Global modeling of gross primary production (GPP) is a critical component of climate change research. On local scales, GPP can be assessed from measuring CO₂ exchange above the plant canopy using tower-based eddy covariance (EC) systems. The limited footprint inherent to this method however, restricts observations to relatively few discrete areas making continuous predictions of global CO₂ fluxes difficult. Recently, the advent of high resolution optical remote sensing devices has offered new possibilities to address some of the scaling issues related to GPP using remote sensing. One key component for inferring GPP spectrally is the efficiency (ε) with which plants can use absorbed photosynthetically active radiation to produce biomass. While recent years have seen progress in measuring ε using the photochemical reflectance index (PRI), little is known about the temporal and spatial requirements for up-scaling these findings continuously throughout the landscape. Satellite observations of canopy reflectance are subject to view and illumination effects induced by the bi-directional reflectance distribution function(BRDF) which can confound the desired PRI signal. Further uncertainties include dependencies of PRI on canopy structure, understorey, species composition and leaf pigment concentration. The objective of this research was to investigate the effects of these factors on PRI to facilitate the modeling of GPP in a continuous fashion. Canopy spectra were sampled over a one-year period using an automated tower-based, multi-angular spectroradiometer platform (AMSPEC), designed to sample high spectral resolution data. The wide range of illumination and viewing geometries seen by the instrument permitted comprehensive modeling of the BRDF. Isolation of physiologically induced changes in PRI yielded a high correlation (r²=0.82, p<0.05) to EC-measured ε, thereby demonstrating the capability of PRI to model ε throughout the year. The results were extrapolated to the landscape scale using airborne laser-scanning (light detection and ranging, LiDAR) and high correlations were found between remotely-sensed and EC-measured GPP (r²>0.79, p<0.05). Permanently established tower-based canopy reflectance measurements are helpful for ongoing research aimed at up-scaling ε to landscape and global scales and facilitate a better understanding of physiological cycles of vegetation and serve as a calibration tool for broader band satellite observations.

Recent studies have demonstrated that images constructed from lidar reflectance information exhibit superior robustness to lighting changes. However, due to the scanning nature of the lidar and assumptions made in previous implementations, data acquired during continuous vehicle motion suffer from geometric motion distortion and can subsequently result in poor metric visual odometry (VO) estimates, even over short distances (e.g., 5-10 m). The first part of this thesis revisits the measurement timing assumption made in previous systems, and proposes a frame-to-frame VO estimation framework based on a pose-interpolation scheme that explicitly accounts for the exact acquisition time of each intrinsic, geometric feature measurement. The second part of this thesis investigates a novel method of lidar calibration that can be applied without consideration of the internal structure of the sensor. Both methods are validated using experimental data collected from a planetary analogue environment with a real scanning laser rangefinder.

Previously disturbed and regenerating forests make up a significant proportion of the North American land area, and therefore play an important role in the exchanges of heat and trace gases between the terrestrial biosphere and the atmosphere. Assessment of local to global variability in CO2 exchanges by forests requires a combination of CO2 measurements made by eddy covariance (EC), field measurements, remote sensing data, and ecosystem models. The integration of these is problematic because of a mis-match in scale between measurement techniques. Despite the importance of regenerating forests on the global carbon balance, the processes affecting the carbon cycle within these forests is not well understood. Airborne scanning light detection and ranging (lidar) instruments provide new opportunities to examine three-dimensional forest characteristics from the level of individual trees to ecosystems and beyond. Lidar is therefore an effective link between plot measurements, eddy covariance, and low resolution remote sensing pixels. This thesis dissertation presents new science on the use of airborne lidar for evaluating remote sensing products within heterogeneous and previously clearcut ecosystems. The goals of this thesis were to first understand the processes affecting CO2 exchanges within a previously disturbed boreal jack pine chronosequence located in Saskatchewan, Canada and then to apply this understanding to evaluate low resolution remote sensing data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) using airborne lidar. The first objective of this dissertation examined the factors that control light use efficiency (LUE) within the jack pine chronosequence during dry and wet years. The second objective examined the importance of vegetation structure and ground surface elevation on CO2 fluxes within a mature jack pine forest. The third objective developed and tested a simple model of lidar fractional cover and related this to the fraction of photosynthetically active radiation absorbed by the canopy (fPAR). This was then used to evaluate the MODIS fPAR product across the lower part of a watershed. Finally, the fourth objective was to model gross primary production (GPP) from airborne lidar. Lidar estimates of GPP were then compared with those from the EC system at the jack pine chronosequence and with the MODIS GPP (Collection 5) product. / Thesis (Ph.D, Geography) -- Queen's University, 2008-08-22 08:50:51.44

