| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | mtc-m21c.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34R/3U5UNR9 | |||
| Repository | sid.inpe.br/mtc-m21c/2019/09.30.13.02.40 | |||
| Metadata Repository | sid.inpe.br/mtc-m21c/2019/09.30.13.02.41 | |||
| Metadata Last Update | 2020:01.06.11.42.22 (UTC) administrator | |||
| Secondary Key | INPE--PRE/ | |||
| Citation Key | AlmeidaGaArOmJaPeSa:2019:SeHyVa | |||
| Title | Selection of hyperspectral variables for aboveground biomass estimation in the Brazilian Amazon  | |||
| Year | 2019 | |||
| Access Date | 2024, Apr. 26 | |||
| Secondary Type | PRE CI | |||
| 2. Context | ||||
| Author | 1 Almeida, Catherine Torres de 2 Galvão, Lênio Soares 3 Aragão, Luiz Eduardo Oliveira e Cruz de 4 Ometto, Jean Pierre Henry Balbaud 5 Jacon, Aline Daniele 6 Pereira, Francisca Rocha de Souza 7 Sato, Luciane Yumie | |||
| Resume Identifier | 1 2 8JMKD3MGP5W/3C9JHLF | |||
| Group | 1 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 2 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 3 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 4 COCST-COCST-INPE-MCTIC-GOV-BR 5 6 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 7 COCST-COCST-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 Nacional de Pesquisas Espaciais (INPE) 5 Instituto Nacional de Pesquisas Espaciais (INPE) 6 Instituto Nacional de Pesquisas Espaciais (INPE) 7 Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Author e-Mail Address | 1 catherine.almeida@inpe.br 2 lenio.galvao@inpe.br 3 luiz.aragao@inpe.br 4 jean.ometto@inpe.br 5 6 francisca.pereira@inpe.br 7 luciane.sato@inpe.br | |||
| Conference Name | Congresso Mundial da IUFRO | |||
| Conference Location | Curitiba, PR | |||
| Date | 29 set. - 05 out. | |||
| History (UTC) | 2019-09-30 13:02:41 :: simone -> administrator :: 2019-10-01 16:31:12 :: administrator -> simone :: 2019 2019-12-06 19:28:55 :: simone -> administrator :: 2019 2020-01-06 11:42:22 :: administrator -> simone :: 2019 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Content Type | External Contribution | |||
| Abstract | Due to the limited coverage of field Aboveground Biomass (AGB), remote sensing becomes an alternative for monitoring carbon stocks at the landscape scale. However, the most commonly used sensors have limited spectral resolution. Hyperspectral imaging (HSI) provides high-resolution information, although its high data dimensionality becomes a challenge for modeling. In this context, selection of suitable variables is a critical step for estimating AGB from HSI data. Support Vector Regression coupled with the Recursive Feature Elimination approach (SVR-RFE) can produce parsimonious models from a reduced subset of features. We applied the SVR-RFE in a 5-fold cross-validation strategy with 5 repetitions to determine which hyperspectral variables were most effective to estimate AGB. We used field AGB from 147 inventory plots across the Brazilian Amazon and 64 plot-level HSI metrics, including 14 reflectance bands, 30 vegetation indices, continuum-removal absorption features at five wavelengths (495, 670, 980, 1200, and 2100 nm), and endmember fractions (green vegetation, shade, and non-photosynthetic vegetation/soil) from Spectral Mixture Analysis. The SVR-RFE explained 67% of the AGB variation, by selecting eight HSI variables. The three most effective variables came from the shortwave infrared region (width and depth of the 2100-nm absorption band and the NDNI index), related to canopy moisture and lignin-cellulose-nitrogen absorption bands. Four metrics were retrieved from the water absorption band centered at 980 nm (depth, asymmetry, and the indices PWI and LWVI1). The width of the band placed at 495 nm was also selected. SVR-RFE proved to be an efficient technique for estimating AGB from HSI data. | |||
| Area | SRE | |||
| Arrangement 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Selection of hyperspectral... | |||
| Arrangement 2 | urlib.net > Fonds > Produção anterior à 2021 > COCST > Selection of hyperspectral... | |||
| doc Directory Content | there are no files | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
| |||
| 4. Conditions of access and use | ||||
| Language | en | |||
| User Group | simone | |||
| Reader Group | administrator simone | |||
| Visibility | shown | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Next Higher Units | 8JMKD3MGPCW/3ER446E 8JMKD3MGPCW/3F3T29H | |||
| Host Collection | urlib.net/www/2017/11.22.19.04 | |||
| 6. Notes | ||||
| Empty Fields | archivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format isbn issn keywords label lineage mark mirrorrepository nextedition notes numberoffiles numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle size sponsor subject targetfile tertiarymark tertiarytype type url versiontype volume | |||
| 7. Description control | ||||
| e-Mail (login) | simone | |||
| update | ||||