| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | plutao.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | J8LNKAN8RW/3C63LC5 |
| Repository | dpi.inpe.br/plutao/2012/06.21.18.33.21 (restricted access) |
| Last Update | 2012:08.10.13.19.06 (UTC) marciana |
| Metadata Repository | dpi.inpe.br/plutao/2012/06.21.18.33.22 |
| Metadata Last Update | 2018:06.05.00.01.44 (UTC) administrator |
| DOI | 10.1080/01431161.2012.661095 |
| ISSN | 0143-1161 |
| Label | lattes: 1913003589198061 3 QuintanoFernShimPere:2012:SpUn |
| Citation Key | QuintanoFernShimPere:2012:SpUn |
| Title | Spectral unmixing  |
| Year | 2012 |
| Month | Sep. |
| Access Date | 2024, May 18 |
| Type of Work | journal article |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 287 KiB |
| 2. Context | |
| Author | 1 Quintano, Carmen 2 Fernández-Manso, Alfonso 3 Shimabukuro, Yosio Edemir 4 Pereira, Gabriel |
| Resume Identifier | 1 2 3 8JMKD3MGP5W/3C9JJCQ |
| Group | 1 2 3 DSR-OBT-INPE-MCTI-GOV-BR 4 DSR-OBT-INPE-MCTI-GOV-BR |
| Affiliation | 1 †Electronic Technology Department, University of Valladolid, Valladolid 47014, Spain 2 Agrarian Sciences and Engineering Department, University of Leon Ponferrada 24010, Spain 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) |
| Author e-Mail Address | 1 2 3 yosio@ltid.inpe.br 4 gabriel@dsr.inpe.br |
| e-Mail Address | yosio@ltid.inpe.br |
| Journal | International Journal of Remote Sensing |
| Volume | 33 |
| Number | 17 |
| Pages | 5307-5340 |
| Secondary Mark | B3_BIOTECNOLOGIA A1_CIÊNCIA_DA_COMPUTAÇÃO A2_CIÊNCIAS_AGRÁRIAS_I B2_CIÊNCIAS_BIOLÓGICAS_I B1_ECOLOGIA_E_MEIO_AMBIENTE B1_ENGENHARIAS_I B2_ENGENHARIAS_II B1_ENGENHARIAS_III A2_ENGENHARIAS_IV B1_GEOCIÊNCIAS A1_GEOGRAFIA A2_INTERDISCIPLINAR B1_ODONTOLOGIA A1_PLANEJAMENTO_URBANO_E_REGIONAL_/_DEMOGRAFIA A2_SAÚDE_COLETIVA |
| History (UTC) | 2012-06-22 00:10:59 :: lattes -> administrator :: 2012 2012-07-12 19:37:40 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012 2012-08-10 13:19:06 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012 2012-09-10 18:38:54 :: administrator -> banon :: 2012 2012-09-26 16:39:51 :: banon -> administrator :: 2012 2016-06-04 01:08:01 :: administrator -> marciana :: 2012 2016-08-19 13:53:51 :: marciana -> administrator :: 2012 2018-06-05 00:01:44 :: administrator -> marciana :: 2012 |
| 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 | Complex model Computing time Constrained least squares method Digital numbers Endmembers Environmental problems Field of views Forest fires Ground surfaces Image pixels Matrix elements Remotely sensed images Satellite images Sensor measurements Specific location Spectral radiance Spectral unmixing Unmixing |
| Abstract | Satellite imagery is formed by finite digital numbers representing a specific location of ground surface in which each matrix element is denominated as a picture element or pixel. The pixels represent the sensor measurements of spectral radiance. The radiance recorded in the satellite images is then an integrated sum of the radiances of all targets within the instantaneous field of view (IFOV) of the sensors. Therefore, the radiation detected is caused by a mixture of several different materials within the image pixels. For this reason, spectral unmixing has been used as a technique for analysing the mixture of components in remotely sensed images for almost 30 years. Different spectral unmixing approaches have been described in the literature. In recent years, many authors have proposed more complex models that permit obtaining a higher accuracy and use less computing time. Although the most widely used method consists of employing a single set of endmembers (typically three or four) on the whole image and using a constrained least squares method to perform the unmixing linearly, every different algorithm has its own merits and no single approach is optimal and applicable to all cases. Additionally, the number of applications using unmixing techniques is increasing. Spectral unmixing techniques are used mainly for providing information to monitor different natural resources (agricultural, forest, geological, etc.) and environmental problems (erosion, deforestation, plagues and disease, forest fires, etc.). This article is a comprehensive exploration of all of the major unmixing approaches and their applications. |
| Area | SRE |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Spectral unmixing |
| 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 | Quintano_C.pdf |
| User Group | administrator banon lattes secretaria.cpa@dir.inpe.br |
| Reader Group | administrator marciana |
| Visibility | shown |
| Archiving Policy | denypublisher denyfinaldraft12 |
| 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; MGA; COMPENDEX. |
| Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notes | |
| Notes | Review |
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark mirrorrepository nextedition orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Description control | |
| e-Mail (login) | marciana |
| update | |