{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:46:48Z","timestamp":1760240808586,"version":"build-2065373602"},"reference-count":4,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T00:00:00Z","timestamp":1568937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Recently, remote sensing for traffic and especially aviation meteorology has become a focus of attention by the aviation industry and air navigation services [...]<\/jats:p>","DOI":"10.3390\/rs11192197","type":"journal-article","created":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T10:48:14Z","timestamp":1568976494000},"page":"2197","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Editorial for: Remote Sensing Methods and Applications for Traffic Meteorology"],"prefix":"10.3390","volume":"11","author":[{"given":"Matthias","family":"Jerg","sequence":"first","affiliation":[{"name":"German Meteorological Service, Aeronautical Meteorology Department, Frankfurter Stra\u00dfe 135, 63067 Offenbach, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Han, D., Lee, J., Im, J., Sim, S., Lee, S., and Han, H. (2019). A Novel Framework of Detecting Convective Initiation Combining Automated Sampling, Machine Learning, and Repeated Model Tuning from Geostationary Satellite Data. Remote Sens., 11.","DOI":"10.3390\/rs11121454"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"M\u00fcller, R., Haussler, S., Jerg, M., and Heizenreder, D. (2019). A Novel Approach for the Detection of Developing Thunderstorm Cells. Remote Sens., 11.","DOI":"10.3390\/rs11040443"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"M\u00fcller, R., Haussler, S., and Jerg, M. (2018). The Role of NWP Filter for the Satellite Based Detection of Cumulonimbus Clouds. Remote Sens., 10.","DOI":"10.3390\/rs10030386"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sim, S., Im, J., Park, S., Park, H., Ahn, M.H., and Chan, P.-W. (2018). Icing Detection over East Asia from Geostationary Satellite Data Using Machine Learning Approaches. Remote Sens., 10.","DOI":"10.3390\/rs10040631"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/19\/2197\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:22:27Z","timestamp":1760188947000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/19\/2197"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,20]]},"references-count":4,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2019,10]]}},"alternative-id":["rs11192197"],"URL":"https:\/\/doi.org\/10.3390\/rs11192197","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,9,20]]}}}