Abstract
There 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.
Highlights
Minas Gerais State is the most important milk-producing area in Brazil
This principle was adopted for the analysis of Normalized difference vegetation index (NDVI) data series in pastures of the studied region and considered the specifics related to herbaceous vegetation and decumbent, tussock-forming foliage, and it can reflect photosynthetic activity for all soil covers, despite the potential for overgrazing, which is typically caused by local livestock
The present study used the NDVI/Moderate Resolution Imaging Spectroradiometer (MODIS) Terra data series to estimate pasture growth-related metrics and integrated them through multicriteria and categorization by Hurst exponents using a simplified expert system employed to demonstrate long-term memory processes in conjunction with vegetation phenological parameters expressed in time series
Summary
Minas Gerais State is the most important milk-producing area in Brazil. It produces approximately nine billion liters of milk per year, and the Zona da Mata region is responsible for 10% of the total production [1]. The preparation of hypertemporal databases involves the elimination of invalid values while maintaining the time series behavior This principle was adopted for the analysis of NDVI data series in pastures of the studied region and considered the specifics related to herbaceous vegetation and decumbent, tussock-forming foliage, and it can reflect photosynthetic activity for all soil covers, despite the potential for overgrazing, which is typically caused by local livestock. The aim of the present study was to analyze grassland development in Zona da Mata based on seasonal metrics and statistics of time series, integrating the weighted MCA and ESS This methodology was employed in a raster-based geographic information system (GIS) and generated management guidelines from the temporal vigor classes, which may enable decision-making and support public policies in the agricultural sector. For the areas classified with a high vegetative density and persistence over time, continuous stocking can be adopted, considering the rapid leaf growth of tillers and saturation of leaf biomass production
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