Three dimensional laser scanning, also known as Light Detection and Ranging (LiDAR) has quickly been expanding in its applications in the field of geological engineering due to its ability to rapidly acquire highly accurate three dimensional positional data. Recently is has been shown that LiDAR scanning can be easily integrated into an excavation sequence in an underground environment for the purpose of collecting rockmass and discontinuity information. As scans are often taken multiple times of the same environment, the next logical application of LiDAR scanning is for monitoring for change and deformation. Traditionally, deformation and change in an underground environment is measured using a series of five or more permanent control points installed around the profile of an excavation. Using LiDAR for profile analysis provides many benefits as compared to traditional monitoring techniques. Due to the high density of the point cloud data, the change in profile is able to be fully characterized, and areas of anomalous movement can easily be separated from overall closure trends. Furthermore, monitoring with LiDAR does not require the permanent installation of control points, therefore monitoring can be completed more quickly after excavation, and scanning is non-invasive therefore no damage is done during the installation of temporary control points. The main drawback of using LiDAR scanning for deformation monitoring is that the raw point accuracy is generally the same magnitude as the smallest level of deformations that need to be measured. To overcome this, statistical techniques for profile analysis must be developed. This thesis outlines the development one such method, called the Elliptical Fit Analysis (EFA) and LiDAR Profile Analysis (EFA) for tunnel and shaft convergence analysis. Testing of the EFA and LPA has proved the robustness of this technique in its ability to deal with accuracy and precision issues associated with LiDAR scanning. / Thesis (Master, Geological Sciences & Geological Engineering) -- Queen's University, 2012-05-15 13:24:28.398

Recent studies have demonstrated that images constructed from lidar reflectance information exhibit superior robustness to lighting changes. However, due to the scanning nature of the lidar and assumptions made in previous implementations, data acquired during continuous vehicle motion suffer from geometric motion distortion and can subsequently result in poor metric visual odometry (VO) estimates, even over short distances (e.g., 5-10 m). The first part of this thesis revisits the measurement timing assumption made in previous systems, and proposes a frame-to-frame VO estimation framework based on a pose-interpolation scheme that explicitly accounts for the exact acquisition time of each intrinsic, geometric feature measurement. The second part of this thesis investigates a novel method of lidar calibration that can be applied without consideration of the internal structure of the sensor. Both methods are validated using experimental data collected from a planetary analogue environment with a real scanning laser rangefinder.

Light Detection And Ranging (LiDAR) mapping has been emerging over the past few years as a mainstream tool for the dense acquisition of three dimensional point data. Besides the conventional mapping missions, LiDAR systems have proven to be very useful for a wide spectrum of applications such as forestry, structural deformation analysis, urban mapping, and reverse engineering. The wide application scope of LiDAR lead to the development of many laser scanning technologies that are mountable on multiple platforms (i.e., airborne, mobile terrestrial, and tripod mounted), this caused variations in the characteristics and quality of the generated point clouds. As a result of the increased popularity and diversity of laser scanners, one should address the heterogeneous LiDAR data post processing (i.e., registration and segmentation) problems adequately. Current LiDAR integration techniques do not take into account the varying nature of laser scans originating from various platforms. In this dissertation, the author proposes a methodology designed particularly for the registration and segmentation of heterogeneous LiDAR data. A data characterization and filtering step is proposed to populate the points’ attributes and remove non-planar LiDAR points. Then, a modified version of the Iterative Closest Point (ICP), denoted by the Iterative Closest Projected Point (ICPP) is designed for the registration of heterogeneous scans to remove any misalignments between overlapping strips. Next, a region-growing-based heterogeneous segmentation algorithm is developed to ensure the proper extraction of planar segments from the point clouds. Validation experiments show that the proposed heterogeneous registration can successfully align airborne and terrestrial datasets despite the great differences in their point density and their noise level. In addition, similar testes have been conducted to examine the heterogeneous segmentation and it is shown that one is able to identify common planar features in airborne and terrestrial data without resampling or manipulating the data in any way. The work presented in this dissertation provides a framework for the registration and segmentation of airborne and terrestrial laser scans which has a positive impact on the completeness of the scanned feature. Therefore, the derived products from these point clouds have higher accuracy as seen in the full manuscript.

