Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens
Autor(a) principal: | |
---|---|
Data de Publicação: | 2009 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | http://locus.ufv.br/handle/123456789/655 |
Resumo: | To study the top-soil rugosity using the remote sense techniques, we used one area of 1.200 m², divided on three blocks with five treatments each one, where the dimensions of the parcels were from 20 m of length by 3 m of wideness and 1 m between each parcel, and each block had an area of 20 x 18 m. In every block it was made an assortment of the localization of the parcels of the five treatments. The treatments consisted in five distinct ways to prepare the soil, where the plowing was made in all treatments. The harrow was used only in four treatments and in three treatments we used the rotavator with different regulations, providing different rugosities. To obtain the aerial images, we put two digital cameras in a balloon. One camera had colored images and the other was prepared to collect the infrared images. It was developed two circuits to shoot the cameras remotely. One circuit, named of base earth, where it was configured the way to shoot: manual or automatic. The other circuit was named remote base, where the cameras were plugged. We evaluated for heights: 4, 20, 50 e 100 m. The images obtained were processed with the co- occurrence matrix techniques where there were extracted eight texture descriptors of the images. We still evaluated the influence of the size of the blocks, removed from the image to classify the rugosity classes in the images. It was made a soil sampling to measure the moisture, texture and chemical analysis as a characterization of the soil. The treatment only with the plowing presented a higher rugosity index and the smaller was for the treatment with the plow, harrow and rotavator with the cover closed. The perfilometer doesn t distinguish the five rugosity classes, statistically. In relation to the size of the blocks of the image, the block with the bigger dimension, 250x250 pixels presented the higher values of the kappa index for the heights of 4 and 20 m. For the height of 50 m, the block 90 x 90 obtained the best result. The systems developed to obtain the images are completely practicable to use with the remote sense techniques, with the advantage to be cheaper. The angle orientation of the pixel to produce the co-occurrence matrix with a better performance in the classification was for 45º e 135º. Only the bands B, R and IV B, for the height of 20 m, had the kappa index values the same as 1,0. The bands B, IV G and IV B had the tendency to present a higher % of the kappa index up than 0,90. The combination of the texture descriptors had the tendency to have higher values of the kappa index with the combination of 2, 3, 4 and 5 descriptors. The proposed classifier was considered reliable to study the top-soil rugosity. The classified distinguished the five classes of the top-soil rugosity. |
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Reis, Leonardo Rubimhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4710153P0Santos, Nerilson Terrahttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4782537A2Schaefer, Carlos Ernesto Gonçalves Reynaudhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4723204Y8Vieira, Luciano Baiãohttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4781763J4Lima, Julião Soares de Souzahttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4788865P4Rodrigues, Denilson Eduardohttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728409A5Fernandes, Haroldo Carloshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4761460E62015-03-26T12:31:08Z2009-09-042015-03-26T12:31:08Z2009-02-20REIS, Leonardo Rubim. Evaluation of soil surface roughness using remote sensing techniques and analysis of image. 2009. 140 f. Tese (Doutorado em Construções rurais e ambiência; Energia na agricultura; Mecanização agrícola; Processamento de produ) - Universidade Federal de Viçosa, Viçosa, 2009.http://locus.ufv.br/handle/123456789/655To study the top-soil rugosity using the remote sense techniques, we used one area of 1.200 m², divided on three blocks with five treatments each one, where the dimensions of the parcels were from 20 m of length by 3 m of wideness and 1 m between each parcel, and each block had an area of 20 x 18 m. In every block it was made an assortment of the localization of the parcels of the five treatments. The treatments consisted in five distinct ways to prepare the soil, where the