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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Milho e Sorgo. |
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Data corrente: |
07/12/2018 |
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Data da última atualização: |
07/01/2020 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
SAMUEL-ROSA, A.; DALMOLIN, R. S. D.; GUBIANI, P. I.; OLIVEIRA, S. R. de M.; TEIXEIRA, W. G.; VIANA, J. H. M.; RIBEIRO, E.; TORNQUIST, C. G.; ANJOS, L. H. C. dos; SOUZA, J. J. E. L. de; OTTONI, M. V.; MEDEIROS, P. S. C. de; GRIS, D. J.; ROSIN, N. A.; BUENO, J. M. M.; SANTOS, H. G. dos; WEBER, E. J.; FLORES, C. A.; COSTA, E. M.; OLIVEIRA, R. P. de; FILIPPINI ALBA, J. M.; PEDROSO NETO, J. C.; PEDRON, F. de A.; CAVIGLIONE, J. H.; VALLADARES, G. S.; MIRANDA, C. S. S.; DEMATTÊ, J. A. M.; MARQUES JÚNIOR, J.; SIQUEIRA, D. S.; AQUINO, R. E. de; SILVERO, N. E. Q.; GENÚ, A. M.; BROETTO, T.; CANCIAN, L. C.; MIGUEL, P.; ZALAMENA, J.; DOTTO, A. C.; ALMEIDA, J. A. de; REICHERT.; CURCIO, G. R.; COLLIER, L. S.; CARVALHO JUNIOR, W. de; FONTANA, A.; OLIVEIRA, A. P. de; VOGELMANN, E. S.; MALLMANN, F. J. K.; VASQUES, G. de M.; LEPSCH, I. F.; FINK, J. R.; KER, J. C.; SILVA, L. S. da; FREITAS, P. L. de; BIELUCZYK, B.; TIECHER, T. |
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Afiliação: |
ALESSANDRO SAMUEL-ROSA, UFSM; RICARDO SIMÃO DINIZ DALMOLIN, UFSM; PAULO IVONIR GUBIANI, UFSM; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; WENCESLAU GERALDES TEIXEIRA, CNPS; JOAO HERBERT MOREIRA VIANA, CNPMS; ELOI RIBEIRO, ISRIC World Soil Information; CARLOS GUSTAVO TORNQUIST, UFRGS; LÚCIA HELENA CUNHA DOS ANJOS, UFRRJ; JOSÉ JOÃO LELIS LEAL DE SOUZA, UFRGN; MARTA VASCONCELOS OTTONI, Serviço Geológico do Brasil; PAULA SUÉLEN CORRÊA DE MEDEIROS, IBGE; DIEGO JOSÉ GRIS, UFSM; NÍCOLAS AUGUSTO ROSIN, UFSM; JEAN MICHEL MOURA BUENO, UFSM; HUMBERTO GONCALVES DOS SANTOS, CNPS; ELISEU JOSÉ WEBER, UFRGS; CARLOS ALBERTO FLORES, CPACT; ELIAS MENDES COSTA, UFRRJ; RONALDO PEREIRA DE OLIVEIRA, CNPS; JOSE MARIA FILIPPINI ALBA, CPACT; JOÃO CHRISÓSTOMO PEDROSO NETO, Epamig; FABRÍCIO DE ARAÚJO PEDRON, UFSM; JOÃO HENRIQUE CAVIGLIONE, Iapar; GUSTAVO SOUZA VALLADARES, UFPI; CARMEM SUEZE SILVA MIRANDA, Univasf; JOSÉ ALEXANDRE MELO DEMATTÊ, USP; JOSÉ MARQUES JÚNIOR, Unesp; DIEGO SILVA SIQUEIRA, Unesp; RENATO ELEOTERIO DE AQUINO, Unesp; NELIDA ELIZABET QUIÑONEZ SILVERO, Unesp; ALINE MARQUES GENÚ, UNICENTRO; TIAGO BROETTO, Catena Planejamento Territorial; LUCIANO CAMPOS CANCIAN, UFSM; PABLO MIGUEL, UFPel; JOVANI ZALAMENA, UFSC; ANDRÉ CARNIELETTO DOTTO, USP; JAIME ANTONIO DE ALMEIDA, Udesc; JOSÉ MIGUEL REICHERT, UFSM; GUSTAVO RIBAS CURCIO, CNPF; LEONARDO SANTOS COLLIER, UFG; WALDIR DE CARVALHO JUNIOR, CNPS; ADEMIR FONTANA, CNPS; ALINE PACOBAHYBA DE OLIVEIRA, CNPS; EDUARDO SALDANHA VOGELMANN, FURG; FÁBIO JOEL KOCHEM MALLMANN, Universidade Regional Integrada do Alto Uruguai e das Missões; GUSTAVO DE MATTOS VASQUES, CNPS; IGO FERNANDO LEPSCH, USP; JESSÉ RODRIGO FINK, IFPR; JOÃO CARLOS KER, UFV; LEANDRO SOUZA DA SILVA, UFSM; PEDRO LUIZ DE FREITAS, CNPS; WANDERLEI BIELUCZYK, USP; TALES TIECHER, UFRGS. |
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Título: |
Bringing together Brazilian soil scientists to share soil data. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS, 2018. |
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Páginas: |
Não paginado. |
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Idioma: |
Inglês |
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Notas: |
WCSS 2018. |
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Conteúdo: |
