13 research outputs found

    Use of Naturally Available Reference Targets to Calibrate Airborne Laser Scanning Intensity Data

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    We have studied the possibility of calibrating airborne laser scanning (ALS) intensity data, using land targets typically available in urban areas. For this purpose, a test area around Espoonlahti Harbor, Espoo, Finland, for which a long time series of ALS campaigns is available, was selected. Different target samples (beach sand, concrete, asphalt, different types of gravel) were collected and measured in the laboratory. Using tarps, which have certain backscattering properties, the natural samples were calibrated and studied, taking into account the atmospheric effect, incidence angle and flying height. Using data from different flights and altitudes, a time series for the natural samples was generated. Studying the stability of the samples, we could obtain information on the most ideal types of natural targets for ALS radiometric calibration. Using the selected natural samples as reference, the ALS points of typical land targets were calibrated again and examined. Results showed the need for more accurate ground reference data, before using natural samples in ALS intensity data calibration. Also, the NIR camera-based field system was used for collecting ground reference data. This system proved to be a good means for collecting in situ reference data, especially for targets with inhomogeneous surface reflection properties

    Radiometric Calibration of Terrestrial Laser Scanners with External Reference Targets

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    The intensity data produced by terrestrial laser scanners has become a topic of increasing interest in the remote sensing community. We present a case study of radiometric calibration for two phase-shift continuous wave (CW) terrestrial scanners and discuss some major issues in correcting and applying the intensity data, and a practical calibration scheme based on external reference targets. There are differences in the operation of detectors of different (although similar type) instruments, and the detector effects must be known in order to calibrate the intensity data into values representing the target reflectance. It is, therefore, important that the effects of distance and target reflectance on the recorded intensity are carefully studied before using the intensity data from any terrestrial laser scanner

    Tree Root System Characterization and Volume Estimation by Terrestrial Laser Scanning and Quantitative Structure Modeling

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    The accurate characterization of three-dimensional (3D) root architecture, volume, and biomass is important for a wide variety of applications in forest ecology and to better understand tree and soil stability. Technological advancements have led to increasingly more digitized and automated procedures, which have been used to more accurately and quickly describe the 3D structure of root systems. Terrestrial laser scanners (TLS) have successfully been used to describe aboveground structures of individual trees and stand structure, but have only recently been applied to the 3D characterization of whole root systems. In this study, 13 recently harvested Norway spruce root systems were mechanically pulled from the soil, cleaned, and their volumes were measured by displacement. The root systems were suspended, scanned with TLS from three different angles, and the root surfaces from the co-registered point clouds were modeled with the 3D Quantitative Structure Model to determine root architecture and volume. The modeling procedure facilitated the rapid derivation of root volume, diameters, break point diameters, linear root length, cumulative percentages, and root fraction counts. The modeled root systems underestimated root system volume by 4.4%. The modeling procedure is widely applicable and easily adapted to derive other important topological and volumetric root variables

    Change Detection of Tree Biomass with Terrestrial Laser Scanning and Quantitative Structure Modelling

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    We present a new application of terrestrial laser scanning and mathematical modelling for the quantitative change detection of tree biomass, volume, and structure. We investigate the feasibility of the approach with two case studies on trees, assess the accuracy with laboratory reference measurements, and identify the main sources of error, and the ways to mitigate their effect on the results. We show that the changes in the tree branching structure can be reproduced with about ±10% accuracy. As the current biomass detection is based on destructive sampling, and the change detection is based on empirical models, our approach provides a non-destructive tool for monitoring important forest characteristics without laborious biomass sampling. The efficiency of the approach enables the repeating of these measurements over time for a large number of samples, providing a fast and effective means for monitoring forest growth, mortality, and biomass in 3D
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