Estimation of leaf area index and canopy openness in broad-leaved forest using an airborne laser scanner in comparison with high-resolution near-infrared digital photography

We estimated leaf area index (LAI) and canopy openness of broad-leaved forest using discrete return and small-footprint airborne laser scanner (ALS) data. We tested four ALS variables, including two newly proposed ones, using three echo types (first, last, and only) and three classes (ground, vegetation, and upper vegetation), and compared the accuracy by means of correlation and regression analysis with seven conventional vegetation indices derived from simultaneously acquired high-resolution near-infrared digital photographs. Among the ALS variables, the ratio of the “only-and-ground” pulse to “only” pulse (OGF) was the best estimator of both LAI (adjusted R2 = 0.797) and canopy openness (adjusted R2 = 0.832), followed by the ratio of the pulses that reached the ground to projected lasers (GF). Among the vegetation indices, the normalized differential vegetation index (NDVI) was the best estimator of both LAI (adjusted R2 = 0.791) and canopy openness (adjusted R2 = 0.764). Resampling analysis on ALS data to examine whether the estimation of LAI and canopy openness was possible with lower point densities revealed that GF maintained a high adjusted R2 until a fairly low density of about 0.226 points/m2, while OGF performed marginally when the point density was reduced to about 1 point/m2, the standard density of high-density products on the market as of February 2008. Consequently, the ALS variables proposed in the present study, GF and OGF, seemed to have great potential to estimate LAI and canopy openness of broad-leaved forest, with accuracy comparable to NDVI, from high-resolution near-infrared imagery.

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