|
|
Registro Completo |
Biblioteca(s): |
Embrapa Pesca e Aquicultura; Embrapa Tabuleiros Costeiros. |
Data corrente: |
22/12/2021 |
Data da última atualização: |
27/12/2021 |
Tipo da produção científica: |
Documentos |
Autoria: |
LEGAT, A. P.; LEGAT, J. F. A.; ROUTLEDGE, E. A. B.; MANOS, M. G. L.; ROCHA, H. S.; SOUZA, K. L. A. de. |
Afiliação: |
ANGELA PUCHNICK LEGAT, CPATC; JEFFERSON FRANCISCO ALVES LEGAT, CPATC; ERIC ARTHUR BASTOS ROUTLEDGE, CNPASA; MARIA GEOVANIA LIMA MANOS, CPATC; HAINNAN SOUZA ROCHA; KADJA LUANA ALMEIDA DE SOUZA. |
Título: |
Instituições brasileiras atuantes em pesquisa, desenvolvimento e inovação na área de malacocultura. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Aracaju: Embrapa Tabuleiros Costeiros, 2021. |
Série: |
(Embrapa Tabuleiros Costeiros. Documentos, 244). |
ISSN: |
1678-1953 |
Idioma: |
Português |
Notas: |
ODS 14: vida na água. |
Conteúdo: |
Introdução. Material e Métodos. Resultados e considerações. Distribuição nacional de instituições e profissionais atuantes em malacocultura. Formação profissional. Área de atuação e linhas de pesquisa. Espécies pesquisadas. Área de atuação complementar à pesquisa. Equipes de pesquisa. Projetos de pesquisa. Infraestrutura. Sugestões para a solução dos desafios da malacocultura. Considerações finais. |
Palavras-Chave: |
Malacocultura. |
Thesagro: |
Cadeia Produtiva; Molusco; Pesquisa. |
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/229598/1/Ok.DOC-244-21-Embrapa-Tabuleiros-Costeiros.pdf
|
Marc: |
LEADER 01203nam a2200253 a 4500 001 2138310 005 2021-12-27 008 2021 bl uuuu u0uu1 u #d 022 $a1678-1953 100 1 $aLEGAT, A. P. 245 $aInstituições brasileiras atuantes em pesquisa, desenvolvimento e inovação na área de malacocultura.$h[electronic resource] 260 $aAracaju: Embrapa Tabuleiros Costeiros$c2021 490 $a(Embrapa Tabuleiros Costeiros. Documentos, 244). 500 $aODS 14: vida na água. 520 $aIntrodução. Material e Métodos. Resultados e considerações. Distribuição nacional de instituições e profissionais atuantes em malacocultura. Formação profissional. Área de atuação e linhas de pesquisa. Espécies pesquisadas. Área de atuação complementar à pesquisa. Equipes de pesquisa. Projetos de pesquisa. Infraestrutura. Sugestões para a solução dos desafios da malacocultura. Considerações finais. 650 $aCadeia Produtiva 650 $aMolusco 650 $aPesquisa 653 $aMalacocultura 700 1 $aLEGAT, J. F. A. 700 1 $aROUTLEDGE, E. A. B. 700 1 $aMANOS, M. G. L. 700 1 $aROCHA, H. S. 700 1 $aSOUZA, K. L. A. de
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Tabuleiros Costeiros (CPATC) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
Registro Completo
Biblioteca(s): |
Embrapa Cerrados. |
Data corrente: |
12/02/2015 |
Data da última atualização: |
12/02/2015 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 3 |
Autoria: |
CARVALHO JÚNIOR, O. A. de; GUIMARÃES, R. F.; MONTGOMERY, D. R.; GILLESPIE, A. R.; GOMES, R. A. T.; MARTINS, E. de S.; SILVA, N. C. |
Afiliação: |
OSMAR ABÍLIO DE CARVALHO JÚNIOR; RENATO FONTES GUIMARÃES; DAVID R. MONTGOMERY; ALAN R. GILLESPIE; ROBERTO ARNALDO TRANCOSO GOMES; EDER DE SOUZA MARTINS, CPAC; NILTON CORREIA SILVA. |
Título: |
Karst depression detection using ASTER, ALOS/PRISM and SRTM-Derived digital elevation models in the Bambuí Group, Brazil. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
Remote sensing, v. 6, p. 330-351, 2014. |
DOI: |
10.3390/rs6010330 |
Idioma: |
Inglês |
Conteúdo: |
Abstract: Remote sensing has been used in karst studies to identify limestone terrain, describe exokarst features, analyze karst depressions, and detect geological structures important to karst development. The aim of this work is to investigate the use of ASTER-, SRTM- and ALOS/PRISM-derived digital elevation models (DEMs) to detect and quantify natural karst depressions along the São Francisco River near Barreiras city, northeast Brazil. The study area is a karst landscape characterized by karst depressions (dolines), closed depressions in limestone, many of which contain standing water connected with the ground-water table. The base of dolines is typically sealed with an impermeable clay layer covered by standing water or herbaceous vegetation. We identify dolines by combining the extraction of sink depth from DEMs, morphometric analysis using GIS, and visual interpretation. Our methodology is a semi-automatic approach involving several steps: (a) DEM acquisition; (b) sink-depth calculation using the difference between the raw DEM and the corresponding DEM with sinks filled; and (c) elimination of falsely identified karst depressions using morphometric attributes. The advantages and limitations of the applied methodology using different DEMs are examined by comparison with a sinkhole map generated from traditional geomorphological investigations based on visual interpretation of the high-resolution remote sensing images and field surveys. The threshold values of the depth, area size and circularity index appropriate for distinguishing dolines were identified from the maximum overall accuracy obtained by comparison with a true doline map. Our results indicate that the best performance of the proposed methodology