Retrieval of Global Long-term Leaf Area Index from LTDR AVHRR and MODIS Observations--《Journal of Geo-Information Science》2015年11期
Retrieval of Global Long-term Leaf Area Index from LTDR AVHRR and MODIS Observations
LIU YLIU RState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of S
Leaf area index(LAI) is a primary parameter for charactering the water, carbon and energy exchanges among soil, vegetation and the atmosphere. Global long-term LAI datasets help to understand the response and feedback of vegetation to climate change. In this paper, the global LAI was retrieved during a 32- year period from 1981 to 2012 by utilizing a combination of MODIS measurements and reprocessed long-term data record(LTDR) AVHRR observations. The high- quality MODIS observations were used to constrain the LAI retrieval from historical AVHRR data, by establishing the pixel- by- pixel relationship between them directly. Thus, the inconsistency of LAI derived from these two notably different sensors could be reduced, and the quality of LAI derived from AVHRR data could be improved. Firstly, MODIS LAI series() were generated from high- quality MODIS land surface reflectance based on the GLOBCARBON LAI algorithm. Then, the relationships between AVHRR Simple Ratio(SR) and MODIS LAI were regressed pixel- by- pixel using the multi- year average values of these two data for each 8- day period. After that, the AVHRR LAI was estimated from historical AVHRR observations based on these pixel- level relationships from 1981 to 1999. The retrieved LAI could represent the spatial distribution of global vegetation and the seasonal characteristics of the major biomes. The LAI derived from AVHRR was inter- compared with that from MODIS. The results demonstrate a good consistency between the LAIs from these two different sensors. The comparison with NASA MODIS standard products of MOD15A2 shows that our results are consistent with MOD15A2 in both spatial pattern and seasonal cycle.
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Li Xiaodong,Wang Xuefeng,He Peng(Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,P.R.China);[J];Journal of Northeast Forestry U2013-08
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