plowing was made in all treatments. The harrow was used only in four treatments and in three treatments we used the rotavator with different regulations, providing different rugosities. To obtain the aerial images, we put two digital cameras in a balloon. One camera had colored images and the other was prepared to collect the infrared images. It was developed two circuits to shoot the cameras remotely. One circuit, named of base earth, where it was configured the way to shoot: manual or automatic. The other circuit was named remote base, where the cameras were plugged. We evaluated for heights: 4, 20, 50 e 100 m. The images obtained were processed with the co- occurrence matrix techniques where there were extracted eight texture descriptors of the images. We still evaluated the influence of the size of the blocks, removed from the image to classify the rugosity classes in the images. It was made a soil sampling to measure the moisture, texture and chemical analysis as a characterization of the soil. The treatment only with the plowing presented a higher rugosity index and the smaller was for the treatment with the plow, harrow and rotavator with the cover closed. The perfilometer doesn t distinguish the five rugosity classes, statistically. In relation to the size of the blocks of the image, the block with the bigger dimension, 250x250 pixels presented the higher values of the kappa index for the heights of 4 and 20 m. For the height of 50 m, the block 90 x 90 obtained the best result. The systems developed to obtain the images are completely practicable to use with the remote sense techniques, with the advantage to be cheaper. The angle orientation of the pixel to produce the co-occurrence matrix with a better performance in the classification was for 45º e 135º. Only the bands B, R and IV B, for the height of 20 m, had the kappa index values the same as 1,0. The bands B, IV G and IV B had the tendency to present a higher % of the kappa index up than 0,90. The combination of the texture descriptors had the tendency to have higher values of the kappa index with the combination of 2, 3, 4 and 5 descriptors. The proposed classifier was considered reliable to study the top-soil rugosity. The classified distinguished the five classes of the top-soil rugosity.Para realizar o estudo de rugosidade superficial do solo por meio de técnicas de sensoriamento remoto, foi feito em uma área de 1.200 m², três blocos com cinco tratamentos cada, sendo as dimensões da parcela de 20 m de comprimento por 3,0 m de largura e 1,0 entre cada parcela, cada bloco com uma área de 20 x 19 m. Em cada bloco foi realizado o sorteio da localização nas parcelas dos cinco tratamentos. Os tratamentos consistiram de cinco preparos distintos de solo, proporcionando rugosidades diferentes, sendo que a aração foi comum a todos os tratamentos, gradagem apenas em quatro tratamentos e em três tratamentos foi utilizada a enxada rotativa com três regulagens diferentes. Para obtenção das imagens aéreas colocou-se duas câmeras digitais a bordo de um balão inflável, uma para captar imagens coloridas e a outra configurada para captar na faixa do infravermelho. Dois circuitos foram desenvolvidos para disparar as câmeras remotamente, um denominado de base terra onde se configurava o modo de disparo, manual ou automático, e outro denominado de base remota onde as câmeras foram plugadas. O balão foi posicionado em quatro alturas, 4, 20, 50 e 100 m. As imagens obtidas foram processadas utilizando técnicas de matriz de coocorrência de onde foram extraídos oito descritores de textura das imagens, também avaliou-se a influência do tamanho dos blocos retirados da imagem para a classificação das classes de rugosidade nas imagens. A amostragem do solo foi feita para medida da umidade, textura e análise química para a caracterização do solo. O tratamento com apenas aração apresentou o maior índice de rugosidade, e o menor foi para o tratamento com arado, grade e enxada rotativa com tampa traseira fechada. O perfilômetro não distingue as cinco classes de rugosidade, estatisticamente. Em relação ao tamanho dos blocos da imagem, o bloco com maior dimensão, 250x250 pixel apresentou os maiores valores do índice kappa, para altura de 4 e 20 m. Na altura de 50 m o bloco 90x90 pixel teve melhor desempenho. Os sistemas de aquisição de imagens desenvolvidos são totalmente viáveis para uso em técnicas de sensoriamento remoto. Os ângulos de orientação do pixel vizinho para a montagem da matriz de co-ocôrrencia com melhor desempenho na classificação