Publications

Liu, RY; Ren, HZ; Liu, SH; Liu, Q; Yan, BK; Gan, FP (2018). Generalized FPAR estimation methods from various satellite sensors and validation. AGRICULTURAL AND FOREST METEOROLOGY, 260, 55-72.

Abstract
Fraction of absorbed photosynthetically active radiation (FPAR) is a key parameter in ecosystem productivity and carbon balance estimation. FPAR can be estimated from various satellite images but its product might have significant differences due to the usage of various algorithms. This work proposes a generalized FPAR retrieval method for Landsat 5/ Thematic Mapper (TM), Landsat 7/Enhanced Thematic Mapper Plus (ETM +), Landsat 8/ Operational Land Imager (OLI), Moderate Resolution Imaging Spectroradiometer(MODIS), Advanced Spacebome Thermal Emission and Reflection Radiometer (ASTER), SPOT/VEGETATION, and HJ-1/CCD in the form of two linear models, namely, the BOA (bottom of atmosphere) model and the TOA (top of atmosphere) model, to reduce FPAR discrepancy among sensors. The BOA model estimates canopy FPAR from land surface multiband reflectance after atmospheric correction, whereas the TOA model estimates FPAR from apparent multiband reflectance at the TOA. Analysis results found that the FPAR errors from the BOA and TOA models were approximately 0.03 and 0.06, respectively, and the difference among FPAR estimated from different sensors was turned out to be less than 0.015 in theory. In addition, the FPAR difference between the two models was generally small, especially under low aerosol optical depth (AOD) and densely vegetated conditions. Ground validation using the datasets from the Hi WATER and Validation of Land European Remote Sensing Instruments (VALERO programs showed that the FPAR errors were 0.16 and 0.18 for the BOA and TOA models, respectively, which might be affected by the time interval of ground and satellite observation, spatial scale effect, and atmospheric correction errors. Moreover, this paper applied the new methods to estimate FPAR in different dates at the Heihe River basin and conduct a cross-comparison of FPAR from various sensors, and consequently obtained acceptable results.

DOI:
10.1016/j.agrformet.2018.05.024

ISSN:
0168-1923