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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
13/12/2013 |
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Data da última atualização: |
18/02/2015 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
STOLLE, L.; LINGNAU, C.; ARCE, J. E.; BOGNOLA, I. A. |
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Afiliação: |
LORENA STOLLE, ENGENHEIRA FLORESTAL; CHRISTEL LINGNAU, UFPR; JULIO EDUARDO ARCE, UFPR; ITAMAR ANTONIO BOGNOLA, CNPF. |
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Título: |
Simulação do impacto das atividades florestais na fragilidade potencial em plantios de pinus. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Cerne, Lavras, v. 18, n. 4, p. 683-693 out./dez. 2012. |
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Idioma: |
Português |
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Conteúdo: |
Este trabalho, realizado em uma área com povoamento de Pinus taeda, teve por objetivo simular e mapear a influência do valor de impacto das atividades florestais na fragilidade potencial. Variáveis do solo, de declividade do terreno, valor de impacto e de cobertura vegetal foram utilizadas para gerar os mapas. Os resultados expressos pelo modelo adotado mostraram que as áreas mais frágeis apresentam em sua maioria declividades superiores a 75 % e textura que variam de arenosa a média, e as áreas menos frágeis apresentam predominantemente relevo plano (até 3 %) e textura argilosa. Quando simulado o impacto das atividades florestais sobre esse ambiente, verificou-se que na maior parte da área (78 %) todas as atividades florestais podem ser realizadas sem influência na degradação do meio ambiente e para algumas áreas (11 %) o ambiente foi considerado menos frágil, em razão da presença de cobertura vegetal. |
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Palavras-Chave: |
Ecosystem Management Decision Support; Lógica fuzzy; Solos florestais. |
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Thesaurus Nal: |
forest soils; fuzzy logic. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/93938/1/cerne-18.pdf
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Marc: |
LEADER 01564naa a2200217 a 4500
001 1973766
005 2015-02-18
008 2012 bl uuuu u00u1 u #d
100 1 $aSTOLLE, L.
245 $aSimulação do impacto das atividades florestais na fragilidade potencial em plantios de pinus.
260 $c2012
520 $aEste trabalho, realizado em uma área com povoamento de Pinus taeda, teve por objetivo simular e mapear a influência do valor de impacto das atividades florestais na fragilidade potencial. Variáveis do solo, de declividade do terreno, valor de impacto e de cobertura vegetal foram utilizadas para gerar os mapas. Os resultados expressos pelo modelo adotado mostraram que as áreas mais frágeis apresentam em sua maioria declividades superiores a 75 % e textura que variam de arenosa a média, e as áreas menos frágeis apresentam predominantemente relevo plano (até 3 %) e textura argilosa. Quando simulado o impacto das atividades florestais sobre esse ambiente, verificou-se que na maior parte da área (78 %) todas as atividades florestais podem ser realizadas sem influência na degradação do meio ambiente e para algumas áreas (11 %) o ambiente foi considerado menos frágil, em razão da presença de cobertura vegetal.
650 $aforest soils
650 $afuzzy logic
653 $aEcosystem Management Decision Support
653 $aLógica fuzzy
653 $aSolos florestais
700 1 $aLINGNAU, C.
700 1 $aARCE, J. E.
700 1 $aBOGNOLA, I. A.
773 $tCerne, Lavras$gv. 18, n. 4, p. 683-693 out./dez. 2012.
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Registro original: |
Embrapa Florestas (CNPF) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Meio Ambiente. Para informações adicionais entre em contato com cnpma.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
29/06/2012 |
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Data da última atualização: |
05/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 3 |
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Autoria: |
PRADO, H. A. do; FERNEDA, E.; RODRIGUES, F. C. da L.; MARTINS, E. de S.; CARVALHO JUNIOR, O. A. de; LUIZ, A. J. B. |
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Afiliação: |
HERCULES ANTONIO DO PRADO, SGE; EDILSON FERNEDA, UNIVERSIDADE CATÓLICA DE BRASÍLIA; FRANCISCO CARLOS DA LUZ RODRIGUES, UNIVERSIDADE CATÓLICA DE BRASÍLIA; EDER DE SOUZA MARTINS, CPAC; OSMAR ABÍLIO DE CARVALHO JUNIOR, UNB; ALFREDO JOSE BARRETO LUIZ, CNPMA. |
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Título: |
Structuring taxonomies from texts: a case-study on defining soil classes. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Lecture Notes in Computer Science, Berlin, v. 7335, p. 657-666, 2012. |
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Idioma: |
Inglês |
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Conteúdo: |
