Multitemporal and multisensor signatures evaluation for lithologic classification
Focuses on the evaluation of the potentiality of remote sensing exploitation for geological applications in the Mediterranean area. The test site of the "Fossa Bradanica" (South of Italy) has been considered. Different data sets have been considered: optical multitemporal, microwave multit...
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| creator | Loizzo, R. Sylos Labini, G. Pappalepore, M. Pieri, P. Pasquariello, G. Antoninetti, M. |
| description | Focuses on the evaluation of the potentiality of remote sensing exploitation for geological applications in the Mediterranean area. The test site of the "Fossa Bradanica" (South of Italy) has been considered. Different data sets have been considered: optical multitemporal, microwave multitemporal and combined optical and microwave. On the basis of a maximum likelihood rule an analysis of the spectral signatures extracted from lithologic classes obtained by cartographic maps and ground truth has been performed, either on LANDSAT TM data or ERS-1 data. In order to reduce the vegetation influence in lithological signature evaluation vegetation mask is used. Then the best data combination and the best season of acquisition for the minimization of the confusion are defined. The obtained results are shown. |
| doi_str_mv | 10.1109/IGARSS.1995.524150 |
| format | Conference Proceeding |
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The test site of the "Fossa Bradanica" (South of Italy) has been considered. Different data sets have been considered: optical multitemporal, microwave multitemporal and combined optical and microwave. On the basis of a maximum likelihood rule an analysis of the spectral signatures extracted from lithologic classes obtained by cartographic maps and ground truth has been performed, either on LANDSAT TM data or ERS-1 data. In order to reduce the vegetation influence in lithological signature evaluation vegetation mask is used. Then the best data combination and the best season of acquisition for the minimization of the confusion are defined. The obtained results are shown.</description><identifier>ISBN: 0780325672</identifier><identifier>ISBN: 9780780325678</identifier><identifier>DOI: 10.1109/IGARSS.1995.524150</identifier><language>eng</language><publisher>IEEE</publisher><subject>Data analysis ; Data mining ; Geology ; Optical sensors ; Remote sensing ; Rivers ; Satellites ; Spectral analysis ; Testing ; Vegetation mapping</subject><ispartof>1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. 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Quantitative Remote Sensing for Science and Applications</title><addtitle>IGARSS</addtitle><description>Focuses on the evaluation of the potentiality of remote sensing exploitation for geological applications in the Mediterranean area. The test site of the "Fossa Bradanica" (South of Italy) has been considered. Different data sets have been considered: optical multitemporal, microwave multitemporal and combined optical and microwave. On the basis of a maximum likelihood rule an analysis of the spectral signatures extracted from lithologic classes obtained by cartographic maps and ground truth has been performed, either on LANDSAT TM data or ERS-1 data. In order to reduce the vegetation influence in lithological signature evaluation vegetation mask is used. Then the best data combination and the best season of acquisition for the minimization of the confusion are defined. The obtained results are shown.</description><subject>Data analysis</subject><subject>Data mining</subject><subject>Geology</subject><subject>Optical sensors</subject><subject>Remote sensing</subject><subject>Rivers</subject><subject>Satellites</subject><subject>Spectral analysis</subject><subject>Testing</subject><subject>Vegetation mapping</subject><isbn>0780325672</isbn><isbn>9780780325678</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1995</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9zrsOgjAYBeAmxsQbL8DUFxBboCqjMd4GB8WdNFjwN4WS_sXEtxcvs2c5yfmWQ4jPWcA5S2aH3eqcpgFPEhGIMOaC9ciILZYsCsV8EQ6Ih3hnXWIhong-JKdjqx04VTXGSk1lfaXVe0FVo7EUoayla61Cqh5St9KBqWnRiQZ3M9qUkNNcS0QoIP_ohPQLqVF5vx4Tf7u5rPdTUEpljYVK2mf2PRf9xRfOe0DT</recordid><startdate>1995</startdate><enddate>1995</enddate><creator>Loizzo, R.</creator><creator>Sylos Labini, G.</creator><creator>Pappalepore, M.</creator><creator>Pieri, P.</creator><creator>Pasquariello, G.</creator><creator>Antoninetti, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1995</creationdate><title>Multitemporal and multisensor signatures evaluation for lithologic classification</title><author>Loizzo, R. ; Sylos Labini, G. ; Pappalepore, M. ; Pieri, P. ; Pasquariello, G. ; Antoninetti, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_5241503</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1995</creationdate><topic>Data analysis</topic><topic>Data mining</topic><topic>Geology</topic><topic>Optical sensors</topic><topic>Remote sensing</topic><topic>Rivers</topic><topic>Satellites</topic><topic>Spectral analysis</topic><topic>Testing</topic><topic>Vegetation mapping</topic><toplevel>online_resources</toplevel><creatorcontrib>Loizzo, R.</creatorcontrib><creatorcontrib>Sylos Labini, G.</creatorcontrib><creatorcontrib>Pappalepore, M.</creatorcontrib><creatorcontrib>Pieri, P.</creatorcontrib><creatorcontrib>Pasquariello, G.</creatorcontrib><creatorcontrib>Antoninetti, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Loizzo, R.</au><au>Sylos Labini, G.</au><au>Pappalepore, M.</au><au>Pieri, P.</au><au>Pasquariello, G.</au><au>Antoninetti, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Multitemporal and multisensor signatures evaluation for lithologic classification</atitle><btitle>1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications</btitle><stitle>IGARSS</stitle><date>1995</date><risdate>1995</risdate><volume>3</volume><spage>2209</spage><epage>2211 vol.3</epage><pages>2209-2211 vol.3</pages><isbn>0780325672</isbn><isbn>9780780325678</isbn><abstract>Focuses on the evaluation of the potentiality of remote sensing exploitation for geological applications in the Mediterranean area. The test site of the "Fossa Bradanica" (South of Italy) has been considered. Different data sets have been considered: optical multitemporal, microwave multitemporal and combined optical and microwave. On the basis of a maximum likelihood rule an analysis of the spectral signatures extracted from lithologic classes obtained by cartographic maps and ground truth has been performed, either on LANDSAT TM data or ERS-1 data. In order to reduce the vegetation influence in lithological signature evaluation vegetation mask is used. Then the best data combination and the best season of acquisition for the minimization of the confusion are defined. The obtained results are shown.</abstract><pub>IEEE</pub><doi>10.1109/IGARSS.1995.524150</doi></addata></record> |
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| identifier | ISBN: 0780325672 |
| ispartof | 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications, 1995, Vol.3, p.2209-2211 vol.3 |
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| language | eng |
| recordid | cdi_ieee_primary_524150 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Data analysis Data mining Geology Optical sensors Remote sensing Rivers Satellites Spectral analysis Testing Vegetation mapping |
| title | Multitemporal and multisensor signatures evaluation for lithologic classification |
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