Land cover analysis using the random forest algorithm
Land covers play a crucial role in a variety of environmental and ecological processes. They influence the susceptibility and vulnerability of an area to various natural hazards, such as floods, landslides, forest fires and droughts. Detecting and quantifying these changes over time makes it possibl...
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| Formato: | Artículo revista |
| Lenguaje: | Español |
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Facultad de Ciencias Exactas y Naturales y Agrimensura
2024
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| Acceso en línea: | https://revistas.unne.edu.ar/index.php/fce/article/view/7776 |
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I48-R154-article-77762024-12-26T15:40:24Z Land cover analysis using the random forest algorithm Análisis de la cobertura del suelo a partir del uso del algoritmo Random Forest Arce Cendoya, Sebastián Barragán, Federico Gastón Geraldi, Alejandra Mabel Cobertura del suelo Índices espectrales Sentinel Imágenes satelitales Árboles de decisi´ón Land cover Spectral indices Sentinel Satellite images Decision trees Land covers play a crucial role in a variety of environmental and ecological processes. They influence the susceptibility and vulnerability of an area to various natural hazards, such as floods, landslides, forest fires and droughts. Detecting and quantifying these changes over time makes it possible to assess the impact of human activities such as agriculture, urbanisation and mining on the environment and to take corrective measures to mitigate their negative effects. The aim of this work is to determine the land cover for the Puan district in two seasons (summer and winter) by applying the Random Forest algorithm. We worked with Sentinel-2 satellite images corrected to surface, with which we obtained spectral indices and a subsequent supervised classification for the determination of land cover. The time scale corresponds to the year 2023, with the summer season (January) and the winter season (July). The results allowed us to identify the distribution of land uses in the Puan district and their response to seasonal variations in the same year. Las coberturas del suelo desempeñan un papel crucial en una variedad de procesos ambientales y ecológicos. Las mismas influyen en la susceptibilidad y la vulnerabilidad de un área a diversos riesgos naturales, como inundaciones, deslizamientos de tierra, incendios forestales y sequías. Detectar y cuantificar estos cambios a lo largo del tiempo permite evaluar el impacto de actividades humanas como la agricultura, la urbanización y la minería en el medio ambiente y tomar medidas correctivas para mitigar sus efectos negativos. El trabajo tiene como objetivo determinar las coberturas del suelo para el partido de Puan en dos temporadas (estival e invernal) a partir de la aplicación del algoritmo Random Forest. Se trabajo con imágenes satelitales de Sentinel – 2 corregidas a superficie, con las cuales se obtuvieron índices espectrales y una posterior clasificación supervisada para la determinación de las coberturas del suelo. Las escala temporal corresponde al año 2023, con la estación estival (enero) y la estación invernal (julio). Los resultados permitieron identificar la distribución de los usos del suelo en el partido de Puan y su respuesta frente a las variaciones estacionales en un mismo año. Facultad de Ciencias Exactas y Naturales y Agrimensura 2024-12-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unne.edu.ar/index.php/fce/article/view/7776 10.30972/fac.3427776 FACENA; Vol. 34 Núm. 2 (2024); 270-289 1851-507X 0325-4216 spa https://revistas.unne.edu.ar/index.php/fce/article/view/7776/7500 |
| institution |
Universidad Nacional del Nordeste |
| institution_str |
I-48 |
| repository_str |
R-154 |
| container_title_str |
Revistas UNNE - Universidad Nacional del Noroeste (UNNE) |
| language |
Español |
| format |
Artículo revista |
| topic |
Cobertura del suelo Índices espectrales Sentinel Imágenes satelitales Árboles de decisi´ón Land cover Spectral indices Sentinel Satellite images Decision trees |
| spellingShingle |
Cobertura del suelo Índices espectrales Sentinel Imágenes satelitales Árboles de decisi´ón Land cover Spectral indices Sentinel Satellite images Decision trees Arce Cendoya, Sebastián Barragán, Federico Gastón Geraldi, Alejandra Mabel Land cover analysis using the random forest algorithm |
| topic_facet |
Cobertura del suelo Índices espectrales Sentinel Imágenes satelitales Árboles de decisi´ón Land cover Spectral indices Sentinel Satellite images Decision trees |
| author |
Arce Cendoya, Sebastián Barragán, Federico Gastón Geraldi, Alejandra Mabel |
| author_facet |
Arce Cendoya, Sebastián Barragán, Federico Gastón Geraldi, Alejandra Mabel |
| author_sort |
Arce Cendoya, Sebastián |
| title |
Land cover analysis using the random forest algorithm |
| title_short |
Land cover analysis using the random forest algorithm |
| title_full |
Land cover analysis using the random forest algorithm |
| title_fullStr |
Land cover analysis using the random forest algorithm |
| title_full_unstemmed |
Land cover analysis using the random forest algorithm |
| title_sort |
land cover analysis using the random forest algorithm |
| description |
Land covers play a crucial role in a variety of environmental and ecological processes. They influence the susceptibility and vulnerability of an area to various natural hazards, such as floods, landslides, forest fires and droughts. Detecting and quantifying these changes over time makes it possible to assess the impact of human activities such as agriculture, urbanisation and mining on the environment and to take corrective measures to mitigate their negative effects. The aim of this work is to determine the land cover for the Puan district in two seasons (summer and winter) by applying the Random Forest algorithm. We worked with Sentinel-2 satellite images corrected to surface, with which we obtained spectral indices and a subsequent supervised classification for the determination of land cover. The time scale corresponds to the year 2023, with the summer season (January) and the winter season (July). The results allowed us to identify the distribution of land uses in the Puan district and their response to seasonal variations in the same year. |
| publisher |
Facultad de Ciencias Exactas y Naturales y Agrimensura |
| publishDate |
2024 |
| url |
https://revistas.unne.edu.ar/index.php/fce/article/view/7776 |
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2025-05-17T05:10:29Z |
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2025-05-17T05:10:29Z |
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