I use temporal lidar and radar to reveal fault rupture kinematics and to test a method of mapping earthquake-induced structural damage. Using pre- and post-event data, these applications of remote technology offer unique perspectives of earthquake effects. Lidar point clouds can produce high resolution, three-dimensional terrain maps, so subtle landscape shifts can be discerned through temporal analysis, providing detailed imagery of co-seismic ground displacement and faulting. All-weather radar systems record back-scattered signal amplitude and phase. Pre- and post-event comparisons of phase can illuminate co-seismic structural damage using an oblique look angle, most sensitive to changes in building heights. Extracted information from these geodetic methods may be used to inform decisions on future earthquake modeling and emergency response. In the first major section of this thesis, I calculate co-seismic 3D ground deformation produced by the Papatea fault using differential lidar. I demonstrate that this fault - a key element within the 2016 Mw 7.8 Kaikoura earthquake - has a distinctly non-planar geometry, far exceeded typical co-seismic slip-to-length ratios, and defied Andersonian mechanics by slipping vertically at steep angles. Its surface deformation is poorly reproduced by elastic dislocation models, suggesting the Papatea fault did not release stored strain energy as typically assumed, perhaps explaining its seismic quiescence in back-projections. Instead, it slipped in response to neighboring fault movements, creating a localized space problem, accounting for its anelastic deformation field. Thus, modeling complex, multiple-fault earthquakes as slip on planar faults embedded in an elastic medium may not always be appropriate. For the second major part of this thesis, I compare mean values of interferometric synthetic aperture radar (InSAR) coherence change across four case studies of earthquake-induced building damage. These include the 2016 Amatrice earthquake, the 2017 Puebla-Morelos earthquake, the 2017 Sarpol-e-Zahab earthquake, and the 2018 Anchorage earthquake. I examine the influences of environmental and urban characteristics on co-seismic coherence change using Sentinel-1 imagery and compare the outcomes of various damage levels. I do not find consistent values of mean coherence change to distinguish levels of damage across the case studies, indicating coherence change values vary with location, environment, and damage pattern. However, this method of damage mapping shows potential as a useful tool in earthquake emergency response, capable of quickly identifying localized areas of high damage in areas with low snow and vegetation cover. Given the large spatial coverage and relatively quick, low-cost acquisition of SAR imagery, this method could provide damage estimates for unsafe or remote regions or for areas unable to self-report damage. / Graduate

There are considerable expenditures by government and private forest industry to enhance the growth of forests and reduce time required for crop rotation. The effectiveness of some of these treatments is dependent on site productivity. In addition, as responsible stewards of the forest resource and habitat, it is important that the state of forests are actively monitored, especially in the face of a changing climate and increased rates of disturbance. This dissertation reports on the development of a method for estimating and mapping forest productivity. The Shawnigan Lake thinning and fertilization forest installation, established in 1971 by CFS, was selected as the study site largely for its rich mensuration history. Square treatment plots were 0.04ha in area and included two thinning levels (1/3 & 2/3 of the basal area), two fertilization treatments (224kg & 448kg N/ha) with repeated fertilizations and macronutrient experiments (S, P) and control plots. A sample of plots was selected for high precision ground based lidar reference surveys. In September of 2012 a multi-sensor airborne survey of SLP was conducted that collected high-density lidar (up to ~70pnts/m2) and VNIR imaging spectroscopy. A thorough empirical radiometric calibration was conducted in addition to a spatial calibration at the Victoria International Airport. A combination of area based height percentile, point density ratios and statistical moments with individual lidar tree metrics including height distribution and proximity metrics were generated. Topographic metrics were also generated from the lidar ground classified point cloud. A library of spectral indices was computed from the imaging spectrometer data, with an emphasis on those indices known to be associated with vegetation health. These metrics were summarized to the plot level for a coarse scale regression analysis. A control survey and ground based lidar was used to facilitate an individual tree based fine scale of analysis, where reference data could unambiguously be matched to airborne collected data through the projected positions. Regression analysis was conducted applying the best subset regression with exhaustive feature selection search criteria and included a critical evaluation of the resulting selected features. Models were investigated considering the data source and in combination, that is, lidar metrics were considered independent of spectroscopy as well as the converse, and lidar metrics in combination with spectral metrics. The contribution of this study is the revelation that existing area based point cloud metrics are highly correlated, potentially noisy and sensitive to variations in point density, resulting in unstable feature selection and coefficients in model building. The approach offered as an alternative is the gridded lidar treetops method, which is evidently lacking within the literature and which this study overwhelmingly advocates. Additionally, the breadth and diversity of metrics assessed, the size and quality of the reference data applied, and the fine spatial scale of analysis are unique within the research area. This study also contributes to the knowledge base, in that, productivity can be estimated by remote sensing technologies. The use of gridded generalizations of the individual tree approach reduced estimation errors for both structural and productivity attributes. At the plot-level, crown structure and crown health features best estimated productivity. This study emphasizes the dangers of empirical modeling; at the even-aged SLP installation, growth is strongly tied to structure and the extrapolation to other sites is expected to provide biased values. It is my perspective that physical lidar structural models of the dominant and co-dominant crown classes be used to augment spatially explicit tree and stand growth models. In addition, direct measures should be obtained by multi-temporal lidar surveys or as an alternative photogrammetric point clouds after an initial lidar survey to quantify growth and aid in calibrating growth models. / Graduate