{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:51:45Z","timestamp":1760403105543,"version":"build-2065373602"},"reference-count":57,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T00:00:00Z","timestamp":1587686400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA19060304"],"award-info":[{"award-number":["XDA19060304"]}]},{"name":"LZJTU EP","award":["201806"],"award-info":[{"award-number":["201806"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Oil palm is the main cash crop grown in Malaysia, and palm oil plays an important role in the world oil market. A number of studies have used multisource remote sensing data to conduct research on oil palms in Malaysia, but there are a lack of long-term oil palm mapping studies, especially when the percentage of oil palm tree cover was higher than other plantations in Malaysia during the period of 2000\u20132012. To overcome this limitation, we used the Google Earth Engine platform to perform oil palm classification based on Landsat reflectance data. The spatial distribution of oil palms in Malaysia in five periods from 2000 to 2018 was obtained. Then, the planting center of gravity transfer method was applied to analyze the expansion of oil palms in Malaysia from 2000 to 2018 using Landsat data, elevation data, oil palm planting area, crude palm oil price, and other statistical data. Meanwhile, the driving factors affecting the change in oil palm planting area were also analyzed. The results showed that: (1) During 2000\u20132018, the oil palm planted area in Malaysia increased by 5.06 Mha (million ha), with a growth rate of 83.50%. Specifically, the increased area and growth rate for West Malaysia were 2.05 Mha and 62.05% and for East Malaysia were 3.01 Mha and 109.45%, respectively. (2) Three expansion patterns of oil palms were observed: (i) from a fragmented pattern to a connected area, (ii) expansion along a river, and (iii) from a plain to a gently sloped area. (3) The maximum shift of the center of gravity of the oil palms in West Malaysia was 10 km, while in East Malaysia, it reached 100 km. The East Malaysia oil palm planting potential was greater than that of West Malaysia and showed a trend of shifting from coastal areas to inland areas. (4) Malaysia\u2019s oil palms are mainly planted in areas below 100 m above sea level; although a trend of expansion into high altitudes is visible, oil palm plantings extend to areas below 300 m above sea level. (5) Topography, crude palm oil prices, and deforestation are closely related to changes in oil palm planted area.<\/jats:p>","DOI":"10.3390\/ijgi9040280","type":"journal-article","created":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T11:42:14Z","timestamp":1587728534000},"page":"280","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Spatial\u2013Temporal Evolution and Analysis of the Driving Force of Oil Palm Patterns in Malaysia from 2000 to 2018"],"prefix":"10.3390","volume":"9","author":[{"given":"Wenhui","family":"Li","sequence":"first","affiliation":[{"name":"Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China"},{"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":"National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China"},{"name":"Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3062-2727","authenticated-orcid":false,"given":"Dongjie","family":"Fu","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":"Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China"}]},{"given":"Fenzhen","family":"Su","sequence":"additional","affiliation":[{"name":"Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China"},{"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":"Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China"}]},{"given":"Yang","family":"Xiao","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":"Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China"},{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Scanes, C.G. 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