Search Results (2)

Due to climate change, situations that threaten humanity, such as temperature increases, drought, forest fires, sea level rise, erosion, floods, and migrations, are gradually increasing. Understanding climate change has gained more importance day by day due to the negative effects of disasters. Quantitative spatial analyses were carried out with the help of Remote Sensing (RS) and Earth Observation (EO) technology using Geographic Information Systems (GIS) by establishing an Internet of Things (IoT) Meteorological Station (IoT-PWS) with Erasmus+ support. The dataset consists of Road, Meteorological Station, Climate (Temperature, Wind Speed), Land Use—Land Cover (Copernicus LULC), and Population data. As a result of the findings of the research, it was determined that IoT-PWS has a positive contribution to many areas such as agriculture, traffic, scientific studies, local administration, and local public information in the region, and the positive contribution will continue as the station data flow continues. The study is designed as a guide to the use of GIS, RS, and EO technology for educators working on curriculum renewal and project implementation in the field of Environment and Combating Climate Change, one of the four key priorities of Erasmus+. The study contributes indirectly to all indicators in the Sustainable Development Goals as well as directly contributes to Goal 11, Goal 13, and Goal 15. Full article

A new macroscopic traffic system is devised that observes the transition distance between the vehicles and driver sensitivity during traffic evolution. The driver sensitivity in this system is based on the traversed time over a 200 m road section and speed (velocity). In addition, the proposed system considers the safe distance headway as the distance between vehicles changes. An analogy system for vehicle flow behavior is devised from a spring–mass system with changes in traffic. The proposed system can characterize traffic evolution for small and large changes in density. Furthermore, the changes in the travel of traffic rearwards during congestion and forward during smooth flow are dependent on driver sensitivity, transition distance, and safe distance headway. The proposed traffic system is hyperbolic. The Payne Whitham traffic system is based on uniform constant velocity for different conditions, which characterizes traffic evolution unrealistically. The proposed traffic system and the Payne Whitham system are assessed over a 2000 m circular road for large changes in density in two examples. Both the Payne Whitham and proposed traffic systems are numerically implemented with the first order centered scheme in Matlab. The discretization stability of both systems is enforced with the Courant–Friedrich–Levy (CFL) condition. The proposed system with lower driver sensitivity evolves with larger changes, whereas the proposed system with larger density has smaller changes in density and velocity. The simulation results showed that the traffic evolution with the proposed system is more appropriate than with the Payne Whitham system. Full article