Soil science has produced a great deal of data. Most of the information is published as a single paper, and the primary data is unavailable to other researchers. As data underutilization is a waste of resources and refrains the advancement of knowledge, many isolated soil data rescue and sharing efforts have emerged in the scientific community. Lately, soil scientists have increased their concerns with data discoverability and reusability, and reproducible research. To address these issues, Brazilian soil scientists have recently created a data repository using community-built standards and following open data policies. The Free Brazilian Repository for Open Soil Data ? febr, www.ufsm.br/febr ? is a centralized repository targeted at storing open soil data and serving it in a standardized and harmonized format. The repository infrastructure was built using open source and/or free (of cost) software, and was primarily designed for the individual management of datasets. A dataset-driven structure helps datasets authors to be properly acknowledged. Moreover, it gives the flexibility to accommodate many types of data of any soil variable. This is accomplished by storing each dataset using a collection of spreadsheets accessible through an online application. Spreadsheets are familiar to any soil scientist, the reason why it is easier to enter, manipulate and visualize soil data in febr. They also facilitate the participation of soil survey experts in the recovery and quality assessment of legacy data. Soil scientists can help in the definition of standards and data management choices through a public discussion forum, febr-forum@googlegroups.com. A comprehensive documentation is available to guide febr maintainers and data contributors. A detailed catalog gives access to the 14 477 soil observations ? 42% of them from south and southeastern Brazil ? from 232 datasets contained in febr. Global and dataset-specific visualization and search tools and multiple download facilities are available. The latter includes standard file formats and connections with R and QGIS through the febr package. Various products can be derived from data in febr: specialized databases, pedotransfer functions, fertilizer recommendation guides, classification systems, and detailed soil maps. By sharing data through a centralized soil data storing and sharing facility, soil scientists from different fields have the opportunity to increase collaboration and the much needed soil knowledge. MenosSoil science has produced a great deal of data. Most of the information is published as a single paper, and the primary data is unavailable to other researchers. As data underutilization is a waste of resources and refrains the advancement of knowledge, many isolated soil data rescue and sharing efforts have emerged in the scientific community. Lately, soil scientists have increased their concerns with data discoverability and reusability, and reproducible research. To address these issues, Brazilian soil scientists have recently created a data repository using community-built standards and following open data policies. The Free Brazilian Repository for Open Soil Data ? febr, www.ufsm.br/febr ? is a centralized repository targeted at storing open soil data and serving it in a standardized and harmonized format. The repository infrastructure was built using open source and/or free (of cost) software, and was primarily designed for the individual management of datasets. A dataset-driven structure helps datasets authors to be properly acknowledged. Moreover, it gives the flexibility to accommodate many types of data of any soil variable. This is accomplished by storing each dataset using a collection of spreadsheets accessible through an online application. Spreadsheets are familiar to any soil scientist, the reason why it is easier to enter, manipulate and visualize soil data in febr. They also facilitate the participation of soil survey experts in the recovery and quality ass... Mostrar Tudo |
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Palavras-Chave: |
Anthropic soils; Árvore de decisão; Data mining techniques; Decision tree; Estoque de carbono; Mineração de dados; Soil management system. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 04933nam a2200853 a 4500
001 2100995
005 2020-01-07
008 2018 bl uuuu u00u1 u #d
100 1 $aSAMUEL-ROSA, A.
245 $aBringing together Brazilian soil scientists to share soil data.$h[electronic resource]
260 $aIn: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS$c2018
300 $aNão paginado.
