{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T16:33:48Z","timestamp":1770741228498,"version":"3.49.0"},"reference-count":52,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,12,26]],"date-time":"2018-12-26T00:00:00Z","timestamp":1545782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant Nos. 41571095 and 41161140352"],"award-info":[{"award-number":["Grant Nos. 41571095 and 41161140352"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Assessing changes in rice cropping systems is essential for ensuring food security, greenhouse gas emissions, and sustainable water management. However, due to the insufficient availability of images with moderate to high spatial resolution, caused by frequent cloud cover and coarse temporal resolution, high-resolution maps of rice cropping systems at a large scale are relatively limited, especially in tropical and subtropical regions. This study combined the difference of Normalized Difference Vegetation Index (dNDVI) method and the Normalized Difference Vegetation Index (NDVI) threshold method to monitor changes in rice cropping systems of Southern China using Landsat images, based on the phenological differences between different rice cropping systems. From 1990\u20132015, the sown area of double cropping rice (DCR) in Southern China decreased by 61054.5 km2, the sown area of single cropping rice (SCR) increased by 20,110.7 km2, the index of multiple cropping decreased from 148.3% to 129.3%, and the proportion of DCR decreased by 20%. The rice cropping systems in Southern China showed a \u201cdouble rice shrinking and single rice expanding\u201d change pattern from north to south, and the most dramatic changes occurred in the Middle-Lower Yangtze Plain. This study provided an efficient strategy that can be applied to moderate to high resolution images with deficient data availability, and the resulting maps can be used as data support to adjust agricultural structures, formulate food security strategies, and compile a greenhouse gas emission inventory.<\/jats:p>","DOI":"10.3390\/rs11010035","type":"journal-article","created":{"date-parts":[[2018,12,26]],"date-time":"2018-12-26T11:31:21Z","timestamp":1545823881000},"page":"35","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Decreasing Rice Cropping Intensity in Southern China from 1990 to 2015"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3510-9829","authenticated-orcid":false,"given":"Min","family":"Jiang","sequence":"first","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Liangjie","family":"Xin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Xiubin","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Minghong","family":"Tan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Renjing","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,26]]},"reference":[{"key":"ref_1","unstructured":"FAOSTAT (2018, December 24). 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