| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | plutao.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP3W/45U879M |
| Repository | sid.inpe.br/plutao/2021/12.09.15.05.16 (restricted access) |
| Last Update | 2021:12.15.11.01.09 (UTC) lattes |
| Metadata Repository | sid.inpe.br/plutao/2021/12.09.15.05.17 |
| Metadata Last Update | 2022:04.03.22.27.18 (UTC) administrator |
| DOI | 10.5753/jidm.2021.1786 |
| ISSN | 2178-7107 |
| Label | lattes: 1649941449641846 2 FelgueirasOrtCamNamKor:2021:ExGeMo |
| Citation Key | FelgueirasOrtCamNamKör:2021:ExGeMo |
| Title | Exploring Geostatistical Modeling and Visualization Techniques of Uncertainties for Categorical Spatial Data  |
| Year | 2021 |
| Access Date | 2024, May 18 |
| Type of Work | journal article |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 859 KiB |
| 2. Context | |
| Author | 1 Felgueiras, Carlos Alberto 2 Ortiz, Jussara de Oliveira 3 Camargo, Eduardo Celso Gerbi 4 Namikawa, Laércio Massaru 5 Körting, Thales Sehn |
| Resume Identifier | 1 8JMKD3MGP5W/3C9JGQD 2 8JMKD3MGP5W/3C9JHKL 3 8JMKD3MGP5W/3C9JGUK 4 8JMKD3MGP5W/3C9JHL5 |
| Group | 1 DIOTG-CGCT-INPE-MCTI-GOV-BR 2 DIOTG-CGCT-INPE-MCTI-GOV-BR 3 DIOTG-CGCT-INPE-MCTI-GOV-BR 4 DIOTG-CGCT-INPE-MCTI-GOV-BR 5 DIOTG-CGCT-INPE-MCTI-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) |
| Author e-Mail Address | 1 carlinhos.felg@gmail.com 2 jussara.ortiz@inpe.br 3 eduardo.camargo@inpe.br 4 namikawa@gmail.com 5 contato.tsk@gmail.com |
| Journal | Journal of Information and Data Management - JIDM |
| Volume | 12 |
| Number | 4 |
| Pages | 330-341 |
| Secondary Mark | B3_INTERDISCIPLINAR B3_CIÊNCIA_DA_COMPUTAÇÃO B4_CIÊNCIAS_SOCIAIS_APLICADAS_I B5_SAÚDE_COLETIVA B5_MEDICINA_II B5_ENGENHARIAS_III B5_CIÊNCIAS_BIOLÓGICAS_I B5_BIODIVERSIDADE |
| History (UTC) | 2021-12-16 19:08:12 :: lattes -> administrator :: 2021 2022-04-03 22:27:18 :: administrator -> simone :: 2021 |
| 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 | Indicator geostatistics Spatial Modeling of Categorical Attributes Uncertainty visualization |
| Abstract | This article presents and analyzes the indicator geostatistical modeling and some visualization techniques of uncertainty models for categorical spatial attributes. A set of sample points of some categorical attribute is used as input information. The indicator approach requires a transformation of sample points on fields of indicator samples according to the classes of interest. Experimental and theoretical semivariograms of the indicator fields are defined representing the spatial variation of the indicator information. The indicator fields, along with their semivariograms, are used to determine the uncertainty model, the conditioned probability distribution function, of the attribute at any location inside the geographic region delimited by the samples. The probability functions are considered for producing prediction and probability maps based on the maximum class probability criterion. These maps can be visualized using different techniques. In this article, it is considered individual visualization of the predicted and probability maps and a combination of them. The predicted maps can also be visualized with or without constraints related to the uncertainty probabilities. The combined visualizations are based on three-dimensional (3D) planar projection and on the RedGreen-Blue to Intensity-Hue-Saturation (RGB-IHS) fusion transformation techniques. The methodology of this article is illustrated by a case study with real data, a sample set of soil textures observed in an experimental farm located in the region of São Carlos city in São Paulo State, Brazil. The resulting maps of the case study are presented and the advantages and the drawbacks of the visualization options are analyzed and discussed. |
| Area | SRE |
| Arrangement | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Exploring Geostatistical Modeling... |
| 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 | felgueiras_exploring.pdf |
| Reader Group | administrator lattes |
| Visibility | shown |
| Read Permission | deny from all and allow from 150.163 |
| Update Permission | not transferred |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPCW/46KUATE |
| Citing Item List | sid.inpe.br/mtc-m21/2012/07.13.14.43.05 2 sid.inpe.br/mtc-m21/2012/07.13.14.53.06 1 sid.inpe.br/mtc-m21/2012/07.13.14.44.59 1 |
| Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notes | |
| Empty Fields | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress format isbn lineage mark mirrorrepository month nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url usergroup |
| 7. Description control | |
| e-Mail (login) | simone |
| update | |