| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | mtc-m21b.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34P/3N36JMP | |||
| Repository | sid.inpe.br/mtc-m21b/2016/12.20.17.50 | |||
| Last Update | 2021:02.12.13.33.25 (UTC) simone | |||
| Metadata Repository | sid.inpe.br/mtc-m21b/2016/12.20.17.50.17 | |||
| Metadata Last Update | 2023:08.16.17.49.25 (UTC) administrator | |||
| Secondary Key | INPE--PRE/ | |||
| Citation Key | MarettoKörCasFonSan:2016:SpAtSe | |||
| Title | Spectral attributes selection based on data mining for remote sensing image classification  | |||
| Year | 2016 | |||
| Access Date | 2024, May 11 | |||
| Secondary Type | PRE CI | |||
| Number of Files | 1 | |||
| Size | 1004 KiB | |||
| 2. Context | ||||
| Author | 1 Maretto, Raian 2 Körting, Thales Sehn 3 Castejon, Emiliano Ferreira 4 Fonseca, Leila Maria Garcia 5 Santos, Rafael Duarte Coelho dos | |||
| Resume Identifier | 1 2 3 4 8JMKD3MGP5W/3C9JHLD 5 8JMKD3MGP5W/3C9JJ4N | |||
| Group | 1 2 3 4 5 LAC-CTE-INPE-MCTI-GOV-BR | |||
| Affiliation | 1 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Author e-Mail Address | 1 2 thales.korting@inpe.br 3 emiliano.castejon@inpe.br 4 leila.fonseca@inpe.br 5 rafael.santos@inpe.br | |||
| Conference Name | Workshop de Computação Aplicada, 16 (WORCAP) | |||
| Conference Location | São José dos Campos, SP | |||
| Date | 25-26 out. | |||
| History (UTC) | 2016-12-20 17:50:29 :: simone -> administrator :: 2016 2016-12-21 02:22:02 :: administrator -> simone :: 2016 2016-12-22 16:44:58 :: simone -> administrator :: 2016 2018-06-04 02:41:43 :: administrator -> simone :: 2016 2021-02-12 13:33:26 :: simone -> administrator :: 2016 2023-08-16 17:49:25 :: administrator -> simone :: 2016 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Content Type | External Contribution | |||
| Abstract | Remote sensing images are a rich source of information for studying large-scale geographic areas. The increased accessibility of the new generation high-spatial resolution multispectral sensors has improved the level of complexity required in the analysis techniques. In particular, many traditional per-pixel analysis may not be suitable to high-spatial resolution imagery, due to its high-frequency components and the horizontal layover caused by off-nadir look angles [Im et al. 2008]. Aiming to overcome this problem, in the last decades, several approaches and platforms have been developed with algorithms that consider contextual information and pixel region properties [Körting et al. 2013; Syed et al. 2005; Walter 2004]. Current software can extract several statistical, spatial, color, texture or topological attributes. However, most of them often do not help to distinguish between the classes of interest, due to its high correlation. Thus, the attributes selection phase often relies on ad hoc decisions about what of them can better describe the classes. The huge number of attributes available makes a detailed exploratory time-consuming and dependent on expertise [Körting et al. 2013]. Many works have proved that data mining techniques can be useful to this purpose [Dash and Liu 1997; Kohavi and Kohavi 1997; Laliberte et al. 2012]. In this context, the main objective of this work is to analyze the correlation of the spectral attributes between a set of classes of interest, in order to verify what of them best distinguish these classes. A case study is presented over a small region of the city of São José dos Campos, using a WorldView-2 image. It is important to emphasize that although this study is in a preliminary stage, the results are promising and reached improvements in the accuracy of the classification, even as a good reduction in the computational time. | |||
| Area | SRE | |||
| Arrangement 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Spectral attributes selection... | |||
| Arrangement 2 | urlib.net > BDMCI > Fonds > WORCAP > XVI WORCAP > Spectral attributes selection... | |||
| Arrangement 3 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGIP > XVI WORCAP > Spectral attributes selection... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
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| 4. Conditions of access and use | ||||
| data URL | http://urlib.net/ibi/8JMKD3MGP3W34P/3N36JMP | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGP3W34P/3N36JMP | |||
| Language | en | |||
| Target File | maretto_spectral.pdf | |||
| User Group | simone | |||
| Reader Group | administrator simone | |||
| Visibility | shown | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Mirror Repository | urlib.net/www/2011/03.29.20.55 | |||
| Next Higher Units | 8JMKD3MGPCW/3ESGTTP 8JMKD3MGPDW34P/49L898E | |||
| Citing Item List | sid.inpe.br/mtc-m16c/2023/08.16.17.44 2 sid.inpe.br/mtc-m21/2012/07.13.14.58.32 1 | |||
| Host Collection | sid.inpe.br/mtc-m21b/2013/09.26.14.25.20 | |||
| 6. Notes | ||||
| Empty Fields | archivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format isbn issn keywords label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url versiontype volume | |||
| 7. Description control | ||||
| e-Mail (login) | simone | |||
| update | ||||