Explore the vast range of titles available.

Natural landslide dams pose severe hazards when they fail, and understanding their breach processes remain challenging because such events are rarely observed directly in the field. To address this gap, we conducted large‐scale overtopping experiments with compacted (CP) and non‐compacted (NCP) dams, supported by a synchronized multi‐sensor framework that combined UAV and ground‐based photogrammetry, particle tracking velocimetry, water level gauges, autonomous scouring particles, and seismic monitoring. In situ density tests confirmed that CP dams had higher dry bulk volumetric weight and lower water content (2.33 t/m3, 4.9%) than NCP dams (2.04–1.98 t/m3, 6.8%–4.4%), corresponding to compaction levels of ∼104% for CP and 88%–89% for NCP. The multi‐sensor observations captured both surface and subsurface processes throughout failure, revealing that CP dams breached rapidly with sharp peak discharges and narrow, deeply incised channels, whereas NCP dams breached more gradually, producing flatter hydrographs and wider, shallower channels. Despite these differences, the underwater cross‐sections consistently evolved toward parabolic geometries. In addition, several characteristic signatures were observed across data sets, including concentrated velocity jets in CP versus dispersed flows in NCP, and V‐shaped seismic spectrograms observed during the processes of incision and widening. Because these experiments are approximately five times larger than typical laboratory flume studies, they captured scale‐dependent behaviors not observable in smaller facilities, including slower incision rates, later peak discharges, and more gradual hydrograph development at larger scale. These findings clarify how compaction and scale jointly influence breach timing and erosion pathways and provide physically grounded constraints for improving numerical breach models and hazard assessments.

As housing prices are largely affected by location characteristics, the failure to consider the spatial dependence of housing prices may result in overvaluation. In view of this issue, the first objective of this study was to combine the difference-in-difference and spatial econometrics methods to estimate the impact of urban renewal on neighborhood housing prices. The second objective of this study was to estimate and compare the impact of urban renewal on neighborhood housing prices by dividing the urban renewal process into two phases, with the aim of observing whether expectations prior to the completion of urban renewal can have an impact on housing prices. The empirical results indicated that the influence of urban renewal was found to have already caused a continuous response in terms of neighborhood housing prices even prior to the completion of reconstruction.

Earth dams or embankments are susceptible to instability due to internal seepage, piping, and erosion, which can lead to catastrophic failure. Therefore, monitoring the seepage water level before the dam collapses is an important task for early warning of dam failure. Currently, there are hardly any monitoring methods that use wireless underground transmission to monitor the water content inside earth dams. Real-time monitoring of changes in the soil moisture content can more directly determine the water level of seepage. Wireless transmission of sensors buried underground requires signal transmission through the soil medium, which is more complex than traditional air transmission. Henceforth, this study establishes a wireless underground transmission sensor that overcomes the distance limitation of underground transmission through a hop network. A series of feasibility tests were conducted on the wireless underground transmission sensor, including peer-to-peer transmission tests, multi-hop underground transmission tests, power management tests, and soil moisture measurement tests. Finally, field seepage tests were conducted to apply wireless underground transmission sensors to monitor the internal seepage water level before an earth dam failure. The findings show that wireless underground transmission sensors can achieve the monitoring of seepage water levels inside earth dams. In addition, the results supersede those of a conventional water level gauge. This could be crucial in early warning systems during the era of climate change, which has caused unprecedented flooding events.

This study examined the impact of urban renewal delineation time on housing prices in neighborhoods undergoing urban renewal. More specifically, the study used the difference-in-difference method to assess successful housing transactions in Taipei City from 2008 to 2011. According to the empirical results, before the implementation of urban renewal, the average housing price in the areas that later underwent urban renewal (the treatment group) was lower than that in neighborhoods that did not undergo urban renewal (the control group) by 11,180 NTD. After the urban renewal projects were publicly announced, the price per ping of the control group was increased by 148,800 NTD, while the price per ping of the treatment group was increased by 163,680 NTD. This means that the housing prices per ping in the urban renewal areas were increased by 14,880 NTD more than the housing prices per ping in the areas not affected by urban renewal after the urban renewal projects were publicly announced. This increase, then, indicates the value added after implementation of urban renewal delineation time on houses in the neighborhood. Therefore, research into the impact of urban renewal on housing prices should be concerned not only with the neighborhood factors or time factors of urban renewal delineation. Rather, the two types of factors should be considered at the same time.

This study explored the impacts of urban renewal projects on neighboring housing prices. Hierarchical linear modeling (HLM) was employed to analyze urban renewal projects in Taipei City. The Level 1 independent variables pertained to a house itself (19,157 pieces of data), such as its structure and neighborhood attributes. The Level 2 variable pertained to an urban renewal project (23 cases of urban renewal), and the explanatory variable was the scale of each urban renewal project. The study examined whether differences exist between the impacts of various urban renewal projects on neighboring housing prices, and analyzed the extent to which the differences in neighboring housing prices are caused by the differences between urban renewal projects. The empirical results showed that the mean housing price varies significantly between each urban renewal project. In regard to the variance in the mean house price, 31.46% was caused by the differences between the urban renewal projects. The estimated coefficient of the grand floor area of urban renewal (FLAREA) had a positive value and attained a 1% level of significance. This indicates that the larger the scale of an urban renewal project, the larger its effects on neighboring housing prices. The empirical results of this study could better explain the impacts of the scale of an urban renewal project on the externalities of urban renewal. First published online 17 January 2022

