| 1. Identity statement | ||||
| Reference Type | Journal Article | |||
| Site | mtc-m21d.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34T/4935L2P | |||
| Repository | sid.inpe.br/mtc-m21d/2023/05.03.13.56 | |||
| Last Update | 2023:05.03.13.56.22 (UTC) simone | |||
| Metadata Repository | sid.inpe.br/mtc-m21d/2023/05.03.13.56.22 | |||
| Metadata Last Update | 2024:01.02.17.16.43 (UTC) administrator | |||
| DOI | 10.1117/1.JRS.17.014513 | |||
| ISSN | 1931-3195 | |||
| Citation Key | DinizGamReiOliMar:2023:PlBrUs | |||
| Title | Estimating stem volume of Eucalyptus sp. and Pinus sp. plantations in Brazil, using Sentinel-1B and ALOS-2/PALSAR-2 data  | |||
| Year | 2023 | |||
| Month | Jan. | |||
| Access Date | 2024, May 19 | |||
| Type of Work | journal article | |||
| Secondary Type | PRE PI | |||
| Number of Files | 1 | |||
| Size | 6539 KiB | |||
| 2. Context | ||||
| Author | 1 Diniz, Juliana Maria Ferreira de Souza 2 Gama, Fábio Furlan 3 Reis, Aliny Aparecida dos 4 Oliveira, Cleber Gonzales de 5 Marques, Eduardo Resende Girardi | |||
| Resume Identifier | 1 2 8JMKD3MGP5W/3C9JH3P | |||
| ORCID | 1 0000-0003-3642-7332 2 0000-0002-4585-5067 3 4 5 0000-0002-8690-3758 | |||
| Group | 1 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 2 DIOTG-CGCT-INPE-MCTI-GOV-BR | |||
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Universidade Estadual de Campinas (UNICAMP) 4 VISIONA Tecnologia Espacial 5 KLABIN S.A. | |||
| Author e-Mail Address | 1 julianadinizengflorestal@gmail.com 2 fabio.furlan@inpe.br 3 aareis@unicamp.br 4 cleber.oliveira@visionaespacial.com.br 5 eduardo.rgmarques@gmail.com | |||
| Journal | Journal of Applied Remote Sensing | |||
| Volume | 17 | |||
| Number | 1 | |||
| Pages | e014513 | |||
| Secondary Mark | A2_GEOGRAFIA B1_GEOCIÊNCIAS B1_CIÊNCIAS_AGRÁRIAS_I B1_BIODIVERSIDADE B5_CIÊNCIAS_AMBIENTAIS | |||
| History (UTC) | 2023-05-03 13:56:22 :: simone -> administrator :: 2023-05-03 13:56:23 :: administrator -> simone :: 2023 2023-05-03 13:56:53 :: simone -> administrator :: 2023 2024-01-02 17:16:43 :: administrator -> simone :: 2023 | |||
| 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 | machine learning multifrequency polarimetry synthetic aperture radar | |||
| Abstract | Multifrequency synthetic aperture radar (SAR) data have been applied to discriminate subtle differences in the vegetation and to better characterize its structural properties, since each SAR frequency will interact with the different sections of the vegetation canopy. In this study, our main objective was to evaluate the use of multifrequency Sentinel-1 and ALOS-2/PALSAR-2 data for stem volume estimations in Eucalyptus sp. and Pinus sp. plantations using three different machine learning algorithms: random forest (RF), support vector regression (SVR), and extreme gradient boosting (XGB). Different experiments were carried out using combinations of predictor variables derived from both SAR sensors: backscattering, polarimetric decompositions, and interferometry data, and field data considering specific models for Eucalyptus sp. and Pinus sp. and a generic model comprising all forest plantations data. The machine learning models using predictor variables derived from SAR data achieved moderately high accuracy to predict stem volume, mainly when SAR data were used in combination with stand age (Experiment iv). In the best prediction scenario (Experiment iv), the RF, SVR, and XGB models were able to explain 81.7%, 68.5%, and 81.8% [coefficient of variation (R2) values] of stem volume variability considering the generic models, respectively. Our results pointed out that the RF algorithm showed the best performance in predicting stem volume with significant good results and easier implementation in comparison with the other two algorithms (SVR and XGB). | |||
| Area | SRE | |||
| Arrangement 1 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Estimating stem volume... | |||
| Arrangement 2 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Estimating stem volume... | |||
| 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/4935L2P | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGP3W34T/4935L2P | |||
| Language | en | |||
| Target File | 014513_1.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/3F3NU5S 8JMKD3MGPCW/46KUATE | |||
| Citing Item List | sid.inpe.br/bibdigital/2013/10.18.22.34 3 sid.inpe.br/mtc-m21/2012/07.13.14.45.57 1 sid.inpe.br/bibdigital/2022/04.03.22.23 1 | |||
| Dissemination | WEBSCI; PORTALCAPES; COMPENDEX; SCOPUS. | |||
| Host Collection | urlib.net/www/2021/06.04.03.40 | |||
| 6. Notes | ||||
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes 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 | ||||