{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T06:42:03Z","timestamp":1769928123051,"version":"3.49.0"},"reference-count":63,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,10]],"date-time":"2022-04-10T00:00:00Z","timestamp":1649548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the CAS Earth Big Data Science Project","award":["XDA19060303"],"award-info":[{"award-number":["XDA19060303"]}]},{"name":"the National Science Foundation of China","award":["41901354"],"award-info":[{"award-number":["41901354"]}]},{"name":"the Innovation Project of LREIS","award":["O88RAA01YA"],"award-info":[{"award-number":["O88RAA01YA"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High-precision spatial mapping of paddy planting areas is very important for food security risk assessment and agricultural monitoring. Previous studies have mainly been based on multi-source satellite imagery, the fusion of Synthetic Aperture Radar (SAR) with optical data, and the combined use of multi-scale and multi-source sensors. However, there have been few studies on paddy spatial mapping using collaborative multi-source remote sensing product information, especially in tropical regions such as Southeast Asia. Therefore, based on the Google Earth Engine (GEE) platform, in this study, Cambodia, which is dominated by agriculture, was taken as the study area, and an extraction scheme for paddy planting areas was developed from collaborative multi-source information, including multi-source remote sensing images (Sentinel-1 and Sentinel-2), multi-source remote sensing land cover products (GFSAD30SEACE, GLC_FCS30-2015, FROM_GLC2015, SERVIR MEKONG, and GUF), paddy phenology information, and topographic features. Evaluation and analysis of the extraction results and the SERVIR MEKONG and ESACCI-LC paddy products revealed that the accuracy of the paddy planting areas extracted using the proposed method is the highest, with an overall accuracy of 89.90%. The results of the proposed method are better than those of the other products in terms of the outline of the paddy planting areas and the description of the road information. The results of this study provide a reference for future high-precision paddy mapping.<\/jats:p>","DOI":"10.3390\/rs14081823","type":"journal-article","created":{"date-parts":[[2022,4,10]],"date-time":"2022-04-10T23:06:01Z","timestamp":1649631961000},"page":"1823","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Collaborative Extraction of Paddy Planting Areas with Multi-Source Information Based on Google Earth Engine: A Case Study of Cambodia"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9598-4350","authenticated-orcid":false,"given":"Junmei","family":"Kang","sequence":"first","affiliation":[{"name":"Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1643-8480","authenticated-orcid":false,"given":"Xiaomei","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6776-2910","authenticated-orcid":false,"given":"Zhihua","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Chong","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jun","family":"Wang","sequence":"additional","affiliation":[{"name":"Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1007\/s10584-006-9122-6","article-title":"Assessing the impacts of climate change on rice yields in the main rice areas of China","volume":"80","author":"Yao","year":"2007","journal-title":"Clim. 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