{"id":"doi:10.1016/j.rse.2013.10.026","kind":"article","title":"Improving the accuracy of rainfall rates from optical satellite sensors with machine learning — A random forests-based approach applied to MSG SEVIRI","authors":["Meike Kühnlein","Tim Appelhans","Boris Thies","Thomas Nauß"],"author_count":4,"year":2013,"published":"2013-11-22","venue":"Remote Sensing of Environment","cited_by":221,"doi":"10.1016/j.rse.2013.10.026","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.rse.2013.10.026","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.rse.2013.10.026","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2055308682","pdf_url":"https://www.sciencedirect.com/science/article/pii/S0034425713003945/pdf","abstract":null,"abstract_license":null,"license":"cc-by-nc-sa","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Precipitation Measurement and Analysis"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"ai-weather-climate","name":"AI Weather & Climate Modeling","domain_slug":"energy"}],"cited_in_dossiers":[]}