Estudio del NDVI mediante análisis multiescalar y series temporales utilizando imágenes SPOT, durante el período 1998-2012 en el Uruguay Resumen: Los índices de vegetación suponen una de las principales fuentes de información para el monitoreo y espacialización de la vegetación a distintas escalas, siendo el Normalized Difference Vegetation Index (NDVI) uno de los más utilizados. Este trabajo pretende describir y analizar la tendencia del NDVI en los sistemas ambientales de Uruguay, como una variable síntesis del comportamiento del sistema ambiental. Se aplicó un análisis multiescalar (país, cuenca, sitios), mediante la utilización del análisis de series temporales, siendo las imágenes SPOT 4 y 5, a través del programa del instrumento Vegetation (VGT) la fuente de información. Las series temporales analizadas mostraron un ajuste significativo del modelo de Autocorrelación Integrado de Medias Móviles (ARIMA), siguiendo una autocorrelación de orden 2, con nivel de integración de orden 1, ARIMA (211). Se observó una tendencia significativa a la baja del NDVI para el total de las unidades espaciales, siendo las unidades agrícolas (escala sitio) las que presentaron mayor tendencia a la baja. El desarrollo del estudio permitió construir una base de datos sin antecedentes en Uruguay, junto con la elaboración de una metodología precisa y robusta para el análisis espacio-temporal del NDVI. Se demuestra que la teledetección es una herramienta útil para la mejorar de la gestión de los sistemas ambientales.Palabras clave: NDVI, series temporales, SPOT, enfoque multiescalar, percepción remota. Study of the NDVI with multi-scale and time-series analysis using SPOT imagery during the period 1998-2012 in UruguayAbstract: Vegetation indices are a relevant source of information for spatial monitoring of vegetation at multiple scales. Among them, the Normalized Difference Vegetation Index (NDVI) is one of the most commonly used. This study aims to describe and analyze the spatial patterns of the NDVI in terrestrial systems in Uruguay at the onset of the 21st Century. A multiscalar approach (country, basin and sites) was applied using time series analysis of NDVI values obtained from SPOT 4 and 5 images through the program Instrument Vegetation (VGT). The analyzed time series showed a significant fit of the Autocorrelated Integrated Moving Averages (ARIMA) model, with an autocorrelation of order 2

The agri-exporting enclaves of the current corporate food regime intensively exploit natural assets in global strategies that govern the local processes. Their multidimensional impacts contribute to the environmental and civilizational crisis. Linked to the agrarian metabolism in its appropriation phase, land use has impacts on local systems. To understand this process, it is necessary to identify the systemic and spatial expression of environmental transformation. The objective of this work was to analyze the dynamic adjustment of aboveground net primary production (ANPP) to agricultural intensification between the years 2000 and 2017, using a land use intensity index and the soils’ productive potential. Agricultural expansion and consolidation are observed, as well as the significant intensification throughout the period in 65% of the country’s area—with differences between regions—associated with soil types. ANPP is higher in areas of low land use intensity and lower in high intensity areas, varying from high to low in soils with low to high productive potential, respectively, and growing throughout the period—depending on the area, with less growth in areas of greater intensity. The appropriation of edaphic wealth puts the systemic functionality at risk and challenges these transforming dynamics, with a strong impact on southern systems.

Agricultural intensification promotes floods and threatens family livestock production in the protected area of Farrapos Estuaries, Uruguay. Using the Holistic Risk Index (Barrera, 2011), this study analyzes the interrelationships among threat, vulnerability and responsiveness. Four livestock producers were shown to have low risk due to their high responsiveness; eighteen producers were shown to have medium risk and were divided into high vulnerability, low vulnerability and increased responsiveness groups; and three producers were shown to have high risk due to high threat and vulnerability and a lower responsiveness.A c c e p t e d M a n u s c r i p t 2 Responsiveness is related to the use of agroecological principles and the agroecological criteria that guide strategies among producers and within the protected area.

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