Urban Аnalytics. Private Cars Map

The topic of our last posts was “Urban Analytics module” and the tools it includes. One of the tools is “Road accidents” for revealing the road accidents hotspots.

Now let us introduce “Private cars map” tool. It is characterized by its main purpose: visualization of car density and their location in the city. Knowing the detailed information of this kind can be useful in many processes like planning the layout of parking spots or evaluating car-dependency level of the city.

When a polygonal object representing real-life objects like green spaces or lawns is stored in the system, it is possible to reveal areas where lawn parking violations take place.

But such information is not easy to obtain. The proposed method for solving the problem is based on computer vision technology. The neural network takes orthophotomaps or high-resolution satellite images and distinguishes vehicles on it, classifying each as a car or a truck. A centroid is then assigned to each vehicle as its representation in the system.

Location of cars on the city map

As a result, thematic data layer is created that can be interpreted by GIS tools. Use cases include comparing with other objects of the system to solve real-life issues.

The accumulation of historical data in the system with new relevant orthophotomaps becoming available will help to see the dynamics of the situation.

The tool also allows you to calculate the density of cars in each point of the city and display the results of the calculation on the map. Following map shows distribution of cars and cars clusters around the city.

map shows distribution of cars

Another developed feature is identification of residential areas with overcrowded parking lots.

Car congestion in courtyards

Announcing the topic of next time: the “Number of residents” tool.

You can read about all the features of the Urban Analytics module in our article.

Urban Аnalytics. Road Accidents

This year, we launched the Urban Analytics module, which helps make decisions about the future of the urban environment using measurable data. The module has six tools in total, and today we highlight the one that will save lives, it is called “Road accidents”.

Reducing road traffic fatalities, as well as reducing accident-prone sections on the road network, are important national objectives. They are declared among the priority goals of the Safe and High-Quality Roads project in Russia, which is aimed at creating a comfortable and safe living environment.

We rose to the challenge and we made a cartographic analytical service that would allow us to visualize road accidents, their hotspot locations, the causes and dynamics of their changes over time. This information will help to prioritize when working on the development or reconstruction of the road network.

Another benefit is that it gives valuable insights on the measures taken to improve traffic safety. Imagine city management puts a new road sign, traffic light or a pedestrian island by the road, or maybe reconstructs the road itself. Find out if these measures took the expected effect and reduced the number of accidents

With the help of the “Road accidents” tool, you can easily find the most problematic sections of the city’s road network in terms of safety, focus on them and find effective solutions.

What features go with the tool?

User can choose object and display its record with attributes of each accident: the date of the accident, the category of the accident, the number of injured, the number of deaths, the severity of the accident, the weather conditions at the time of the accident, or whether pedestrians were involved. Filter can be applied by any of listed attributes to show only filtered accidents on the map:

Road accidents on the map

With the help of the tool, it is possible to find the hotspots of accidents for a given period of time (orange symbols) and accidents involving pedestrians (dark gray symbols). The map shows the proportion of accidents involving pedestrians in each of the accident hotspot:

Road accidents locations

The tool also highlights the concentration of accidents in terms of severity and harm to health: bright pink symbols show severe accidents. Here you can also see the proportion of severe accidents in relation to minor ones:

Concentration of road accidents on the map in terms of severity and injury

Another feature is a comparison map showing change in the number of accidents relative to the same time of year in the past. The user provides input of two time periods, and the system shows if number of accidents has increased or decreased in each part of the city. The size of the arrows is proportional to the number of accidents:

The map of changes in the number of accidents

Thus, the “Road accidents” tool makes it possible to find out details about specific accidents, their concentration in different parts of the city and compare data with the same time of the year in the past. In the next article, we will talk about the “Private cars density” tool, which helps our users get information about how cars are distrubuted around the city.

You can read about all the features of the Urban Analytics module in our article.

Creation of the Information System for Management of a Million-plus City

The integrated municipal geoinformation system of Kazan city, created on the basis of Geometa, is designed to solve the city problems associated with the processing of spatial data. This is a single source of comprehensive information about the territory.

The system allows the leadership of Kazan city in a convenient and understandable form to receive up-to-date information on the state of the urban environment and on the administration of land resources, visualize the city needs, help to make decisions on infrastructure development and to determine the necessary amount of funding for municipal programs and city projects.

The system is used by investors interested in business development in Kazan. They receive legitimate information about the possibility of implementing their projects. Thus the system contributes to the investment attractiveness of the city.

Moreover, the system contributes to the reduction of mandatory procedures terms in construction, helps to synchronize the plans of conducted works, which leads to savings in investment and budgetary funds. Construction is a high-budget area of activity where the optimization of resources is extremely important.

The system contains full functionality to support urban planning activities: characteristics of all capital construction projects, documents, data on urban planning, zoning, information on land parcels and land rights. To date, 100% of municipal services related to construction are automated through the system.

Kazan


The development of the system continues, its functionality is expanded by analytical tools that visualize various aspects of managing the processes of city territory modernization. Data on the population number and density is compared with data on the location of social, recreational, and transport infrastructure facilities to identify the points of greatest unmet demand for urban facilities.

Calculable, quantitative indicators allow to reduce managerial errors since decisions are made based on data, not just on experts’ opinion.

In a city with a population of one million, there are a huge number of control objects, they are interdependent. So the effective city management is an extremely non-trivial task. Modern cities compete with one another to attract the best minds, talents, businesses and capital, and it will not be possible to win the competitive race without the help of advanced technologies.

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