Proximal versus remote sensing to monitor pasture quality in a Mediterranean Montado ecosystem

Abstract

Montado is an agro-forestry system that covers substantial areas in countries of the Mediterranean region. In this system, the natural dryland pasture is the principal source of animal feed in extensive grazing. The climatic seasonality associated with the inter-annual irregularity of precipitation greatly determines the development of the pasture vegetative cycle. As the spring reaches its end, there is a notable reduction in the nutritive value of the plants, and a critical period begins. The objective of this work was to evaluate, through the relationship between pasture quality indices (pasture quality degradation index, PQDI and normalized difference vegetation index, NDVI), two technological approaches to monitor the evolution of the quality of a biodiverse pasture in the period of greatest vegetative development (between February and June): (i) through proximal sensing (PS), with the use of an active optical sensor; (ii) through remote sensing (RS), using images captured by the Sentinel-2 satellite. The results of this study show strong and significant relationships between PQDI and NDVI (obtained by PS or RS). These two techniques (PS or RS) can, therefore, be used in a complementary way to identify and anticipate the animal supplementation needs and support the farmer’s decision making process.