Remote sensing of temperate coniferous forest leaf area index: The influence of canopy closure, understory vegetation and background reflectance
International Journal of Remote Sensing
The relationship between the leaf area index (LAI) of temperate coniferous forests in the western United States and Thematic Mapper (TM) data corrected for atmospheric effects and Sun-surface-sensor geometry was influenced by canopy closure, understory vegetation and background reflectance. Strong inverse curvilinear relationships were observed between coniferous forest LAI and both TM bands 3 (0-63-0-69μm) and 5 (1-55-1-75μm). The inverse relationships are explained by increased reflectance of understory vegetation and background in open stands of lower LAI and decreased reflectance of the overstory in closed canopy stands with higher LAI. A strong positive relationship was observed between LAI and TM band 4 (0-76-0-90μm) radiance in stands with greater than 89 per cent canopy closure. Open stands with low overstory LAI had elevated band 4 radiances caused by understory vegetation and/or a highly reflective granite background. Old growth stands with incomplete overstories had low band 4 radiances as a result of less reflective forest litter and shadows. A ratio of band 4/band 3 compensated for the elevated band 4 radiance in open stands with vegetated or highly reflective backgrounds, but did not compensate for the low band 4 radiance in old growth stands with less reflective backgrounds of forest litter and shadows. Analysis of atmospheric and Sun-surface-sensor geometry corrections applied to the TM data indicated that path radiance contributed approximately 50 per cent of the radiance in TM band 3,20 per cent in band 4, and less than 10 per cent in band 5.
© 1990 Taylor & Francis
Spanner, Michael A., Pierce, Lars L., Peterson, David L., and Running, Steven W. (1990). Remote sensing of temperate coniferous forest leaf area index The influence of canopy closure, understory vegetation and background reflectance. International Journal of Remote Sensing: 11(1), 95-111. http://dx.doi.org/10.1080/01431169008955002