摘要
为探究东北三省植被春季物候(SOS)对极端温度事件的响应机制,研究基于MODIS NDVI数据集和ERA5-Land等遥感数据,采用动态阈值法提取该地2001—2020年植被SOS;以1981—2020年气象数据为基准期,采用百分位阈值法确定温度阈值,提取2001—2020年极端温度事件;结合Theil-Sen趋势分析和Mann-Kendall检验法探究研究区植被SOS变化情况,再通过Pearson相关分析探究植被SOS与极端温度事件的关系。结果表明,研究区2001—2020年植被SOS大部分集中在第100~130天,整体的变化速率为-0.25 d/a,呈提前的变化趋势;植被春季物候与极端高温指标普遍呈负相关,且对3月、4月极端高温事件的响应更为显著,而与极端低温指标的相关关系较为模糊。综上,极端高温事件发生频次、强度增加会使研究区植被春季物候提前,研究区植被SOS对极端低温事件的响应较为复杂。
To explore the response mechanism of vegetation start of the growing season(SOS)in the three Northeastern Provinces to extreme temperature events,this study utilized the MODIS NDVI dataset and remote sensing data such as ERA5-Land,and employed the dynamic threshold method to extract the vegetation SOS of this area from 2001 to 2020.Based on the meteorological data from 1981 to 2020,the temperature threshold was determined using the percentile threshold method,and extreme temperature events from 2001 to 2020 were extracted.The Theil-Sen trend analysis method and Mann-Kendall test method were combined to investigate the changes in the vegetation SOS in the three northeastern provinces.Furthermore,Pearson correlation analysis was conducted to explore the relationship between the vegetation SOS and extreme temperature events.The results showed that the vegetation SOS in the study area was mostly concentrated in the period from day 100 to day 130 from 2001 to 2020,with an overall change rate of-0.25 d/a,indicating an advancing trend.The vegetation SOS was generally negatively correlated with extreme high-temperature indicators,and the response to extreme high-temperature events in March and April was more significant.However,the correlation with extreme low-temperature indicators was relatively ambiguous.In summary,an increase in the frequency and intensity of extreme high-temperature events will cause the vegetation SOS in the study area to advance.The response of the vegetation SOS in the study area to extreme low-temperature events is more complex.
作者
李禹凝
Li Yuning(Harbin Normal University,Harbin 150025,China)
出处
《安徽农学通报》
2026年第2期62-66,共5页
Anhui Agricultural Science Bulletin
关键词
植被春季物候
归一化植被指数
极端温度
气候变化
遥感
vegetation start of the growing season
normalized difference vegetation index
extreme temperature
climate change
remote sensing
