Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru)

In Peru, grasslands monitoring is essential to support public policies related to the identification, recovery and management of livestock systems. In this study, therefore, we evaluated the spatial dynamics of grasslands in Pomacochas and Ventilla micro-watersheds (Amazonas, NW Peru). To do this, w...

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Autores principales: Atalaya Marin, Nilton, Barboza Castillo, Elgar, Salas López, Rolando, Vásquez Pérez, Héctor Vladimir, Gómez Fernández, Darwin, Terrones Murga, Renzo E., Rojas Briceño, Nilton B., Oliva Cruz, Manuel, Gamarra Torres, Oscar Ándres, Silva López, Jhonsy Omar, Turpo Cayo, Efrain
Formato: info:eu-repo/semantics/article
Lenguaje:Español
Publicado: MDPI 2022
Materias:
Acceso en línea:https://hdl.handle.net/20.500.12955/1691
https://doi.org/10.3390/land11050674
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author Atalaya Marin, Nilton
Barboza Castillo, Elgar
Salas López, Rolando
Vásquez Pérez, Héctor Vladimir
Gómez Fernández, Darwin
Terrones Murga, Renzo E.
Rojas Briceño, Nilton B.
Oliva Cruz, Manuel
Gamarra Torres, Oscar Ándres
Silva López, Jhonsy Omar
Turpo Cayo, Efrain
author_browse Atalaya Marin, Nilton
Barboza Castillo, Elgar
Gamarra Torres, Oscar Ándres
Gómez Fernández, Darwin
Oliva Cruz, Manuel
Rojas Briceño, Nilton B.
Salas López, Rolando
Silva López, Jhonsy Omar
Terrones Murga, Renzo E.
Turpo Cayo, Efrain
Vásquez Pérez, Héctor Vladimir
author_facet Atalaya Marin, Nilton
Barboza Castillo, Elgar
Salas López, Rolando
Vásquez Pérez, Héctor Vladimir
Gómez Fernández, Darwin
Terrones Murga, Renzo E.
Rojas Briceño, Nilton B.
Oliva Cruz, Manuel
Gamarra Torres, Oscar Ándres
Silva López, Jhonsy Omar
Turpo Cayo, Efrain
author_sort Atalaya Marin, Nilton
collection Repositorio INIA
description In Peru, grasslands monitoring is essential to support public policies related to the identification, recovery and management of livestock systems. In this study, therefore, we evaluated the spatial dynamics of grasslands in Pomacochas and Ventilla micro-watersheds (Amazonas, NW Peru). To do this, we used Landsat 5, 7 and 8 images and vegetation indices (normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and soil adjusted vegetation index (SAVI). The data were processed in Google Earth Engine (GEE) platform for 1990, 2000, 2010 and 2020 through random forest (RF) classification reaching accuracies above 85%. The application of RF in GEE allowed surface mapping of grasslands with pressures higher than 85%. Interestingly, our results reported the increase of grasslands in both Pomacochas (from 2457.03 ha to 3659.37 ha) and Ventilla (from 1932.38 ha to 4056.26 ha) micro-watersheds during 1990–2020. Effectively, this study aims to provide useful information for territorial planning with potential replicability for other cattle-raising regions of the country. It could further be used to improve grassland management and promote semi-extensive livestock farming.
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spelling INIA16912023-06-21T15:47:44Z Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru) Atalaya Marin, Nilton Barboza Castillo, Elgar Salas López, Rolando Vásquez Pérez, Héctor Vladimir Gómez Fernández, Darwin Terrones Murga, Renzo E. Rojas Briceño, Nilton B. Oliva Cruz, Manuel Gamarra Torres, Oscar Ándres Silva López, Jhonsy Omar Turpo Cayo, Efrain Grassland dynamics Google Earth Engine (GEE) Sustainable livestock Remote sensing Random forest (RF) Landsat https://purl.org/pe-repo/ocde/ford#4.05.00 In Peru, grasslands monitoring is essential to support public policies related to the identification, recovery and management of livestock systems. In this study, therefore, we evaluated the spatial dynamics of grasslands in Pomacochas and Ventilla micro-watersheds (Amazonas, NW Peru). To do this, we used Landsat 5, 7 and 8 images and vegetation indices (normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and soil adjusted vegetation index (SAVI). The data were processed in Google Earth Engine (GEE) platform for 1990, 2000, 2010 and 2020 through random forest (RF) classification reaching accuracies above 85%. The application of RF in GEE allowed surface mapping of grasslands with pressures higher than 85%. Interestingly, our results reported the increase of grasslands in both Pomacochas (from 2457.03 ha to 3659.37 ha) and Ventilla (from 1932.38 ha to 4056.26 ha) micro-watersheds during 1990–2020. Effectively, this study aims to provide useful information for territorial planning with potential replicability for other cattle-raising regions of the country. It could further be used to improve grassland management and promote semi-extensive livestock farming. Abstract. 1. Introduction. 2. Materials and Methods. 3. Results. 4. Discussion. 5. Conclusions. References. 2022-06-02T21:45:18Z 2022-06-02T21:45:18Z 2022-05-01 info:eu-repo/semantics/article Marin, N.A.; Barboza, E.; López, R.S.; Vásquez, H.V.; Gómez Fernández, D.; Terrones Murga, R.E.; Rojas Briceño, N.B.; Oliva-Cruz, M.; Gamarra Torres, O.A.; Silva López, J.O.; et al. Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru). Land 2022, 11, 674. doi: 10.3390/land11050674 https://hdl.handle.net/20.500.12955/1691 Land https://doi.org/10.3390/land11050674 spa Land 2022, 11(5), 674 https://doi.org/10.3390/land11050674 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ application/pdf application/pdf Perú MDPI Suiza Instituto Nacional de Innovación Agraria Repositorio Institucional - INIA
spellingShingle Grassland dynamics
Google Earth Engine (GEE)
Sustainable livestock
Remote sensing
Random forest (RF)
Landsat
https://purl.org/pe-repo/ocde/ford#4.05.00
Atalaya Marin, Nilton
Barboza Castillo, Elgar
Salas López, Rolando
Vásquez Pérez, Héctor Vladimir
Gómez Fernández, Darwin
Terrones Murga, Renzo E.
Rojas Briceño, Nilton B.
Oliva Cruz, Manuel
Gamarra Torres, Oscar Ándres
Silva López, Jhonsy Omar
Turpo Cayo, Efrain
Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru)
title Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru)
title_full Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru)
title_fullStr Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru)
title_full_unstemmed Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru)
title_short Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru)
title_sort spatiotemporal dynamics of grasslands using landsat data in livestock micro watersheds in amazonas nw peru
topic Grassland dynamics
Google Earth Engine (GEE)
Sustainable livestock
Remote sensing
Random forest (RF)
Landsat
https://purl.org/pe-repo/ocde/ford#4.05.00
url https://hdl.handle.net/20.500.12955/1691
https://doi.org/10.3390/land11050674
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