Estimation of direct, diffuse, and total FPARs from Landsat surface reflectance data and ground-based estimates over six FLUXNET sites
Estimation of direct, diffuse, and total FPARs from Landsat surface reflectance data and ground-based estimates over six FLUXNET sites
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根据 Landsat 表面反射率数据和六个 FLUXNET 站点的地面估计来估计直接、漫射和总 FPAR
DOI:
10.1002/2014jg002754
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发表时间:
2015-01-01
影响因子:
3.7
通讯作者:
Fang, Hongliang
中科院分区:
文献类型:
--
作者:
Li, Wenjuan;Fang, Hongliang
The fraction of photosynthetically active radiation (PAR) absorbed by green elements (FPAR) is an essential climate variable in quantifying canopy absorbed PAR (APAR) and gross and net primary production. Current satellite FPAR products typically correspond to black-sky FPAR under direct illumination only, but the radiation transfer and vegetation absorption processes differ for direct and diffuse PARs. To address this, the present study developed a new approach to estimate direct, diffuse, and total FPARs, separately, from Landsat surface reflectance data. Field-measured direct and diffuse FPARs were first derived for crops, deciduous broadleaf forests, and evergreen needleleaf forests at six FLUXNET sites. Then, a coupled soil-leaf-canopy radiative transfer model (SLC) was used to simulate surface reflectance under direct and diffuse illumination conditions. Direct, diffuse, and total FPARs were estimated by comparing Landsat-5 Thematic Mapper (TM) data and simulated surface reflectances using a lookup table approach. The differences between the Landsat-estimated and the field-measured FPARs are less than 0.05 (10%). The diffuse FPAR is higher than the direct FPAR by up to 19.38%, whereas the total FPAR is larger than the direct FPAR by up to 16.07%. The direct APAR is higher than the diffuse APAR under clear-sky conditions, but underestimates the total APAR by -277.72 mu mols(-1)m(-2) on average. The approach described here can be extended to estimate direct, diffuse, and total FPARs from other satellite data and the obtained FPAR variables could be helpful to improve modeling of vegetation processes.