500 $aWCSS 2018.
520 $aSoil science has produced a great deal of data. Most of the information is published as a single paper, and the primary data is unavailable to other researchers. As data underutilization is a waste of resources and refrains the advancement of knowledge, many isolated soil data rescue and sharing efforts have emerged in the scientific community. Lately, soil scientists have increased their concerns with data discoverability and reusability, and reproducible research. To address these issues, Brazilian soil scientists have recently created a data repository using community-built standards and following open data policies. The Free Brazilian Repository for Open Soil Data ? febr, www.ufsm.br/febr ? is a centralized repository targeted at storing open soil data and serving it in a standardized and harmonized format. The repository infrastructure was built using open source and/or free (of cost) software, and was primarily designed for the individual management of datasets. A dataset-driven structure helps datasets authors to be properly acknowledged. Moreover, it gives the flexibility to accommodate many types of data of any soil variable. This is accomplished by storing each dataset using a collection of spreadsheets accessible through an online application. Spreadsheets are familiar to any soil scientist, the reason why it is easier to enter, manipulate and visualize soil data in febr. They also facilitate the participation of soil survey experts in the recovery and quality assessment of legacy data. Soil scientists can help in the definition of standards and data management choices through a public discussion forum, febr-forum@googlegroups.com. A comprehensive documentation is available to guide febr maintainers and data contributors. A detailed catalog gives access to the 14 477 soil observations ? 42% of them from south and southeastern Brazil ? from 232 datasets contained in febr. Global and dataset-specific visualization and search tools and multiple download facilities are available. The latter includes standard file formats and connections with R and QGIS through the febr package. Various products can be derived from data in febr: specialized databases, pedotransfer functions, fertilizer recommendation guides, classification systems, and detailed soil maps. By sharing data through a centralized soil data storing and sharing facility, soil scientists from different fields have the opportunity to increase collaboration and the much needed soil knowledge.
653 $aAnthropic soils
653 $aÁrvore de decisão
653 $aData mining techniques
653 $aDecision tree
653 $aEstoque de carbono
653 $aMineração de dados
653 $aSoil management system
700 1 $aDALMOLIN, R. S. D.
700 1 $aGUBIANI, P. I.
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aTEIXEIRA, W. G.
700 1 $aVIANA, J. H. M.
700 1 $aRIBEIRO, E.
700 1 $aTORNQUIST, C. G.
700 1 $aANJOS, L. H. C. dos
700 1 $aSOUZA, J. J. E. L. de
700 1 $aOTTONI, M. V.
700 1 $aMEDEIROS, P. S. C. de
700 1 $aGRIS, D. J.
700 1 $aROSIN, N. A.
700 1 $aBUENO, J. M. M.
700 1 $aSANTOS, H. G. dos
700 1 $aWEBER, E. J.
700 1 $aFLORES, C. A.
700 1 $aCOSTA, E. M.
700 1 $aOLIVEIRA, R. P. de
700 1 $aFILIPPINI ALBA, J. M.
700 1 $aPEDROSO NETO, J. C.
700 1 $aPEDRON, F. de A.
700 1 $aCAVIGLIONE, J. H.
700 1 $aVALLADARES, G. S.
700 1 $aMIRANDA, C. S. S.
700 1 $aDEMATTÊ, J. A. M.
700 1 $aMARQUES JÚNIOR, J.
700 1 $aSIQUEIRA, D. S.
700 1 $aAQUINO, R. E. de
700 1 $aSILVERO, N. E. Q.
700 1 $aGENÚ, A. M.
700 1 $aBROETTO, T.
700 1 $aCANCIAN, L. C.
700 1 $aMIGUEL, P.
700 1 $aZALAMENA, J.
700 1 $aDOTTO, A. C.
700 1 $aALMEIDA, J. A. de
700 1 $aREICHERT.
700 1 $aCURCIO, G. R.
700 1 $aCOLLIER, L. S.
700 1 $aCARVALHO JUNIOR, W. de
700 1 $aFONTANA, A.
700 1 $aOLIVEIRA, A. P. de
700 1 $aVOGELMANN, E. S.
700 1 $aMALLMANN, F. J. K.
700 1 $aVASQUES, G. de M.
700 1 $aLEPSCH, I. F.
700 1 $aFINK, J. R.
700 1 $aKER, J. C.
