Articles | Volume 25, issue 6
Research article
16 Jun 2021
Research article |  | 16 Jun 2021

Satellite rainfall products outperform ground observations for landslide prediction in India

Maria Teresa Brunetti, Massimo Melillo, Stefano Luigi Gariano, Luca Ciabatta, Luca Brocca, Giriraj Amarnath, and Silvia Peruccacci

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Cited articles

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Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., and Levizzani, V.: Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data, J. Geophys. Res., 119, 5128–5141,, 2014. 
Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S., Schüller, L., Bojkov, B., and Wagner, W.: SM2RAIN-ASCAT (2007–June 2020): global daily satellite rainfall from ASCAT soil moisture (Version 1.3) [Data set], Zenodo,, 2019. 
Short summary
Satellite and rain gauge data are tested to predict landslides in India, where the annual toll of human lives and loss of property urgently demands the implementation of strategies to prevent geo-hydrological instability. For this purpose, we calculated empirical rainfall thresholds for landslide initiation. The validation of thresholds showed that satellite-based rainfall data perform better than ground-based data, and the best performance is obtained with an hourly temporal resolution.