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Previous housing price studies based on hedonic price modeling have mainly focused on applying various factors, including built environment variables in the analysis, without establishing a comprehensive theoretical framework as a basis for the model formulation. To address this gap, this study introduces a more systematic framework for decomposing housing prices into land prices as determined by built form, neighborhood socioeconomic characteristics and individual dwellings' physical conditions. Following this logic, this study experiments with the related variables through regression analysis, including consideration of spatial lags, as well as develops a housing price model using a random forests (RF) algorithm. A comprehensive time-series database of housing transaction data for the City of Toronto is used. Modeling results show that neighborhood socioeconomic factors contribute the most to the explanation of housing prices, while housing characteristics and accessibility measures are also significantly influential. The RF model achieves an overall accuracy of 85%, a relatively good performance in reproducing observed prices. The findings provide insights for planners concerning factors influencing housing prices and, hence, residential location decision-making. [ABSTRACT FROM AUTHOR]

This study analyzed the low irrigation water use efficiency (IWUE) on the Sanjiang Plain. To do so, we established IWUE as the dependent variable and rainfall, evapotranspiration, and ten other factors as independent variables in a stepwise regression model to globally analyze the factors that influence IWUE. Based on this model, we locally analyzed the factors that influence IWUE with a geographical weighted regression (GWR). The results showed that the average temperature and crop yield were not significantly correlated with IWUE; however, rainfall, evapotranspiration, the canal system lining rate, the irrigation facility intact rate, and the irrigation equipment rate were positively correlated with IWUE. Additionally, the paddy field area ratio, canal system complexity, and irrigation water quantity were negatively correlated with IWUE. IWUE and its influencing factors exhibited different degrees of spatial autocorrelation on the Sanjiang Plain, and the spatial heterogeneities of three variables (IWUE, evapotranspiration, and the canal system lining rate) were particularly high. In the local analysis, the spatial distributions of the regression coefficients of each influencing factor illustrated the influence of each factor on the IWUE in different territories. These results provide a scientific basis for improving the IWUE on the Sanjiang Plain. [ABSTRACT FROM AUTHOR]

Shallow water bathymetry is critical in understanding and managing marine ecosystems. Bathymetric inversion models using airborne/satellite multispectral data are an efficient way to retrieve shallow bathymetry due to the affordable cost of airborne/satellite images and less field work required. With the increasing availability and popularity of unmanned aerial vehicle (UAV) imagery, this paper explores a new approach to obtain bathymetry using UAV visual-band (RGB) images. A combined approach is therefore proposed for retrieving bathymetry from aerial stereo RGB imagery, which is the combination of a new stereo triangulation method (an improved projection image based two-medium stereo triangulation method) and spectral inversion models. In general, the inversion models require some bathymetry reference points, which are not always feasible in many scenarios, and the proposed approach employs a new stereo triangulation method to obtain reliable bathymetric points, which act as the reference points of the inversion models. Using various numbers of triangulation points as the reference points together with a Geographical Weighted Regression (GWR) model, a series of experiments were conducted using UAV RGB images of a small island, and the results were validated against LiDAR points. The promising results indicate that the proposed approach is an efficient technique for shallow water bathymetry retrieval, and together with UAV platforms, it could be deployed easily to conduct a broad range of applications within marine environments. [ABSTRACT FROM AUTHOR]