Software-defined traffic light preemption for faster emergency medical service response in smart cities.

Proper management of rescue operations following an accident is one of the most fundamental challenges faced by today's smart cities. Taking advantage of vehicular communications, in this paper we propose novel mechanisms for the acceleration of the rescue operation resulting in a reduction in fatalities in accidents. We propose a Software-Defined Traffic Light Preemption (SD-TLP) mechanism that enables Emergency Medical Vehicles (EMVs) to travel along the rescue route with minimal interruptions.

Geomorphological evolution along international riverine borders: The flow of the Aras River through Iran, Azerbaijan, and Armenia.

International rivers are one of the most politicized natural resources. Their dynamism, whether driven by the influence of natural processes or artificial drivers, can generate political issues between countries where de river is the common boundary. The present study has tried to discern the role of international riverine borders as a limiting factor of their dynamics from a geomorphological point of view.

Spatial and temporal analysis of urban heat island using Landsat satellite images.

The average land surface temperature (LST) of Earth has increased since the late nineteenth century due to the warming of the Earth's atmosphere. Increased surface temperatures, especially in cities, are a significant environmental problem that intensifies urban heat islands (UHIs). In this study, land surface temperature, urban thermal field variance index (UTFVI), and UHI index were mapped using Landsat 4, 5, 7, and 8 satellite images to identify the distribution and determine the intensities of the UHI.

Assessing the susceptibility of schools to flood events in Iran.

Catastrophic floods cause deaths, injuries, and property damages in communities around the world. The losses can be worse among those who are more vulnerable to exposure and this can be enhanced by communities' vulnerabilities. People in undeveloped and developing countries, like Iran, are more vulnerable and may be more exposed to flood hazards.

A machine learning framework for multi-hazards modeling and mapping in a mountainous area.

This study sought to produce an accurate multi-hazard risk map for a mountainous region of Iran. The study area is in southwestern Iran. The region has experienced numerous extreme natural events in recent decades.

Assessing, mapping, and optimizing the locations of sediment control check dams construction.

Check dams are considered to be one of the most effective measures for conservation of the soil and water resources. However, identifying the most suitable sites for the installation of check dams remain quite demanding. This research investigates and compares five machine learning algorithms (MLAs) - boosted regression trees (BRT), multivariate adaptive regression spline (MARS), mixture discriminant analysis (MDA), random forest (RF), and support vector machine (SVM) - for generating check-dam site-suitability maps (CDSSMs) and assessing them in Firuzkuh County, Iran.

Using machine learning algorithms to map the groundwater recharge potential zones.

Groundwater recharge is indispensable for the sustainable management of freshwater resources, especially in the arid regions. Here we address some of the important aspects of groundwater recharge through machine learning algorithms (MLAs). Three MLAs including, SVM, MARS, and RF were validated for higher prediction accuracies in generating groundwater recharge potential maps (GRPMs).

Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling.

Gully erosion is identified as an important sediment source in a range of environments and plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing spatial occurrence pattern of this phenomenon is very important. Different ensemble models and their single counterparts, mostly data mining methods, have been used for gully erosion susceptibility mapping; however, their calibration and validation procedures need to be thoroughly addressed.

Interplay between river dynamics and international borders: The Hirmand River between Iran and Afghanistan.

Fluvial dynamics in riverine borders can play an important role in political relationships between countries. Rivers move and evolve under the influence of natural processes and external drivers (e.g.

Accuracy assessment of land cover/land use classifiers in dry and humid areas of Iran.

Land cover/land use (LCLU) maps are essential inputs for environmental analysis. Remote sensing provides an opportunity to construct LCLU maps of large geographic areas in a timely fashion. Knowing the most accurate classification method to produce LCLU maps based on site characteristics is necessary for the environment managers.