FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU
Descripción del Articulo
The loss of forests is one of the main environmental problems in Peru and in various parts of the world. The present work aims to calculate the forest cover by 2021 within the Leoncio Prado province, located in the Huánuco region, Peru. Sentinel-2 images were used, which were classified on the Googl...
Autores: | , |
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Formato: | artículo |
Fecha de Publicación: | 2022 |
Institución: | Universidad Nacional Federico Villarreal |
Repositorio: | Revistas - Universidad Nacional Federico Villarreal |
Lenguaje: | español |
OAI Identifier: | oai:ojs2.revistas.unfv.edu.pe:article/1319 |
Enlace del recurso: | https://revistas.unfv.edu.pe/rtb/article/view/1319 |
Nivel de acceso: | acceso abierto |
Materia: | Artificial intelligence deforestation Google Earth Engine Random Forest Sentinel-2 Deforestación inteligencia artificial |
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FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERUCOBERTURA BOSCOSA AL 2021 EN LA PROVINCIA LEONCIO PRADO, PERÚPuerta Tuesta, Ronald Fajardo-Gamarra, Raí Artificial intelligencedeforestationGoogle Earth EngineRandom ForestSentinel-2DeforestaciónGoogle Earth Engineinteligencia artificialRandom ForestSentinel-2The loss of forests is one of the main environmental problems in Peru and in various parts of the world. The present work aims to calculate the forest cover by 2021 within the Leoncio Prado province, located in the Huánuco region, Peru. Sentinel-2 images were used, which were classified on the Google Earth Engine platform using the Random Forest artificial intelligence algorithm. Likewise, the thematic accuracy of the resulting classification was evaluated using high spatial resolution Planet images. As results, it was found that the study area includes 349,811.47 ha, which represents more than 70% of the total area, while the degraded and intervened areas add up to a total of 131,392.12 ha, which come mainly from the change in use of forest to agricultural areas. Regarding the metrics that evaluate the thematic accuracy of the classification, a value of 0.77 was found in the Kappa Index and 89.14% global accuracy. Therefore, it is concluded that the forest cover is the most predominant in the Leoncio Prado province, which was classified with high thematic accuracy.La pérdida de bosques es uno de los principales problemas ambientales en el Perú y en diversas partes del mundo, en ese sentido el presente trabajo tiene por objetivo calcular la cobertura boscosa al 2021 dentro de la provincia Leoncio Prado, ubicada en la región Huánuco, Perú. Para ello, se utilizó las imágenes Sentinel-2 que fueron clasificadas en la plataforma Google Earth Engine utilizando el algoritmo de inteligencia artificial Random Forest. Asimismo, se evaluó la exactitud temática de la clasificación resultante utilizando imágenes de alta resolución espacial Planet. Como resultados se encontró que la zona de estudio presenta 349 811,47 ha lo que representa más del 70% del área total, mientras que las áreas degradas e intervenidas suman un total de 131 392,12 ha que proceden principalmente del cambio de uso de bosque a zonas agrícolas. Respecto a las métricas que evalúan la exactitud temática de la clasificación, se encontró un valor de 0,77 en el Índice de Kappa y 89,14% de exactitud global. Por lo que se concluye que la cobertura boscosa es la de mayor predominancia en la provincia Leoncio Prado, la cual fue clasificada con alta exactitud temática.Universidad Nacional Federico Villarreal. Facultad de Ciencias Naturales y Matemática. Escuela Profesional de Biología2022-02-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlapplication/epub+zipapplication/pdfhttps://revistas.unfv.edu.pe/rtb/article/view/1319The Biologist; Vol. 20 No. 1 (2022): The Biologist (Lima); 93-101The Biologist; Vol. 20 Núm. 1 (2022): The Biologist (Lima); 93-1011994-90731816-0719reponame:Revistas - Universidad Nacional Federico Villarrealinstname:Universidad Nacional Federico Villarrealinstacron:UNFVspahttps://revistas.unfv.edu.pe/rtb/article/view/1319/1573https://revistas.unfv.edu.pe/rtb/article/view/1319/1574https://revistas.unfv.edu.pe/rtb/article/view/1319/1421https://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessoai:ojs2.revistas.unfv.edu.pe:article/13192023-01-18T17:40:04Z |
