Chinese Geographical Science ›› 2021, Vol. 31 ›› Issue (3): 459-473.doi: 10.1007/s11769-021-1204-x

• Articles • Previous Articles    

Vegetation Phenology in Permafrost Regions of Northeastern China Based on MODIS and Solar-induced Chlorophyll Fluorescence

WEN Lixiang1, GUO Meng1, YIN Shuai2, HUANG Shubo1, LI Xingli1, YU Fangbing1   

  1. 1. Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China;
    2. Centers for Global Environmental Research, National Institute for Environmental Studies, Tsukuba 305-8555, Japan
  • Received:2020-11-02 Published:2021-04-29
  • Contact: GUO Meng E-mail:guom521@nenu.edu.cn
  • Supported by:
    Under the auspices of National Key Research and Development Projects (No. 2018YFE0207800), National Natural Science Foundation of China (No. 41871103)

Abstract: Vegetation phenology is an indicator of vegetation response to natural environmental changes and is of great significance for the study of global climate change and its impact on terrestrial ecosystems. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), extracted from the Moderate Resolution Imaging Spectrometer (MODIS), are widely used to monitor phenology by calculating land surface reflectance. However, the applicability of the vegetation index based on ‘greenness’ to monitor photosynthetic activity is hindered by poor observation conditions (e.g., ground shadows, snow, and clouds). Recently, satellite measurements of solar-induced chlorophyll fluorescence (SIF) from OCO-2 sensors have shown great potential for studying vegetation phenology. Here, we tested the feasibility of SIF in extracting phenological metrics in permafrost regions of the northeastern China, exploring the characteristics of SIF in the study of vegetation phenology and the differences between NDVI and EVI. The results show that NDVI has obvious SOS advance and EOS lag, and EVI is closer to SIF. The growing season length based on SIF is often the shortest, while it can represent the true phenology of vegetation because it is closely related to photosynthesis. SIF is more sensitive than the traditional remote sensing indices in monitoring seasonal changes in vegetation phenology and can compensate for the shortcomings of traditional vegetation indices. We also used the time series data of MODIS NDVI and EVI to extract phenological metrics in different permafrost regions. The results show that the length of growing season of vegetation in predominantly continuous permafrost (zone I) is longer than in permafrost with isolated taliks (zone II). Our results have certain significance for understanding the response of ecosystems in cold regions to global climate change.

Key words: vegetation phenology, permafrost, Moderate Resolution Imaging Spectrometer (MODIS), solar-induced chlorophyll fluorescence (SIF), northeastern China