Pakistan has been a victim of earthquakes from time to time. A reliable quantification of seismic hazard is important to reduce the life and economic losses in future. This paper presents the details of probabilistic seismic hazard analysis for Pakistan which was conducted to determine ground motion parameters required for the design of structures. A seismicity model comprising areal sources and fault systems was employed for modelling earthquake activity. The country was divided into several areal zones considering the spatial and temporal distribution of earthquakes which was documented with the help of a catalogue. A number of faults and fault systems were also included in the analysis. Two types of Poissonian models were used to model earthquake recurrence for the areal and lines sources separately. Existing attenuation relationships in the literature were employed to relate the seismicity with the distance. The analysis was carried out using a commercial computer programme and hazard curves were determined for different return periods and spectral periods for response spectral acceleration. A seismic zonation map for Pakistan was developed for the quantification of seismic loading. Uniform hazard spectra were calculated and were compared with the design spectra in the existing code which indicated differences between the two types of spectra.

The development of smart cities relies on the implementation of cutting-edge technologies. Unmanned aerial vehicles (UAVs) and deep learning (DL) models are examples of such disruptive technologies with diverse industrial applications that are gaining traction. When it comes to road traffic monitoring systems (RTMs), the combination of UAVs and vision-based methods has shown great potential. Currently, most solutions focus on analyzing traffic footage captured by hovering UAVs due to the inherent georeferencing challenges in video footage from nonstationary drones. We propose an innovative method capable of estimating traffic speed using footage from both stationary and nonstationary UAVs. The process involves matching each pixel of the input frame with a georeferenced orthomosaic using a feature-matching algorithm. Subsequently, a tracking-enabled YOLOv8 object detection model is applied to the frame to detect vehicles and their trajectories. The geographic positions of these moving vehicles over time are logged in JSON format. The accuracy of this method was validated with reference measurements recorded from a laser speed gun. The results indicate that the proposed method can estimate vehicle speeds with an absolute error as low as 0.53 km/h. The study also discusses the associated problems and constraints with nonstationary drone footage as input and proposes strategies for minimizing noise and inaccuracies. Despite these challenges, the proposed framework demonstrates considerable potential and signifies another step towards automated road traffic monitoring systems. This system enables transportation modelers to realistically capture traffic behavior over a wider area, unlike existing roadside camera systems prone to blind spots and limited spatial coverage.

Purpose This paper aims to present the studies which were carried out to determine building typology in Northern Pakistan, which is a seismically active region. Design/methodology/approach A total of 41 towns and cities were surveyed to collect the data of building types. Help was also taken from global positioning system and satellite imagery. Findings In total, 14 different types of buildings were identified in the region based on the structural system and combination of wall and roof materials; each of them was assigned an appropriate designation. The walls in these buildings were made of block, stone or brick, whereas the roof consisted of corrugated galvanised iron sheet, thatched roof, precast concrete planks or reinforced concrete (RC). Only 6 per cent buildings were found to be engineered RC buildings; this indicates a significance proportion of non-engineered building stock in Northern Pakistan. Research limitations/implications The surveys were conducted in some of the selected areas. Other areas are beyond the scope of this work. Practical implications The presence of a huge deficient building stock in Pakistan indicates a major seismic risk. The seismic losses are largely dependent on the earthquake resistance of existing buildings and building stock. An inventory of existing buildings and their types can help in assessing seismic vulnerability of the built environment, which may lead to the development of policies for seismic risk reduction. Originality/value Presently, housing encyclopaedia does not exist in Pakistan. As a result, housing typology in the country is not known. The presented study addresses this gap in part. Housing typology surveys were conducted to study the typical construction practices in the selected areas and to determine the proportions of different building types in the overall building stock.