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| 2. |  | GALLO, D.; NAKANO, O.; SILVEIRA NETO, S.; CARVALHO, R. P. L.; BATISTA, G. C. de; BERTI FILHO, E.; PARRA, J. R. P.; ZUCCHI, R. A.; ALVES, S. B. Manual de entomologia agrícola. Sao Paulo: Agronômica Ceres, 1978. 531 p.| Biblioteca(s): Embrapa Acre; Embrapa Agropecuária Oeste; Embrapa Algodão; Embrapa Amazônia Oriental; Embrapa Arroz e Feijão; Embrapa Clima Temperado; Embrapa Florestas; Embrapa Hortaliças; Embrapa Meio Norte / UEP-Parnaíba; Embrapa Semiárido; Embrapa Soja; Embrapa Tabuleiros Costeiros; Embrapa Uva e Vinho. MenosEmbrapa Acre; Embrapa Agropecuária Oeste; Embrapa Algodão; Embrapa Amazônia Oriental; Embrapa Arroz e Feijão; Embrapa Clima Temperado; Embrapa Florestas; Embrapa Hortaliças; Embrapa Meio Norte / UEP-Parnaíba; Embrapa Semiárido... Mostrar Todas |
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| 3. | | GALLO, D.; NAKANO, O.; SILVEIRA NETO, S.; CARVALHO, R. P. L.; BAPTISTA, G. C. de; BERTI FILHO, E.; PARRA, J. R. P.; ZUCCHI, R. A.; ALVES, S. B.; VENDRAMIM, J. D.; MARCHINI, L. C.; LOPES, J. R. S.; OMOTO, C. Entomologia agrícola. Piracicaba: FEALQ, 2002. 920p. il. (FEALQ. Biblioteca de CIências Agrárias Luiz de Queiroz, 10).| Biblioteca(s): Embrapa Acre; Embrapa Arroz e Feijão; Embrapa Hortaliças; Embrapa Meio Ambiente; Embrapa Meio Norte / UEP-Parnaíba; Embrapa Milho e Sorgo; Embrapa Pecuária Sudeste; Embrapa Suínos e Aves. |
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| 4. | | GALLO, D.; NAKANO, O.; SILVEIRA NETO, S.; CARVALHO, R. P. L.; BATISTA, G. C. de; BERTI FILHO, E.; PARRA, J. R. P.; ZUCCHI, R. A.; ALVES, S. B.; VENDRAMIM, J. D. Manual de entomologia agricola. 2. ed. Sao Paulo: Agronomica Ceres, 1988. 649 p.| Biblioteca(s): Embrapa Acre; Embrapa Amapá; Embrapa Arroz e Feijão; Embrapa Cerrados; Embrapa Cocais; Embrapa Florestas; Embrapa Hortaliças; Embrapa Meio Ambiente; Embrapa Meio-Norte; Embrapa Milho e Sorgo; Embrapa Pantanal; Embrapa Recursos Genéticos e Biotecnologia; Embrapa Rondônia; Embrapa Trigo. MenosEmbrapa Acre; Embrapa Amapá; Embrapa Arroz e Feijão; Embrapa Cerrados; Embrapa Cocais; Embrapa Florestas; Embrapa Hortaliças; Embrapa Meio Ambiente; Embrapa Meio-Norte; Embrapa Milho e Sorgo... Mostrar Todas |
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| Registros recuperados : 4 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
08/11/2019 |
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Data da última atualização: |
11/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
SAMUEL-ROSA, A.; DALMOLIN, R. S. D.; MOURA-BRUNO, J. M.; TEIXEIRA, W. G.; FILIPPINI ALBA, J. M. |
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Afiliação: |
ALESSANDRO SAMUEL-ROSA, UTFPR; RICARDO SIMÃO DINIZ DALMOLIN, UFSM; JEAN MICHEL MOURA-BUENO, UFSM; WENCESLAU GERALDES TEIXEIRA, CNPS; JOSE MARIA FILIPPINI ALBA, CPACT. |
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Título: |
Open legacy soil survey data in Brazil: geospatial data quality and how to improve it. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Scientia Agricola, v. 77, n. 1, e20170430, 2020. |
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DOI: |
https://doi.org/10.1590/1678-992X-2017-0430 |
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Idioma: |
Inglês |
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Conteúdo: |
Spatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil observations, estimated using the web mapping service, were validated with the true coordinates measured in the field. Overall, inconsistencies of different types and magnitudes were found in half of the observations, causing mild to severe misplacements. The involuntary substitution of symbols and numeric characters with similar appearance when recording geospatial data was the most common typing mistake. Among the geospatial data sources, the web mapping service was the most useful, due to operational advantages and lower positional error (~6 m). However, the quality of the description of the observation location controls the accuracy of estimated coordinates. Thus, the error of coordinates estimated using the web mapping service ranged between 30 and 1000 m. This is equivalent to coordinates measured from arc-seconds to arc-minutes, respectively. Under this scenario, the feedback from soil survey experts is crucial to improving the quality of geospatial data. MenosSpatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil observations, estimated using the web mapping service, were validated with the true coordinates measured in the field. Overall, inconsistencies of different types and magnitudes were found in half of the observations, causing mild to severe misplacements. The involuntary substitution of symbols and numeric characters with similar appearance when recording geospatial data was the most common typing mistake. Among the geospatial data sources, the web mapping service was the most useful, due to operational advantages and lower positional error (~6 m). However, the quality of the description of the observation location controls the accuracy of estimated coordinates. Thus, the error of coordinates estimated using the web mapping... Mostrar Tudo |
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Palavras-Chave: |
Digital soil mapping; Free Brazilian Repository for Open Soil Data; Mapeamento digital do solo; Pedometrics; PronaSolos; Soil data recovery. |
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Thesagro: |
Base de Dados; Solo. |
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Thesaurus NAL: |
Databases; Soil. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/204430/1/Open-legacy-soil-survey-data-in-Brazil-2020.pdf
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Marc: |
LEADER 02659naa a2200301 a 4500
001 2114070
005 2021-11-11
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1590/1678-992X-2017-0430$2DOI
100 1 $aSAMUEL-ROSA, A.
245 $aOpen legacy soil survey data in Brazil$bgeospatial data quality and how to improve it.$h[electronic resource]
260 $c2020
520 $aSpatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil observations, estimated using the web mapping service, were validated with the true coordinates measured in the field. Overall, inconsistencies of different types and magnitudes were found in half of the observations, causing mild to severe misplacements. The involuntary substitution of symbols and numeric characters with similar appearance when recording geospatial data was the most common typing mistake. Among the geospatial data sources, the web mapping service was the most useful, due to operational advantages and lower positional error (~6 m). However, the quality of the description of the observation location controls the accuracy of estimated coordinates. Thus, the error of coordinates estimated using the web mapping service ranged between 30 and 1000 m. This is equivalent to coordinates measured from arc-seconds to arc-minutes, respectively. Under this scenario, the feedback from soil survey experts is crucial to improving the quality of geospatial data.
650 $aDatabases
650 $aSoil
650 $aBase de Dados
650 $aSolo
653 $aDigital soil mapping
653 $aFree Brazilian Repository for Open Soil Data
653 $aMapeamento digital do solo
653 $aPedometrics
653 $aPronaSolos
653 $aSoil data recovery
700 1 $aDALMOLIN, R. S. D.
700 1 $aMOURA-BRUNO, J. M.
700 1 $aTEIXEIRA, W. G.
700 1 $aFILIPPINI ALBA, J. M.
773 $tScientia Agricola$gv. 77, n. 1, e20170430, 2020.
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Embrapa Solos (CNPS) |
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