Currently, most of the information digitally available is presented in textual form and it is largely acknowledged that, in many fields, the advance of knowledge may strongly benefit from this source of information. The treatment of this vast amount of texts by means of Text Mining (TM) techniques has produced interesting information in fields like Competitive Intelligence and Bibliometry that need to make sense from textual descriptions of facts. In this paper we approach the problem of taxonomy generation from texts, a common need from a large set of scientific disciplines. Taxonomy generation refers to building a hierarchical structure that organizes concepts in a knowledge domain. We applied TM techniques to help experts in Pedology in building taxonomy from redundant soils descriptions. The motto of the application is the fact that, in the early eighties, different organizations mapped and described equivalent classes of soils from Brazilian savannas, generating redundant descriptions with different class labels. There were produced 28 soil maps that covered 4,101 descriptions of soil classes. This profusion of redundant soil descriptions clearly represents a Babel Tower that makes difficult tasks like environment management and food production. The proposed process is based in clustering analysis and runs on the soil descriptions, performing a successive refinement of the abstractions found in soil descriptions. The method builds a frame that shows, for each cluster formed, the prototype (a representative word vector) and the soil descriptions related to that cluster. The results have been analyzed by a team of experts as input information to the laborious reasoning process involved in building concepts from the semantic relations among the soil descriptions. Without a help like the present process, the experts would have to compare visually at least 4,101 × 4.100 × ?× 1 soil descriptions to define the clusters, what is much more laborious. MenosCurrently, most of the information digitally available is presented in textual form and it is largely acknowledged that, in many fields, the advance of knowledge may strongly benefit from this source of information. The treatment of this vast amount of texts by means of Text Mining (TM) techniques has produced interesting information in fields like Competitive Intelligence and Bibliometry that need to make sense from textual descriptions of facts. In this paper we approach the problem of taxonomy generation from texts, a common need from a large set of scientific disciplines. Taxonomy generation refers to building a hierarchical structure that organizes concepts in a knowledge domain. We applied TM techniques to help experts in Pedology in building taxonomy from redundant soils descriptions. The motto of the application is the fact that, in the early eighties, different organizations mapped and described equivalent classes of soils from Brazilian savannas, generating redundant descriptions with different class labels. There were produced 28 soil maps that covered 4,101 descriptions of soil classes. This profusion of redundant soil descriptions clearly represents a Babel Tower that makes difficult tasks like environment management and food production. The proposed process is based in clustering analysis and runs on the soil descriptions, performing a successive refinement of the abstractions found in soil descriptions. The method builds a frame that shows, for each cluster fo... Mostrar Tudo |
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Palavras-Chave: |
Mineração de texto; Text mining. |
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Thesagro: |
Cerrado; Solo; Taxonomia. |
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Thesaurus NAL: |
Soil taxonomy. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02714naa a2200253 a 4500
001 1927451
005 2023-01-05
008 2012 bl uuuu u00u1 u #d
100 1 $aPRADO, H. A. do
245 $aStructuring taxonomies from texts$ba case-study on defining soil classes.$h[electronic resource]
260 $c2012
520 $aCurrently, most of the information digitally available is presented in textual form and it is largely acknowledged that, in many fields, the advance of knowledge may strongly benefit from this source of information. The treatment of this vast amount of texts by means of Text Mining (TM) techniques has produced interesting information in fields like Competitive Intelligence and Bibliometry that need to make sense from textual descriptions of facts. In this paper we approach the problem of taxonomy generation from texts, a common need from a large set of scientific disciplines. Taxonomy generation refers to building a hierarchical structure that organizes concepts in a knowledge domain. We applied TM techniques to help experts in Pedology in building taxonomy from redundant soils descriptions. The motto of the application is the fact that, in the early eighties, different organizations mapped and described equivalent classes of soils from Brazilian savannas, generating redundant descriptions with different class labels. There were produced 28 soil maps that covered 4,101 descriptions of soil classes. This profusion of redundant soil descriptions clearly represents a Babel Tower that makes difficult tasks like environment management and food production. The proposed process is based in clustering analysis and runs on the soil descriptions, performing a successive refinement of the abstractions found in soil descriptions. The method builds a frame that shows, for each cluster formed, the prototype (a representative word vector) and the soil descriptions related to that cluster. The results have been analyzed by a team of experts as input information to the laborious reasoning process involved in building concepts from the semantic relations among the soil descriptions. Without a help like the present process, the experts would have to compare visually at least 4,101 × 4.100 × ?× 1 soil descriptions to define the clusters, what is much more laborious.
650 $aSoil taxonomy
650 $aCerrado
650 $aSolo
650 $aTaxonomia
653 $aMineração de texto
653 $aText mining
700 1 $aFERNEDA, E.
700 1 $aRODRIGUES, F. C. da L.
700 1 $aMARTINS, E. de S.
700 1 $aCARVALHO JUNIOR, O. A. de
700 1 $aLUIZ, A. J. B.
773 $tLecture Notes in Computer Science, Berlin$gv. 7335, p. 657-666, 2012.
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Embrapa Meio Ambiente (CNPMA) |
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