Die vorliegende Arbeit beschäftigt sich mit der Auswertung und den Ergebnissen von Mehrwellenlängen–Polarisations–Ramanlidarmessungen, die im Rahmen des Saharastaubschließungsexperiments Saharan Mineral Dust Experiment (SAMUM) durchgeführt wurden. Das SAMUM–Projekt erstreckte sich über zwei Intensivmesszeiträume im Mai und Juni 2006 in Marokko (SAMUM–1) und im Januar und Februar 2008 auf den Kapverdischen Inseln (SAMUM–2). Desweiteren werden zusätzliche Lidarmessungen besprochen, die im Mai und Juni 2008 auf den Kapverdischen Inseln durchgeführt wurden. Die geometrischen und optischen Eigenschaften der während dieser Experimente mit mehreren hochmodernen Lidargeräten beobachteten Mineralstaub- und Biomassenverbrennungsaerosolschichten werden anhand von Fallstudien und mehrwöchigen, höhenaufgelösten Mittelwerten beschrieben. Zudem werden Kalibrierungen und Korrekturen vorgestellt, die zur Qualitätssicherung der gewonnenen Messdaten durchgeführt wurden. Ein im Rahmen der Arbeit entwickeltes, auf quantitativen Messungen des linearen Partikeldepolarisationsverhältnisses basierendes Verfahren zur höhenaufgelösten Trennung der Anteile von Mineralstaub und Biomassenverbrennungsaerosol an den während SAMUM–2 gemessenen Rücktreu- und Extinktionsprofilen wird vorgestellt und angewandt. Die Auswertung der Mehrwellenlängenlidarmessungen der SAMUM–Kampagnen ermöglichte eine spektral aufgelöste Charakterisierung der optischen Eigenschaften von Saharastaubpartikeln. Besondere Aufmerksamkeit wurde auf die Bestimmung der intensiven Parameter Extinktions–zu–Rückstreuverhältnis (Lidarverhältnis), lineares Partikeldepolarisationsverhältnis sowie Ångströmexponent der Rückstreu- und Extinktionskoeffizienten gelegt. Die im Rahmen von SAMUM bei den Wellenlängen 355, 532 und 1064 nm durchgeführten Lidarmessungen ergaben mittlere Lidarverhältnisse von 55±5 sr für reinen Saharastaub. Während SAMUM wurden außerdem erstmals quantitative Messergebnisse des linearen Partikeldepolarisationsverhältnisses von reinem Saharastaub bei mehreren Wellenlängen gewonnen. Die mittleren Werte dieser Größe lagen bei 0.26±0.06 (355 und 1064 nm), 0.31±0.03 (532 nm) und 0.37±0.07 (710 nm). Diese Erkenntnisse liefern wichtige Informationen für die Auswertung von Messungen mit weniger fortschrittlichen Lidargeräten. Die durch SAMUM gewonnenen Erkenntnisse der optischen Eigenschaften von Mineralstaub erlauben eine eindeutige Identifikation des Staubanteils in Aerosolschichten im Abluftbereich der Wüsten. Zudem wurden Richtgrößen ermittelt, die zur Validierung von Modellen zur Beschreibung von Lichtstreuung an großen, nicht–kugelförmigen Teilchen verwendet werden können. Derartige Streumodelle werden für die Auswertung von Messungen der optischen Eigenschaften von Mineralstaubpartikeln mit passiven Sensoren benötigt und befinden sich zur Zeit eher in einer frühen Entwicklungsphase.

Darmstadt, Techn. Universiẗat, Diss., 2006.

Zugl.: Kassel, Univ., Diss., 2005

Techn. University, Diss., 2006--Darmstadt.