Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/64103 |
Resumo: | This research demonstrated a Geographic Information System (GIS) of licensed fish farms in Rondônia state, Brazil. Based on structuring of the GIS, spatial analyzes of location and distribution of fish farms were carried out in relation to highway network; to drainage; to microregions of Rondônia and the verification of the density. Methodological procedure consisted of modeling the Database (DB), whose information was obtained from Secretaria do Estado de Rondônia para Desenvolvimento Ambiental (SEDAM/RO), which holds the references of licensed fish farms processed in SPRING and ARCGIS 9 Arcmap 9.3 software. For spatial statistics, the Kernel density estimator was applied. The main result is the fact that GIS made it quick and easy to search for data and information about the fish farms studied. The highest density was 4937.64 fish farms per unit area in Ji-Paraná microregion, which is located in the Central region of Rondônia state. In thematic mapping, the fish farms showed some spatial dependencies, as follows: I – They depend on main access, highway BR 364. II – The cluster of fish farms is arranged where there is greater availability of water, that is, they depend on water courses. Therefore, positioning and distribution of fish farms take place in the three main microregions, Ji-Paraná 40.30% of licensed fish farms, followed by microregions of Cacoal 16.02% and Ariquemes 15.87%. |
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Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western AmazonGeotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western AmazonDatabase; Information systems; Kernel density estimator; Spatial Analysis.Database; Information systems; Kernel density estimator; Spatial Analysis.This research demonstrated a Geographic Information System (GIS) of licensed fish farms in Rondônia state, Brazil. Based on structuring of the GIS, spatial analyzes of location and distribution of fish farms were carried out in relation to highway network; to drainage; to microregions of Rondônia and the verification of the density. Methodological procedure consisted of modeling the Database (DB), whose information was obtained from Secretaria do Estado de Rondônia para Desenvolvimento Ambiental (SEDAM/RO), which holds the references of licensed fish farms processed in SPRING and ARCGIS 9 Arcmap 9.3 software. For spatial statistics, the Kernel density estimator was applied. The main result is the fact that GIS made it quick and easy to search for data and information about the fish farms studied. The highest density was 4937.64 fish farms per unit area in Ji-Paraná microregion, which is located in the Central region of Rondônia state. In thematic mapping, the fish farms showed some spatial dependencies, as follows: I – They depend on main access, highway BR 364. II – The cluster of fish farms is arranged where there is greater availability of water, that is, they depend on water courses. Therefore, positioning and distribution of fish farms take place in the three main microregions, Ji-Paraná 40.30% of licensed fish farms, followed by microregions of Cacoal 16.02% and Ariquemes 15.87%.This research demonstrated a Geographic Information System (GIS) of licensed fish farms in Rondônia state, Brazil. Based on structuring of the GIS, spatial analyzes of location and distribution of fish farms were carried out in relation to highway network; to drainage; to microregions of Rondônia and the verification of the density. Methodological procedure consisted of modeling the Database (DB), whose information was obtained from Secretaria do Estado de Rondônia para Desenvolvimento Ambiental (SEDAM/RO), which holds the references of licensed fish farms processed in SPRING and ARCGIS 9 Arcmap 9.3 software. For spatial statistics, the Kernel density estimator was applied. The main result is the fact that GIS made it quick and easy to search for data and information about the fish farms studied. The highest density was 4937.64 fish farms per unit area in Ji-Paraná microregion, which is located in the Central region of Rondônia state. In thematic mapping, the fish farms showed some spatial dependencies, as follows: I – They depend on main access, highway BR 364. II – The cluster of fish farms is arranged where there is greater availability of water, that is, they depend on water courses. Therefore, positioning and distribution of fish farms take place in the three main microregions, Ji-Paraná 40.30% of licensed fish farms, followed by microregions of Cacoal 16.02% and Ariquemes 15.87%.Universidade Estadual De