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Hypervelocity collisions of asteroids onto planetary bodies have catastrophic effects on the target rocks through the process of shock metamorphism. The resulting features, impact craters, are circular depressions with a sharp rim surrounded by an ejecta blanket of variably shocked rocks. With increasing impact energy, the inner crater cavity can preserve complex morphologies including terraced walls, central uplifts, and melted rocks. The lack of erosion due to the absence of water or an atmosphere makes the Moon the perfect target to study impact crater processes, in particular the distribution of highly shocked materials within impact craters of different sizes. This study focuses on the characterization and distribution of highly shocked impact melt deposits using multispectral satellite datasets around three complex craters on the farside of the Moon. The study sites have varying morphologies of central uplifts on the crater floor: 1) the 81 km Olcott crater has a cluster of peak hills; 2) Kovalevskaya crater is a 113 km diameter complex crater with a central peak; and 3) Schrodinger basin has a central peak ring. Models propose that the collapse of crater walls and central uplifts during the final stages of crater formation determine where much of the melt rich rocks are eventually emplaced. The results of this study indicate that for increasing crater sizes, the volume of melt-rich rocks generated also increases – at rates greater than model estimates. Impact melt deposits are emplaced beyond the crater rims at each of the sites and preserve a range of morphologies, including melt veneers, melt sheet, and ponded deposits. The regional and local topography, together with crater modification processes greatly affect where the impact melts are finally emplaced. The compositional analyses of the farside crust, using multispectral reflectance spectroscopy in the UV-VIS-NIR range, indicates that there is increasing evidence of highly mafic compositions (i.e., rocks rich in high-Ca pyroxene, olivine, spinel) intercalated within the original crustal highlands (rocks rich in plagioclase feldspar, and low-Ca pyroxenes) on the lunar farside, proving that the lunar farside is a far more geologically complicated terrain than originally assumed.

Surface temperature plays a key role in many micro-scale urban processes. Walls comprise a significant percentage of the urban surface, yet are under-represented by many methods of thermal remote sensing and not considered in detail by micro-scale surface temperature mod- els. This thesis presents a novel method of mobile thermal observation performed in urban street canyons in London, ON that uses a thermal imager as well as a visual spectrum camera to provide dense spatial and temporal resolution of micro-scale wall temperature distributions. Images are manually classified by a series of nominal variables and the resulting data set discusses the influence of micro-scale wall geometry on shading patterns and temperature distributions. Results show that micro-scale geometry both cools and heats walls, that small amounts of geo- metric complexity significantly affect temperature distributions, and that micro-scale structure may warm facets at night. Implications for temperature and wind applications are discussed.

Buildings play an essential role in urban intra-construction, urban planning, climate studies and disaster management. The precise knowledge of buildings not only serves as a primary source for interpreting complex urban characteristics, but also provides decision makers with more realistic and multidimensional scenarios for urban management. In this thesis, the 2D extraction and 3D reconstruction methods are proposed to map and visualize urban buildings. Chapter 2 presents an object-based method for extraction of building footprints using LiDAR derived NDTI (Normalized Difference Tree Index) and intensity data. The overall accuracy of 94.0% and commission error of 6.3% in building extraction is achieved with the Kappa of 0.84. Chapter 3 presents a GIS-based 3D building reconstruction method. The results indicate that the method is effective for generating 3D building models. The 91.4% completeness of roof plane identification is achieved, and the overall accuracy of the flat and pitched roof plane classification is 88.81%, with the user’s accuracy of the flat roof plane 97.75% and pitched roof plane 100%.

