{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T08:38:38Z","timestamp":1769330318096,"version":"3.49.0"},"reference-count":64,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,24]],"date-time":"2022-11-24T00:00:00Z","timestamp":1669248000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Taiwan Ministry of Science and Technology","award":["MOST 111-2111-M-008-027"],"award-info":[{"award-number":["MOST 111-2111-M-008-027"]}]},{"name":"Taiwan Ministry of Science and Technology","award":["111-2119-M-008-006"],"award-info":[{"award-number":["111-2119-M-008-006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Increasing the accuracy of rainfall forecasts is crucial as an effort to prevent hydrometeorological disasters. Weather changes that can occur suddenly and in a local scope make fast and precise weather forecasts increasingly difficult to inform. Additionally, the results of the numerical weather model used by the Indonesia Agency for Meteorology, Climatology, and Geophysics are only able to predict the rainfall with a temporal resolution of 1\u20133 h and cannot yet address the need for rainfall information with high spatial and temporal resolution. Therefore, this study aims to provide the rainfall forecast in high spatiotemporal resolution using Himawari-8 and GPM IMERG (Global Precipitation Measurement: The Integrated Multi-satellite Retrievals) data. The multivariate LSTM (long short-term memory) forecasting is employed to predict the cloud brightness temperature by using the selected Himawari-8 bands as the input and training data. For the rain rate regression, we used the random forest technique to identify the rainfall and non-rainfall pixels from GPM IMERG data as the input in advance. The results of the rainfall forecast showed low values of mean error and root mean square error of 0.71 and 1.54 mm\/3 h, respectively, compared to the observation data, indicating that the proposed study may help meteorological stations provide the weather information for aviation purposes.<\/jats:p>","DOI":"10.3390\/rs14235950","type":"journal-article","created":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T03:00:13Z","timestamp":1669345213000},"page":"5950","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Rainfall Forecast Using Machine Learning with High Spatiotemporal Satellite Imagery Every 10 Minutes"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7047-2308","authenticated-orcid":false,"given":"Febryanto","family":"Simanjuntak","sequence":"first","affiliation":[{"name":"Malikussaleh Meteorological Station, The Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG), Jl. Bandara Malikussaleh, Muara Batu, Aceh Utara 24355, Indonesia"},{"name":"The Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG), Jl. Angkasa I No. 2, Kemayoran, Jakarta Pusat 10720, Indonesia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6928-4951","authenticated-orcid":false,"given":"Ilham","family":"Jamaluddin","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Central University, No. 300, Jhongda Rd., Jhongli Dist., Taoyuan City 32001, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1045-3196","authenticated-orcid":false,"given":"Tang-Huang","family":"Lin","sequence":"additional","affiliation":[{"name":"Center for Space and Remote Sensing Research, National Central University, No. 300, Jhongda Rd., Jhongli Dist, Taoyuan City 32001, Taiwan"},{"name":"Center for Astronautical Physics and Engineering, National Central University, No. 300, Jhongda Rd., Jhongli Dist, Taoyuan City 32001, Taiwan"}]},{"given":"Hary Aprianto Wijaya","family":"Siahaan","sequence":"additional","affiliation":[{"name":"The Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG), Jl. Angkasa I No. 2, Kemayoran, Jakarta Pusat 10720, Indonesia"},{"name":"Domine Eduard Osok Meteorological Station, The Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG), Klabala, West Sorong, Sorong City 98411, Indonesia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5448-9900","authenticated-orcid":false,"given":"Ying-Nong","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Central University, No. 300, Jhongda Rd., Jhongli Dist., Taoyuan City 32001, Taiwan"},{"name":"Center for Space and Remote Sensing Research, National Central University, No. 300, Jhongda Rd., Jhongli Dist, Taoyuan City 32001, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.jaridenv.2013.05.013","article-title":"Evaluation of satellite-based precipitation estimation over Iran","volume":"97","author":"Nasrollahi","year":"2013","journal-title":"J. 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