DETECTING LATITUDINAL VARIATIONS IN PHENOLOGY OVER THE NORTHEAST ASIA BASED ON REMOTE SENSING VEGETATION INDEX

被引:0
|
作者
Jin, Jiaxin [1 ]
Jiang, Hong [1 ]
Zhang, Xiuying [1 ]
Wang, Ying [1 ]
机构
[1] Nanjing Univ, Int Inst Earth Syst Sci, Nanjing, Jiangsu, Peoples R China
来源
2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2012年
关键词
Northeast Asia; Leaf Area Index; Phenology; Global Change; SATELLITE SENSOR DATA; TIME-SERIES; AMERICA; CLIMATE; TUNDRA; MODIS;
D O I
10.1109/IGARSS.2012.6351514
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We aim to detect responses of carbon sinking of plants to temperature and precipitation gradient across mid-latitudes of northeast Asia. MODIS Leaf Area Index (LAI) data were used to detect patterns and variations in annual integrated vegetation index (S. integral) for nine land cover types during 2001-2011. A smoothing algorithm using asymmetric Gaussian model was applied to smooth LAI time-series and estimate the values of S. integral. The result shows that the S. integral of forests was larger than that of other types during last ten years. However, the latitudinal variation in S. integral of forests was less pronounced. For grasslands and savannas, the S. integral was more significantly influenced by precipitation rather than temperature. In general, the S. integral of all types showed a decline trend in the southernmost of the study area. Then it presented an increasing trend from 35 degrees N to 41 degrees N. Between 43 degrees N and 61 degrees N, the S. integral kept decreasing again except around 52 degrees N.
引用
收藏
页码:634 / 637
页数:4
相关论文
共 50 条
  • [21] Remote sensing based global vegetation products: From vegetation spectral index to fusion datasets
    Qiu S.
    Hu T.
    Hu Y.
    Ding Z.
    Liu Y.
    Peng J.
    Dili Xuebao/Acta Geographica Sinica, 2022, 77 (05): : 1102 - 1119
  • [22] Impact of freshwater diversions on vegetation in coastal wetlands based on remote sensing derived vegetation index
    Wu, Wei
    Grimes, Evan
    Suir, Glenn
    FRONTIERS IN MARINE SCIENCE, 2023, 10
  • [23] Spatiotemporal Variations of Forest Vegetation Phenology and Its Response to Climate Change in Northeast China
    Zheng, Wenrui
    Liu, Yuqi
    Yang, Xiguang
    Fan, Wenyi
    REMOTE SENSING, 2022, 14 (12)
  • [24] Estimating Crop Coefficients Using Remote Sensing-Based Vegetation Index
    Kamble, Baburao
    Kilic, Ayse
    Hubbard, Kenneth
    REMOTE SENSING, 2013, 5 (04) : 1588 - 1602
  • [25] Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing
    Glenn, Edward P.
    Nagler, Pamela L.
    Huete, Alfredo R.
    SURVEYS IN GEOPHYSICS, 2010, 31 (06) : 531 - 555
  • [26] A New Remote Sensing Desert Vegetation Detection Index
    Song, Zhenqi
    Lu, Yuefeng
    Ding, Ziqi
    Sun, Dengkuo
    Jia, Yuanxin
    Sun, Weiwei
    REMOTE SENSING, 2023, 15 (24)
  • [27] Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing
    Edward P. Glenn
    Pamela L. Nagler
    Alfredo R. Huete
    Surveys in Geophysics, 2010, 31 : 531 - 555
  • [28] A REMOTE SENSING BASED SYSTEM TO PREDICT EARLY SPRING PHENOLOGY OVER BOREAL FOREST
    Sekhon, Navdee S.
    Hassan, Quazi K.
    Sleep, Robert W.
    2010 CANADIAN GEOMATICS CONFERENCE AND SYMPOSIUM OF COMMISSION I, ISPRS CONVERGENCE IN GEOMATICS - SHAPING CANADA'S COMPETITIVE LANDSCAPE, 2010, 38
  • [29] MTCARI: A Kind of Vegetation Index Monitoring Vegetation Leaf Chlorophyll Content Based on Hyperspectral Remote Sensing
    Meng Qing-ye
    Dong Heng
    Qin Qi-ming
    Wang Jin-liang
    Zhao Jiang-hua
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32 (08) : 2218 - 2222
  • [30] Julian dates and introduced temporal error in remote sensing vegetation phenology studies
    Thayn, J. B.
    Price, K. P.
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2008, 29 (20) : 6045 - 6049