Desarrollo de una plataforma web sig para el monitoreo dinámico de pastizales en Magallania

Opazo, Sergio; Garay, Eduardo; Muñoz, René; López-Saldaña, Gerardo; Aguilar, Rolando; Radic, Sergio

doi:10.4067/s0718-686x2014000200003

Cited by 2 publications

(1 citation statement)

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“…In recent years, new remote sensing technologies, such as GEE, radar images and the use of Remotely Piloted Aircraft System (RPAS) equipped with hyperspectral cameras and machine learning algorithms, have allowed more accurate predictions of grassland quality. Grassland mapping allows distinguishing different grassland ecologies that influence management practices, degradation and productivity over time [99][100][101]. In our study, multitemporal images were analyzed that allowed us to monitor the dynamics of the grasslands in the study area, reporting consistent accuracies and demonstrating the increase in the grasslands in both micro-watersheds.…”

Section: Discussionmentioning

confidence: 97%

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

Marin

Castillo

López

et al. 2022

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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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Section: Discussionmentioning

confidence: 97%