foram de 45º e 135º. Apenas as bandas B, R e IV B, para a altura de 20 m, tiveram valores do índice kappa igual a 1,0. Nas imagens com as câmeras a 100 m, as bandas R e G, tiveram valor do índice kappa igual a 1,0. As bandas B, IV G e IV B tenderam a apresentar maior porcentagem dos índices kappa acima de 0,90. A combinação dos descritores texturais que tendeu a ter maiores valores do índice kappa foi com a combinação de 2, 3, 4 e 5 descritores. O classificador proposto se mostrou confiável para o estudo da rugosidade superficial do solo. O classificador discriminou as cinco classes de rugosidade superficial do solo.Fundação de Amparo a Pesquisa do Estado de Minas Geraisapplication/pdfporUniversidade Federal de ViçosaDoutorado em Engenharia AgrícolaUFVBRConstruções rurais e ambiência; Energia na agricultura; Mecanização agrícola; Processamento de produClassificação de imagensCâmera digitalRugosidadeImage classificationDigital cameraRoughnessCNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA::MECANIZACAO AGRICOLAAvaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagensEvaluation of soil surface roughness using remote sensing techniques and analysis of imageinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALtexto completo.pdfapplication/pdf1529892https://locus.ufv.br//bitstream/123456789/655/1/texto%20completo.pdfd0e4fe4edc79c12b0fc1236b48f3b66fMD51TEXTtexto completo.pdf.txttexto completo.pdf.txtExtracted texttext/plain213270https://locus.ufv.br//bitstream/123456789/655/2/texto%20completo.pdf.txt9f6888ec63690d486b162f8846559073MD52THUMBNAILtexto completo.pdf.jpgtexto completo.pdf.jpgIM Thumbnailimage/jpeg3626https://locus.ufv.br//bitstream/123456789/655/3/texto%20completo.pdf.jpg306fd0cc825ba8b050a9d06050ef07ecMD53123456789/6552016-04-06 23:10:35.093oai:locus.ufv.br:123456789/655Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452016-04-07T02:10:35LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.por.fl_str_mv |
Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens |
dc.title.alternative.eng.fl_str_mv |
Evaluation of soil surface roughness using remote sensing techniques and analysis of image |
title |
Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens |
spellingShingle |
Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens Reis, Leonardo Rubim Classificação de imagens Câmera digital Rugosidade Image classification Digital camera Roughness CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA::MECANIZACAO AGRICOLA |
title_short |
Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens |
title_full |
Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens |
title_fullStr |
Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens |
title_full_unstemmed |
Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens |
title_sort |
Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens |
author |
Reis, Leonardo Rubim |
author_facet |
Reis, Leonardo Rubim |
author_role |
author |
dc.contributor.authorLattes.por.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4710153P0 |
dc.contributor.author.fl_str_mv |
Reis, Leonardo Rubim |
dc.contributor.advisor-co1.fl_str_mv |
Santos, Nerilson Terra |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4782537A2 |
dc.contributor.advisor-co2.fl_str_mv |
Schaefer, Carlos Ernesto Gonçalves Reynaud |
dc.contributor.advisor-co2Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4723204Y8 |
dc.contributor.advisor1.fl_str_mv |
Vieira, Luciano Baião |
dc.contributor.advisor1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4781763J4 |
dc.contributor.referee1.fl_str_mv |
Lima, Julião Soares de Souza |
dc.contributor.referee1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4788865P4 |
dc.contributor.referee2.fl_str_mv |
Rodrigues, Denilson Eduardo |
dc.contributor.referee2Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728409A5 |
dc.contributor.referee3.fl_str_mv |
Fernandes, Haroldo Carlos |
dc.contributor.referee3Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4761460E6 |
contributor_str_mv |
Santos, Nerilson Terra Schaefer, Carlos Ernesto Gonçalves Reynaud Vieira, Luciano Baião Lima, Julião Soares de Souza Rodrigues, Denilson Eduardo Fernandes, Haroldo Carlos |
dc.subject.por.fl_str_mv |
Classificação de imagens Câmera digital Rugosidade |
topic |
Classificação de imagens Câmera digital Rugosidade Image classification Digital camera Roughness CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA::MECANIZACAO AGRICOLA |
dc.subject.eng.fl_str_mv |
