Leaf Area Index (LAI) indicates the amount of live green leaf above ground surface. Many agro-meteorology, atmospheric general circulation, and biogeochemical models rely on LAI to parameterize the vegetation interactions with the atmosphere. A series of LAI products have been generated from different satellite data. However, to effectively use these LAI products in various disciplines, it is important to know how these products perform.
Continuous field leaf area index (LAI) measurement has become increasingly important for the validation of remote sensing LAI products. Prof. FANG Hongliang, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), and his colleagues had led several field campaigns to take continuous LAI measurements over paddy rice fields in NE China since 2012. Three indirect optical methods, LAI-2200, digital hemispherical photography (DHP), and AccuPAR, were compared with a destructive sampling method conducted concurrently. They found that LAI-2200 and DHP produce consistent LAI estimates over the season (R2=0.76, RMSE=0.97). The optical LAI values estimated from LAI-2200 and DHP correspond very well with the destructive values. Nevertheless, AccuPAR underestimates the destructive LAI values by up to 30%. They conclude that rice PAI could be accurately estimated with LAI-2200 and DHP before senescence. The seasonal continuous LAI measurements obtained from their study can be provided for similar validation studies.
Their work was supported by the National Natural Science Foundation of China and the Chinese Academy of Sciences.
The studies have been published in the recent issue of Agricultural and Forest Meteorology(Fang, H., et al., 2014.Seasonal variation of leaf area index (LAI) over paddy rice fields in NE China: Intercomparison of destructive sampling, LAI-2200, digital hemispherical photography (DHP), and AccuPAR methods. Agricultural and Forest Meteorology, 198-199, 126-141).
