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摘要： 20世纪90年代以来橡胶林种植面积在西双版纳地区迅猛扩大，对该区域橡胶林种植面积、种植结构变化的精确监测是客观评价该地区橡胶林种植与生态环境变化关系的关键。针对西双版纳热带山地地区植被光谱特征的相似性及地形和气候条件的复杂性问题，结合该地区橡胶林冬季落叶的物候特征，采用时空数据融合算法，分别选取中分辨率的ETM+、OLI、Sentinel-2A数据与高时间分辨率的MODIS数据融合，建立高时空分辨率可见光遥感数据集，并分析不同融合数据源对热带山地环境下橡胶林识别精度的差异。结果表明：①基于时空融合数据提取的橡胶林物候变化特征能够实现较高精度的橡胶林识别，识别精度可以达到89%以上，Kappa高于0.83；②运用10 m分辨率的Sentinel-2A数据进行分类时，能够获取比Landsat数据更高精度的分类结果，表明Sentinel-2A数据在高时空数据融合及热带植被遥感应用中有较好前景。 关键词： 橡胶林识别;  时空数据融合;  热带山地;  ')" href="#">Sentinel-2A     Abstract: Since 1990s，rubber plantations has been growing rapidly in Xishuangbanna，it is vitally important to the evaluation of the relationship between the rubber plantation and the change of ecological environment in the region.Aiming at the problem of similarity of vegetation's spectral feature and complexity of topography and climatic conditions，combined with the phenological characteristics of rubber plantation fallen leaf in winter in the region，ESTARFM algorithm was used and we selected ETM+，OLI and Sentinel\|2A data to fuse with high temporal resolution MODIS data respectively to establish a high spatial and temporal resolution visible remote sensing data setand analyze the difference of the recognition accuracy of the rubber plantations in tropical mountainous environments by different fusion data sources.The results show that：(1) During the key phenological period of the rubber plantation from January to March，the phenological features extracted using remote sensing data based on high spatial and temporal resolution can remarkably improve the identification accuracy of rubber plantations，the recognition accuracy more than 89% and Kappa higher than 0.83;(2) in the vegetation classification of fragmented mountainous area，10 m resolution Sentinel\|2A data used classification will obtain higher classification accuracy than Landsat data，which indicates that the Sentinel\|2A data is more promising in the high spatial\|temporal data fusion and the tropical vegetation remote sensing application.

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