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Validation and analysis of remote sensing phenology products in the Heihe River Basin

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：wangcong@radi.ac.cn
  • Introduction：王聪(1992—　)，女，硕士研究生，研究方向为遥感植被物候。E-mail：wangcong@radi.ac.cn
WANG Cong12,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

  • Email：lijing01@radi.ac.cn
  • Introduction：李静(1978—　)，女，副研究员，研究方向为植被辐射传输模型、叶面积指数反演。E-mail：lijing01@radi.ac.cn
LI Jing1*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

LIU Qinhuo12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

BAI Junhua1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

XU Baodong12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

ZHAO Jing1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

ZENG Yelu12

resumen

Land surface phenology is of great significance in the fields of global change response, agricultural management, and ecological applications. However, compared with the strong demand for vegetation phenology mapping for global and regional research and applications, the development of remote sensing vegetation phenology products is slower than that of other remote sensing parameters, such as Leaf Area Index (LAI) and Vegetation Index (VI). Although Enhanced Vegetation Index (EVI) and LAI are the most widely used vegetation parameters for remote sensing phenology extraction, this study aims to compare the remote sensing phenology products derived from MODerate-resolution Imaging Spectroradiometer (MODIS) EVI and global land surface satellite product LAI in Heihe River Basin. Moreover, this study aims to assess the difference inphenology information that was extracted from EVI and LAI time series. The validity and accuracy between the MODIS global Land Cover Dynamics product (MLCD) and Universal Multi-life-cycle Phenology Monitoring Method (UMPM) product in the Heihe River Basin were compared. Validity contains the missing product rate and stability. Accuracy was assessed using representative observation sites. The sites were the basis of the two proposed indications (the mean bias and mean absolute bias) for the evaluation of remote sensing phonological metrics. Furthermore, phenology information that was extracted from EVI and LAI products was compared. Then, the variances between ground observations and phenology products were discussed in detail. The validity of UMPM is better than that of MLCD as a whole. However, in sparse vegetation that is mainly composed of shrubs and grasslands, UMPM has more missing data and lower spatial-temporal stability because its precision value is lower than that of EVI. For maize, EVI is more suitable for extracting the start of growing season, whereas LAI performs better for extracting the peak of growing season. However, field observations focus on fruit development during the later period of maize growth, whereas remote sensing phenology detection is specific to leaf development. Both MLCD and UMPM are inconsistent with ground observations after the peak of the growing season. Either MLCD or UMPM has advantages in different vegetation types and various phenological developmental stages. Uniting multisource data can improve the accuracy and validity of remote sensing phenology products. In addition, owing to the coarse spatial resolution of current remote sensing phenology products, it inevitably includes other plants within one square kilometers, which may lead to variability in phenological developmental stages and a weak relationship between remote sensing data and ground observations. Improving the spatial resolution of remote sensing phenology products is significant in the future promotion of their application and development.

palabra clave

remote sensing phenology product;the start of growing season;the end of growing season;validation;Heihe river basin

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