University of Twente Student Theses


Comparison of digital aerial image and LiDAR data to estimate forest parameters

Shrestha, Shrota (2013) Comparison of digital aerial image and LiDAR data to estimate forest parameters.

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Abstract:The estimation of forest parameters plays important role on forest inventory. The forest inventory is expensive and time consuming, but also important on forest management. The development on remote sensing techniques such as digital aerial images, satellite images, LiDAR has provide more efficient way of forest inventory. Many researches are going on to study more accurate and efficient way of forest inventory using different remote sensing techniques. This study aims to demonstrate the accuracy of estimation of forest parameters by using digital aerial image and LiDAR. In addition with, the potential LiDAR metrics were selected to estimate height, basal area and volume. The plot based approach was adopted as the study area has 1.0 point density m-2 and was not enough to generate the height, basal area and volume on individual tree level. Eight LiDAR metrics were selected for basal area model and seven LiDAR metrics were selected for height model and validated with field measured data. The final model was determined with selected LiDAR metrics after stepwise selection procedures. 10th and 90th percentiles of LiDAR canopy height was selected for final height model and maximum and mean of LiDAR canopy heights, 50th, 75th and 90th percentiles of LiDAR canopy heights, coefficient of variation of LiDAR canopy heights and canopy cover density was selected for final basal area model. While volume model used LiDAR tree height estimated after stepwise selection procedures and canopy density metrics from LiDAR data. The coefficient determination for height, basal area and volume was found to be 71%, 78% and 81% respectively with field measured data. Due to low GSD and low forward overlap on aerial image generate poor quality DSM and DTM, which affect the quality of CHM. The height of tree cannot be extracted from aerial image CHM and further analysis cannot be performed on this study area with aerial image CHM.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
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