Deriving Forest Canopy Characteristics from MULTI-ANGLE IMAGING SPECTRORADIOMETER (MISR) Data for a Lodgepole Pine Forest of Central Montana, USA

Canopy structure is an essential component to understanding a multitude of ecosystem processes such as carbon and nutrient cycling, hydrology, forecasting stand susceptibility to insect outbreaks, maintaining biodiversity, and wildlife habitat studies. The amount and vertical position of canopy vegetation is not only important to the ecosystem modeling community, but to the fire community as well. Knowledge of the spatial arrangement and amount of biomass in the canopy could greatly enhance real-time and planning-mode fire growth prediction capabilities and crown fire modeling, assist the implementation of fuels treatments that mitigate the occurrence of catastrophic fires, aid in smoke emission and fire effects modeling. Traditional remote sensing techniques have been unable to adequately characterize the full dimensionality of forest canopies. A new breed of multi-view angle sensors shows great promise in being able to discriminate canopy structural features through bidirectional reflectance factor information. The Multi-angle Imaging Spectroradiometer (MISR) aboard the Terra spacecraft, is one of the newest sensors that has yet to be tested for its full capacity as a land surface remote sensor. MISR is unique in that it images the earth in nine different view angles; each of the nine cameras collects reflectance in four color bands (blue, green, red and near-infrared). MISR data may allow the inference of canopy structure because of the three-dimensional component of the nadir and off-nadir camera angles. This study explored the ability of MISR data to map canopy structure and fuel characteristics of lodgepole pine (Pinus contorta) forests at the Tenderfoot Creek Experimental Forest, Montana. 

Principal investigator: Kristen Schmidt