The main discussion is about methods for assessing the intensity of traffic flows using geoinformation technologies. The intensity of traffic flows is one of the key indicators that determine the emission from transport in urban areas. In Russia, the growth in the volume and share of motor transport in pollution is increasing under the influence of an increase in the number of cars. This is most obvious examples of it are regions of the Central Federal District, but in the regional centers, under the influence of the improvement in the structure of the vehicle park, the growth of pollution is much slower, and in Moscow it has practically stabilized. At the local level, the determining factor of road traffic pollution is the change in the building density and the transport-planning structure. The collection and calculation of indicators that give an idea of the spatial differentiation of emissions from road transport is a very time-consuming stage of the study. The most common method of obtaining information on the transport and environmental situation in the city is directly field data collection. However, this method is quite time consuming for research. In conditions when the transport infrastructure is developing rapidly, the speed of field observations does not allow promptly updating information on changes in the traffic load of the road network and, as a result, assessing the current ecological situation in the territory. As an alternative to the traditional collection of information, modern sources of geoinformation data can be used. The services, originally developed to provide operational monitoring of the traffic situation and the construction of optimal routes, can also serve as a source of data for models for assessing the intensity of traffic load in environmental studies. The proposed technique has been tested at the level of districts and administrative districts of Moscow. The results obtained are compared with control field observations. The relatively low measurement error when using data from information systems is compensated by the possibility of more efficiently obtaining information about the traffic load on the sections of the road network.
The article describes the assessment of the areas and spatial distribution of adjoining green spaces as one of the most vulnerable and low studied kind of green spaces in cities. Usually gardening near the residential houses is not legally regulated is being destroyed during the implementation of urban renovation projects. The characteristics of adjoining green spaces were assessed for the city of Nur-Sultan, where, on the one hand, natural properties make green spaces vulnerable, and on the other hand, the acquisition of capital functions increases the value for the urban environment. A large-scale assessment, carried out using unmanned aerial vehicles, has demonstrated its high efficiency in assessing the vertical and horizontal structure of adjacent green spaces and other elements of the city. As a result of aerial imagery sessions for representative key points, a series of orthophotomaps with the horizontal resolution of 3–4 cm and digital terrain models with a horizontal resolution of 3 cm and a vertical resolution of about 4 cm were obtained. These products provided possibility to identify 12 historically established morphotypes of urban buildings, characterized by different levels and types of adjacent landscaping. Using a three-dimensional model of green cover, the average size of the biomass and the density of biomass per 1 m2 of the area in the selected morphotypes of the building were calculated. Territorial differences of adjoining green spaces in the different morphotypes depend on the period of construction, distance from the river, types of the building and urban planning standards typical for the period of the morphotype forming. Losses of the adjoining green spaces during the implementation of the renovation program according to the modern General Plan, excluding restoration, for the city of Nur-Sultan, will be mor than 11.5 % (+/-3.5 %) of the city’s tree cover.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.