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遥感技术与应用  2019, Vol. 34 Issue (3): 667-676    DOI: 10.11873/j.issn.1004-0323.2019.3.0667
遥感应用     
基于变化点的青藏高原植被时空动态变化研究
许文鑫1,周玉科2 ,梁娟珠1
(1.福州大学 空间信息工程研究中心 数据挖掘与信息共享教育部重点实验室,福建 福州 350116;
2.中国科学院地理科学与资源研究所 生态系统网络观测与模拟院重点实验室,北京 100101)
A Breakpoints based Spatio-temporal Analysis of Tibetan Plateau Vegetation
Xu Wenxin1,Zhou Yuke2,Liang Juanzhu1
(1.Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education,
Fuzhou University,Spatial Information Research Center of Fujian Province,Fuzhou  350116,China;
2.Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographicand Nature Resources Research,Chinese Academy of Sciences,Beijing 100101,China)
 全文: PDF(12586 KB)  
摘要:

青藏高原脆弱的生态圈和独特的高寒地理环境,使得高原植被对气候变化反应敏感,因此探讨青藏高原植被变化趋势在认识植被对气候变化响应和区域生态保护方面具有重要意义。基于1982~2012年GIMMS NDVI3g植被指数数据集,通过季节趋势分析和变化点检测方法建立季节趋势模型对变化趋势进行分类研究,并结合土地覆被分类情况明确了高原植被在时间序列变化点前后变化趋势的时空格局。结果表明:①季节趋势模型能够有效地识别植被时间序列的变化点,发现青藏高原植被变化点时间分布跨度大,空间异质性强;②高原植被的改善区域面积大于退化区域面积,西部植被略呈退化趋势,南部和东北部植被退化趋势明显,中东部植被情况有所改善。此外,有58.93%的区域中植被状态趋于稳定,32.3%的区域中植被状态变化显著;③在高原植被状态发生一般或显著变化的区域中,单调趋势和中断趋势的植被改善情况多于退化情况,逆趋势中退化情况多于改善情况;3.14%的区域发生单调趋势变化,58.36%的区域发生中断趋势变化,38.50%的区域发生逆趋势变化;单调趋势和中断趋势的时间分布较为集中,逆趋势则布满整个时间序列;④高原不同的土地覆被类型中植被改善和退化的情况有所差异,其中改善率最高的类型是沙漠(53.30%),稀疏植被的退化率最高(60.14%)。总体而言,青藏高原植被趋于改善,但空间异质性比较显著。

关键词: 青藏高原植被指数时间序列变化点季节趋势模型趋势变化
    
Abstract: Due to the fragile ecosystem and unique geographical environment on the TP,the vegetation strongly responds to climatic shifts.Therefore,it is of great significance to discuss the spatiotemporal trend shift of vegetation,to evaluate the climate change of the plateau and to predict regional ecological development.Using the GIMMS NDVI3g dataset from 1982 to 2012 to extract the NDVI information of the TP,as well as establishing seasonal trend model to classify research through the seasonal trend analysis and breakpoints detection method,reveals the spatiotemporal pattern of the trend shifts of plateau vegetation at both ends of the breakpoints combining the classification of land cover.The results shows that conclusions.(1) The seasonal trend model can effectively identify the breakpoints of vegetation time series,moreover the time span of the breakpoints were large and the spatial heterogeneity were strong.(2) The trend of vegetation degeneration in the western part of the Tibetan Plateau was small,vegetation degeneration in the south and northeast regions was obvious,and vegetation in the central and eastern regions has improved.58.93% of the vegetation status tends to be stable.The area where the vegetation status changes significantly accounts for about 32.3% of the entire plateau.(3) In the area where the vegetation status is generally or significantly changed,the vegetation improvement of monotonous trend and interruption trend were more than that of degradation,and the degenerative situation in the reverse trend were more than the improvement.Monotonous trend changed in 3.14% of the regions,58.36% of the regions occurred interruption trend changes,and 38.50% of regions occurred reverse trends.The time distribution of the monotonous trend and the interruption trend were more concentrated,while the reverse trend covered the entire time series.(4) The vegetation improvement and degradation in different land cover types were various conditions.The type with the highest rate of improvement was desert(53.30%),and the type with the highest rate of degradation was sparse vegetation(60.14%).Overall,the vegetation in Tibetan plateau tends to be greening,but the spatial heterogeneity remains significant.
Key words: Tibetan Plateau(TP)    NDVI    Time series    Breakpoints    Seasonal trend model    Trend shifts
收稿日期: 2018-01-22 出版日期: 2019-07-10
ZTFLH:  TP79  
基金资助: 国家自然科学基金项目(41601478),国家重点研发计划(2016YFC0500103),中国科学院STS项目(KFJ-SW-STS-167),资源与环境信息系统国家重点实验室开放基金(2016)。
作者简介: 许文鑫(1995-),男,安徽六安人,硕士研究生,主要从事生态遥感、时空大数据挖掘研究。Email:xuwxfors@foxmail.com。
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引用本文:

许文鑫, 周玉科, 梁娟珠. 基于变化点的青藏高原植被时空动态变化研究 [J]. 遥感技术与应用, 2019, 34(3): 667-676.

Xu Wenxin, Zhou Yuke, Liang Juanzhu. A Breakpoints based Spatio-temporal Analysis of Tibetan Plateau Vegetation . Remote Sensing Technology and Application, 2019, 34(3): 667-676.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.3.0667        http://www.rsta.ac.cn/CN/Y2019/V34/I3/667

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