A LONG-TERM GLOBAL LEAF AREA INDEX DATASET (1981-2009) FROM AVHRR AND MODIS DATA

被引:1
|
作者
Liu, Yang [1 ]
Liu, Ronggao [1 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
关键词
Leaf area index; long-term time series; AVHRR; MODIS; SATELLITE IMAGERY;
D O I
10.1109/IGARSS.2011.6049247
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
A global multi-decade long-term Leaf area index (LAI) record from remote sensing measurements is required for global change modeling and analysis. The dataset is generated through the fusion of MODIS and historical AVHRR data based on global pixel-based AVHRR SR-MODIS LAI relationship which is established with AVHRR data and LAI derived form high quality MODIS observations in the overlapping years from 2000 to 2006. Based on this relationship, historical AVHRR retrieval from 1981 to 2006 is constrained with high quality MODIS observations. The comparisons of the results from 2000 to 2006 show high consistency between the derived AVHRR and MODIS LAI dataset. The derived AVHRR and MODIS LAI were directly validated with 120 field measurements in global 36 sites with various vegetation types, with RMSE of 0.91 and 1.01, respectively.
引用
收藏
页码:783 / 786
页数:4
相关论文
共 50 条
  • [1] Retrospective retrieval of long-term consistent global leaf area index (1981-2011) from combined AVHRR and MODIS data
    Liu, Yang
    Liu, Ronggao
    Chen, Jing M.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES, 2012, 117
  • [2] Generating a Long-term Land Data Record from the AVHRR and MODIS instruments
    Pedelty, Jeffrey
    Devadiga, Sadashiva
    Masuoka, Edward
    Brown, Molly
    Pinzon, Jorge
    Tucker, Compton
    Roy, David
    Ju, Junchang
    Vermote, Eric
    Prince, Stephen
    Nagol, Jyotheshwar
    Justice, Christopher
    Schaaf, Crystal
    Liu, Jicheng
    Privette, Jeffrey
    Pinheiro, Ana
    [J]. IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 1021 - 1024
  • [3] Long-Time-Series Global Land Surface Satellite Leaf Area Index Product Derived From MODIS and AVHRR Surface Reflectance
    Xiao, Zhiqiang
    Liang, Shunlin
    Wang, Jindi
    Xiang, Yang
    Zhao, Xiang
    Song, Jinling
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2016, 54 (09): : 5301 - 5318
  • [4] Long-Term Variation of Global GEOV2 and MODIS Leaf Area Index (LAI) and Their Uncertainties: An Insight into the Product Stabilities
    Fang, Hongliang
    Wang, Yao
    Zhang, Yinghui
    Li, Sijia
    [J]. JOURNAL OF REMOTE SENSING, 2021, 2021
  • [5] Estimating Global Gross Primary Production Using an Improved MODIS Leaf Area Index Dataset
    Wang, Shujian
    Zhang, Xunhe
    Hou, Lili
    Sun, Jiejie
    Xu, Ming
    [J]. Remote Sensing, 2024, 16 (19)
  • [6] Reconstruction of a complete global time series of daily vegetation index trajectory from long-term AVHRR data
    Zhang, Xiaoyang
    [J]. REMOTE SENSING OF ENVIRONMENT, 2015, 156 : 457 - 472
  • [7] Long-Term Global Land Surface Satellite (GLASS) Fractional Vegetation Cover Product Derived From MODIS and AVHRR Data
    Jia, Kun
    Yang, Linqing
    Liang, Shunlin
    Xiao, Zhiqiang
    Zhao, Xiang
    Yao, Yunjun
    Zhang, Xiaotong
    Jiang, Bo
    Liu, Duanyang
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 12 (02) : 508 - 518
  • [8] Deriving long term snow cover extent dataset from AVHRR and MODIS data: Central Asia case study
    Zhou, Hang
    Aizen, Elena
    Aizen, Vladimir
    [J]. REMOTE SENSING OF ENVIRONMENT, 2013, 136 : 146 - 162
  • [9] A long-term dataset of lake surface water temperature over the Tibetan Plateau derived from AVHRR 1981–2015
    Baojian Liu
    Wei Wan
    Hongjie Xie
    Huan Li
    Siyu Zhu
    Guoqing Zhang
    Lijuan Wen
    Yang Hong
    [J]. Scientific Data, 6
  • [10] Global Detection of Long-Term (1982-2017) Burned Area with AVHRR-LTDR Data
    Oton, Gonzalo
    Ramo, Ruben
    Lizundia-Loiola, Joshua
    Chuvieco, Emilio
    [J]. REMOTE SENSING, 2019, 11 (18)