| 1. Identity statement | |
| Reference Type | Conference Paper (Conference Proceedings) |
| Site | plutao.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP3W/3MTMTJ5 |
| Repository | sid.inpe.br/plutao/2016/12.05.18.46.24 |
| Last Update | 2016:12.08.18.39.09 (UTC) lattes |
| Metadata Repository | sid.inpe.br/plutao/2016/12.05.18.46.25 |
| Metadata Last Update | 2018:06.04.23.26.11 (UTC) administrator |
| DOI | 10.13140/RG.2.2.21067.39206 |
| Label | lattes: 5156610731557884 1 GirolamoNetoPessKortFons:2016:DeAtFo |
| Citation Key | GirolamoNetoPessKörtFons:2016:DeAtFo |
| Title | Detecting atlantic forest patches applying geobia and data mining techniques  |
| Format | DVD |
| Year | 2016 |
| Access Date | 2024, Apr. 26 |
| Secondary Type | PRE CI |
| Number of Files | 1 |
| Size | 133 KiB |
| 2. Context | |
| Author | 1 Girolamo Neto, Cesare Di 2 Pessôa, Ana Carolina Moreira 3 Körting, Thales Sehn 4 Fonseca, Leila Maria Garcia |
| Resume Identifier | 1 2 3 4 8JMKD3MGP5W/3C9JHLD |
| Group | 1 SER-SRE-SPG-INPE-MCTI-GOV-BR 2 DSR-OBT-INPE-MCTI-GOV-BR 3 DPI-OBT-INPE-MCTI-GOV-BR 4 OBT-OBT-INPE-MCTI-GOV-BR |
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) |
| Author e-Mail Address | 1 cesare@dsr.inpe.br 2 ana.pessoa@inpe.br 3 thales.korting@inpe.br 4 leila.fonseca@inpe.br |
| Conference Name | GEOBIA 2016 : Solutions and Synergies |
| Conference Location | Enschede |
| Date | 14-16 set. |
| Book Title | Proceedings |
| History (UTC) | 2016-12-05 19:55:03 :: lattes -> administrator :: 2016 2016-12-06 19:45:58 :: administrator -> lattes :: 2016 2016-12-08 18:39:09 :: lattes -> administrator :: 2016 2018-06-04 23:26:11 :: 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 |
| Version Type | publisher |
| Keywords | Land cover Classification Landsat-8 Random Forest Artificial Neural Networks Feature selection |
| Abstract | Brazilian Atlantic Forest is one of the most devastated tropical forests in the world. Considering that approximately only 12% of its original extent still exists, studies in this area are highly relevant. In this context, this study maps the land cover of Atlantic Forest within the Protected Area of Macaé de Cima, in Rio de Janeiro State, Brazil, combining GEOBIA and data mining techniques on an OLI/Landsat-8 image. The methodology proposed in this work includes the following steps: (a) image pan-sharpening; (b) image segmentation; (c) feature selection; (d) classification and (e) model evaluation. A total of 15 features, including spectral information, vegetation indices and principal components were used to distinguish five patterns, including Water, Natural forest, Urban area, Bare soil/pasture and Rocky mountains. Features were selected considering well-known algorithms, such as Wrapper, the Correlation Feature Selection and GainRatio. Following, Artificial Neural Networks, Decision Trees and Random Forests classification algorithms were applied to the dataset. The best results were achieved by Artificial Neural Networks, when features were selected through the Wrapper algorithm. The global classification accuracy obtained was of 98.3%. All the algorithms presented great recall and precision values for the Natural forest, however the patterns of Urban area and Bare soil/pastures presented higher confusion. |
| Area | SRE |
| Arrangement 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Detecting atlantic forest... |
| Arrangement 2 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Detecting atlantic forest... |
| Arrangement 3 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > CGOBT > Detecting atlantic forest... |
| Arrangement 4 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Detecting atlantic forest... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| data URL | http://urlib.net/ibi/8JMKD3MGP3W/3MTMTJ5 |
| zipped data URL | http://urlib.net/zip/8JMKD3MGP3W/3MTMTJ5 |
| Language | en |
| Target File | girolamo_detecting.pdf |
| Reader Group | administrator lattes |
| Visibility | shown |
| Read Permission | allow from all |
| Update Permission | not transferred |
| 5. Allied materials | |
| Mirror Repository | urlib.net/www/2011/03.29.20.55 |
| Next Higher Units | 8JMKD3MGPCW/3EQCCU5 8JMKD3MGPCW/3ER446E 8JMKD3MGPCW/3EU2H28 8JMKD3MGPCW/3F3NU5S |
| URL (untrusted data) | http://proceedings.utwente.nl/362/ |
| Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notes | |
| Empty Fields | archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition editor isbn issn lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type usergroup volume |
| 7. Description control | |
| e-Mail (login) | simone |
| update | |