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A set of 57 novel canopy metrics of potential value for snow modeling were created from airborne LiDAR data. The metrics were meant to estimate size and relative location of gap openings around a point within forested areas, allowing for measures of the spatial arrangement of surrounding canopy elements. These new metrics were correlated with snow interception measured in the field (8488 manually measured snow interception points). The results were further compared to the correlation values between effective interception and traditionally used forest parameters (CC and LAI). The correspondence between all metrics was also analyzed in order to understand the potential cross correlation between each variable. LAI (average R: 0.57) demonstrated low correlations when directly compared to snow interception and further showed a large cross correlation with canopy closure (average R: 0.72). A new metric, ‘mean distance to canopy’ had the highest correlation (average R: 0.78) over all storm events to the effective interception. But in contrast to LAI, this metric did not show any cross correlation with canopy closure (CC). Likewise, ‘total gap area,’ an indirect measurement of apparent gap fraction (another new metric), also showed a high correlation to effective interception (average R: 0.72) without demonstrating a significant cross correlation to CC or to mean distance to canopy. These findings suggest that modeling forest snow processes with both CC and LAI may not be the best option due to both the low correlation of LAI as well as high cross correlation between these parameters. However, the pairing of mean distance to canopy and/or total gap area with canopy closure could give more robust estimations of snow interception within heterogeneous terrain.

Forest canopy structure and associated solar radiation fluxes greatly influence snow accumulation and melt and have large implications for water availability from forested areas. The ability to efficiently and explicitly infer canopy parameters at high resolution is crucial to improve the success of large scale applications of snow water resources modeling within these areas. In this paper, the utility of estimating leaf area index (LAI), canopy closure (CC) and below canopy potential incoming solar radiation (PISR) from synthetic hemispheric photos derived from airborne LiDAR data was evaluated. LAI and CC estimates from the synthetic LiDAR images were directly compared to actual hemispherical photos taken at 16 points at 7 field areas with heterogeneous canopy stand characteristics for a total of 112 photo comparison points. The synthetic data was further analyzed against LAI and CC derived from more traditional aerial LiDAR methods using a Cartesian space which integrates values over an area rather than a point based angular viewpoint. Furthermore, the PISR estimates were directly compared to in-situ radiometer measurements taken at 30 different locations during clear sky conditions with heterogeneous canopy stand properties. When compared to the actual hemispherical photos, the CC and LAI metrics from synthetic images showed higher correlations and lower biases for all canopy coverage classes (r: 0.93 for CC and r: 0.83 for LAI) than the metrics from the Cartesian approach which displayed decreased correlations and higher biases with increasing canopy closure. Using a clear sky partitioning scheme for the direct and diffuse portions of the incoming shortwave radiation, the PISR was also accurately estimated from the synthetic images with average site correlations ranging from 0.90 to 0.94 where the timing and peak trends of both the diffuse and direct radiation components were well represented. Finally, a basic methodology for the steps toward automation of the process was presented in order to explicitly derive these metrics within similar LiDAR datasets.

In order to estimate the influence of plant architectural traits on the erosivity of throughfall we studied throughfall kinetic energy (KE) under tree saplings in a plantation-like experiment in the humid subtropics. Our analyses of rainfall and throughfall KE are based on measurements using calibrated splash cups. Two experiments were carried out, one focusing on density effects and the other testing for species-specific effects and effects of species mixtures. The major architectural traits were measured to characterize sapling morphology. Mixed effects models were used for statistical analysis. In both models, rainfall KE was identified as the most important effect on throughfall KE. Overall, rainfall KE per area was reduced by 59% below the canopy of the studied saplings. We found a significant effect of sapling density on throughfall KE. This is primarily due to the relation between free throughfall and released throughfall. As free throughfall possesses a far higher KE than released throughfall originating from saplings, lower sapling density results in higher total throughfall KE. We also showed that the influence of density on throughfall KE decreases with increasing sapling height due to lateral canopy growth of the saplings. Throughfall KE was significantly different among species. We attribute this to species-specific differences in crown architectural traits. These traits have opposite influence on throughfall KE and interact with each other. Depending on its magnitude, one crown trait can possibly superimpose contrary effects of others. In order to estimate the influence of plant architectural traits on the erosivity of throughfall we studied throughfall kinetic energy (KE) under tree saplings in a plantation-like experiment in the humid subtropics. Our analyses of rainfall and throughfall KE are based on measurements using calibrated splash cups. Two experiments were carried out, one focusing on density effects and the other testing for species-specific effects and effects of species mixtures. The major architectural traits were measured to characterize sapling morphology. Mixed effects models were used for statistical analysis. In both models, rainfall KE was identified as the most important effect on throughfall KE. Overall, rainfall KE per area was reduced by 59% below the canopy of the studied saplings. We found a significant effect of sapling density on throughfall KE. This is primarily due to the relation between free throughfall and released throughfall. As free throughfall possesses a far higher KE than released throughfall originating from saplings, lower sapling density results in higher total throughfall KE. We also showed that the influence of density on throughfall KE decreases with increasing sapling height due to lateral canopy growth of the saplings.Throughfall KE was significantly different among species. We attribute this to species-specific differences in crown architectural traits. These traits have opposite influence on throughfall KE and interact with each other. Depending on its magnitude, one crown trait can possibly superimpose contrary effects of others. © 2012 Elsevier B.V.

a b s t r a c t Consumer-grade digital cameras are recognized as a cost-effective method of monitoring plant health and phenology. The capacity to use these cameras to produce time series information contributes to a better understanding of relationships between environmental conditions, vegetation health, and produc- tivity. In this study we evaluate the use of consumer grade digital cameras modified to capture infrared wavelengths for monitoring vegetation. The use of infrared imagery is very common in satellite remote sensing, while most current near sensing studies are limited to visible wavelengths only. The use of infrared-visible observations is theoretically superior over the use of just visible observation due to the strong contrast between infrared and visible reflection of vegetation, the high correlation of the three visible bands and the possibilities to use spectral indices like the Normalized Difference Vegetation Index. This paper presents two experiments: the first study compares infrared modified and true color cameras to detect seasonal development of understory plants species in a forest; the second is aimed at evaluation of spectrometer and camera data collected during a laboratory plant stress experiment. The main goal of the experiments is to evaluate the utility of infrared modified cameras for the monitoring of plant health and phenology. Results show that infrared converted cameras perform less than standard color cameras in a monitoring setting. Comparison of the infrared camera response to spectrometer data points at limits in dynamic range, and poor band separation as the main weaknesses of converted consumer cameras. Our results support the use of standard color cameras as simple and affordable tools for the monitoring of plant stress and phenology.