisting to reduce production losses and refine estimations of CH4 emission rates from this segment.</abstract>
		<area>SRE</area>
		<type>Sensoriamento remoto hiperespectral</type>
		<language>pt</language>
		<targetfile>59376.pdf</targetfile>
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		<url>http://marte2.sid.inpe.br/rep-/sid.inpe.br/marte2/2017/10.27.16.27</url>
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