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Monitoring Drought Impacts on Rainfed Olive Orchards in the Iberian Peninsula Using Satellite-Derived Vegetation Indices
* 1, 2 , * 1, 3 , * 4 , * 5 , * 6 , * 1, 3 , * 1, 2
1  Centre for the Research and Technology of Agro-Environmental and Biological Sciences, Institute for Innovation, Capacity Building, and Sustainability of Agri-Food Production, Universidade de Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
2  Department of Agronomy, School of Agrarian and Veterinary Sciences, Universdade de Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
3  School of Sciences and Technology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
4  LEAF—Linking Landscape, Environment, Agriculture and Food—Research Center, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisboa, Portugal
5  Department of Graphic Expression, School of Agricultural Engineering, Universidad de Extremadura (UEX), Avda. Adolfo Suárez, s/n., 06007 Badajoz, Spain
6  Department of Graphic Expression, School of Industrial Engineering, Universidad de Extremadura, Avda. de Elvas, s/n., 06006 Badajoz, Spain
Academic Editor: Oscar Vicente

Abstract:

Olive growing plays an important socioeconomic role in Mediterranean agriculture, particularly in the Iberian Peninsula (IP), where rainfed systems are increasingly vulnerable to drought under climate change. This study investigates the spatial and temporal responses of olive orchards to drought in two traditional production regions: the Trás-os-Montes (TM) agrarian region in Portugal and the Badajoz (BA) province in Spain. Satellite-based multispectral data were used to compute vegetation indices from the Harmonized Landsat Sentinel-2 dataset (HLSL30), specifically the Soil-Adjusted Vegetation Index (SAVI) and the Normalized Difference Moisture Index (NDMI), which were analysed over the 2015–2023 period. Drought intensity was assessed using the Mediterranean Palmer Drought Severity Index (MedPDSI), specifically adapted for olive ecosystems. Correlation and lag analyses were performed to explore drought–vegetation relationships and temporal responses.
Results revealed regional differences, with the BA region experiencing more intense and prolonged drought episodes, stronger negative correlations between MedPDSI and vegetation indices (r = −0.72, p < 0.05), and a lagged vegetation response of approximately 2 months. On the other hand, the TM region showed milder drought conditions and a more stable vegetation response, suggesting slightly higher resilience. Both SAVI and NDMI detected vegetation stress during the severe drought years of 2017 and 2022, confirming their sensitivity to variations in soil moisture and canopy greenness.
This approach demonstrates the potential of combining satellite-based vegetation indices with drought indicators to monitor stress in perennial crops. Although spatial resolution and cloud cover may introduce some uncertainty for constant real-time monitoring, the results provide valuable perspectives for early drought detection and adaptive water management. The proposed framework supports the development of sustainable strategies to improve the resilience and productivity of olive orchards in Mediterranean environments.

Keywords: olive orchards; MedPDSI; SAVI; NDMI; remote sensing
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