| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | mtc-m12.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 6qtX3pFwXQZ3r59YD6/JgabV |
| Repository | sid.inpe.br/iris@1912/2005/11.24.17.10 (restricted access) |
| Last Update | 2005:11.24.17.10.00 (UTC) marciana |
| Metadata Repository | sid.inpe.br/iris@1912/2005/11.24.17.10.53 |
| Metadata Last Update | 2018:06.05.00.40.33 (UTC) administrator |
| Secondary Key | INPE-13202-PRE/8458 |
| DOI | 10.1109/TGRS.2005.848692 |
| ISSN | 0196-2892 |
| Citation Key | HaertelShim:2005:SpLiMi |
| Title | Spectral linear mixing model in low spatial resolution image data  |
| Project | Sensoriamento Remoto Aplicado à Ecossistemas Terrestres |
| Year | 2005 |
| Month | Nov. |
| Access Date | 2024, May 23 |
| Type of Work | journal article |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 1697 KiB |
| 2. Context | |
| Author | 1 Haertel, V. F 2 Shimabukuro, Yosio Edemir |
| Resume Identifier | 1 2 8JMKD3MGP5W/3C9JJCQ |
| Group | 1 2 DSR-INPE-MCT-BR |
| Affiliation | 1 Center for Remote Sensing, Federal University at Rio Grande do Sul, Porto Alegre, RS, 91501-970, Brazil 2 Instituto Nacional de Pesquisas Espaciais, Divisão de Sensoriamento Remoto (INPE, DSR) |
| Journal | IEEE Transactions on Geoscience and Remote Sensing |
| Volume | 43 |
| Number | 11 |
| Pages | 2555-2562 |
| History (UTC) | 2006-03-17 14:44:13 :: sergio -> administrator :: 2006-09-03 21:43:05 :: administrator -> sergio :: 2007-04-23 21:07:06 :: sergio -> marciana :: 2008-04-04 17:27:28 :: marciana -> administrator :: 2008-06-09 19:20:30 :: administrator -> marciana :: 2011-11-03 11:59:02 :: marciana -> administrator :: 2005 2012-07-13 16:13:03 :: administrator -> marciana :: 2005 2013-03-04 13:55:08 :: marciana -> administrator :: 2005 2016-06-04 23:29:52 :: administrator -> marciana :: 2005 2016-09-14 12:35:08 :: marciana -> administrator :: 2005 2018-06-05 00:40:33 :: administrator -> marciana :: 2005 |
| 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 | Landset Enhanced Thematic Mapper Plus Low spatial resolution image data Mixed pixels Spectral reflectance Mathematical models Mixtures Optical resolving power Radiometers Spectrum analyzers Image analysis |
| Abstract | Different ways to estimate the spectral reflectance for the component classes in a mixture problem have been proposed in the literature (pure pixels, spectral library, field measurements). One of the most common approaches consists in the use of pure pixels, i.e., pixels that are covered by a single component class. This approach presents the advantage of allowing the extraction of the components' reflectance directly from the image data. This approach, however, is generally not feasible in the case of low spatial resolution image data, due to the large ground area covered by a single pixel. In this paper, a methodology aiming to overcome this limitation is proposed. The proposed approach makes use of the spectral linear mixing model. In the proposed methodology, the components' proportions in image data are estimated using a medium spatial resolution image as auxiliary data. The linear mixing model is then solved for the unknown spectral reflectances. Experiments are presented, using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Enhanced Thematic Mapper Plus, as low and medium spatial resolution image data, respectively, acquired on the same date over the Tapajos study site, Brazilian Amazon. Three component classes or endmembers are present in the scene covered by the experiment, namely vegetation, exposed soil, and shade. The components' spectral reflectance for the Terra MODIS spectral bands were then estimated by applying the proposed methodology. The reliability of these estimates is appraised by analyzing scatter diagrams produced by the Terra MODIS spectral bands and also by comparing the fraction images produced using both image datasets. This methodology appears appropriate for up-scaling information for regional and global studies. |
| Area | SRE |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Spectral linear mixing... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| Language | en |
| Target File | spectral linear.pdf |
| User Group | administrator marciana sergio |
| Reader Group | administrator marciana |
| Visibility | shown |
| Copy Holder | SID/SCD |
| Archiving Policy | denypublisher allowfinaldraft |
| Read Permission | deny from all and allow from 150.163 |
| Update Permission | not transferred |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPCW/3ER446E |
| Dissemination | WEBSCI; PORTALCAPES; IEEEXplore. |
| Host Collection | sid.inpe.br/banon/2001/04.06.10.52 |
| 6. Notes | |
| Empty Fields | alternatejournal archivist callnumber copyright creatorhistory descriptionlevel e-mailaddress electronicmailaddress format isbn label lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress rightsholder schedulinginformation secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Description control | |
| e-Mail (login) | marciana |
| update | |