| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | plutao.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | J8LNKAN8RW/3C649CL |
| Repository | dpi.inpe.br/plutao/2012/06.21.21.48 (restricted access) |
| Last Update | 2012:08.14.14.06.11 (UTC) administrator |
| Metadata Repository | dpi.inpe.br/plutao/2012/06.21.21.48.06 |
| Metadata Last Update | 2018:06.05.00.01.51 (UTC) administrator |
| DOI | 10.1016/j.isprsjprs.2012.03.010 |
| ISSN | 0924-2716 1872-8235 |
| Label | lattes: 9840759640842299 4 LiLuMorDutBat:2012:CoAnAL |
| Citation Key | LiLuMorDutBat:2012:CoAnAL |
| Title | A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region  |
| Year | 2012 |
| Month | June |
| Access Date | 2024, May 19 |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 2059 KiB |
| 2. Context | |
| Author | 1 Li, Guiying 2 Lu, Dengsheng 3 Moran, Emilio 4 Dutra, Luciano Vieira 5 Batistella, Mateus |
| Resume Identifier | 1 2 3 4 8JMKD3MGP5W/3C9JHMA |
| Group | 1 2 3 4 DPI-OBT-INPE-MCTI-GOV-BR |
| Affiliation | 1 Indiana University, Anthropological Center for Training and Research on Global Environmental Change, Bloomington, Indiana 47405 2 Indiana University, Anthropological Center for Training and Research on Global Environmental Change, Bloomington, Indiana 47405 3 Indiana University, Anthropological Center for Training and Research on Global Environmental Change, Bloomington, Indiana 47405 4 Instituto Nacional de Pesquisas Espaciais (INPE) |
| Author e-Mail Address | 1 2 3 4 dutra@dpi.inpe.br |
| e-Mail Address | dutra@dpi.inpe.br |
| Journal | ISPRS Journal of Photogrammetry and Remote Sensing |
| Volume | 70 |
| Pages | 26-38 |
| Secondary Mark | A1_CIÊNCIAS_AGRÁRIAS_I A2_ECOLOGIA_E_MEIO_AMBIENTE B1_ENGENHARIAS_IV A2_GEOCIÊNCIAS A1_INTERDISCIPLINAR |
| History (UTC) | 2012-06-22 00:11:01 :: lattes -> administrator :: 2012 2012-07-26 23:15:52 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012 2012-08-14 14:06:11 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012 2018-06-05 00:01:51 :: 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 | ALOS PALSAR RADARSAT Texture Land-cover classification Amazon |
| Abstract | This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Transformed divergence was used to identify potential textural images which were calculated with the gray-level co-occurrence matrix method. The standard deviation of selected textural images and correlation coefficients between them were then used to determine the best combination of texture images for land-cover classification. Classification results based on different scenarios with maximum likelihood classifier were compared. Based on the identified best scenarios, different classification algorithms maximum likelihood classifier, classification tree analysis, Fuzzy ARTMAP (a neural-network method), k-nearest neighbor, object-based classification, and support vector machine were compared for examining which algorithm was suitable for land-cover classification in the tropical moist region. This research indicates that the combination of radiometric images and their textures provided considerably better classification accuracies than individual datasets. The L-band data provided much better landcover classification than C-band data but neither L-band nor C-band was suitable for fine land-cover classification system, no matter which classification algorithm was used. L-band data provided reasonably good classification accuracies for coarse land-cover classification system such as forest, succession, agropasture, water, wetland, and urban with an overall classification accuracy of 72.2%, but C-band data provided only 54.7%. Compared to the maximum likelihood classifier, both classification tree analysis and Fuzzy ARTMAP provided better performances, object-based classification and support vector machine had similar performances, and k-nearest neighbor performed poorly. More research should address the use of multitemporal radar data and the integration of radar and optical sensor data for improving land-cover classification. |
| Area | SRE |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > A comparative analysis... |
| 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 | Guiying_et_al_2012.pdf |
| User Group | administrator lattes marciana secretaria.cpa@dir.inpe.br |
| Reader Group | administrator marciana |
| Visibility | shown |
| Archiving Policy | denypublisher denyfinaldraft24 |
| Read Permission | deny from all and allow from 150.163 |
| Update Permission | not transferred |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPCW/3EQCCU5 |
| Citing Item List | sid.inpe.br/bibdigital/2013/09.09.15.05 2 |
| Dissemination | WEBSCI; PORTALCAPES; MGA; COMPENDEX. |
| Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notes | |
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark mirrorrepository nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url |
| 7. Description control | |
| e-Mail (login) | marciana |
| update | |