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• Plant diversity is higher in pastures with grazing donkeys than in abandoned pastures. • Catalan donkey grazing reduces phytovolume and biomass in pastures. • Sentinel-2 images can help monitoring donkey grazing activities. • In Puy de Cinca, northeast Spain, forest expansion in mountain landscapes has increased 8-fold in 6 decades. • Current and historic aerial imagery contributes to assessing mountain landscapes changes. Traditional Mediterranean Mountain landscapes in Spain have suffered dramatic environmental and social changes over the last seven decades. The loss of these landscapes has had consequences for biodiversity, soil erosion, landscape quality and ecosystem services as croplands and pastures were mainly converted into forests and scrublands. Many animal breeds present in traditional land uses such as the Catalan donkey (Equus asinus var. catalana), are also at risk of extinction, but can provide environmental services while recovering traditional landscapes. In Puy de Cinca, a village in mountainous northeast Spain, we studied how grazing by Catalan donkeys reduces pasture biomass and the effects on plant diversity in pastures. We used Sentinel-2 satellite imagery to calculate the Normalized Difference Vegetation Index (NDVI), a biomass sensitive spectral index, throughout the grazing period to monitor pasture biomass and compared it to pastures without grazing. We also calculated several plant diversity indicators in pastures with and without grazing donkeys. Furthermore, we studied land use changes over the last seven decades using old (1956) and current (2018) aerial images, with forest, agricultural lands, and trails interconnecting the village being mapped to understand landscape changes. The results indicated a great increase in the forested area (348.3 ± 17.0 ha). Meanwhile, a severe decrease in cropland area (73 %) and trail length (62.5 %) was also observed. Concerning the effect of donkey grazing, biomass was lower in pastures with grazing donkeys, with NDVI values decreasing once donkeys started grazing. Nevertheless, plant diversity was higher in pastures with grazing donkeys than in abandoned pastures. This study demonstrated the capacity of low-to-moderate-intensity donkey grazing to improve plant diversity and reduce biomass in pastures. Furthermore, the study of land use changes allowed an understanding of landscape dynamics, which can help address the social and environmental recovery of the village. [ABSTRACT FROM AUTHOR]

Reliable methods for estimating wheat grain yield before harvest could help improve farm management and, if applied on a regional level, also help identify spatial factors that influence yield. Regional grain yield can be estimated using conventional methods, but the typical process is complex and labor-intensive. Here we describe the development of a streamlined approach using publicly accessible agricultural data, field-level yield, and remote sensing data from Sentinel-2 satellite to estimate regional wheat grain yield. We validated our method on wheat croplands in Navarre in northern Spain, which features heterogeneous topography and rainfall. First, this study developed stepwise multilinear equations to estimate grain yield based on various vegetation indices, which were measured at various phenological stages in order to determine the optimal timings. Second, the most suitable model was used to estimate grain yield in wheat parcels mapped from Sentinel-2 satellite images. We used a supervised pixel-based random forest classification and the estimates were compared to government-published post-harvest yield statistics. When tested, the model achieved an R2 of 0.83 in predicting grain yield at field level. The wheat parcels were mapped with an accuracy close to 86% for both overall accuracy and compared to official statistics. Third, the validated model was used to explore potential relationships of the mapped per-parcel grain yield estimation with topographic features and rainfall by using geographically weighted regressions. Topographic features and rainfall together accounted for an average for 11 to 20% of the observed spatial variation in grain yield in Navarre. These results highlight the ability of our method for estimating wheat grain yield before harvest and determining spatial factors that influence yield at the regional scale. [ABSTRACT FROM AUTHOR]

The use of satellites to monitor crops and support their management is gathering increasing attention. The improved temporal, spatial, and spectral resolution of the European Space Agency (ESA) launched Sentinel-2 A + B twin platform is paving the way to their popularization in precision agriculture. Besides the Sentinel-2 A + B constellation technical features the open-access nature of the information they generate, and the available support software are a significant improvement for agricultural monitoring. This paper was motivated by the challenges faced by researchers and agrarian institutions entering this field; it aims to frame remote sensing principles and Sentinel-2 applications in agriculture. Thus, we reviewed the features and uses of Sentinel-2 in precision agriculture, including abiotic and biotic stress detection, and agricultural management. We also compared the panoply of satellites currently in use for land remote sensing that are relevant for agriculture to the Sentinel-2 A + B constellation features. Contrasted with previous satellite image systems, the Sentinel-2 A + B twin platform has dramatically increased the capabilities for agricultural monitoring and crop management worldwide. Regarding crop stress monitoring, Sentinel-2 capacities for abiotic and biotic stresses detection represent a great step forward in many ways though not without its limitations; therefore, combinations of field data and different remote sensing techniques may still be needed. We conclude that Sentinel-2 has a wide range of useful applications in agriculture, yet still with room for further improvements. Current and future ways that Sentinel-2 can be utilized are also discussed. [ABSTRACT FROM AUTHOR]