| 1. Identity statement | ||||
| Reference Type | Journal Article | |||
| Site | mtc-m21c.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34R/42JUGCE | |||
| Repository | sid.inpe.br/mtc-m21c/2020/06.02.12.38 | |||
| Last Update | 2020:06.02.12.38.09 (UTC) simone | |||
| Metadata Repository | sid.inpe.br/mtc-m21c/2020/06.02.12.38.09 | |||
| Metadata Last Update | 2022:03.18.22.15.08 (UTC) administrator | |||
| DOI | 10.3390/RS12081288 | |||
| ISSN | 2072-4292 | |||
| Citation Key | BragaPDFTACSW:2020:TrCrDe | |||
| Title | Tree crown delineation algorithm based on a convolutional neural network  | |||
| Year | 2020 | |||
| Month | Apr. | |||
| Access Date | 2024, Apr. 19 | |||
| Type of Work | journal article | |||
| Secondary Type | PRE PI | |||
| Number of Files | 1 | |||
| Size | 22738 KiB | |||
| 2. Context | ||||
| Author | 1 Braga, José Renato Garcia 2 Peripato, Vinícius Borges Pereira 3 Dalagnol da Silva, Ricardo 4 Ferreira, Matheus P. 5 Tarabalka, Yuliya 6 Aragão, Luiz Eduardo Oliveira e Cruz de 7 Campos Velho, Haroldo Fraga de 8 Shiguemori, Elcio H. 9 Wagner, Fabien Hubert | |||
| Resume Identifier | 1 2 3 4 5 6 7 8JMKD3MGP5W/3C9JHC3 | |||
| Group | 1 SER-SRE-SESPG-INPE-MCTIC-GOV-BR 2 SER-SRE-SESPG-INPE-MCTIC-GOV-BR 3 SER-SRE-SESPG-INPE-MCTIC-GOV-BR 4 5 6 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 7 LABAC-COCTE-INPE-MCTIC-GOV-BR 8 9 DIDSR-CGOBT-INPE-MCTIC-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 Militar de Engenharia (IME) 5 Inria Sophia Antipolis 6 Instituto Nacional de Pesquisas Espaciais (INPE) 7 Instituto Nacional de Pesquisas Espaciais (INPE) 8 Instituto de Estudos Avançado (IEAv) 9 Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Author e-Mail Address | 1 2 peripatto@gmail.com 3 ricds@hotmail.com 4 pferreira.matheus@gmail.com 5 yuliya.tarabalka@inria.fr 6 luiz.aragao@inpe.br 7 haroldo.camposvelho@inpe.br 8 elcio@ieav.cta.br 9 wagner.h.fabien@gmail.com | |||
| Journal | Remote Sensing | |||
| Volume | 12 | |||
| Number | 8 | |||
| Pages | e1288 | |||
| Secondary Mark | B3_GEOGRAFIA B3_ENGENHARIAS_I B4_GEOCIÊNCIAS B4_CIÊNCIAS_AMBIENTAIS B5_CIÊNCIAS_AGRÁRIAS_I | |||
| History (UTC) | 2020-06-02 12:38:09 :: simone -> administrator :: 2020-06-02 12:38:09 :: administrator -> simone :: 2020 2020-06-02 12:39:42 :: simone -> administrator :: 2020 2020-07-08 17:10:56 :: administrator -> simone :: 2020 2020-12-14 14:15:53 :: simone -> administrator :: 2020 2022-03-18 22:15:08 :: administrator -> simone :: 2020 | |||
| 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 | tree crown delineation tropical forests optical satellite images deep learning | |||
| Abstract | Tropical forests concentrate the largest diversity of species on the planet and play a key role in maintaining environmental processes. Due to the importance of those forests, there is growing interest in mapping their components and getting information at an individual tree level to conduct reliable satellite-based forest inventory for biomass and species distribution qualification. Individual tree crown information could be manually gathered from high resolution satellite images; however, to achieve this task at large-scale, an algorithm to identify and delineate each tree crown individually, with high accuracy, is a prerequisite. In this study, we propose the application of a convolutional neural networkMask R-CNN algorithmto perform the tree crown detection and delineation. The algorithm uses very high-resolution satellite images from tropical forests. The results obtained are promisingthe Recall, Precision, and F1 score values obtained were were 0.81, 0.91, and 0.86, respectively. In the study site, the total of tree crowns delineated was 59, 062. These results suggest that this algorithm can be used to assist the planning and conduction of forest inventories. As the algorithm is based on a Deep Learning approach, it can be systematically trained and used for other regions. | |||
| Area | SRE | |||
| Arrangement 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Tree crown delineation... | |||
| Arrangement 2 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Tree crown delineation... | |||
| Arrangement 3 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Tree crown delineation... | |||
| 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/8JMKD3MGP3W34R/42JUGCE | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGP3W34R/42JUGCE | |||
| Language | en | |||
| Target File | remotesensing-12-01288-v3.pdf | |||
| User Group | simone | |||
| Reader Group | administrator simone | |||
| Visibility | shown | |||
| Archiving Policy | allowpublisher allowfinaldraft | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Next Higher Units | 8JMKD3MGPCW/3ER446E 8JMKD3MGPCW/3ESGTTP 8JMKD3MGPCW/3F3NU5S | |||
| Citing Item List | sid.inpe.br/mtc-m21/2012/07.13.14.49.40 2 sid.inpe.br/bibdigital/2013/09.22.23.14 2 sid.inpe.br/bibdigital/2013/10.18.22.34 1 | |||
| Dissemination | WEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS. | |||
| Host Collection | urlib.net/www/2017/11.22.19.04 | |||
| 6. Notes | ||||
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readpermission rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url | |||
| 7. Description control | ||||
| e-Mail (login) | simone | |||
| update | ||||