Авторизоваться
Для зарегистрированных пользователей

Broadleaf forest is a major type of Earth’s land cover with the highest observable vegetation density. Retrievals of biophysical parameters, such as leaf area index (LAI), of broadleaf forests  at  global  scale  constitute  a  major  challenge  to  modern remote sensing techniques in view of low sensitivity (saturation) of surface reflectances to such parameters over dense vegetation. The goal  of  the  performed  research  is  to  demonstrate  physical  principles of LAI retrievals over broadleaf forests with the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI algorithm and  to  establish  a  basis  for   algorithm  refinement.  To  sample natural variability in biophysical parameters of broadleaf forests, we  selected  MODIS  data  subsets  covering  deciduous  broadleaf forests  of  the  eastern  part  of  North  America  and  evergreen broadleaf forests of  Amazonia. The analysis of an annual course of  the  Terra  MODIS  Collection  4  LAI  product  over  broadleaf forests  indicated  a  low  portion  of  best  quality  main  radiative transfer-based algorithm retrievals and dominance of low-reliable backup algorithm retrievals during the growing season. We found that this retrieval anomaly was due to an inconsistency between simulated  and  MODIS  surface  reflectances.  LAI  retrievals  over dense  vegetation  are  mostly  performed  over  a  compact  location in  the  spectral  space  of  saturated  surface  reflectances,  which need to be accurately modeled. New  simulations were performed with  the  stochastic  radiative  transfer  model,  which  poses  high numerical accuracy at the condition of saturation. Separate sets of parameters of the LAI algorithm were generated for deciduous and evergreen broadleaf forests to account for the differences in the  corresponding  surface  reflectance  properties.  The  optimized algorithm  closely  captures  physics  of seasonal  variations  in  surface reflectances and delivers a majority of LAI retrievals during a  phenological  cycle,  consistent  with  field  measurements.  The analysis of the optimized retrievals indicates that the precision of MODIS surface reflectances, the natural variability, and mixture of  species  set  a  limit  to  improvements  of  the  accuracy  of  LAI retrievals over broadleaf forests