The effective adoption and implementation of Building Information Modeling (BIM) is still challenging for the construction industry. However, studies and reports show a significant increase in the rate of BIM implementation and adoption in mainstream construction activities over the last five years. In contrast, Pre-Engineered Building (PEB) construction, a specialized construction system which provides a very efficient approach for construction of primarily industrial buildings, has not seen the same uptake in BIM implementation and adoption. The thesis reviews the benefits and the main applications of BIM for the PEB industry as well as challenges of its practical implementation. To facilitate the implementation of BIM in the PEB industry, a BIM framework is adapted from Pre-fabrication (Pre-fab) industry and new workflows, process maps, and data-exchange strategies are developed. As the PEB industry traditionally makes significant use of automation in its design and fabrication process, accordingly this work investigates the technical challenges of incorporating automation into the proposed BIM process. Two new BIM concepts, “Planar Concept” and “Floating LOD”, are then developed and implemented as a solution to these challenges. To define the proper input/output criteria for automated BIM design processes, a numerical study was performed to identify an “Optimum LOD”. A software implementation embodying the research outcomes was developed to illustrate the feasibility of the results. Its step-by-step deployment is analyzed and discussed using an example industry PEB design project. Further, the impact of this work is extended by integrating the developed BIM framework and automated design process with wind engineering design activities and tools and procurement systems. The study concludes that the deployment of the proposed BIM framework could significantly address existing issues in project design through to operation processes found in the PEB industry. Also, the results indicate the developed concepts have the potential for supporting the application of automation in the other sectors of the general construction industry. This thesis is written using the "Integrated Article" format and includes various complementary studies.

The video game industry has been examined since the 1970’s, yet individual country analysis from an economic geography perspective has been lacking. It is the contribution of this dissertation to utilize the agglomeration economy and location theory literature in its application to the Canadian video game industry. To understand this industry, a mixed-method approach is used. Kernel density maps, standard deviational ellipses, and mapping processes were used to illustrate the dispersion and clustering patterns of studios in Canada. In addition, a Poisson regression was performed using count data of the number of video game firms in census metropolitan areas. The resulting data displayed strong clustering in the major trade cities of Vancouver, Toronto, and Montreal, with the Poisson regression showing a positive relationship between the two variables, population and number of video game studios. The interview data revealed that this is influenced by a mix of urban hierarchy and financial aid. These two go hand in hand as often these areas with the highest population and therefore the greatest number of video game studios, have the most opportunities for this aid. Interviews also revealed the additional element of networking. While this is somewhat limited in some given locations, there are more instances of open communication in the smaller-scale operations between developers. The growth of the video game industry relies heavily on the branch economy that has developed over time. While it is possible to apply the initial growth of the industry in Canada to the economic geography literature, this is reduced to initial stages of development and labour pools.

The two-dimensional (2D) footprints and three-dimensional (3D) structures of buildings are of great importance to city planning, natural disaster management, and virtual environmental simulation. As traditional manual methodologies for collecting 2D and 3D building information are often both time consuming and costly, automated methods are required for efficient large area mapping. It is challenging to extract building information from remotely sensed data, considering the complex nature of urban environments and their associated intricate building structures. Most 2D evaluation methods are focused on classification accuracy, while other dimensions of extraction accuracy are ignored. To assess 2D building extraction methods, a multi-criteria evaluation system has been designed. The proposed system consists of matched rate, shape similarity, and positional accuracy. Experimentation with four methods demonstrates that the proposed multi-criteria system is more comprehensive and effective, in comparison with traditional accuracy assessment metrics. Building height is critical for building 3D structure extraction. As data sources for height estimation, digital surface models (DSMs) that are derived from stereo images using existing software typically provide low accuracy results in terms of rooftop elevations. Therefore, a new image matching method is proposed by adding building footprint maps as constraints. Validation demonstrates that the proposed matching method can estimate building rooftop elevation with one third of the error encountered when using current commercial software. With an ideal input DSM, building height can be estimated by the elevation contrast inside and outside a building footprint. However, occlusions and shadows cause indistinct building edges in the DSMs generated from stereo images. Therefore, a “building-ground elevation difference model” (EDM) has been designed, which describes the trend of the elevation difference between a building and its neighbours, in order to find elevation values at bare ground. Experiments using this novel approach report that estimated building height with 1.5m residual, which out-performs conventional filtering methods. Finally, 3D buildings are digitally reconstructed and evaluated. Current 3D evaluation methods did not present the difference between 2D and 3D evaluation methods well; traditionally, wall accuracy is ignored. To address these problems, this thesis designs an evaluation system with three components: volume, surface, and point. As such, the resultant multi-criteria system provides an improved evaluation method for building reconstruction.

