Trackers installed in vehicles gives insights into many useful information and predict future mobility patterns and other aspects related to vehicles movement which can be used for smart and sustainable cities planning. A novel approach is used with the COPERT model to estimate fuel consumption on a huge dataset collected over a period of one year. Since the data size is enormous, Apache Spark, a big data analytical framework is used for performance gains while estimating vehicle fuel consumption with the lowest latency possible. The research presents peak and off-peak hours fuel consumption’s in three major cities, i.e., Karachi, Lahore and Islamabad. The results can assist smart city professionals to plan alternative trip routes, avoid traffic congestion in order to save fuel and time, and protect against urban pollution for effective smart city planning. The research will be a step towards Industry 5.0 by combining sustainable disruptive technologies.

Developing countries with hard pressed economies and a rapidly growing population have a myriad of issues to face. Karachi is one of the largest cities of Pakistan and is rapidly growing. The city has been hit by floods in the year 2016, 2018, 2019 and 2020, recently. Since the early 1990s Karachi has seen a rapid spike in development and in the process many natural streams have been built over. This has led reduced space for rainwater runoff and has created problems for urban flood managers. To ascertain this, topographic records of 1940s and 1980s and Landsat imagery of 2000, 2008, 2015 and 2020 were used to map historical urban extent. Sentinel—1, Synthetic Aperture Radar (SAR) imagery was used to extract flooded areas during 2015, 2017, 2019 and 2020 floods. In the year 2020, 64.3 km² of area was flooded which was the highest. There has been a growth of 286% in urban area observed between 1980 and 2000. The city was built with several natural flood water carrying streams, north and west of it. It was found that that out of 3600 km of these streams, 870 km of streams have either been blocked or removed and a 100% in core urban area. DEM of difference (DOD) prepared by subtracting 1945 DEM from SRTM DEM indicated that most of embankments along these streams were in the areas that show erosion in DOD surface, thus explaining the expansion of built areas along historical stream channels. Forcing floods to enter these built areas.

Rapid urban growth necessitates focused attention regarding its policy and governance to ensure affordable housing, transparent and efficient real-world systems, reduce social inequalities, and promote sustainable development. This study delves into the semantics and ontology for developing a Land Administration Domain Model (LADM) profile in the context of Pakistan’s Land Administration Systems (LASs), which currently face issues due to manual record-keeping, lack of transparency, frauds, and disintegration. Establishing a baseline through Record of Rights (RoR) and Property Information Report (PIR), alongside surveying and mapping procedures defined by laws and rules, forms the foundation for LADM profile development. This study explores the transition from manual LAS to 2D/3D representation, using LADM as a conceptual guideline. The LADM profile’s three key packages—PK_Party, PK_Administrative, and PK_SpatialUnit—a sub-package, and external classes are examined, with proposals for digitalisation and modernisation. Additionally, the study includes expert consultation, and highlights the significant support that the LADM implementation offers to achieve Sustainable Development Goals (SDGs) in Pakistan. In conclusion, the study underscores the need for a comprehensive and inclusive approach to address organisational overlaps and ambiguities within LAS, positioning PK LADM as a transformative force for sustainable urban LAS in Pakistan, aligning with broader SDGs. Recommendations include exploring realistic land valuation, integrated ownership and location verification systems, addressing historical survey data challenges, and promoting wider stakeholder adoption for sustainable 2D/3D urban LAS using LADM and its edition II as a way forward towards the creation of a smart city and digital twin.

Drones are a valuable tool in flood response, providing high-resolution data and real-time monitoring capabilities. However, their limited range, swath, and battery life make it challenging to cover extensive flood-prone areas. This study addresses these limitations by introducing the drone-optimized flood risk map (DOFRM) framework, integrating drones with geographic information systems (GIS) and multi-criteria decision model to prioritize survey areas. The approach leverages analytical hierarchy process (AHP) to rank high-priority zones for effective drone survey and disaster response. The study evaluated 178 drones to identify an optimal survey grid size of 1.2 × 1.2 km for efficient drone operation. This grid was placed over a flood risk map, which is a combination of various hazard and vulnerability factors, with each factor given a weight based on AHP criteria. DOFRM revealed that 17% of the region was highly susceptible to flooding. This high-risk area was further divided based on the critical regions: urban areas (3%), active channels (5%), roads (6%), rail networks (1%), stream networks (3%), and populated areas (9%). DOFRM was perceived effective and easier to use through technology acceptance model-based stakeholder’s survey. The framework enables prioritized drone deployment during large-scale flood events by optimizing resources for rapid assessment of vulnerable areas. By combining AHP-based prioritization with a GIS-based drone-optimized grid, the approach offers a systematic solution for flood risk mapping and disaster mitigation. This innovative framework enhances targeted flood surveys, enabling drone operations more effective and responsive to surveying needs.

This paper investigates the impact of tube wells on the discharge and water table of the Quetta Valley aquifer and conducts a financial analysis of the solar photovoltaic water pumping system (SPVWP) in comparison with a typical pumping system for the Water and Sanitation Agency of Quetta’s (WASA) tube wells. Quetta Valley is dependent on groundwater as surface resources are on decline and unpredictable. The population of this city has exponentially increased from 0.26 million in 1975 to 2.2 million in 2017 which has put a lot of pressure on the groundwater aquifer by installing more than 500 large capacity tube wells by WASA and Public Health Engineering (PHE) departments in addition to thousands of low-capacity private tube wells. The unprecedented running of these wells has resulted in drying of the historical Karez system, agricultural activities, and the sharp increase in power tariffs. There are 423 tube wells in operation installed by WASA in addition to PHE, Irrigation and Military Engineering Services (MES), which covers 60% of the city’s water demand. The results will be beneficial for organizations and positively impact the operation of these wells to meet public water demand. For the two zones, i.e., Zarghoon and Chiltan in Quetta Valley, recommendations are given for improved water management.