02638naa a2200253 a 450000100080000000500110000800800410001902400440006010000160010424501670012026000090028752018430029665000160213965000150215565000190217065300090218965300250219865300160222370000230223970000230226270000220228570000230230777300540233021185822024-02-06       2019    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.3390/rs112429562DOI1 aHOTT, M. C.  aAnalysis of grassland degradation in Zona da Mata, MG, Brazil, based on NDVI time series data with the integration of phenological metrics.h[electronic resource]  c2019  aThere is currently a lot of interest in determining the state of Brazilian grasslands. Governmental actions and programs have recently been implemented for grassland recovery in Brazilian states, with the aim of improving production systems and socioeconomic indicators. The aim of this study is to evaluate the vegetative growth, temporal vigor, and long-term scenarios for the grasslands in Zona da Mata, Minas Gerais State, Brazil, by integrating phenological metrics. We used metrics derived from the normalized difference vegetation index (NDVI) time series from moderate resolution imaging spectroradiometer (MODIS) data, which were analyzed in a geographic information system (GIS), using multicriteria analysis, the analytical hierarchy process, and a simplified expert system (ESS). These temporal metrics, i.e., the growth index (GI) for 16-day periods during the growing season; the slope; and the maximum, minimum, and mean for the time series, were integrated to investigate the grassland vegetation conditions and degradation level. The temporal vegetative vigor was successfully described using the rescaled range (R/S statistic) and the Hurst exponent, which, together with the metrics estimated for the full time series, imagery, and field observations, indicated areas undergoing degradation or areas that were inadequately managed (approximately 61.5%). Time series analysis revealed that most grasslands showed low or moderate vegetative vigor over time with long-term persistence due to farming practices associated with burning and overgrazing. A small part of the grasslands showed high and sustainable plant densities (approximately 8.5%). A map legend for grassland management guidelines was developed using the proposed method with remote sensing data, which were applied using GIS software and a field campaign.  aDegradation  aGrasslands  aRemote sensing  aNDVI  aPhenological metrics  aTime series1 aCARVALHO, L. M. T.1 aANTURNES, M. A. H.1 aRESENDE, J. C. de1 aROCHA, W. S. D. da  tRemote Sensinggv. 11, n. 24, article 2956, 2019.