700 1 $aSILVA, L. S. da
700 1 $aFREITAS, P. L. de
700 1 $aBIELUCZYK, B.
700 1 $aTIECHER, T.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Biblioteca |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
23/04/1999 |
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Data da última atualização: |
04/03/2020 |
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Autoria: |
SANTOS, H. G. dos. |
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Afiliação: |
HUMBERTO GONCALVES DOS SANTOS, CNPS. |
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Título: |
Some strategies of quality control for reconnaissance soil survey. |
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Ano de publicação: |
1978 |
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Fonte/Imprenta: |
1978. |
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Páginas: |
xiii, 128 f. |
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Idioma: |
Inglês |
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Notas: |
Thesis (Master of Science) - Faculty of the Graduate School of Cornell University, Ithaca, NY. |
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Conteúdo: |
Soil maps of nine areas representing distinct physiographic patterns and land use were evaluated by three different procedures to study the accuracy in predicting mapping unit composition, and the relevance of procedures for different kinds of areas in relation to effort required. The physiographic and soil patterns studied are believed to be representative of range, forest, and mixed range and forest in mountainous terrain, nearly level, rainfed and irrigated cropland, general farming in rolling and hilly terrain, coastal areas and desert areas. Delineations of selected soil association on generalized soil maps at scales ranging from 1:190,080 to 1:380,160 were tested by point transects, line transects and pilot areas using soil surveys at scales of 1:20,000 or larger as the ground truth. Topographic maps and aerial photographs were used to identify physiographic units, land use patterns and topographic characteristics. Random transects that crossed the grain of the landscape were selected and drawn on detailed soil maps of each of the study areas. With the point transect method, soil units were noted on pre-fixed point at constant intervals of 0.05 kilometer up to 4.0 kilometers along the paths of observation. Soil units were noted along the same transect using different intervals, that is, observations at each 0.05 kilometer along its entire length, then at each 0.1 kilometer and so on up to 4.0-kilometer intervals. Line transects were located similarly, and all soil changes along the of observation noted. Pilot areas were selected to depict small, representative areas according to physiographic features that could be extrapolated to similar units of landscapes. Point transects provided the number of point observations of each soil unit; line transects provided length, in kilometers, of soil units between soil changes; and pilot areas provided the extension, in hectares, of each soil unit observed. Because transects and pilot areas were of different sizes, data obtained by these procedures were statistically analyzed by a cluster type of analysis to estimate proportions of kinds of soils in each association. In additon to proportions of soil units, confidence intervals, accuracy of predicting mapping unit composition, standard deviation, standard error of the mean, coefficient of variation and number of elements needed (transects or pilot areas) were calculated. The numbers of transects and pilot areas were calculated to meet certain probability levels. For example, 80 percent probability with 10 percent allowable error around the mean was used for mountainous areas, and 95 percent probability with 10 percent allowable error for all other areas. Point transects with intervals between observations ranging from 0.05 Kilometer to 0.2 kilometer required more effort per square kilometer than line transects or point transects with larger intervals between observations. Effort per square kilometer decreased with increasing spacing between observations along point transects, but the number of transects needed to meet predetermined levels of accuracy tended to increase when intervals larger than 0.5 kilometer were used. Increasing the number of transects or pilot areas to test soil association provided more accurate estimates of soil proportions and smaller erros of estimations, however, with increasing effort per square kilometer. Based on number of transects and pilot areas needed to attain the accuracy level fixed for the study areas, it was found that the effort per square kilometer varies with profound that the effort per square kilometer varies with procedure and type of landscape. In general, the point and line transects required less effort per square kilometer in all areas tested. Point transects with intervals between observations ranging from 0.2 kilometer to 2.0 kilometer generally required less effort in most of the test areas. For some areas the line transect method is equivalent or slightly better than point transects in terms of effort in man-hours/km2. MenosSoil maps of nine areas representing distinct physiographic patterns and land use were evaluated by three different procedures to study the accuracy in predicting mapping unit composition, and the relevance of procedures for different kinds of areas in relation to effort required. The physiographic and soil patterns studied are believed to be representative of range, forest, and mixed range and forest in mountainous terrain, nearly level, rainfed and irrigated cropland, general farming in rolling and hilly terrain, coastal areas and desert areas. Delineations of selected soil association on generalized soil maps at scales ranging from 1:190,080 to 1:380,160 were tested by point transects, line transects and pilot areas using soil surveys at scales of 1:20,000 or larger as the ground truth. Topographic maps and aerial photographs were used to identify physiographic units, land use patterns and topographic characteristics. Random transects that crossed the grain of the landscape were selected and drawn on detailed soil maps of each of the study areas. With the point transect method, soil units were noted on pre-fixed point at constant intervals of 0.05 kilometer up to 4.0 kilometers along the paths of observation. Soil units were noted along the same transect using different intervals, that is, observations at each 0.05 kilometer along its entire length, then at each 0.1 kilometer and so on up to 4.0-kilometer intervals. Line transects were located similarly, and all soil cha... Mostrar Tudo |
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Thesagro: |
Controle de Qualidade; Levantamento; Reconhecimento do Solo; Solo. |
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Thesaurus NAL: |
Quality control; soil surveys. |
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Categoria do assunto: |
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P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 04650nam a2200205 a 4500
001 1331065
005 2020-03-04
008 1978 bl uuuu m 00u1 u #d
100 1 $aSANTOS, H. G. dos
245 $aSome strategies of quality control for reconnaissance soil survey.
