2017
DOI: 10.15359/rca.52-1.1
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Análisis espacial de susceptibilidad de erosión en una cuenca hidrográfica del trópico húmedo de Costa Rica

Abstract: Los artículos publicados se distribuye bajo una Licencia Creative Commons Atribución 4.0 Internacional (CC BY 4.0) basada en una obra en http://www. revistas.una.ac.cr/ambientales., lo que implica la posibilidad de que los lectores puedan de forma gratuita descargar, almacenar, copiar y distribuir la versión final aprobada y publicada del artículo, siempre y cuando se mencione la fuente y autoría de la obra.

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Cited by 4 publications
(6 citation statements)
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“…The northern slope of Cerro Anguciana (Fig. 2c) seems more deforested as compared to the southern slope (our observations in 2003, Pérez-Rubio & Mende 2018, possibly because of a lower steepness for logger trucks on the former. In view of this, the national park of Piedras Blancas created in September 1991 could be expanded to the northeast to include the southern slope of Cerro Anguciana.…”
Section: Discussionmentioning
confidence: 42%
“…The northern slope of Cerro Anguciana (Fig. 2c) seems more deforested as compared to the southern slope (our observations in 2003, Pérez-Rubio & Mende 2018, possibly because of a lower steepness for logger trucks on the former. In view of this, the national park of Piedras Blancas created in September 1991 could be expanded to the northeast to include the southern slope of Cerro Anguciana.…”
Section: Discussionmentioning
confidence: 42%
“…Spatial statistical analyses, such as the Moran Index, have been used to evaluate the distribution of physical phenomena such as soil erosion [26], rainfall [27], and ecological features [28], generating clustered results similar to those of this study. On the other hand, this process has mostly been applied in human and social studies, in order to evaluate distribution, segregation, and transformations, among other social phenomena [29,30], while other studies have focused on distribution phenomena or spatial autocorrelation theory [31][32][33].…”
Section: Introductionmentioning
confidence: 53%
“…Empirical results suggest a strong spatial correlation between the erosion susceptibility index and land use and land cover data. The highest index values were reached in pasturelands and disturbed forests, and the lowest values in natural forest areas [80,81]. As part of an integrated assessment approach, employing primary data, an erosion susceptibility map was generated by using artificial neural networks [80].…”
Section: Gis Erosion Susceptibility Assessmentmentioning
confidence: 99%
“…Empirical results suggest a strong spatial correlation between the erosion susceptibility index and land use and land cover data. The highest index values were reached in pasturelands and disturbed forests, and the lowest values in natural forest areas [80,81]. Research and restoration projects have been carried out over the past decade on abandoned and degraded agricultural and pasture lands near the upper sub-watershed of the river.…”
Section: Gis Erosion Susceptibility Assessmentmentioning
confidence: 99%
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