| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | marte.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Repository | dpi.inpe.br/sbsr@80/2008/11.17.14.03 | |||
| Last Update | 2009:03.30.21.45.32 (UTC) administrator | |||
| Metadata Repository | dpi.inpe.br/sbsr@80/2008/11.17.14.03.35 | |||
| Metadata Last Update | 2022:07.07.03.46.40 (UTC) administrator | |||
| Secondary Key | INPE-16045-PRE/10654 | |||
| ISBN | 978-85-17-00044-7 | |||
| Citation Key | SousaTeixSilv:2009:ClBiCa | |||
| Title | Classificação de bioma caatinga usando Support Vector Machines (SVM)  | |||
| Format | DVD, On-line. | |||
| Year | 2009 | |||
| Access Date | 2024, May 18 | |||
| Secondary Type | PRE CN | |||
| Number of Files | 1 | |||
| Size | 660 KiB | |||
| 2. Context | ||||
| Author | 1 Sousa, Beatriz Fernandes Simplicio 2 Teixeira, Adunias dos Santos 3 Silva, Francisco de Assis Tavares Ferreira da | |||
| Resume Identifier | 1 2 3 8JMKD3MGP5W/3C9JH4L | |||
| Group | 1 2 3 CRN-CCR-INPE-MCT-BR | |||
| Affiliation | 1 Universidade Federal do Ceará 2 Universidade Federal do Ceará 3 Instituto Nacional de Pesquisas Espaciais | |||
| Author e-Mail Address | 1 beatrizsimplicio@yahoo.com.br 2 adunias@ufc.br 3 tavares@roen.inpe.br | |||
| Editor | Epiphanio, José Carlos Neves Galvão, Lênio Soares | |||
| e-Mail Address | beatrizsimplicio@yahoo.com.br | |||
| Conference Name | Simpósio Brasileiro de Sensoriamento Remoto, 14 (SBSR) | |||
| Conference Location | Natal | |||
| Date | 25-30 abr. 2009 | |||
| Publisher | Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Publisher City | São José dos Campos | |||
| Pages | 7917-7924 | |||
| Book Title | Anais | |||
| Tertiary Type | Artigo | |||
| Organization | Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| History (UTC) | 2008-11-17 14:03:35 :: beatrizsimplicio@yahoo.com.br -> sbsr :: 2008-12-15 19:35:19 :: sbsr -> administrator :: 2009-04-20 16:28:52 :: administrator -> beatrizsimplicio@yahoo.com.br :: 2009-04-22 01:15:25 :: beatrizsimplicio@yahoo.com.br -> administrator :: 2009-06-16 13:14:54 :: administrator -> marciana :: 2009-06-22 13:55:17 :: marciana -> erich@sid.inpe.br :: 2009-06-26 17:54:12 :: erich@sid.inpe.br -> administrator :: 2009-08-05 01:55:47 :: administrator -> erich@sid.inpe.br :: 2010-05-14 02:40:34 :: erich@sid.inpe.br -> marciana :: 2011-02-16 14:17:05 :: marciana -> administrator :: 2009 2022-07-07 03:46:40 :: administrator -> :: 2009 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Keywords | artificial intelligence semi arid satellite image classification confusion matrix | |||
| Abstract | Support Vector Machines (SVMs) are a kind of neural network and a relatively new supervised classification technique to the land cover mapping community. This paper aims to analyze the performance of SVMs to classify caatinga biome and compare these results with the supervised classification method of maximum likelihood. The general procedure involved the classification from satellite image LANDSAT-TM, bands 2, 3 e 4. The classifications using SVM methods were made using commercial software (ENVI 4.3) and a toolbox in MATLAB 7.0 (SVM-KMToolbox). And the classification using the maximum likelihood were made using ENVI 4.3. The study area was Iguatu, Ceara, Brazil. Iguatu is located at Brazilian caatinga biome. Quantitative Validation has been done by comparison between 137 GPS collected points used as a ground truth and the image obtained of each classification proposed. Using these points, it was generated a confusion matrix to each classification and it was calculated the Kappa coefficient and the overall accuracy. Experimental results allow us to conclude through the Kappa coefficient values that SVM presented a superior performance comparing with the Maximum Likelihood algorithm. Same manner, it is also possible to conclude that the SVMKMToolbox presented superior performance comparing with the SVM of ENVI 4.3. | |||
| Area | SRE | |||
| Type | Técnicas de Classificação e Mineração de Dados | |||
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > CRCRN > Classificação de bioma... | |||
| doc Directory Content | access | |||
| source Directory Content |
| |||
| agreement Directory Content | there are no files | |||
| 4. Conditions of access and use | ||||
| data URL | http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.17.14.03 | |||
| zipped data URL | http://urlib.net/zip/dpi.inpe.br/sbsr@80/2008/11.17.14.03 | |||
| Language | pt | |||
| Target File | 7917-7924.pdf | |||
| User Group | administrator beatrizsimplicio@yahoo.com.br marciana erich@sid.inpe.br administrator | |||
| Reader Group | administrator beatrizsimplicio@yahoo.com.br | |||
| Visibility | shown | |||
| 5. Allied materials | ||||
| Mirror Repository | dpi.inpe.br/marte1@80/2009/05.26.17.02 | |||
| Next Higher Units | 8JMKD3MGPCW/3EUAPES | |||
| Citing Item List | sid.inpe.br/mtc-m21/2012/07.13.14.46.21 2 | |||
| Host Collection | dpi.inpe.br/netuno@1905/2006/07.17.20.18 dpi.inpe.br/banon/2003/12.10.19.30 | |||
| 6. Notes | ||||
| Sponsor | CNPq | |||
| Mark | 1 | |||
| Empty Fields | archivingpolicy archivist callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition identifier issn label lineage nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor shorttitle tertiarymark url versiontype volume | |||