dc.title.none.fl_str_mv |
FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU COBERTURA BOSCOSA AL 2021 EN LA PROVINCIA LEONCIO PRADO, PERÚ |
title |
FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU |
spellingShingle |
FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU Puerta Tuesta, Ronald Artificial intelligence deforestation Google Earth Engine Random Forest Sentinel-2 Deforestación Google Earth Engine inteligencia artificial Random Forest Sentinel-2 |
title_short |
FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU |
title_full |
FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU |
title_fullStr |
FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU |
title_full_unstemmed |
FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU |
title_sort |
FOREST COVER BY 2021 IN THE LEONCIO PRADO PROVINCE, PERU |
dc.creator.none.fl_str_mv |
Puerta Tuesta, Ronald Fajardo-Gamarra, Raí |
author |
Puerta Tuesta, Ronald |
author_facet |
Puerta Tuesta, Ronald Fajardo-Gamarra, Raí |
author_role |
author |
author2 |
Fajardo-Gamarra, Raí |
author2_role |
author |
dc.subject.none.fl_str_mv |
Artificial intelligence deforestation Google Earth Engine Random Forest Sentinel-2 Deforestación Google Earth Engine inteligencia artificial Random Forest Sentinel-2 |
topic |
Artificial intelligence deforestation Google Earth Engine Random Forest Sentinel-2 Deforestación Google Earth Engine inteligencia artificial Random Forest Sentinel-2 |
description |
The loss of forests is one of the main environmental problems in Peru and in various parts of the world. The present work aims to calculate the forest cover by 2021 within the Leoncio Prado province, located in the Huánuco region, Peru. Sentinel-2 images were used, which were classified on the Google Earth Engine platform using the Random Forest artificial intelligence algorithm. Likewise, the thematic accuracy of the resulting classification was evaluated using high spatial resolution Planet images. As results, it was found that the study area includes 349,811.47 ha, which represents more than 70% of the total area, while the degraded and intervened areas add up to a total of 131,392.12 ha, which come mainly from the change in use of forest to agricultural areas. Regarding the metrics that evaluate the thematic accuracy of the classification, a value of 0.77 was found in the Kappa Index and 89.14% global accuracy. Therefore, it is concluded that the forest cover is the most predominant in the Leoncio Prado province, which was classified with high thematic accuracy. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-02-06 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://revistas.unfv.edu.pe/rtb/article/view/1319 |
url |
https://revistas.unfv.edu.pe/rtb/article/view/1319 |
dc.language.none.fl_str_mv |
spa |
language |
spa |
dc.relation.none.fl_str_mv |
https://revistas.unfv.edu.pe/rtb/article/view/1319/1573 https://revistas.unfv.edu.pe/rtb/article/view/1319/1574 https://revistas.unfv.edu.pe/rtb/article/view/1319/1421 |
dc.rights.none.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html application/epub+zip application/pdf |
dc.publisher.none.fl_str_mv |
Universidad Nacional Federico Villarreal. Facultad de Ciencias Naturales y Matemática. Escuela Profesional de Biología |
publisher.none.fl_str_mv |
Universidad Nacional Federico Villarreal. Facultad de Ciencias Naturales y Matemática. Escuela Profesional de Biología |
dc.source.none.fl_str_mv |
The Biologist; Vol. 20 No. 1 (2022): The Biologist (Lima); 93-101 The Biologist; Vol. 20 Núm. 1 (2022): The Biologist (Lima); 93-101 1994-9073 1816-0719 reponame:Revistas - Universidad Nacional Federico Villarreal instname:Universidad Nacional Federico Villarreal instacron:UNFV |
instname_str |
Universidad Nacional Federico Villarreal |
instacron_str |
UNFV |
institution |
UNFV |
reponame_str |
Revistas - Universidad Nacional Federico Villarreal |
collection |
Revistas - Universidad Nacional Federico Villarreal |
repository.name.fl_str_mv |
|
repository.mail.fl_str_mv |
|
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1789172152427085824 |
score |
13.7211075 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).