| 1. Identity statement | |
| Reference Type | Conference Paper (Conference Proceedings) |
| Site | plutao.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP3W/3MTN3LM |
| Repository | sid.inpe.br/plutao/2016/12.05.19.24.01 |
| Last Update | 2016:12.28.13.12.23 (UTC) administrator |
| Metadata Repository | sid.inpe.br/plutao/2016/12.05.19.24.02 |
| Metadata Last Update | 2018:06.21.04.25.16 (UTC) administrator |
| Label | lattes: 2916855460918534 1 FelgueirasOrtiCama:2016:SPPRCA |
| Citation Key | FelgueirasOrtiCama:2016:SpPrCa |
| Title | Spatial predictions of categorical attributes constrained to uncertainty assessments  |
| Format | DVD |
| Year | 2016 |
| Access Date | 2024, May 18 |
| Secondary Type | PRE CI |
| Number of Files | 1 |
| Size | 399 KiB |
| 2. Context | |
| Author | 1 Felgueiras, Carlos Alberto 2 Ortiz, Jussara de Oliveira 3 Camargo, Eduardo Celso Gerbi |
| Resume Identifier | 1 8JMKD3MGP5W/3C9JGQD 2 8JMKD3MGP5W/3C9JHKL 3 8JMKD3MGP5W/3C9JGUK |
| Group | 1 DPI-OBT-INPE-MCTI-GOV-BR 2 DPI-OBT-INPE-MCTI-GOV-BR 3 DPI-OBT-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) |
| Author e-Mail Address | 1 carlos@dpi.inpe.br 2 jussara@dpi.inpe.br 3 eduardo@dpi.inpe.br |
| Conference Name | Simpósio Internacional SELPER, 17 |
| Conference Location | Puerto Iguazú, Misiones |
| Date | 7-11 nov. |
| Book Title | Proceedings |
| Tertiary Type | Paper |
| History (UTC) | 2016-12-08 15:27:41 :: lattes -> administrator :: 2016 2016-12-09 07:36:11 :: administrator -> lattes :: 2016 2016-12-22 16:51:57 :: lattes -> administrator :: 2016 2018-06-21 04:25:16 :: administrator -> simone :: 2016 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Content Type | External Contribution |
| Keywords | Spatial Analyzes indicator geostatistics Spatial Modeling of Categorical Attributes Uncertainty Assesments Constrained Classifications Decision Making in Environmental Planning |
| Area | SRE |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Spatial predictions of... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| data URL | http://urlib.net/ibi/8JMKD3MGP3W/3MTN3LM |
| zipped data URL | http://urlib.net/zip/8JMKD3MGP3W/3MTN3LM |
| Language | en |
| Target File | ConstrainedPredictionsv3.pdf |
| User Group | lattes self-uploading-INPE-MCTI-GOV-BR |
| Reader Group | administrator lattes |
| Visibility | shown |
| Read Permission | allow from all |
| Update Permission | not transferred |
| 5. Allied materials | |
| Mirror Repository | urlib.net/www/2011/03.29.20.55 |
| Next Higher Units | 8JMKD3MGPCW/3EQCCU5 |
| Citing Item List | sid.inpe.br/mtc-m21/2012/07.13.14.44.59 5 sid.inpe.br/bibdigital/2013/09.09.15.05 2 sid.inpe.br/mtc-m21/2012/07.13.14.43.05 2 |
| URL (untrusted data) | https://selperargentina2016.org/trabajos-aceptados/ |
| Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notes | |
| Notes | Informações Adicionais: Abstract This article explores the use of nonlinear geostatistical procedures, known as kriging and simulation indicator approaches, for spatial modeling of categorical attributes. The categorical information is initially represented by a set of sample points observed within a spatial region of interest. The original sample set is used to generate indicator fields take into account the classes of the categorical data. The indicator fields, or indicator samples, contain 0 and 1 attribute values according to the class they are representing. Empirical and theoretical semivariograms are built from the indicator samples to represent the spatial variation of each class in relation to the others. The geostatistical procedures, making use of the samples and the theoretical semivariograms, allow obtaining an approximation of the stochastic model, the conditioned probability distribution function (cpdf) of the categorical attribute at any desired spatial location. From any cpdf it is possible to assess optimal prediction, or estimate, and uncertainty values associated to the stochastic model. Optimal prediction as mean, median or any quantile values can be assessed. Uncertainty values are obtained by means of the maximum cpdf probability, Shannon entropy, or another criterion. The uncertainty values can be used to qualify the predictions and can also be considered to generate constrained spatial predictions, or constrained classifications, that are important in decision makings related to environmental planning activities, for example. The concepts here presented are applied and tested in a case study developed for a sample set of soil texture observed in an experimental farm in the region of São Carlos city in São Paulo State, Brazil. Four classes of soil texture are considered, sandy, medium clay, clay and too clay, in order to get the cpdf values. Some maps derived by constraints are presented and analyzed considering different probability values from the attribute stocha. |
| Empty Fields | abstract archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor isbn issn lineage mark nextedition numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark type versiontype volume |
| 7. Description control | |
| e-Mail (login) | simone |
| update | |