| dc.creator | Asadzadeh | |
| dc.creator | S; de Souza | |
| dc.creator | CR | |
| dc.date | 2016 | |
| dc.date | 2016-12-06T18:30:12Z | |
| dc.date | 2016-12-06T18:30:12Z | |
| dc.date.accessioned | 2018-03-29T02:02:46Z | |
| dc.date.available | 2018-03-29T02:02:46Z | |
| dc.identifier | | |
| dc.identifier | International Journal Of Applied Earth Observation And Geoinformation. ELSEVIER SCIENCE BV, n. 47, p. 69 - 90. | |
| dc.identifier | 0303-2434 | |
| dc.identifier | WOS:000371099000007 | |
| dc.identifier | 10.1016/j.jag.2015.12.004 | |
| dc.identifier | http://www-sciencedirect-com.ez88.periodicos.capes.gov.br/science/article/pii/S0303243415300696 | |
| dc.identifier | http://repositorio.unicamp.br/jspui/handle/REPOSIP/319980 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1310746 | |
| dc.description | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) | |
| dc.description | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
| dc.description | In this work, many of the fundamental and advanced spectral processing methods available to geologic remote sensing are reviewed. A novel categorization scheme is proposed that groups the techniques into knowledge-based and data-driven approaches, according to the type and availability of reference data. The. two categories are compared and their characteristics and geologic outcomes are contrasted. Using an oil-sand sample scanned through the sisuCHEMA hyperspectral imaging system as a case study, the effectiveness of selected processing techniques from each category is demonstrated. The techniques used to bridge between the spectral data and other geoscience products are then discussed. Subsequently, the hybridization of the two approaches is shown to yield some of the most robust processing techniques available to multi- and hyperspectral remote sensing. Ultimately, current and future challenges that spectral analysis are expected to overcome and some potential trends are highlighted. (C) 2015 Elsevier B.V. All rights reserved. | |
| dc.description | 47 | |
| dc.description | | |
| dc.description | 69 | |
| dc.description | 90 | |
| dc.description | CAPES | |
| dc.description | CNPq | |
| dc.description | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) | |
| dc.description | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
| dc.description | | |
| dc.description | | |
| dc.description | | |
| dc.language | English | |
| dc.publisher | ELSEVIER SCIENCE BV | |
| dc.publisher | AMSTERDAM | |
| dc.relation | International Journal of Applied Earth Observation and Geoinformation | |
| dc.rights | fechado | |
| dc.source | WOS | |
| dc.subject | Spectral Processing | |
| dc.subject | Geologic Remote Sensing | |
| dc.subject | Mineral Mapping | |
| dc.subject | Algorithm | |
| dc.subject | Categorization | |
| dc.subject | Multispectral | |
| dc.subject | Hyperspectral | |
| dc.title | A Review On Spectral Processing Methods For Geological Remote Sensing | |
| dc.type | Resenha | |
