Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional
In this paper we propose a computer vision system to classify permeable and impermeable areas of a bounded area for study including the Micro-basin of Segredo and adjacent micro-basins, located in the municipality of Campo Grande/MS, Brazil, in order to evaluate the increase in urban density between...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Universidade Federal do Paraná
2023-03-01
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| Series: | Desenvolvimento e Meio Ambiente |
| Subjects: | |
| Online Access: | https://revistas.ufpr.br/made/article/view/79431 |
| _version_ | 1797770798074691584 |
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| author | Everton Castelão Tetila Paula Martin de Moraes Michel Constantino Reginaldo Brito da Costa Fabio Martins Ayres Gabriela Oshiro Reynaldo Neire Aparecida Colman Flávia Cristina Albuquerque Palhares Machado Karen Giuliano Soares Maria Madalena Dib Mereb Greco Hemerson Pistori |
| author_facet | Everton Castelão Tetila Paula Martin de Moraes Michel Constantino Reginaldo Brito da Costa Fabio Martins Ayres Gabriela Oshiro Reynaldo Neire Aparecida Colman Flávia Cristina Albuquerque Palhares Machado Karen Giuliano Soares Maria Madalena Dib Mereb Greco Hemerson Pistori |
| author_sort | Everton Castelão Tetila |
| collection | DOAJ |
| description | In this paper we propose a computer vision system to classify permeable and impermeable areas of a bounded area for study including the Micro-basin of Segredo and adjacent micro-basins, located in the municipality of Campo Grande/MS, Brazil, in order to evaluate the increase in urban density between the years 2008 and 2016. The proposed system is based on the image segmentation method Simple Linear Iterative Clustering (SLIC) to partition an image into multiple segments and generate superpixels that differentiate the permeable and impermeable areas; and attribute extraction algorithms to describe the visual features such as color, gradient, texture, and shape. The performance of five supervised learning methods was evaluated for the task of permeable and impermeable areas recognition. The proposed approach achieved an accuracy of 94.6% using the Support Vector Machine (SVM) algorithm. In addition, the results showed an increase of 7.2% in the urban occupation rate of the study area between the analyzed years. The results indicate that the proposed approach can support specialists and managers in the monitoring of urban density and its environmental impact. |
| first_indexed | 2024-03-12T21:28:19Z |
| format | Article |
| id | doaj.art-1ca94020fa4745ef9226a08096407f73 |
| institution | Directory Open Access Journal |
| issn | 1518-952X 2176-9109 |
| language | English |
| last_indexed | 2024-03-12T21:28:19Z |
| publishDate | 2023-03-01 |
| publisher | Universidade Federal do Paraná |
| record_format | Article |
| series | Desenvolvimento e Meio Ambiente |
| spelling | doaj.art-1ca94020fa4745ef9226a08096407f732023-07-28T00:47:03ZengUniversidade Federal do ParanáDesenvolvimento e Meio Ambiente1518-952X2176-91092023-03-0161010.5380/dma.v61i0.7943139890Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacionalEverton Castelão Tetila0Paula Martin de Moraes1Michel Constantino2Reginaldo Brito da Costa3Fabio Martins Ayres4Gabriela Oshiro Reynaldo5Neire Aparecida Colman6Flávia Cristina Albuquerque Palhares Machado7Karen Giuliano Soares8Maria Madalena Dib Mereb Greco9Hemerson Pistori10Universidade Federal da Grande Dourados (UFGD)Universidade Federal da Grande Dourados (UFGD) Universidade Católica Dom Bosco (UCDB)Universidade Católica Dom Bosco (UCDB)Universidade Católica Dom Bosco (UCDB)Universidade Estadual de Mato Grosso do Sul (UEMS)Universidade Católica Dom Bosco (UCDB)Universidade Católica Dom Bosco (UCDB)Universidade Católica Dom Bosco (UCDB)Universidade Católica Dom Bosco (UCDB)Universidade Católica Dom Bosco (UCDB)Universidade Católica Dom Bosco (UCDB)In this paper we propose a computer vision system to classify permeable and impermeable areas of a bounded area for study including the Micro-basin of Segredo and adjacent micro-basins, located in the municipality of Campo Grande/MS, Brazil, in order to evaluate the increase in urban density between the years 2008 and 2016. The proposed system is based on the image segmentation method Simple Linear Iterative Clustering (SLIC) to partition an image into multiple segments and generate superpixels that differentiate the permeable and impermeable areas; and attribute extraction algorithms to describe the visual features such as color, gradient, texture, and shape. The performance of five supervised learning methods was evaluated for the task of permeable and impermeable areas recognition. The proposed approach achieved an accuracy of 94.6% using the Support Vector Machine (SVM) algorithm. In addition, the results showed an increase of 7.2% in the urban occupation rate of the study area between the analyzed years. The results indicate that the proposed approach can support specialists and managers in the monitoring of urban density and its environmental impact.https://revistas.ufpr.br/made/article/view/79431visão computacionaladensamento urbanoimpermeabilidadeimpacto ambiental |
| spellingShingle | Everton Castelão Tetila Paula Martin de Moraes Michel Constantino Reginaldo Brito da Costa Fabio Martins Ayres Gabriela Oshiro Reynaldo Neire Aparecida Colman Flávia Cristina Albuquerque Palhares Machado Karen Giuliano Soares Maria Madalena Dib Mereb Greco Hemerson Pistori Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional Desenvolvimento e Meio Ambiente visão computacional adensamento urbano impermeabilidade impacto ambiental |
| title | Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional |
| title_full | Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional |
| title_fullStr | Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional |
| title_full_unstemmed | Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional |
| title_short | Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional |
| title_sort | classificacao e monitoramento de areas urbanizadas usando tecnicas de visao computacional |
| topic | visão computacional adensamento urbano impermeabilidade impacto ambiental |
| url | https://revistas.ufpr.br/made/article/view/79431 |
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