In Taiwan, many housing transactions are special relationship-based transactions that involve family and friends, debt relations, urgent purchases and sales, and government agencies. As such, the prices in such transactions should differ from those in what we consider to be normal arm’s length transactions. In this regard, social capital theory can be used to analyze these transactions. The empirical data on housing transactions conducted in Taipei City from January 1, 2012 to December 31, 2018 were collected for this study. The empirical results showed that the prices in transactions involving debt relations and urgent purchases and sales were 22.6% lower than those in normal arm’s length transactions. The prices in transactions with government agencies were 48.9% lower than those in normal arm’s length transactions. The prices in transactions with first-degree, second-degree, and third-degree relatives were respectively, 57.3%, 53.1%, and 50.3% lower than those in normal arm’s length transactions. The prices in transactions involving friends were 28.0% lower than those in normal arm’s length transactions. The empirical results highlight the importance of the impacts of personal relationships or social relations on housing prices in special relationship-based transactions. The results also supported the social capital hypothesis.

Large woody debris (LWD) strongly influences river systems, especially in forested and mountainous catchments. In Taiwan, LWD are mainly from typhoons and extreme torrential events. To effectively manage the LWD, it is necessary to conduct regular surveys on river systems. Simple, low cost, and accurate tools are therefore necessary. The proposed methodology applies image processing and machine learning (XGBoost classifier) to quantify LWD distribution, location, and volume in river channels. XGBoost algorithm was selected due to its scalability and faster execution speeds. Nishueibei River, located in Taitung County, was used as the area of investigation. Unmanned aerial vehicles (UAVs) were used to capture the terrain and LWD. Structure from Motion (SfM) was used to build high-resolution orthophotos and digital elevation models (DEM), after which machine learning and different color spaces were used to recognize LWD. Finally, the volume of LWD in the river was estimated. The findings show that RGB color space as LWD recognition factor suffers serious collinearity problems, and it is easy to lose some LWD information; thus, it is not suitable for LWD recognition. On the contrary, the combination of different factors in different color spaces enhances the results, and most of the factors are related to the YCbCr color space. The CbCr factor in the YCbCr color space was best for identifying LWD. LWD volume was then estimated from the identified LWD using manual, field, and automatic measurements. The results indicate that the manual measurement method was the best (R2 = 0.88) to identify field LWD volume. Moreover, automatic measurement (R2 = 0.72) can also obtain LWD volume to save time and workforce.

This study adopts the hierarchical linear growth modeling approach to analyze the differences in the changes of repeat-sales house prices in Kaohsiung City from 2012 to 2020. The Level 1 time-varying factors include house age and the time of repeat-sales; the Level 2 factors include house attributes such as house area, house type, and house location. Based on the results of the null model, the estimated variance is 0.42816, with a 1% level of significance. This shows that significant differences exist in the mean repeat-sales prices between houses. The interclass correlation coefficient is 91.65%, showing that the interclass variation and intraclass variation of the mean repeat-sales prices are 91.65% and 8.35%, respectively. The estimation results of the non-randomly varying slope model indicate that the sales time and sales time squared significantly affect repeat-sales prices. The annual growth rate and quadratic growth of sales prices do not differ by house type (luxury condominiums and apartment buildings) but are affected by house area and house location. The effect of house age on repeat-sales prices is moderated by house area, house type, and house location.

This study investigated the spatial spillover effects of luxury housing during and after construction, in regards to increases in housing prices in neighboring areas as well as the spatial dependence of neighboring housing. This study focused on already completed luxury housing in Taipei, Taiwan. First, the nearest-neighbor matching approach of propensity score matching was used to overcome the problem of data heterogeneity. The difference-in-differences (DD) method and spatial econometrics were used for analysis. The empirical results indicated that the spatial error model had the best goodness of fit. This indicated that housing prices increased by 13.0% during construction of luxury housing nearby. This indicated that housing prices increased by 5.8% after the construction of luxury housing nearby. The empirical results showed that the ongoing and completed construction of luxury housing had spillover effects on housing prices. The effect of ongoing construction of luxury housing was particularly large in scope, indicating its role as a predictor of psychological reaction in the market.

Taiwan’s declining birthrate has changed the housing market, which should become more consumer-oriented in the future. In particular, age-friendly housing has become a salient housing choice among buyers. Age-friendly housing consists of housing units that are suitable for occupants of any age. There are three concepts underlying such housing: aging in place, multigenerational-multiunit living arrangements, and lifetime homes. This study aimed to examine the factors affecting consumers’ choice of age-friendly housing. The participants were residents of Kaohsiung City, and data analysis was performed using a binary logistic model. The empirical results indicated that adult sons/daughters, residents who currently live in the city center, residents who have a high or medium monthly family income, residents who are currently part of a stem family, residents who desire to live under multigenerational-multiunit living arrangements, residents who desire to be a part of a stem family, and residents who prioritize housing type when house-buying are significantly more likely to choose age-friendly housing. These results can serve as a reference regarding age-friendly housing investments for investors, as well as for house buyers who are deliberating between age-friendly housing and ordinary housing.