Avaliação da rugosidade superficial do solo utilizando técnicas de sensoriamento remoto e análise de imagens

Detalhes bibliográficos
Autor(a) principal: Reis, Leonardo Rubim
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.
id UFV_2e90b77062237455efb6d7222a595402
oai_identifier_str oai:locus.ufv.br:123456789/655
network_acronym_str UFV
network_name_str LOCUS Repositório Institucional da UFV
repository_id_str 2145
spelling 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
format 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
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Viçosa
dc.publisher.program.fl_str_mv Doutorado em Engenharia Agrícola
dc.publisher.initials.fl_str_mv 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
publisher.none.fl_str_mv Universidade Federal de Viçosa
dc.source.none.fl_str_mv reponame:LOCUS Repositório Institucional da UFV
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
instacron_str UFV
institution UFV
reponame_str LOCUS Repositório Institucional da UFV
collection LOCUS Repositório Institucional da UFV
bitstream.url.fl_str_mv https://locus.ufv.br//bitstream/123456789/655/1/texto%20completo.pdf
https://locus.ufv.br//bitstream/123456789/655/2/texto%20completo.pdf.txt
https://locus.ufv.br//bitstream/123456789/655/3/texto%20completo.pdf.jpg
bitstream.checksum.fl_str_mv d0e4fe4edc79c12b0fc1236b48f3b66f
9f6888ec63690d486b162f8846559073
306fd0cc825ba8b050a9d06050ef07ec
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
repository.name.fl_str_mv LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)
repository.mail.fl_str_mv fabiojreis@ufv.br
_version_ 1801213101011369984