Stemflow and throughfall on several tree architectural models

The aim of developing urban forests for steep areas is to prevent erosion. Erosion can be caused by stemflow and throughfall. The difference in stemflow and throughfall is thought to be due to differences in the tree architecture model. The study investigates the effects of several tree architectural models on the amount of stemflow and throughfall. It is hoped that data and information of this research can be taken into consideration in selecting tree species for the benefit of soil and water conservation in urban forest areas that have the potential for erosion and sedimentation. The collection and processing of data comprised the rainfall data obtained from Meteorological Climatological and Geophysical Agency, measurement of leaf area index using a hemispherical photograph and Hemiview 2.1 software, measurement of stemflow and throughfall in five tree architectural models (Massart, Aubreville, Koriba, Rauh, and Troll). Afterward, the relationship between the dependent and independent variables is known through multiple linear regression analysis using Minitab 16 software. The result showed that the tree architectural model influences stemflow and throughfall. The tree architectural model with the highest stemflow and throughfall is Rauh, and the lowest belongs to the Massart architectural model. The tree architectural model that can be used for land and water conservation is Massart; the species is Diospyros discolor Willd.

Lidar-based approaches for estimating solar insolation in heavily forested streams

Methods to quantify solar insolation in riparian landscapes are needed due to the importance of stream temperature to aquatic biota. We have tested three lidar predictors using two approaches developed for other applications of estimating solar insolation from airborne lidar using field data collected in a heavily forested narrow stream in western Oregon, USA. We show that a raster methodology based on the light penetration index (LPI) and a synthetic hemispherical photograph approach both accurately predict solar insolation, explaining more than 73 % of the variability observed in pyranometers placed in the stream channel. We apply the LPI-based model to predict solar insolation for an entire riparian system and demonstrate that no field-based calibration is necessary to produce an unbiased prediction of solar insolation using airborne lidar alone.

Lidar-based modelling approaches for estimating solar insolation in heavily forested streams

Methods to quantify solar insolation in riparian landscapes are needed due to the importance of stream temperature to aquatic biota. We have tested two approaches developed for other applications of estimating solar insolation from airborne lidar using field data collected in a heavily forested narrow stream in western Oregon, USA. We show that a raster methodology based on the light penetration index (LPI) and a synthetic hemispherical photograph approach both accurately predict solar insolation, explaining more than 73 % or the variability observed in pyranometers placed in the stream channel. We apply the LPI based model to predict solar insolation for an entire riparian system, and demonstrate that no field-based calibration is necessary to produce unbiased prediction of solar insolation using airborne lidar alone.

Estimating light environment in forests with a new thresholding method for hemispherical photography

Light environment estimates derived from hemispherical photography are known to be affected by variations in sky illumination. During photo acquisition, rapid changes in sky illumination can occur and will result in changes in detected canopy gap size and frequency. Any resulting problems in image consistency will become more serious with increased time lags between setting the reference exposure and hemispherical photograph acquisition. We showed that if the camera exposure setting was kept constant during photo acquisition, the estimated diffuse transmittance would be greatly influenced by sky illumination change. We developed a new pixel thresholding method that calculated the optimal threshold value for the separation of sky and plant pixels as a function of the above-canopy photosynthetic photon flux density (PPFD). We tested the performance of our method for estimating transmittance against two established methods that assume exposure to be held constant to two stops higher than the reference exposure. Our method compensates for changes in sky illumination, producing a smaller pixel threshold value when sky illumination decreases and a larger pixel threshold value when photographs are taken under increased sky illumination. The new method achieved accurate and reproducible results, even in situations where under- or over-exposure was caused by changes in sky illumination during photo acquisition.