This study integrated multi-temporal, multispectral optical and L-band synthetic aperture radar (SAR) imagery to classify agricultural crops throughout a single growing season in northeastern Ontario, Canada. Various optical and SAR band/date combinations were tested to identify optimal dates and datasets for crop classification at various phenological stages using both object-based decision tree rulesets and traditional per-pixel strategies. Object-based decision tree classification of 2 pairs of SPOT-5 optical and L-Band ALOS SAR imagery yielded crop identification accuracy results comparable with hierarchically masked per-pixel classification, with corn classes regularly achieving high classification accuracies (+90%). Regardless of classification approach, results indicate that at least one complimentary date of optical imagery be used in combination with an mid- season optical/ SAR imagery pair to optimally classify northeastern Ontario agricultural landscapes.

This thesis consists of three essays on the economic effects of agricultural and non-agricultural trade. The first essay asks whether the observed low trade intensity of agricultural goods is caused by high trade costs or small gains from agricultural trade. By empirically estimating structural equations from a trade model, I find that it is largely due to high trade costs. I also find large variation in relative efficiency of producing agricultural goods, which suggests that lower agricultural trade costs could lead to large gains from trade. The second essay asks how large are the gains from lower trade costs in the presence of the "Food Problem". I extend the Eaton-Kortum trade model to include a tradeable agriculture sector, minimum consumption and home production of agricultural goods. The calibrated model implies much larger gains from trade for poor countries than prior studies. The main reason for these gains is that intra-sectoral trade leads poor countries to specialize in a set of agricultural goods with high efficiency and inter-sectoral trade enables them to reallocate labor to manufacturing, which often is their comparative advantage sector. The third essay quantitatively evaluates the potential impact of removing China's Hukou system, which restricts rural-urban migration in China, on the world economy. I find that removing Hukou could increase China's income by 4.7%, and would substantially impact some of China's small neighboring economies. This is because removing Hukou increases the relative price of agricultural goods, which benefits net agricultural exporters such as Thailand and hurts net agricultural importers such as Sri Lanka and Bangladesh.

In this thesis, novel methodology is developed to extract surface parameters under vegetation cover and to map crop types, from the polarimetric Synthetic Aperture Radar (PolSAR) images over agricultural areas. The extracted surface parameters provide crucial information for monitoring crop growth, nutrient release efficiency, water capacity, and crop production. To estimate surface parameters, it is essential to remove the volume scattering caused by the crop canopy, which makes developing an efficient volume scattering model very critical. In this thesis, a simplified adaptive volume scattering model (SAVSM) is developed to describe the vegetation scattering as crop changes over time through considering the probability density function of the crop orientation. The SAVSM achieved the best performance in fields of wheat, soybean and corn at various growth stages being in convert with the crop phenological development compared with current models that are mostly suitable for forest canopy. To remove the volume scattering component, in this thesis, an adaptive two-component model-based decomposition (ATCD) was developed, in which the surface scattering is a X-Bragg scattering, whereas the volume scattering is the SAVSM. The volumetric soil moisture derived from the ATCD is more consistent with the verifiable ground conditions compared with other model-based decomposition methods with its RMSE improved significantly decreasing from 19 [vol.%] to 7 [vol.%]. However, the estimation by the ATCD is biased when the measured soil moisture is greater than 30 [vol.%]. To overcome this issue, in this thesis, an integrated surface parameter inversion scheme (ISPIS) is proposed, in which a calibrated Integral Equation Model together with the SAVSM is employed. The derived soil moisture and surface roughness are more consistent with verifiable observations with the overall RMSE of 6.12 [vol.%] and 0.48, respectively.

Urban surface temperatures are important variables in urban climatological processes. This thesis examines the directional variability of remotely sensed urban surface temperatures (thermal anisotropy or Λ) for three vegetated residential neighbourhoods in Salt Lake City, Utah, USA. Airborne thermal remote sensing using a thermal imager sampled the directional brightness temperature (DBT) at three times within a day for each site. Results indicate that temporal variability over a 20 – 30-minute flight was not negligible. Average DBT were then extracted from atmospherically corrected images and plotted on polar plots. For low density residential neighbourhoods Λ is increased with increasing tree-canopy coverage (λtree) due to the increased temperature contrast. The ΛMax for the sites with large λtree were ~8°C compared to ~6°C for the site with sparse λtree. These results indicate Λ for low density residential neighbourhoods is significant and must be considered when discussing land surface temperatures for similar sites.