Using Hyperspectral Remote Sensing to Estimate Leaf Area Index of Loblolly Pine Plantations

Abstract

High spectral resolution (Hyperspectral) and multispectral imagery was used to examine the spectral response of loblolly pine with contrasting LAI and foliar nitrogen concentration. The research studies included very different stand structures (age, number and size of the trees). As a result of treatments applied, seasonal, stand and site variation, the range in LAI (0.4 — 3.6 m2 m2) and foliar nitrogen concentration (0.79 — 1.62%) on our study covered most of the range observed in midrotation loblolly pine plantations. Hyperspectral data was used to calculate narrowband vegetation indices (VIs) based on reflectance in the red (R) and near infrared (NIR). LAI was linearly related to the simple ratio (SR) vegetation index, the relationship was not affected by site, stand structure or season.

We also found a strong relationship between SR calculated from hyperspectral data and SR calculated from readily available Landsat 7 ETM+ data. Using that relationship, we determine an equation to estimate LAI from Landsat 7 ETM+ data.

Hyperspectral data was also used to estimate foliar nitrogen concentration and content of loblolly pine. We found a stronger relationship between nitrogen content and reflectance data than nitrogen concentration and reflectance data.