Paper
17 December 1996 Effect of the understory on the estimation of coniferous forest leaf area index (LAI) based on remotely sensed data
Mario R. Caetano, Jorge M. T. Pereira
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Abstract
The SAIL model, a canopy reflectance model, was used to simulate narrow-band reflectance of overstory/background compositions to study the effect of the background on the estimation of the coniferous forest LAI based on remotely sensed data. We have simulated several mixed targets with a pine tree canopy and different backgrounds, including understory vegetation, soil and litter. For each type of mixed target we have modelled the reflectance for several LAI. The modeled data were used to evaluate the performance of the broad and narrow band NDVI for predicting the LAI. Results show that, for low LAI, the type of background contributes strongly to the reflectance of the mixed targets. Furthermore, the way the understory affects the mixed signal depends significantly on the vegetation species. The sensitivity of the NDVI for estimating the pine canopy LAI depends on the type of background and it was verified that mixed targets with non-vegetation backgrounds have larger sensitivity than the ones with vegetative backgrounds. The results show that the NDVI, calculated with broad or narrow bands, is not adequate to predict the LAI of open pine stands, when one does not known the type of background that is underneath the pine canopy.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mario R. Caetano and Jorge M. T. Pereira "Effect of the understory on the estimation of coniferous forest leaf area index (LAI) based on remotely sensed data", Proc. SPIE 2955, Image and Signal Processing for Remote Sensing III, (17 December 1996); https://doi.org/10.1117/12.262905
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Cited by 5 scholarly publications.
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KEYWORDS
Reflectivity

Data modeling

Vegetation

Near infrared

Atmospheric modeling

Transmittance

Agriculture

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