260 $a1978.$c1978
300 $axiii, 128 f.
500 $aThesis (Master of Science) - Faculty of the Graduate School of Cornell University, Ithaca, NY.
520 $aSoil maps of nine areas representing distinct physiographic patterns and land use were evaluated by three different procedures to study the accuracy in predicting mapping unit composition, and the relevance of procedures for different kinds of areas in relation to effort required. The physiographic and soil patterns studied are believed to be representative of range, forest, and mixed range and forest in mountainous terrain, nearly level, rainfed and irrigated cropland, general farming in rolling and hilly terrain, coastal areas and desert areas. Delineations of selected soil association on generalized soil maps at scales ranging from 1:190,080 to 1:380,160 were tested by point transects, line transects and pilot areas using soil surveys at scales of 1:20,000 or larger as the ground truth. Topographic maps and aerial photographs were used to identify physiographic units, land use patterns and topographic characteristics. Random transects that crossed the grain of the landscape were selected and drawn on detailed soil maps of each of the study areas. With the point transect method, soil units were noted on pre-fixed point at constant intervals of 0.05 kilometer up to 4.0 kilometers along the paths of observation. Soil units were noted along the same transect using different intervals, that is, observations at each 0.05 kilometer along its entire length, then at each 0.1 kilometer and so on up to 4.0-kilometer intervals. Line transects were located similarly, and all soil changes along the of observation noted. Pilot areas were selected to depict small, representative areas according to physiographic features that could be extrapolated to similar units of landscapes. Point transects provided the number of point observations of each soil unit; line transects provided length, in kilometers, of soil units between soil changes; and pilot areas provided the extension, in hectares, of each soil unit observed. Because transects and pilot areas were of different sizes, data obtained by these procedures were statistically analyzed by a cluster type of analysis to estimate proportions of kinds of soils in each association. In additon to proportions of soil units, confidence intervals, accuracy of predicting mapping unit composition, standard deviation, standard error of the mean, coefficient of variation and number of elements needed (transects or pilot areas) were calculated. The numbers of transects and pilot areas were calculated to meet certain probability levels. For example, 80 percent probability with 10 percent allowable error around the mean was used for mountainous areas, and 95 percent probability with 10 percent allowable error for all other areas. Point transects with intervals between observations ranging from 0.05 Kilometer to 0.2 kilometer required more effort per square kilometer than line transects or point transects with larger intervals between observations. Effort per square kilometer decreased with increasing spacing between observations along point transects, but the number of transects needed to meet predetermined levels of accuracy tended to increase when intervals larger than 0.5 kilometer were used. Increasing the number of transects or pilot areas to test soil association provided more accurate estimates of soil proportions and smaller erros of estimations, however, with increasing effort per square kilometer. Based on number of transects and pilot areas needed to attain the accuracy level fixed for the study areas, it was found that the effort per square kilometer varies with profound that the effort per square kilometer varies with procedure and type of landscape. In general, the point and line transects required less effort per square kilometer in all areas tested. Point transects with intervals between observations ranging from 0.2 kilometer to 2.0 kilometer generally required less effort in most of the test areas. For some areas the line transect method is equivalent or slightly better than point transects in terms of effort in man-hours/km2.
650 $aQuality control
650 $asoil surveys
650 $aControle de Qualidade
650 $aLevantamento
650 $aReconhecimento do Solo
650 $aSolo
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