Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects

Tropical deforestation is an ongoing process mainly caused by the construction of new roads, which, without proper environmental planning, contribute to biodiversity loss. Given that the artificial neural networks (ANNs) have the ability to capture nonlinear relationships, they were used to predict...

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Autores:
Gómez-Ossa, Luisa Fernanda
Botero-Fernández, Verónica
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/60381
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/60381
http://bdigital.unal.edu.co/58713/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
Artificial neural networks
prediction
deforestation
roads
Redes neuronales artificiales
predicción
deforestación
vías
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
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spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Gómez-Ossa, Luisa Fernanda6439d863-5d73-43ce-98dd-532ac00683bd300Botero-Fernández, Verónica6fc81cdc-db0f-4f07-9348-20ea83bee86a3002019-07-02T18:11:16Z2019-07-02T18:11:16Z2017-04-01ISSN: 2346-2183https://repositorio.unal.edu.co/handle/unal/60381http://bdigital.unal.edu.co/58713/Tropical deforestation is an ongoing process mainly caused by the construction of new roads, which, without proper environmental planning, contribute to biodiversity loss. Given that the artificial neural networks (ANNs) have the ability to capture nonlinear relationships, they were used to predict deforestation associated with new roads, such as the “Variante Porce” road and the “El Bagre-San Jacinto del Cauca” road in the department of Antioquia. ANN Training was carried out online using the back-propagation algorithm, part of the R software. The predictive capacity was evaluated using the area under the receiver operator characteristic curve (AUC). Also, a network that showed the best predictive capacity for the deforestation surface was generated for the baseline scenario and the simulated scenario incorporating the new roads. The comparison of scenarios suggested that new roads would increase the probability of deforestation for approximately 103.729 ha of forest.La deforestación tropical es un proceso continuo causado principalmente por la construcción de nuevas vías, las cuales sin una planificación ambiental adecuada contribuyen a la pérdida de biodiversidad. Dado que las redes neuronales artificiales (RNAs) tienen la capacidad de capturar relaciones no lineales, se utilizaron para predecir la deforestación asociada a nuevas vías, como la Variante Porce y la vía El Bagre-San Jacinto del Cauca, en el departamento de Antioquia. El entrenamiento de las RNAs se realizó en modo on line con el algoritmo de retropropagación, en el software R. La capacidad de predicción se evaluó con el área bajo la curva ROC (AUC) y con la red que presentó mejor capacidad predictiva se generó la superficie de deforestación para el escenario base y el escenario simulado incorporando las nuevas vías. La comparación de escenarios indica que las nuevas vías incrementarían la probabilidad de deforestación de aproximadamente 103.729 ha de bosque.application/pdfspaUniversidad Nacional de Colombia (Sede Medellín). Facultad de Minas.https://revistas.unal.edu.co/index.php/dyna/article/view/54310Universidad Nacional de Colombia Revistas electrónicas UN DynaDynaGómez-Ossa, Luisa Fernanda and Botero-Fernández, Verónica (2017) Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects. DYNA, 84 (201). pp. 68-73. ISSN 2346-218362 Ingeniería y operaciones afines / EngineeringArtificial neural networkspredictiondeforestationroadsRedes neuronales artificialesprediccióndeforestaciónvíasApplication of artificial neural networks in modeling deforestation associated with new road infrastructure projectsArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL54310-329303-2-PB.pdfapplication/pdf692379https://repositorio.unal.edu.co/bitstream/unal/60381/1/54310-329303-2-PB.pdf6b3e66cdb4d6ba71513ad35aa9720791MD51THUMBNAIL54310-329303-2-PB.pdf.jpg54310-329303-2-PB.pdf.jpgGenerated Thumbnailimage/jpeg9531https://repositorio.unal.edu.co/bitstream/unal/60381/2/54310-329303-2-PB.pdf.jpg70798e0f3ec0156ba1804cc567f010acMD52unal/60381oai:repositorio.unal.edu.co:unal/603812024-04-13 23:10:21.374Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co
dc.title.spa.fl_str_mv Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects
title Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects
spellingShingle Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects
62 Ingeniería y operaciones afines / Engineering
Artificial neural networks
prediction
deforestation
roads
Redes neuronales artificiales
predicción
deforestación
vías
title_short Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects
title_full Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects
title_fullStr Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects
title_full_unstemmed Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects
title_sort Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects
dc.creator.fl_str_mv Gómez-Ossa, Luisa Fernanda
Botero-Fernández, Verónica
dc.contributor.author.spa.fl_str_mv Gómez-Ossa, Luisa Fernanda
Botero-Fernández, Verónica
dc.subject.ddc.spa.fl_str_mv 62 Ingeniería y operaciones afines / Engineering
topic 62 Ingeniería y operaciones afines / Engineering
Artificial neural networks
prediction
deforestation
roads
Redes neuronales artificiales
predicción
deforestación
vías
dc.subject.proposal.spa.fl_str_mv Artificial neural networks
prediction
deforestation
roads
Redes neuronales artificiales
predicción
deforestación
vías
description Tropical deforestation is an ongoing process mainly caused by the construction of new roads, which, without proper environmental planning, contribute to biodiversity loss. Given that the artificial neural networks (ANNs) have the ability to capture nonlinear relationships, they were used to predict deforestation associated with new roads, such as the “Variante Porce” road and the “El Bagre-San Jacinto del Cauca” road in the department of Antioquia. ANN Training was carried out online using the back-propagation algorithm, part of the R software. The predictive capacity was evaluated using the area under the receiver operator characteristic curve (AUC). Also, a network that showed the best predictive capacity for the deforestation surface was generated for the baseline scenario and the simulated scenario incorporating the new roads. The comparison of scenarios suggested that new roads would increase the probability of deforestation for approximately 103.729 ha of forest.
publishDate 2017
dc.date.issued.spa.fl_str_mv 2017-04-01
dc.date.accessioned.spa.fl_str_mv 2019-07-02T18:11:16Z
dc.date.available.spa.fl_str_mv 2019-07-02T18:11:16Z
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dc.identifier.issn.spa.fl_str_mv ISSN: 2346-2183
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dc.identifier.eprints.spa.fl_str_mv http://bdigital.unal.edu.co/58713/
identifier_str_mv ISSN: 2346-2183
url https://repositorio.unal.edu.co/handle/unal/60381
http://bdigital.unal.edu.co/58713/
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.spa.fl_str_mv https://revistas.unal.edu.co/index.php/dyna/article/view/54310
dc.relation.ispartof.spa.fl_str_mv Universidad Nacional de Colombia Revistas electrónicas UN Dyna
Dyna
dc.relation.references.spa.fl_str_mv Gómez-Ossa, Luisa Fernanda and Botero-Fernández, Verónica (2017) Application of artificial neural networks in modeling deforestation associated with new road infrastructure projects. DYNA, 84 (201). pp. 68-73. ISSN 2346-2183
dc.rights.spa.fl_str_mv Derechos reservados - Universidad Nacional de Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
Derechos reservados - Universidad Nacional de Colombia
http://creativecommons.org/licenses/by-nc/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia (Sede Medellín). Facultad de Minas.
institution Universidad Nacional de Colombia
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