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• The increasing occurrence of extreme droughts threatens eucalypt tropical forestry. • Multi-temporal ground surveys and UAV imagery were used to monitor drought. • Area-based image classification and field data were applied for model training. • We applied financial evaluation to estimate production and revenue losses. • Reducing stocking and improving clone selection emerged as priorities. The plantation of fast-growing tree species plays a crucial role in supplying forest products to growing economies while relieving pressure on native forests reducing the overexploitation of native ecosystems. Grown in more than 90 countries, Eucalyptus spp. are fast-growing tree species driving economic production comprising pulp, wood, or thermal energy. Climate change is increasing the frequency and severity of extreme drought episodes: the 2019 drought in Mato Grosso, Brazil, was the second driest episode ever recorded. Forest inventory data comprising thousands of individual tree measurements collected in consecutive surveys - years 2019, 2020, 2021 – were modelled with mixed-effects models to identify significant factors influencing tree mortality after drought. Time-series of growth dynamics of the four eucalypt commercial clones were tested. For the landscape assessment, surveys using unmanned aerial vehicle (UAV) supported a high-resolution image mosaicking to derive digital surface models and the vegetation indexes driving segmentation and classification methods using ground plot-level observations as training data. The impact of drought was measured in terms of mortality, growth dynamics and the financial losses computed when valuing the 1400-ha plantation along the 3-year series. The modelling results showed high-stocking plantations suffered more from extreme water-stress conditions. The interaction between stocking and clone was analysed. On average, the 2019 drought triggered an estimate loss of $3500 per hectare. The estimation of live and dead conditions using UAV-based outcomes reached an overall accuracy of 89% and 0.7 in the Cohen's kappa used to map forest health wall-to-wall. Our findings advocate for a reduction of tree planting density and enhanced clone selection to turn eucalypt plantations more resilient to extreme water-stress. Combining UAV-based remote sensing technology, ground truth data and management expertise in eucalypt management eases the operationalization of data-driven solutions towards more resilient silvicultural guidelines and increased efficiency of forest plantations. [ABSTRACT FROM AUTHOR]