Study On Remote Sensing Estimation Models For FPAR/LAI Of Temperate Grassland In Hulunber

Grasslands are one of the most widespread vegetation types worldwide, and play an important role in the global carbon balance and global changes (Scurlock&Hall, 1998). Leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR) represent two biophysically complementary ways of describing the earth's vegetated surfaces and energy exchange. The area of grassland is very huge in China; to simulate NPP of grassland and its' key parameters is the technological basis of monitoring region carbon balance, security of animal production, so it is very important to study LAI/FPAR of grasslands.The Moderate Resolution Imaging Spectroradiometer (MODIS) 1km LAI/FPAR products are one of the most important remote sensing data sources to monitor NPP in regional or global scale. Product validation and assessment is necessary to establish confidence in the data sets, and to provide a basis for improving the MODIS algorithms. There are a lot of grassland types in China includes tropic shrub, temperate grassland and alpine cold desert sparse vegetation, et al., the algorithm of MODIS LAI/FPAR is too rough to retrieve LAI/FPAR of grassland under special terrain and climate condition accurately.Hulunber grassland is the most concentration and representative area of temperate meadow steppe in China. We took hulunber for example to study LAI/FPAR of grassland. The contents of this paper are as follows:1) The analysis of instantaneous FPAR variation on a diurnal basisWe analyzed the diurnal variations of incoming PAR, transmitted PAR, reflected PAR by canopy and reflected PAR by soil, then analyzed the diurnal variation of FPAR. The result showed that the daily variation of the incoming PAR and transmitted PAR of Leymus Chinensis canopy is obviously, and the curve of variation is sinusoid. The ratio of reflected PAR by soil to the transmitted PAR is almost constant in a day. But the ratio of reflected PAR by canopy to the total incoming PAR is about 0.05-0.35, the variation range is relatively great. On a diurnal basis, FPAR was found to be highest in the morning and late afternoon due to large solar zenith angles and lowest around noon where the solar zenith angle is low.2) The seasonal variation of in situ measured LAI/FPAR in growing seasonWe measured and analyzed the seasonal variation of in situ measured LAI/FPAR in Leymus chinensis site and Stipa baicalensis site of hulunber station, the result showed that the variation of LAI/FPAR of grass canopy like a trend of rise first, then fall, which is the same as the grass' growth pattern. At the same time, We analyzed the seasonal variation of LAI/FPAR in growing season based on MODIS_LAI/FPAR biome map and types of grasslands in 1:10~6 scales, the results indicated that the MODIS LAI/FPAR products captured the seasonal variation trend of grassland in growing season very well, but the MODIS LAI/FPAR products generally overestimated the magnitude of relative to real status of grassland, and there is a little difference among different grassland types.3) The establishment of LAI/FPAR model of different grassland types We analyzed the correlation among LAI/FPAR, NDVI, chlorophyll and height of canopy based on in situ measured data. The result indicated that the correlation among LAI/FPAR, NDVI et al. is different, because the constructive species of the same grassland type are different. We simulated the correlation between canopy reflection and FPAR with the Prospect+SAIL model on condition that the chlorophyll or LAI is constant. We established the LAI/FPAR empirical model of different grassland types based on in situ measured data after analyzing the correlation, regression and curve fit. And we found the best model for estimating LAI/FPAR after analyzing the accuracy of the empirical model's prediction. We also established Look Up Table of remote sensing model for LAI/FPAR of grassland canopy using Prospect+SAIL model after improved related parameters, and retrieved the LAI/FPAR of grassland using LUT method.4) Validation of MODIS LAI/FPAR products and application of the model of LAI/FPARWe validated the MODIS LAI/FPAR products with in situ measured LAI/FPAR in growing season, the result indicated that the MODIS LAI/FPAR products captured the seasonal variation of grassland in experimental sites in growing season very well, but the MODIS LAI/FPAR products generally overestimated the magnitude of relative to both field measurements.LAI/FPAR empirical models of different grassland types were applied to the Beijing-1 image in situ area in order to convert NDVI to LAI/FPAR, and we get the in situ area's LAI/FPAR image using LUT of canopy grassland which established using Prospect+SAIL model. Then compared with MODIS LAI/FPAR products and in situ measured data in both sites, the results showed that the LAI/FPAR retrieved from Beijing-1 image is a little higher than MODIS LAI/FPAR. The LAI/FPAR retrieved from empirical models of different grassland types and LUT method is more accurate than MODIS LAI/FPAR products.