The degradation of pastures and meadows is a global problem with a wide range of impacts. It affects farmers in different ways, such as decreases in cattle production, milk yield, and forage quality. Still, it also has other side effects, such as loss of biodiversity, loss of resources, etc. In this study, the degradation of a semi-natural pasture near the village of Obichnik, Bulgaria, was evaluated using machine learning algorithms, and an unmanned aerial vehicle (UAV) obtained visual spectrum images. A high-quality (HQ) orthomosaic of the area was created and numerous regions of interest were manually marked for training and validation purposes. Three machine learning algorithms were used—Maximum likelihood, Random trees (RT), and Support Vector Machine (SVM). Furthermore, object-based and pixel-based approaches were utilized. The obtained results indicate that the object-based RT and SVM models provide significantly better accuracy, with their Cohen’s Kappa reaching 0.86 and 0.82, respectively. The performed classification showed that approximately 61% of the investigated pasture area is covered with grass, which indicates light-to-medium degradation.

This article presents the results of experimental studies of harmful components contained in the exhaust gases from internal combustion engines in cars. The exp

Density is important characteristic of traffic flows which inform how many vehicles occupying a stretch of road of unit length at a given instant. Its quantity Density is important characteristic of traffic flows which inform how many vehicles occupying a stretch of road of unit length at a given instant. Its quantity

Over the past 30–40 years, vehicle tailpipe emissions of particulate matter (PM), nitrogen oxides (NOx), carbon monoxide (CO), and hydrocarbons (HCs) have decreased significantly. Advanced emission after-treatment technologies have been developed for gasoline and diesel vehicles to meet increasingly stringent regulations, yielding absolute emission reductions from the fleet despite increased vehicle travel. Passenger cars are an important source of air pollution, especially in urban areas. Recently, real-driving emissions (RDE) test procedures have been introduced in the EU aiming to evaluate nitrogen oxides (NOx) and particulate number (PN) emissions from passenger cars during on-road operation. Although RDE accounts for a large variety of real-world driving, it excludes certain driving situations by setting boundary conditions (e.g., in relation to altitude, temperature or dynamic driving). The present work investigates the on-road emissions of NOx, NO2, CO, particle number (PN) and CO2 from a vehicles, including diesel, gasoline, liquid petroleum gas (LPG) and compressed natural gas (CNG) vehicles. The vehicles were tested under different on-road driving conditions outside boundaries. These included ‘baseline’ tests, but also testing conditions beyond the RDE boundary conditions to investigate the performance of the emissions control devices in demanding situations.

Green time period optimization is essential issue about delay time reduction at signalized intersection. The features of traffic flows are variables in rush and other period of day. Optimal values of green time are that guarantee minimum of delay time. It can be accepted that the values that guarantee that in rush period is can be use in others periods of day. The main issue is being considered in paper is green time period optimization at signalized intersection for minimum delay time according to traffic flows features in rush period. That include comparison between three options of movement diagram and two option of phases for the chosen intersection in Town of Pernik. The application of result will make a lot of benefits both for the traveling and for the environment.

The study of traffic parameters in cities is the basis for making adequate decisions related to the organization and regulation of traffic. This publication presents a study of one of the main parameters of transport flows, namely, its intensity. The study covers one of the busiest streets in the city of Sofia, which is part of the radial connection in the radial circular street network of the city, for the evening peak period of the day. Data analysis presents the influence of the intensity of transport flows at the intersections, which are formed by the intersection with other streets, on the load of the studied street. The share of the load of each transport flow at the individual intersections on the total load of the studied section was recorded for the subsequent assessment of the existing traffic management. The results have been provided to the relevant directorates in the structure of Sofia Municipality for information and use.