for meso-scale karst feature detection was using ALOS/PRISM data with a threshold depth > 2 m; areas > 13,125 m2 and circularity indexes > 0.3 (overall accuracy of 0.53). The overall correct identification of around half of the true dolines suggests the potential to substantially improve doline identification using higher-resolution LiDAR-generated DEMs. MenosAbstract: Remote sensing has been used in karst studies to identify limestone terrain, describe exokarst features, analyze karst depressions, and detect geological structures important to karst development. The aim of this work is to investigate the use of ASTER-, SRTM- and ALOS/PRISM-derived digital elevation models (DEMs) to detect and quantify natural karst depressions along the São Francisco River near Barreiras city, northeast Brazil. The study area is a karst landscape characterized by karst depressions (dolines), closed depressions in limestone, many of which contain standing water connected with the ground-water table. The base of dolines is typically sealed with an impermeable clay layer covered by standing water or herbaceous vegetation. We identify dolines by combining the extraction of sink depth from DEMs, morphometric analysis using GIS, and visual interpretation. Our methodology is a semi-automatic approach involving several steps: (a) DEM acquisition; (b) sink-depth calculation using the difference between the raw DEM and the corresponding DEM with sinks filled; and (c) elimination of falsely identified karst depressions using morphometric attributes. The advantages and limitations of the applied methodology using different DEMs are examined by comparison with a sinkhole map generated from traditional geomorphological investigations based on visual interpretation of the high-resolution remote sensing images and field surveys. The threshold values of the depth... Mostrar Tudo |
Palavras-Chave: |
Análise DEM; Brasil. |
Thesagro: |
Calcário; Sensoriamento remoto; Sistema de Informação Geográfica. |
Thesaurus NAL: |
Brazil; Geographic information systems; Karsts; Limestone; Remote sensing. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/117884/1/Karst-depression-Eder.pdf
|
Marc: |
LEADER 03057naa a2200325 a 4500 001 2008550 005 2015-02-12 008 2014 bl uuuu u00u1 u #d 024 7 $a10.3390/rs6010330$2DOI 100 1 $aCARVALHO JÚNIOR, O. A. de 245 $aKarst depression detection using ASTER, ALOS/PRISM and SRTM-Derived digital elevation models in the Bambuí Group, Brazil. 260 $c2014 520 $aAbstract: Remote sensing has been used in karst studies to identify limestone terrain, describe exokarst features, analyze karst depressions, and detect geological structures important to karst development. The aim of this work is to investigate the use of ASTER-, SRTM- and ALOS/PRISM-derived digital elevation models (DEMs) to detect and quantify natural karst depressions along the São Francisco River near Barreiras city, northeast Brazil. The study area is a karst landscape characterized by karst depressions (dolines), closed depressions in limestone, many of which contain standing water connected with the ground-water table. The base of dolines is typically sealed with an impermeable clay layer covered by standing water or herbaceous vegetation. We identify dolines by combining the extraction of sink depth from DEMs, morphometric analysis using GIS, and visual interpretation. Our methodology is a semi-automatic approach involving several steps: (a) DEM acquisition; (b) sink-depth calculation using the difference between the raw DEM and the corresponding DEM with sinks filled; and (c) elimination of falsely identified karst depressions using morphometric attributes. The advantages and limitations of the applied methodology using different DEMs are examined by comparison with a sinkhole map generated from traditional geomorphological investigations based on visual interpretation of the high-resolution remote sensing images and field surveys. The threshold values of the depth, area size and circularity index appropriate for distinguishing dolines were identified from the maximum overall accuracy obtained by comparison with a true doline map. Our results indicate that the best performance of the proposed methodology for meso-scale karst feature detection was using ALOS/PRISM data with a threshold depth > 2 m; areas > 13,125 m2 and circularity indexes > 0.3 (overall accuracy of 0.53). The overall correct identification of around half of the true dolines suggests the potential to substantially improve doline identification using higher-resolution LiDAR-generated DEMs. 650 $aBrazil 650 $aGeographic information systems 650 $aKarsts 650 $aLimestone 650 $aRemote sensing 650 $aCalcário 650 $aSensoriamento remoto 650 $aSistema de Informação Geográfica 653 $aAnálise DEM 653 $aBrasil 700 1 $aGUIMARÃES, R. F. 700 1 $aMONTGOMERY, D. R. 700 1 $aGILLESPIE, A. R. 700 1 $aGOMES, R. A. T. 700 1 $aMARTINS, E. de S. 700 1 $aSILVA, N. C. 773 $tRemote sensing$gv. 6, p. 330-351, 2014.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Cerrados (CPAC) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Nenhum registro encontrado para a expressão de busca informada. |
|
|