| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | mtc-m21d.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34T/454U5F5 | |||
| Repository | sid.inpe.br/mtc-m21d/2021/07.19.13.08 | |||
| Last Update | 2021:07.19.13.08.31 (UTC) simone | |||
| Metadata Repository | sid.inpe.br/mtc-m21d/2021/07.19.13.08.31 | |||
| Metadata Last Update | 2022:04.03.22.28.51 (UTC) administrator | |||
| Secondary Key | INPE--PRE/ | |||
| ISBN | 978-1-61208-871-6 | |||
| ISSN | 2308-393X | |||
| Citation Key | PachecoMaSiSoShEs:2021:ImClMe | |||
| Title | Image Classification Methods Assessment for Identification of Small-Scale Agriculture in Brazilian Amazon  | |||
| Year | 2021 | |||
| Access Date | 2024, May 05 | |||
| Secondary Type | PRE CI | |||
| Number of Files | 1 | |||
| Size | 1032 KiB | |||
| 2. Context | ||||
| Author | 1 Pacheco, Flávia Domingos 2 Matias, Maíra Ramalho 3 Silva, Gabriel Máximo da 4 Souza, Anielli Rosane de 5 Shimabukuro, Yosio Edemir 6 Escada, Maria Isabel Sobral | |||
| Resume Identifier | 1 2 3 4 5 8JMKD3MGP5W/3C9JJCQ 6 8JMKD3MGP5W/3C9JHRG | |||
| Group | 1 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 2 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 3 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 4 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 5 DIOTG-CGCT-INPE-MCTI-GOV-BR 6 DIOTG-CGCT-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) 5 Instituto Nacional de Pesquisas Espaciais (INPE) 6 Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Author e-Mail Address | 1 flavia.pacheco@inpe.br 2 mairamatias.geo@gmail.com 3 gabrielmaximo04@gmail.com 4 aniellirosane@yahoo.com.br 5 edemirshima@gmail.com 6 isabel.escada@inpe.br | |||
| Conference Name | International Conference on Advanced Geographic Information Systems, Applications, and Services, 13 (GEOProcessing) | |||
| Conference Location | Nice, France | |||
| Date | 19-22 july | |||
| Publisher | IARIA | |||
| Pages | 12-19 | |||
| Book Title | Proceedings | |||
| History (UTC) | 2021-07-19 13:09:05 :: simone -> administrator :: 2021 2022-04-03 22:28:51 :: administrator -> simone :: 2021 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Version Type | publisher | |||
| Keywords | digital image processing segmentation land use land cover smallholders planetscope | |||
| Abstract | This paper aims to test different methods for image classification focusing on small-scale agriculture in the region of Mocajuba and Cametá, municipalities in the Northeast of Pará state, Brazil. It is an important land use class, always ignored by Land-Use and Land-Cover monitoring systems because of its small size and variable spectral signature. We used an image from the PlanetScope Surface Reflectance Mosaics (Analysis Ready) with spatial resolution of 4.77 meters and 4 spectral bands (red, green, blue and infra-red). After proceeding with a multiresolution segmentation to identify image objects, two object-oriented classification algorithms were tested: Adapted Nearest-neighbor and C5.0 Decision trees algorithms. We selected 122 random points using the images available on Google Earth Pro as reference to assess the accuracy of classifications. Afterwards, confusion matrices were generated. Both methods showed similar overall accuracy and kappa value. However, C5.0 Decision trees reached a higher producers accuracy to small-scale agriculture (75%) in comparison to Adapted Nearest-neighbor (65%). The average size of the small-scale agriculture segments estimated was less than 1 ha in both maps, showing the need to carry out studies on scales of greater detail, preferably with images of high spatial resolution to represent these systems properly. In this study, C5.0 Decision trees had the best result, representing the most suitable method for mapping small-scale agriculture in Brazilian Amazon. | |||
| Area | SRE | |||
| Arrangement 1 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Image Classification Methods... | |||
| Arrangement 2 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Image Classification Methods... | |||
| 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/8JMKD3MGP3W34T/454U5F5 | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGP3W34T/454U5F5 | |||
| Language | en | |||
| Target File | geoprocessing_2021_1_40_30034.pdf | |||
| User Group | simone | |||
| Visibility | shown | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Next Higher Units | 8JMKD3MGPCW/3F3NU5S 8JMKD3MGPCW/46KUATE | |||
| Host Collection | urlib.net/www/2021/06.04.03.40 | |||
| 6. Notes | ||||
| Empty Fields | archivingpolicy archivist callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format label lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization parameterlist parentrepositories previousedition previouslowerunit progress project publisheraddress readergroup readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url volume | |||
| 7. Description control | ||||
| e-Mail (login) | simone | |||
| update | ||||