| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | mtc-m16d.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP7W/388RB7L |
| Repository | sid.inpe.br/mtc-m19/2010/09.13.17.00 |
| Last Update | 2010:09.13.17.24.03 (UTC) marciana |
| Metadata Repository | sid.inpe.br/mtc-m19/2010/09.13.17.00.24 |
| Metadata Last Update | 2020:04.28.18.34.18 (UTC) administrator |
| Secondary Key | INPE--PRE/ |
| DOI | 10.1590/S0100-204X2010000600008 |
| ISSN | 0100-204X |
| Citation Key | AdamiRizMorTheFer:2010:AmPrEs |
| Title | Amostragem probabilística estratificada por pontos para estimar a área cultivada com soja / Probabilistic stratified point sampling to estimate soybean crop area  |
| Year | 2010 |
| Month | July |
| Access Date | 2024, May 15 |
| Type of Work | journal article |
| Secondary Type | PRE PN |
| Number of Files | 1 |
| Size | 562 KiB |
| 2. Context | |
| Author | 1 Adami, Marcos 2 Rizzi, Rodrigo 3 Moreira, Mauricio Alves 4 Theodor Rudorff, Bernardo Friedrich 5 Ferreira, Camila Cossetin |
| Resume Identifier | 1 2 3 8JMKD3MGP5W/3C9JHT4 4 8JMKD3MGP5W/3C9JGKP |
| Group | 1 DSR-OBT-INPE-MCT-BR 2 3 DSR-OBT-INPE-MCT-BR 4 DSR-OBT-INPE-MCT-BR 5 DSR-OBT-INPE-MCT-BR |
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Univ Fed Pelotas, BR-96001970 Capao Do Leao, RS Brazil 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Instituto Nacional de Pesquisas Espaciais (INPE) |
| Journal | Pesquisa Agropecuária Brasileira |
| Volume | 45 |
| Number | 6 |
| Pages | 585-592 |
| Secondary Mark | B1_ARQUITETURA_E_URBANISMO B5_ASTRONOMIA_/_FÍSICA B4_BIOTECNOLOGIA B2_CIÊNCIA_DE_ALIMENTOS B1_CIÊNCIAS_AGRÁRIAS_I B1_CIÊNCIAS_BIOLÓGICAS_I B5_CIÊNCIAS_BIOLÓGICAS_II B2_ECOLOGIA_E_MEIO_AMBIENTE B1_ENGENHARIAS_I B2_ENGENHARIAS_II B1_ENGENHARIAS_III B1_ENGENHARIAS_IV B2_GEOCIÊNCIAS B1_GEOGRAFIA A2_INTERDISCIPLINAR B2_MEDICINA_II B1_MEDICINA_VETERINÁRIA B4_QUÍMICA B2_SAÚDE_COLETIVA B1_ZOOTECNIA_/_RECURSOS_PESQUEIROS |
| History (UTC) | 2011-09-13 18:01:03 :: marciana -> administrator :: 2010 2016-06-04 23:13:54 :: administrator -> marciana :: 2010 2016-10-09 18:42:17 :: marciana -> administrator :: 2010 2020-04-28 18:34:18 :: administrator -> simone :: 2010 |
| 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 | Estatísticas Agrícolas imagens de satélite Glycine max modelagem Sistema de Informação Geográfica. Glycine max agricultural statistics satellite image multitemporal images modeling geographic information systems Agriculture Glycine max agricultural statistics satellite image multitemporal images modeling geographic information systems statistics frame |
| Abstract | O objetivo deste trabalho foi avaliar o desempenho de um modelo probabilístico de amostragem estratificada por pontos, e definir um tamanho de amostra adequado para estimar a área cultivada com soja no Rio Grande do Sul. A área foi estratificada de acordo com a percentagem de soja cultivada em cada município do estado: menor que 20, de 20 a 40 e maior que 40%. Foram avaliadas estimativas obtidas por meio de seis tamanhos de amostras, resultantes da combinação de três níveis de significância (10, 5 e 1%) e dois valores de erro amostral (5 e 2,5%). Para cada tamanho de amostra, foram realizados 400 sorteios aleatórios. As estimativas foram avaliadas com base na área de soja obtida de um mapa temático de referência proveniente de uma cuidadosa classificação automática e visual de imagens multitemporais dos satélites TM/Landsat-5 e ETM+/Landsat-7 disponível para a safra 2000/2001. A área de soja no Rio Grande do Sul pode ser estimada por meio de um modelo de amostragem probabilística estratificada por pontos, sendo que a melhor estimativa é obtida para o maior tamanho amostral (1.990 pontos), com diferença de apenas -0,14% em relação à estimativa do mapa de referência e um coeficiente de variação de 6,98%. ABSTRACT: The objective of this work was to evaluate the performance of a probabilistic sampling model stratified by points and to define an appropriate sample size to estimate the cultivated soybean area in the state of Rio Grande do Sul, Brazil. The area was stratified according to the percentage of soybean cultivated in each state municipality: less than 20, from 20 to 40 and more than 40%. Estimates were evaluated based on six sample sizes, resulting from the combination of three significance levels (10, 5 and 1%) and two sampling errors (5 and 2,5%), choosing 400 random samples for each sample size. The estimates were compared to a reference soybean thematic map available for the crop year 2000/2001 that was derived from a careful automatic and visual classification of multitemporal TM/Landsat-5 and ETM+/Landsat-7 images. The soybean area in Rio Grande do Sul State can be estimated through a probabilistic sampling model stratified by points with best estimates obtained for the largest sample size (1,990 points), which differed -0.14% in relation to the estimate of the reference map and had a coefficient of variation of 6.98%. Abstract:The objective of this work was to evaluate the performance of a probabilistic sampling model stratified by points and to define an appropriate sample size to estimate the cultivated soybean area in the state of Rio Grande do Sul, Brazil. The area was stratified according to the percentage of soybean cultivated in each state municipality: less than 20, from 20 to 40 and more than 40%. Estimates were evaluated based on six sample sizes, resulting from the combination of three significance levels (10, 5 and 1%) and two sampling errors (5 and 2,5%), choosing 400 random samples for each sample size. The estimates were compared to a reference soybean thematic map available for the crop year 2000/2001 that was derived from a careful automatic and visual classification of multitemporal TM/Landsat-5 and ETM+/Landsat-7 images. The soybean area in Rio Grande do Sul State can be estimated through a probabilistic sampling model stratified by points with best estimates obtained for the largest sample size (1,990 points), which differed -0.14% in relation to the estimate of the reference map and had a coefficient of variation of 6.98%. |
| Area | SRE |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Amostragem probabilística estratificada... |
| 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/8JMKD3MGP7W/388RB7L |
| zipped data URL | http://urlib.net/zip/8JMKD3MGP7W/388RB7L |
| Language | pt |
| Target File | a08v45n6.pdf |
| User Group | administrator marciana |
| Reader Group | administrator marciana |
| Visibility | shown |
| Archiving Policy | allowpublisher allowfinaldraft |
| Update Permission | not transferred |
| 5. Allied materials | |
| Mirror Repository | sid.inpe.br/mtc-m19@80/2009/08.21.17.02.53 |
| Next Higher Units | 8JMKD3MGPCW/3ER446E |
| Citing Item List | sid.inpe.br/mtc-m21/2012/07.13.14.41 2 sid.inpe.br/mtc-m21/2012/07.13.14.56.26 1 |
| Dissemination | WEBSCI; PORTALCAPES; SCIELO. |
| Host Collection | sid.inpe.br/mtc-m19@80/2009/08.21.17.02 |
| 6. Notes | |
| Notes | Scopus CAB Abstracts AGRIS DOAJ Directory of Open Access Journals Free x |
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress electronicmailaddress format isbn label lineage mark nextedition orcid parameterlist parentrepositories previousedition previouslowerunit progress project readpermission rightsholder schedulinginformation secondarydate session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Description control | |
| e-Mail (login) | simone |
| update | |