中国地理科学 ›› 2019, Vol. 20 ›› Issue (5): 756-767.doi: 10.1007/s11769-019-1070-y

• 论文 • 上一篇    下一篇

Effect of Mathematical Expression of Vegetation Indices on the Estima-tion of Phenology Trends from Satellite Data

ZUO Lu1,2, LIU Ronggao1, LIU Yang1, SHANG Rong1   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • 收稿日期:2019-01-24 修回日期:2019-04-18 出版日期:2019-10-27 发布日期:2019-09-26
  • 通讯作者: Liu Ronggao.E-mail:liurg@igsnrr.ac.cn,liurg@lreis.ac.cn E-mail:liurg@igsnrr.ac.cn,liurg@lreis.ac.cn
  • 基金资助:

    Under the auspices of the Strategic Priority Research Program of the Chinese Academy Sciences (No. XDA19080303), the National Key Research and Development Program for Global Change and Adaptation (No. 2016YFA0600201), the Distinctive Institutes Development Program, Chinese Academy of Sciences (No. TSYJS04), the National Natural Sciences Foudation of China (No. 41171285)

Effect of Mathematical Expression of Vegetation Indices on the Estima-tion of Phenology Trends from Satellite Data

ZUO Lu1,2, LIU Ronggao1, LIU Yang1, SHANG Rong1   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-01-24 Revised:2019-04-18 Online:2019-10-27 Published:2019-09-26
  • Contact: Liu Ronggao.E-mail:liurg@igsnrr.ac.cn,liurg@lreis.ac.cn E-mail:liurg@igsnrr.ac.cn,liurg@lreis.ac.cn
  • Supported by:

    Under the auspices of the Strategic Priority Research Program of the Chinese Academy Sciences (No. XDA19080303), the National Key Research and Development Program for Global Change and Adaptation (No. 2016YFA0600201), the Distinctive Institutes Development Program, Chinese Academy of Sciences (No. TSYJS04), the National Natural Sciences Foudation of China (No. 41171285)

摘要:

Vegetation indices (VIs) from satellite remote sensing have been extensively applied to analyze the trends of vegetation phenology. In this paper, the NDVI (normalized difference vegetation index) and SR (simple ration), which are calculated from the same spectral bands of MODIS data with different mathematical expressions, were used to extract the start date (SOS) and end date (EOS) of the growing season in northern China and Mongolia from 2000 to 2015. The results show that different vegetation indices would lead to differences in vegetation phenology especially in their trends. The mean SOS from NDVI is 15.5 d earlier than that from SR, and the mean EOS from NDVI is 13.4 d later than that from SR. It should be noted that 16.3% of SOS and 17.2% of EOS derived from NDVI and SR exhibit opposite trends. The phenology dates and trends from NDVI are also inconsistent with those of SR among various vegetation types. These differences based on different mathematical expressions in NDVI and SR result from different resistances to noise and sensitivities to spectral signal at different stage of growing season. NDVI is prone to be effected more by low noise and is less sensitive to dense vegetation. While SR is affected more by high noise and is less sensitive to sparse vegetation. Therefore, vegetation indices are one of the uncertainty sources of remote sensing-based phenology, and appropriate indices should be used to detect vegetation phenology for different growth stages and estimate phenology trends.

关键词: vegetation phenology, vegetation index, trend consistency, noise effect, spatially temporal comparability, northern China, Mongolia

Abstract:

Vegetation indices (VIs) from satellite remote sensing have been extensively applied to analyze the trends of vegetation phenology. In this paper, the NDVI (normalized difference vegetation index) and SR (simple ration), which are calculated from the same spectral bands of MODIS data with different mathematical expressions, were used to extract the start date (SOS) and end date (EOS) of the growing season in northern China and Mongolia from 2000 to 2015. The results show that different vegetation indices would lead to differences in vegetation phenology especially in their trends. The mean SOS from NDVI is 15.5 d earlier than that from SR, and the mean EOS from NDVI is 13.4 d later than that from SR. It should be noted that 16.3% of SOS and 17.2% of EOS derived from NDVI and SR exhibit opposite trends. The phenology dates and trends from NDVI are also inconsistent with those of SR among various vegetation types. These differences based on different mathematical expressions in NDVI and SR result from different resistances to noise and sensitivities to spectral signal at different stage of growing season. NDVI is prone to be effected more by low noise and is less sensitive to dense vegetation. While SR is affected more by high noise and is less sensitive to sparse vegetation. Therefore, vegetation indices are one of the uncertainty sources of remote sensing-based phenology, and appropriate indices should be used to detect vegetation phenology for different growth stages and estimate phenology trends.

Key words: vegetation phenology, vegetation index, trend consistency, noise effect, spatially temporal comparability, northern China, Mongolia