Maringá2023-09-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/6410310.4025/actascitechnol.v45i1.64103Acta Scientiarum. Technology; Vol 45 (2023): Publicação contínua; e64103Acta Scientiarum. Technology; v. 45 (2023): Publicação contínua; e641031806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/64103/751375156506Copyright (c) 2023 Acta Scientiarum. Technologyhttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessAlbuquerque, Paulo de Tarso da Fonseca Souza, Ricardo Henrique Bastos deRocha, Daiane de Oliveira Cavali, Jucilene Santos, Alex Mota dosDantas Filho, Jerônimo Vieira 2023-10-20T12:43:54Zoai:periodicos.uem.br/ojs:article/64103Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2023-10-20T12:43:54Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon |
title |
Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon |
spellingShingle |
Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon Albuquerque, Paulo de Tarso da Fonseca Database; Information systems; Kernel density estimator; Spatial Analysis. Database; Information systems; Kernel density estimator; Spatial Analysis. |
title_short |
Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon |
title_full |
Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon |
title_fullStr |
Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon |
title_full_unstemmed |
Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon |
title_sort |
Geotechnologies applied to geographic information system (GIS) of Fish farming in Rondônia state, Western Amazon |
author |
Albuquerque, Paulo de Tarso da Fonseca |
author_facet |
Albuquerque, Paulo de Tarso da Fonseca Souza, Ricardo Henrique Bastos de Rocha, Daiane de Oliveira Cavali, Jucilene Santos, Alex Mota dos Dantas Filho, Jerônimo Vieira |
author_role |
author |
author2 |
Souza, Ricardo Henrique Bastos de Rocha, Daiane de Oliveira Cavali, Jucilene Santos, Alex Mota dos Dantas Filho, Jerônimo Vieira |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Albuquerque, Paulo de Tarso da Fonseca Souza, Ricardo Henrique Bastos de Rocha, Daiane de Oliveira Cavali, Jucilene Santos, Alex Mota dos Dantas Filho, Jerônimo Vieira |
dc.subject.por.fl_str_mv |
Database; Information systems; Kernel density estimator; Spatial Analysis. Database; Information systems; Kernel density estimator; Spatial Analysis. |
topic |
Database; Information systems; Kernel density estimator; Spatial Analysis. Database; Information systems; Kernel density estimator; Spatial Analysis. |
description |
This research demonstrated a Geographic Information System (GIS) of licensed fish farms in Rondônia state, Brazil. Based on structuring of the GIS, spatial analyzes of location and distribution of fish farms were carried out in relation to highway network; to drainage; to microregions of Rondônia and the verification of the density. Methodological procedure consisted of modeling the Database (DB), whose information was obtained from Secretaria do Estado de Rondônia para Desenvolvimento Ambiental (SEDAM/RO), which holds the references of licensed fish farms processed in SPRING and ARCGIS 9 Arcmap 9.3 software. For spatial statistics, the Kernel density estimator was applied. The main result is the fact that GIS made it quick and easy to search for data and information about the fish farms studied. The highest density was 4937.64 fish farms per unit area in Ji-Paraná microregion, which is located in the Central region of Rondônia state. In thematic mapping, the fish farms showed some spatial dependencies, as follows: I – They depend on main access, highway BR 364. II – The cluster of fish farms is arranged where there is greater availability of water, that is, they depend on water courses. Therefore, positioning and distribution of fish farms take place in the three main microregions, Ji-Paraná 40.30% of licensed fish farms, followed by microregions of Cacoal 16.02% and Ariquemes 15.87%. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-09-27 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/64103 10.4025/actascitechnol.v45i1.64103 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/64103 |
identifier_str_mv |
10.4025/actascitechnol.v45i1.64103 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/64103/751375156506 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2023 Acta Scientiarum. Technology http://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2023 Acta Scientiarum. Technology http://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 45 (2023): Publicação contínua; e64103 Acta Scientiarum. Technology; v. 45 (2023): Publicação contínua; e64103 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1799315338321461248 |