| 1. Identity statement | ||||
| Reference Type | Journal Article | |||
| Site | mtc-m21d.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34T/45J5K6H | |||
| Repository | sid.inpe.br/mtc-m21d/2021/10.08.12.52 (restricted access) | |||
| Last Update | 2021:10.08.12.52.48 (UTC) simone | |||
| Metadata Repository | sid.inpe.br/mtc-m21d/2021/10.08.12.52.48 | |||
| Metadata Last Update | 2022:04.03.22.27.37 (UTC) administrator | |||
| DOI | 10.1080/01431161.2021.1978584 | |||
| ISSN | 0143-1161 | |||
| Citation Key | ChavesSoarSancFron:2021:CBDaCu | |||
| Title | CBERS data cubes for land use and land cover mapping in the Brazilian Cerrado agricultural belt  | |||
| Year | 2021 | |||
| Month | Nov. | |||
| Access Date | 2024, May 19 | |||
| Type of Work | journal article | |||
| Secondary Type | PRE PI | |||
| Number of Files | 1 | |||
| Size | 15319 KiB | |||
| 2. Context | ||||
| Author | 1 Chaves, Michel Eustáquio Dantas 2 Soares, Anderson R. 3 Sanches, Ieda Del Arco 4 Fronza, José Guilherme | |||
| ORCID | 1 0000-0002-1498-6830 2 0000-0001-6513-2192 3 0000-0003-1296-0933 4 0000-0002-0830-8101 | |||
| Group | 1 DIOTG-CGCT-INPE-MCTI-GOV-BR 2 3 DIOTG-CGCT-INPE-MCTI-GOV-BR 4 DIOTG-CGCT-INPE-MCTI-GOV-BR | |||
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Cognizant Technology Solutions 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Author e-Mail Address | 1 michel.chaves@inpe.br 2 3 iedasanches@gmail.com 4 guilherme.fronza@gmail.com | |||
| Journal | International Journal of Remote Sensing | |||
| Volume | 42 | |||
| Number | 21 | |||
| Pages | 8398-8432 | |||
| Secondary Mark | A1_PLANEJAMENTO_URBANO_E_REGIONAL_/_DEMOGRAFIA A2_INTERDISCIPLINAR A2_GEOGRAFIA A2_ENGENHARIAS_IV A2_ENGENHARIAS_III A2_ENGENHARIAS_I A2_CIÊNCIAS_AMBIENTAIS A2_CIÊNCIA_DA_COMPUTAÇÃO B1_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA B1_GEOCIÊNCIAS B1_ENGENHARIAS_II B1_CIÊNCIAS_AGRÁRIAS_I B1_BIODIVERSIDADE B2_SAÚDE_COLETIVA B2_ODONTOLOGIA B3_CIÊNCIAS_BIOLÓGICAS_I B3_BIOTECNOLOGIA B5_ASTRONOMIA_/_FÍSICA | |||
| History (UTC) | 2021-10-08 12:52:48 :: simone -> administrator :: 2021-10-08 12:52:50 :: administrator -> simone :: 2021 2021-10-08 12:53:36 :: simone -> administrator :: 2021 2022-04-03 22:27:37 :: 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 | |||
| Abstract | The agricultural frontier expansion in the Cerrado biome made Brazil a leader in commodity exports and is changing its landscape. Hence, efforts to accurate land use and land cover (LULC) monitoring in this region are strategic, due to its role in Brazil's food, environmental, and economic security policy. Thinking on planning and technical sovereignty in the spatial sector, the China-Brazil Earth Resources Satellite (CBERS) Program was launched to provide useful data for decision-makers to manage the Brazilian territory independently of external policies. Their data, especially from CBERS-4 Wide-Field Imager (CBERS-4/WFI), are largely applied in deforestation monitoring by remote sensing specialists but less applied than data from other image providers for machine learning-based LULC mapping due to the small number of spectral bands and limitations related to clouds and shadows detection. However, with advances in orbital data analysis, data cubes enabled storing and accessing large spatio-temporal analysis-ready data. Within this scope, the Brazil Data Cube Project (BDC) creates multidimensional data cubes from orbital sensors' data for all Brazilian territory. We applied BDC CBERS-4/WFI data cubes to generate LULC classifications for the Extremo Oeste Baiano agricultural belt correspondent to the 2017/2018 and 2019/2020 harvest periods, at two levels of detail: broad and crop type, incorporating ground truth samples, crop calendar knowledge, and vegetation indices to a dense time series analysis approach. Overall Accuracies were equal to 0.87 and 0.89 for broad, and 0.91 and 0.94 for crop type classifications. The results indicate CBERS-4/WFI data cubes as a useful tool for improving crop monitoring in the Cerrado biome based on machine learning. | |||
| Area | SRE | |||
| Arrangement | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > CBERS data cubes... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
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| 4. Conditions of access and use | ||||
| Language | en | |||
| Target File | chaves_cbers.pdf | |||
| User Group | simone | |||
| Reader Group | administrator simone | |||
| 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/46KUATE | |||
| Citing Item List | sid.inpe.br/bibdigital/2022/04.03.22.23 4 | |||
| Dissemination | WEBSCI; PORTALCAPES; COMPENDEX; SCOPUS. | |||
| Host Collection | urlib.net/www/2021/06.04.03.40 | |||
| 6. Notes | ||||
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn keywords label lineage mark mirrorrepository nextedition notes parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url | |||
| 7. Description control | ||||
| e-Mail (login) | simone | |||
| update | ||||