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Seasonal variations of canopy spectra and their indications to carbon fluxes in a temperate forest in northeast China

文献类型：期刊论文

作者Jiang, Jie5; Yu, Quanzhou4,5; Liu, Yujie3; Liang, Tianquan4,5; Tang, Qingxin4,5; Zhou, Lei2; Zhang, Hongli5; Zhang, Baohua5; Wang, Shaoqiang1
刊名JOURNAL OF APPLIED REMOTE SENSING
出版日期2022-10-01
卷号16期号:4页码:17
关键词Hyperion spectral analysis carbon flux Changbai Mountain forest canopy different seasons spectral indexes
DOI10.1117/1.JRS.16.048503
通讯作者Yu, Quanzhou(yuquanzhou2008@126.com)
英文摘要The seasonal variations of forest canopy spectral characteristics are critical to improving the utilization of remote sensing methodology to quantify forest physiology, especially forest carbon sink. However, the seasonal variations of forest canopy spectra are poorly understood. Combined field survey and EO-1 Hyperion imageries, we extracted the spectral curves of seven forest types of Changbai Mountain in China in seven periods. We also calculated various remote sensing indexes and analyzed their seasonal change of spectral characteristics among different forest types. Optimal indexes were selected to indicate the seasonal variation of forest carbon fluxes. Our results showed that there were differences in spectral curves among forest types. The reflectance of coniferous forests was lower than that of broad-leaved forests in growing season. Changbai Scotch pine forest owned the lowest spectral reflectance, whereas the reflectance of Mongolian oak forest was the highest, especially in the near-infrared region. The red edge slope (RES) of broad-leaved forest was higher than coniferous forest in spring and summer. The RES of broad-leaved and coniferous forests was similar in autumn. The red edge position of various forest types showed slight shift in different seasons. Four typical forest types showed different spectral characteristics with seasonal changes. The seasonal variation of coniferous forest spectral curves was not obvious. The seasonal variation of broad-leaved forest spectra was the largest. Most of the spectral indexes can indicate the seasonal variation characteristics of each forest type. Enhanced vegetation index (EVI) is better than normalized difference vegetation index (NDVI) to indicate the forest phenology. Seasonal curves of spectral indexes were different in all forest types. Spectral indexes of coniferous forests were most stable throughout the year. The curves of each index in broad-leaved forests showed significant difference in autumn, which may be influenced by the understory vegetation after their defoliation. For broad-leaved Korean (BK) pine forest, the scaled value of photochemical reflectance index (SPRI)*EVI owned the highest correlation with gross primary productivity (R = 0.99 and P < 0.01) and net ecosystem exchange (R = -0.77 and P < 0.05), respectively. SPRI*NDVI showed the highest correlation with ecosystem respiration (R = 0.96 and P < 0.01). The seasonal variation of carbon fluxes of different forest types retrieved from the optimal remote sensing index were consistent, but their peaks occurred at different times. (c) 2022 Society of Photo-Optical Instrumentation Engineers (SPIE)
WOS关键词LEAF CHLOROPHYLL CONTENT ; NET ECOSYSTEM EXCHANGE ; DIOXIDE EXCHANGE ; VEGETATION ; RED ; ASSIMILATION ; RESPIRATION ; SEPARATION ; HYPERION
资助项目National Natural Science Foundation of China[31800367] ; Science and Technology Service Network Initiative, CAS[KFZD-SW-310] ; Natural Science Foundation of Shandong Province[ZR2021MD090]
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
WOS记录号WOS:000917345800051
资助机构National Natural Science Foundation of China ; Science and Technology Service Network Initiative, CAS ; Natural Science Foundation of Shandong Province
源URL[http://ir.igsnrr.ac.cn/handle/311030/189880]  
专题中国科学院地理科学与资源研究所
通讯作者Yu, Quanzhou
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China
2.Zhejiang Normal Univ, Coll Geog & Environm Sci, Jinhua, Zhejiang, Peoples R China
3.Chinese Res Inst Environm Sci, Res Ctr Ecol Civilizat, Beijing, Peoples R China
4.Liaocheng Ctr Data & Applicat Natl High Resolut E, Liaocheng, Shandong, Peoples R China
5.Liaocheng Univ, Sch Geog & Environm, Liaocheng, Shandong, Peoples R China
推荐引用方式
GB/T 7714		 Jiang, Jie,Yu, Quanzhou,Liu, Yujie,et al. Seasonal variations of canopy spectra and their indications to carbon fluxes in a temperate forest in northeast China[J]. JOURNAL OF APPLIED REMOTE SENSING,2022,16(4):17.
APA Jiang, Jie.,Yu, Quanzhou.,Liu, Yujie.,Liang, Tianquan.,Tang, Qingxin.,...&Wang, Shaoqiang.(2022).Seasonal variations of canopy spectra and their indications to carbon fluxes in a temperate forest in northeast China.JOURNAL OF APPLIED REMOTE SENSING,16(4),17.
MLA Jiang, Jie,et al."Seasonal variations of canopy spectra and their indications to carbon fluxes in a temperate forest in northeast China".JOURNAL OF APPLIED REMOTE SENSING 16.4(2022):17.

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来源：地理科学与资源研究所

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