您好，欢迎访问江苏省农业科学院 机构知识库！
江苏省农业科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Quantifying uncertainty: The benefits of removing snow cover from remote sensing time series on the extraction of climate-influenced grassland phenology on the Qinghai-Tibet Plateau

文献类型： 外文期刊

作者： Li, Nan 1 ; Zhan, Pei 2 ; Pan, Yaozhong 3 ; Qiu, Lin 1 ; Wang, Jingjing 1 ; Xu, Wenxuan 1 ;

作者机构： 1.Jiangsu Acad Agr Sci, Inst Agr Informat, Nanjing 210014, Peoples R China

2.Nanjing Univ Informat Sci & Technol, Sch Ecol & Appl Meteorol, Nanjing 210044, Peoples R China

3.Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

4.Qinghai Normal Univ, Acad Plateau Sci & Sustainabil, Xining 810016, Peoples R China

关键词： Phenology; Climate change response; SOS; Qinghai -Tibetan Plateau; Grassland

期刊名称：AGRICULTURAL AND FOREST METEOROLOGY （ 影响因子：6.2； 五年影响因子：6.9 ）

ISSN： 0168-1923

年卷期： 2024 年 345 卷

页码：

收录情况： SCI

摘要： Vegetation phenology is a sensitive indicator of climate change. Remote sensing technology is often utilized to estimate vegetation phenology over expansive regions, but it contains uncertainties stemming from methods of data preprocessing and phenology extraction. Previous studies have primarily focused on individual causes of uncertainty, neglecting potential interactions between various causes and the consequent effects on analyzing vegetation's response to climate change. In this study, the uncertainty introduced by multiple time-series processing procedures in extracting the start of the growing season (SOS) of grassland on the Qinghai-Tibetan Plateau (QTP) was assessed using remote sensing data. This includes data preprocessing (time-series smoothing and snow cover removal) and phenology extraction. How these uncertainties might influence the analysis of SOS response to climate change was further quantified. Our findings demonstrated that the average uncertainty in grassland SOS extraction on the QTP for the period 2001-2015 reached 20.01 d, and snow-induced noise emerged as the principal factor affecting SOS estimates. Temporal trends of SOS revealed a regional average uncertainty of 1.06 d/y, both snow cover removal and the smoothing method were influential, each introducing uncertainty of 1.04 d/y and 1.05 d/y, respectively. After the removal of snow cover, uncertainties were reduced by 35 % for the SOS temporal trend. SOS response to climate change was extracted by various methods, leading to divergent and at times conflicting outcomes. The uncertainty for SOS sensitivity to temperature was averagely 10.50 d/degrees C on the QTP, while that for SOS sensitivity to precipitation was 1.75 d/mm. As the duration of snow cover lengthened, uncertainty increased in SOS response to temperature, while uncertainty increased in arid regions for SOS response to precipitation. The insights provided here contribute to enhancing phenology extraction accuracy and understanding the interactions between global climate change and vegetation phenology.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：江苏省农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台