Partial blind model inversion of mountain forest structure from MODIS imagery

Blind model inversion of forest structure allows the user to run powerful physically based canopy reflectance models (CRMs) without having to specify any input model parameters as these are instead automatically derived. This is particularly important for large areas and regional scales where obtaining these model parameters may be costly, impractical, not representative or impossible. This is especially challenging in high-relief mountainous terrain. This article presents the multiple-forward mode-partial blind (MFM-PB) inversion capability as an important advancement from MFM-User and MFM adaptive full-blind (AFB) processing in that MFM-PB permits all available user input data to be utilized, while facilitating PB analyses for model parameters that are missing, a more typical operational-level requirement. MFM-PB was compared with MFM-User analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) data in the Canadian Rocky Mountains and was shown to be comparable in terms of both generated inputs and all biophysical structural outputs, with differences for stand density of +/- 42 stems/ha, crown radii +/- 0.08 m, height to crown centre (HCC) +/- 0.10 m and tree height (HGT) +/- 0.37 m. These mountain results were further compared with MFM results from flat, boreal forest terrain and were found to be comparable. MFM-PB provides full flexibility for CRM inversion, and is particularly important for (but not limited to) larger area, regional-scale studies for which user input data are typically constrained.