Image classification Digital camera Roughness |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::FITOTECNIA::MECANIZACAO AGRICOLA |
description |
To study the top-soil rugosity using the remote sense techniques, we used one area of 1.200 m², divided on three blocks with five treatments each one, where the dimensions of the parcels were from 20 m of length by 3 m of wideness and 1 m between each parcel, and each block had an area of 20 x 18 m. In every block it was made an assortment of the localization of the parcels of the five treatments. The treatments consisted in five distinct ways to prepare the soil, where the plowing was made in all treatments. The harrow was used only in four treatments and in three treatments we used the rotavator with different regulations, providing different rugosities. To obtain the aerial images, we put two digital cameras in a balloon. One camera had colored images and the other was prepared to collect the infrared images. It was developed two circuits to shoot the cameras remotely. One circuit, named of base earth, where it was configured the way to shoot: manual or automatic. The other circuit was named remote base, where the cameras were plugged. We evaluated for heights: 4, 20, 50 e 100 m. The images obtained were processed with the co- occurrence matrix techniques where there were extracted eight texture descriptors of the images. We still evaluated the influence of the size of the blocks, removed from the image to classify the rugosity classes in the images. It was made a soil sampling to measure the moisture, texture and chemical analysis as a characterization of the soil. The treatment only with the plowing presented a higher rugosity index and the smaller was for the treatment with the plow, harrow and rotavator with the cover closed. The perfilometer doesn t distinguish the five rugosity classes, statistically. In relation to the size of the blocks of the image, the block with the bigger dimension, 250x250 pixels presented the higher values of the kappa index for the heights of 4 and 20 m. For the height of 50 m, the block 90 x 90 obtained the best result. The systems developed to obtain the images are completely practicable to use with the remote sense techniques, with the advantage to be cheaper. The angle orientation of the pixel to produce the co-occurrence matrix with a better performance in the classification was for 45º e 135º. Only the bands B, R and IV B, for the height of 20 m, had the kappa index values the same as 1,0. The bands B, IV G and IV B had the tendency to present a higher % of the kappa index up than 0,90. The combination of the texture descriptors had the tendency to have higher values of the kappa index with the combination of 2, 3, 4 and 5 descriptors. The proposed classifier was considered reliable to study the top-soil rugosity. The classified distinguished the five classes of the top-soil rugosity. |
publishDate |
2009 |
dc.date.available.fl_str_mv |
2009-09-04 2015-03-26T12:31:08Z |
dc.date.issued.fl_str_mv |
2009-02-20 |
dc.date.accessioned.fl_str_mv |
2015-03-26T12:31:08Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
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doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
REIS, Leonardo Rubim. Evaluation of soil surface roughness using remote sensing techniques and analysis of image. 2009. 140 f. Tese (Doutorado em Construções rurais e ambiência; Energia na agricultura; Mecanização agrícola; Processamento de produ) - Universidade Federal de Viçosa, Viçosa, 2009. |
dc.identifier.uri.fl_str_mv |
http://locus.ufv.br/handle/123456789/655 |
identifier_str_mv |
REIS, Leonardo Rubim. Evaluation of soil surface roughness using remote sensing techniques and analysis of image. 2009. 140 f. Tese (Doutorado em Construções rurais e ambiência; Energia na agricultura; Mecanização agrícola; Processamento de produ) - Universidade Federal de Viçosa, Viçosa, 2009. |
url |
http://locus.ufv.br/handle/123456789/655 |
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por |
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Universidade Federal de Viçosa |
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Doutorado em Engenharia Agrícola |
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UFV |
dc.publisher.country.fl_str_mv |
BR |
dc.publisher.department.fl_str_mv |
Construções rurais e ambiência; Energia na agricultura; Mecanização agrícola; Processamento de produ |
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Universidade Federal de Viçosa |
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