Please wait a minute...
img

官方微信

遥感技术与应用  2019, Vol. 34 Issue (2): 367-376    DOI: 10.11873/j.issn.1004-0323.2019.2.0367
物候遥感专栏     
基于NDVI数据的江苏省植被物候变化及其影响因子分析
李嘉玲1,董东林1,林刚1,汪箫悦2,王健3,吴朝阳2
 (1.中国矿业大学(北京) 地球科学与测绘工程学院,北京 100083;
2.中国科学院地理科学与资源研究所 陆地表层格局与模拟重点实验室,北京 100101;
3.中国科学院遥感与数字地球研究所 遥感科学国家重点实验室,北京 100101)
 
Changes of Vegetation Phenology in Jiangsu Province and Its Impact Factors based on NDVI Data
 (1.College of Geoscience and Surveying Engineering,China University of Mining & Technology,Beijing 100083,China;2.The Key Laboratory of Land Surface Pattern and Simulation,Institute of Geographical Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;3.State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100101,China)

 
 全文: PDF(10813 KB)  
摘要:

以气候变暖为主要特征的全球气候变化与生态系统的相互作用成为影响可持续发展的重要因素。植被作为陆地生态系统的主要组成部分,在生态环境评价及碳水循环等方面具有重要作用。以江苏省为研究区,利用长时间序列的GIMMS NDVI3g数据集和气象数据,采用Logistic函数法提取该区域过去34 a(1982~2015年)植被生长期物候(Start Of Season SOS,End Of Season EOS)变化的时空分布特征,并用相关性分析法定量确定主要气象因子(温度、降水)对物候变化的贡献。结果表明:①空间上,从江苏省南部到北部,SOS呈递增趋势,EOS呈递减趋势;②时间上,大部分(83.1%)像元的SOS提前,主要分布在江苏省中部及北部地区,大多提前1~2 d/a,69.2%像元的EOS延后,大多延后0~1 d/a;③植被生长期开始SOS/EOS对温度、降水有明显响应,70.5%像元的SOS与温度呈负相关,主要位于江苏省北部及少部分南部地区,55.5%像元的SOS与降水呈负相关,55.2%像元的EOS与温度呈正相关,71.2%像元的EOS与降水呈负相关。整体上,温度的升高导致生长期提前,降水对SOS具有双向作用,秋季物候的影响因子更为复杂,温度和降水的变化并不能导致EOS的提前或者推迟。本研究加深对气候变化与植被生态系统相互作用过程的认识,为未来植被及气候变化分析提供参考。

关联数据DOI:  10.1022/rsta201902116

关键词: 植被物候变化GIMMS NDVI3g气候因子江苏省
    
Abstract: Global climate change characterized by temperature increase has been a hot topic of widespread concern,and environmental protection and governance has become a significant issue affecting sustainable development.As the major component of terrestrial ecosystems,vegetation plays an important role in the aspects of ecologicalenvironment assessment and carbon cycling.based on the logistic function method,the long-term Normalized Difference Vegetation Index(NDVI)from GIMMS3g and meteorological data over 1982~2015 were used to calculate the start(SOS)and the end(EOS)of the season of Jiangsu province.The spatial and temporal characteristics of vegetation phenological changes were also investigated.The effects of main meteorological factors(temperature and precipitation)on phenological changes were explored by correlation analysis.The results showed that:①spatially,SOS showed an increased trend while EOS decreased from south to north,②temporally,SOS for most regions(83.1%)featured advanced trends with a rate of around 1~2 days per year,while 69.2% of pixels showed a delayed EOS by 0~1 day per year,and ③vegetation phenology responded well to air temperature and precipitation,as 70.5% and 55.5% pixels of SOS had significantly negative correlations with air temperature and precipitation.However,for EOS,more than half areas,i.e.55.2% of pixels and 71.2% of pixels respectively demonstrated positive correlation with air temperature and negative correlation with precipitation.Overall,a higher temperature trigged an earlier SOS but increased precipitation did not necessarily advance SOS.Furthermore,climate changes in autumn showed complicate effects on EOS that neither changes in temperature nor precipitation can lead to one directional changes of EOS.These results will deepen the understanding of the interaction between climate change and vegetation ecosystem,and provide a reference for future vegetation and climate change analysis.
Key words: Change of vegetation phenology    GIMMS3g NDVI    Climate factors    Jiangsu province
收稿日期: 2018-11-20      http://119.78.100.137/inf 出版日期: 2019-05-13
ZTFLH:  TP79  
基金资助:

国家重点研发计划(2017YFC0804104),中国工程院院士科技咨询项目(2017-ZD-03-05-01)。


作者简介: 李嘉玲(1996-),女,江苏无锡人,硕士研究生,主要从事植被遥感研究。E-mail:lijialing0125@163.com。
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

李嘉玲, 董东林, 林刚, 汪箫悦, 王健, 吴朝阳. 基于NDVI数据的江苏省植被物候变化及其影响因子分析[J]. 遥感技术与应用, 2019, 34(2): 367-376.

链接本文:

http://www.rsta.ac.cn/CN/Y2019/V34/I2/367

[1] 白淑英,史建桥,沈渭寿,高吉喜,张学成. 卫星遥感西藏高原积雪时空变化及影响因子分析[J]. 遥感技术与应用, 2014, 29(6): 954-962.
[2] 韩辉邦,马明国,严平. 黑河流域NDVI周期性分析及其与气候因子的关系[J]. 遥感技术与应用, 2011, 26(5): 554-560.