| 基于多源遥感数据的青藏高原植被变化特征评价 |
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| 引用本文： | 赵耀华,彭小清,金浩东,杜冉,陈聪,彭思佳.基于多源遥感数据的青藏高原植被变化特征评价[J].冰川冻土,2022,44(4):1216-1230. |
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| 作者姓名： | 赵耀华 彭小清 金浩东 杜冉 陈聪 彭思佳 |
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| 作者单位： | 1.兰州大学 资源环境学院，甘肃 兰州 730000;2.兰州大学 祁连山冻土生态环境野外科学观测研究站，甘肃 兰州 730000 |
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| 基金项目： | 中国科学院战略性先导科技专项（A类）(XDA20100103);国家自然科学基金项目(42171120) |
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| 摘 要： | 近几十年来青藏高原升温速率约为全球同期升温速率的2倍，对植被产生了巨大影响，给脆弱的生态环境增加了许多不确定因素，准确评估该地区植被变化显得尤为重要。不同的卫星遥感数据源对评估结果带来一定的不确定性，而过去对多源数据在该地区评估的差异性研究尚不清晰。利用MODIS、GIMMS和SPOT的NDVI数据集通过Theil-Sen趋势估计和Mann-Kendall趋势检验对2000—2014年青藏高原地区的植被变化进行分析，并对不同数据之间的差异性进行评价。结果表明：SPOT NDVI反映的植被绿化显著且迅速，27.44%的像元显著绿化，分别超出MODIS与GIMMS NDVI 4.10%、15.89%，生长季显著绿化趋势达到0.0182 （10a）-1，高于其他数据0.0078~0.0090 （10a）-1。MODIS NDVI随着分辨率的提高，显著绿化的像元占比与绿化趋势却逐渐降低；MODIS数据之间显著绿化的像元占比相差不足2.80%。GIMMS NDVI显著褐化的像元占比平均达5.83%，超出其他数据3.37%~5.51%，在春季显著褐化像元最多（7.88%），与显著绿化像元占比相当。区域平均NDVI具有最小的显著绿化趋势［0.0092 （10a）-1］，并在春、夏两季表现为植被褐化。因此，基于GIMMS NDVI探究青藏高原植被变化特征时，特别是对春季物候研究，可能会造成结果较大的不确定性。而SPOT与MODIS NDVI体现了较高的一致性，可以互为补充，探究高原植被变化。
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| 关 键 词： | 青藏高原 植被变化 NDVI 多源遥感数据 |
| 收稿时间： | 2021-11-24 |
| 修稿时间： | 2022-08-03 |
Evaluation of vegetation change characteristics on the Tibetan Plateau based on multi-source remote sensing data |
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| Yaohua ZHAO,Xiaoqing PENG,Haodong JIN,Ran DU,Cong CHEN,Sijia PENG.Evaluation of vegetation change characteristics on the Tibetan Plateau based on multi-source remote sensing data[J].Journal of Glaciology and Geocryology,2022,44(4):1216-1230. |
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| Authors: | Yaohua ZHAO Xiaoqing PENG Haodong JIN Ran DU Cong CHEN Sijia PENG |
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| Institution: | 1.College of Earth and Environmental Sciences，Lanzhou University，Lanzhou 730000，China;2.Observation and Research Station on Eco-Environment of Frozen Ground in the Qilian Mountains，Lanzhou University，Lanzhou 730000，China |
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| Abstract: | The warming rate of the Tibetan Plateau in recent decades is about twice the global average warming rate in the same period， with a great impact on the vegetation and adding many uncertainties to the fragile ecological environment. It is particularly important to accurately assess vegetation changes in the region. Different sources of satellite remote sensing data can introduce some uncertainty into the assessment results， and past studies on the variability of multi-source data assessment in the region are unclear. Therefore， in this study， the NDVI datasets from MODIS， GIMMS and SPOT were used to evaluate the vegetation change on the Tibetan Plateau region from 2000 to 2014 through Sen’s slope estimator and Mann-Kendall trend test， and to assess the differences among different datasets. The results illuminated that SPOT NDVI reflected significant and rapid vegetation greening， with 27.44% of the image pixels significantly greening， exceeding MODIS and GIMMS NDVI by 4.10% and 15.89%， respectively， and the significant greening trend in the growing season reached 0.0182 （10a）-1， higher than the other data 0.0078~0.0090 （10a）-1. The percentage of significant greening pixels and the greening trend of MODIS NDVI gradually decreased as the resolution increased， and the difference in the percentage of significantly greening pixels between MODIS data is less than 2.80%. The proportion of significantly browning pixels in GIMMS NDVI averaged 5.83%， exceeding the other data by 3.37%~5.51%， with the most significantly browning pixels in spring （7.88%） being comparable to the proportion of significantly greening pixels. The regional mean NDVI had a minimum significant greening trend of 0.0092 （10a）-1 and showed vegetation browning in spring and summer. Therefore， when exploring the characteristics of vegetation change on the Tibetan Plateau based on GIMMS NDVI， especially for spring phenology studies， it may cause greater uncertainty in the results. In contrast， SPOT and MODIS NDVI show a high degree of agreement and can complement each other in exploring vegetation change on the plateau. |
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| Keywords: | Tibetan Plateau vegetation change NDVI multi-source remote sensing data |
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