{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T23:08:29Z","timestamp":1776294509191,"version":"3.50.1"},"reference-count":80,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,11]],"date-time":"2022-04-11T00:00:00Z","timestamp":1649635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Project of China,","award":["2019YFE0126900"],"award-info":[{"award-number":["2019YFE0126900"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19030201"],"award-info":[{"award-number":["XDA19030201"]}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41861144019"],"award-info":[{"award-number":["41861144019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Alliance of International Science Organizations","award":["ANSO-CR-KP-2020-07"],"award-info":[{"award-number":["ANSO-CR-KP-2020-07"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate and early crop-type maps are essential for agricultural policy development and food production assessment at regional and national levels. This study aims to produce a crop-type map with acceptable accuracy and spatial resolution in northern Mongolia by optimizing the combination of Sentinel-1 (S1) and Sentinel-2 (S2) images with the Google Earth Engine (GEE) environment. A total of three satellite data combination scenarios are set, including S1 alone, S2 alone, and the combination of S1 and S2. In order to avoid the impact of data gaps caused by clouds on crop classification, this study reconstructed the time series of S1 and S2 with a 10-day interval using the median composite method, linear moving interpolation, and Savitzky\u2013Golay (SG) filter. Our results indicated that crop-type classification accuracy increased with the increase in data length to all three data combination scenarios. S2 alone has higher accuracy than S1 alone and the combination of S1 and S2. The crop-type map with the highest accuracy was generated using S2 data from 150 days of the year (DOY) (11 May) to 260 DOY (18 September). The OA and kappa were 0.93 and 0.78, respectively, and the F1-score for spring wheat and rapeseed were 0.96 and 0.80, respectively. The classification accuracy of the crop increased rapidly from 210 DOY (end of July) to 260 DOY (August to mid-September), and then it remained stable after 260 DOY. Based on our analysis, we filled the gap of the crop-type map with 10 m spatial resolution in northern Mongolia, revealing the best satellite combination and the best period for crop-type classification, which can benefit the achievement of sustainable development goals 2 (SDGs2).<\/jats:p>","DOI":"10.3390\/rs14081830","type":"journal-article","created":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T02:48:59Z","timestamp":1649731739000},"page":"1830","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Performance and the Optimal Integration of Sentinel-1\/2 Time-Series Features for Crop Classification in Northern Mongolia"],"prefix":"10.3390","volume":"14","author":[{"given":"Battsetseg","family":"Tuvdendorj","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"National Remote Sensing Center, Information and Research Institute of Meteorology, Hydrology, and Environment (IRIMHE), Ulaanbaatar 15160, Mongolia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongwei","family":"Zeng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5546-365X","authenticated-orcid":false,"given":"Bingfang","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8008-5670","authenticated-orcid":false,"given":"Abdelrazek","family":"Elnashar","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Department of Natural Resources, Faculty of African Postgraduate Studies, Cairo University, Giza 12613, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miao","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1758-8763","authenticated-orcid":false,"given":"Fuyou","family":"Tian","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2362-6711","authenticated-orcid":false,"given":"Mohsen","family":"Nabil","sequence":"additional","affiliation":[{"name":"Division of Agriculture Applications, Soils, and Marine (AASMD), National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 11843, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9131-5099","authenticated-orcid":false,"given":"Lkhagvadorj","family":"Nanzad","sequence":"additional","affiliation":[{"name":"National Remote Sensing Center, Information and Research Institute of Meteorology, Hydrology, and Environment (IRIMHE), Ulaanbaatar 15160, Mongolia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amanjol","family":"Bulkhbai","sequence":"additional","affiliation":[{"name":"National Remote Sensing Center, Information and Research Institute of Meteorology, Hydrology, and Environment (IRIMHE), Ulaanbaatar 15160, Mongolia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natsagsuren","family":"Natsagdorj","sequence":"additional","affiliation":[{"name":"National Remote Sensing Center, Information and Research Institute of Meteorology, Hydrology, and Environment (IRIMHE), Ulaanbaatar 15160, Mongolia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,11]]},"reference":[{"key":"ref_1","unstructured":"NSO (2022, April 05). 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