| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | mtc-m16d.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP7W/3E9AHNP |
| Repository | sid.inpe.br/mtc-m19/2013/06.08.22.47 (restricted access) |
| Last Update | 2013:07.03.18.21.42 (UTC) administrator |
| Metadata Repository | sid.inpe.br/mtc-m19/2013/06.08.22.47.52 |
| Metadata Last Update | 2018:06.05.04.14.09 (UTC) administrator |
| DOI | 10.1016/j.cageo.2013.02.007 |
| ISSN | 0098-3004 |
| Label | scopus |
| Citation Key | KörtingFonsCâma:2013:GeDaMi |
| Title | GeoDMA-Geographic Data Mining Analyst  |
| Year | 2013 |
| Access Date | 2024, May 23 |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 3632 KiB |
| 2. Context | |
| Author | 1 Körting, Thales Sehn 2 Fonseca, Leila Maria Garcia 3 Câmara, Gilberto |
| Resume Identifier | 1 2 8JMKD3MGP5W/3C9JHLD 3 8JMKD3MGP5W/3C9JHB8 |
| 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 thales@dpi.inpe.br 2 leila@dpi.inpe.br 3 gilberto.camara@inpe.br |
| e-Mail Address | marcelo.pazos@inpe.br |
| Journal | Computers and Geosciences |
| Volume | 57 |
| Pages | 133-145 |
| Secondary Mark | A1 A1 A1 A2 A2 B1 B1 B1 B2 B2 |
| History (UTC) | 2018-06-05 04:14:09 :: administrator -> marcelo.pazos@inpe.br :: 2013 |
| 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 | OBIA image processing data mining image segmentation multitemporal analysis landscape ecology |
| Abstract | Remote sensing images obtained by remote sensing are a key source of data for studying large-scale geographic areas. From 2013 onwards, a new generation of land remote sensing satellites from USA, China, Brazil, India and Europe will produce in 1. year as much data as 5 years of the Landsat-7 satellite. Thus, the research community needs new ways to analyze large data sets of remote sensing imagery. To address this need, this paper describes a toolbox for combing land remote sensing image analysis with data mining techniques. Data mining methods are being extensively used for statistical analysis, but up to now have had limited use in remote sensing image interpretation due to the lack of appropriate tools. The toolbox described in this paper is the Geographic Data Mining Analyst (GeoDMA). It has algorithms for segmentation, feature extraction, feature selection, classification, landscape metrics and multi-temporal methods for change detection and analysis. GeoDMA uses decision-tree strategies adapted for spatial data mining. It connects remotely sensed imagery with other geographic data types using access to local or remote database. GeoDMA has methods to assess the accuracy of simulation models, as well as tools for spatio-temporal analysis, including a visualization of time-series that helps users to find patterns in cyclic events. The software includes a new approach for analyzing spatio-temporal data based on polar coordinates transformation. This method creates a set of descriptive features that improves the classification accuracy of multi-temporal image databases. GeoDMA is tightly integrated with TerraView GIS, so its users have access to all traditional GIS features. To demonstrate GeoDMA, we show two case studies on land use and land cover change. |
| Area | SRE |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > GeoDMA-Geographic Data Mining... |
| 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 | 1-s2.0-S0098300413000538-main.pdf |
| User Group | administrator marcelo.pazos@inpe.br self-uploading-INPE-MCTI-GOV-BR |
| Reader Group | administrator marcelo.pazos@inpe.br |
| Visibility | shown |
| Archiving Policy | denypublisher denyfinaldraft24 |
| Read Permission | deny from all and allow from 150.163 |
| Update Permission | not transferred |
| 5. Allied materials | |
| Mirror Repository | iconet.com.br/banon/2006/11.26.21.31 |
| Next Higher Units | 8JMKD3MGPCW/3EQCCU5 |
| Citing Item List | sid.inpe.br/bibdigital/2013/09.09.15.05 4 |
| URL (untrusted data) | http://dx.doi.org/10.1016/j.cageo.2013.02.007 |
| Dissemination | WEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS. |
| Host Collection | sid.inpe.br/mtc-m19@80/2009/08.21.17.02 |
| 6. Notes | |
| Notes | upplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.cageo.2013.02.007. |
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark month nextedition number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype typeofwork |
| 7. Description control | |
| e-Mail (login) | marcelo.pazos@inpe.br |
| update | |