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Spatial Systems
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<a id="navigation-link" href="/city-modelling.html">РУ</a>
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<div class="fullpage">
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<div class="section gradient-text">
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<p>City-modelling ————— a geoinformation ML system for urban space modeling / digital master planning.</p>
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<p>Cities are developing faster every day. The vast amount of data accumulated by the city on population
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movement and visitor numbers to urban socio-economic infrastructure facilities makes it possible to
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create qualitatively new models and elevate the process of city management and development to a new
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level.</p>
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<p>To realize new opportunities in the digital development of Moscow, related to the accumulated urban data
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on visitor numbers to socio-economic infrastructure facilities, we have developed the geoinformation ML
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system City-modelling.</p>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/interface.jpg" />
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<figcaption>System Interface</figcaption>
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</figure>
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</div>
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<div class="section">
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<p>The system provides access to numerous layers with indicators that characterize the provision of
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territories with urban socio-economic infrastructure facilities, such as schools, swimming pools,
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clinics, etc. In total, the system presents 13 categories of facilities. </p>
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<p>Among the displayed indicators are: load on infrastructure facilities, population provision, total
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population provision, pedestrian accessibility, and potential for placement.</p>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/libraries.jpg" />
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<figcaption>Load on libraries and their pedestrian accessibility</figcaption>
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</figure>
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</div>
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<div class="section">
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<p>ML models, built on the basis of real retrospective data on facility visitor numbers and a variety of
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urban environment data, are used to calculate population demand. </p>
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<p>Based on data for planned renovation and the introduction of new commercial housing, all indicators are
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calculated several years in advance so that decisions can be made with future changes in mind.</p>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/clinics.jpg" />
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<figcaption>Load on adult clinics and their placement potential</figcaption>
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</figure>
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</div>
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<div class="section">
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<p>The main feature of the system is the ability to model urban space by performing simulations of the
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construction and demolition of infrastructure facilities or residential buildings and recalculating all
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indicators online based on these actions. </p>
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<p>The system can answer the question "what if?" in a few seconds. After studying the current situation with
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the distribution of provision indicators, you can start experimenting with changing the urban space. You
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can build a new school or a multifunctional center in areas with low provision and see what the load on
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the new facilities will be, how much the load on existing facilities will decrease, how much the
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provision for the local population will increase, and so on. </p>
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<p>For example, by selecting the Swimming Pools category, you can see the overload of existing facilities in
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the Severnoe Tushino district and, consequently, the high potential for placing new ones in this area of
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the city.</p>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/pools.jpg" />
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<figcaption>Overloaded swimming pools and their high potential for placement in the Severnoe and Yuzhnoe
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Tushino districts </figcaption>
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</figure>
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</div>
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<div class="section">
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<p>Let's build a new large swimming pool in the center of the Severnoe Tushino district, specifying its name
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and capacity. Within a few seconds, the indicators will update, taking into account the newly built
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facility. The load on the new pool will be 94%, the load on the two overloaded pools will normalize, and
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the situation in the district related to the pool deficit will stabilize. </p>
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<p>During such a simulation, the data for each cell and each pool point is first updated based on the
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changes made by the user. Then, the previously trained ML model is applied to the updated dataset.</p>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/add.jpg" />
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<figcaption>Adding a new swimming pool </figcaption>
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</figure>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/update.jpg" />
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<figcaption>Updated situation in the district after building a new swimming pool </figcaption>
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</figure>
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</div>
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<div class="section">
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<p>Besides simulating the construction and demolition of infrastructure facilities, the system also allows
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similar operations with residential complexes. For example, you can assess how the situation will change
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if a new residential complex with a specified number of apartments is built. </p>
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<p>Let's build several large residential complexes on the industrial territory of the Pokrovskoye-Streshnevo
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district and evaluate how the situation with schools will change. The facilities in the district will
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become overloaded, and the population's provision will decrease.</p>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/sufficiency.jpg" />
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<figcaption>School provision (blue is high, beige is low) and load on corresponding facilities
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</figcaption>
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</figure>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/new-house.jpg" />
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<figcaption>Adding new residential complexes </figcaption>
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</figure>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/sufficiency-new.jpg" />
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<figcaption>School provision (blue is high, beige is low) and load on corresponding facilities after the
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appearance of new residential complexes </figcaption>
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</figure>
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</div>
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<div class="section">
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<p>All simulations performed by the user are saved in a history log. At any time, they can be canceled to
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restore the system to a previous or initial state. </p>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/history.jpg" />
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<figcaption>User action history </figcaption>
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</figure>
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</div>
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<div class="section">
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<p>The system is equipped with many filters that simplify the search for infrastructure facilities and urban
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areas with the desired characteristics. Using filters, you can quickly select facilities with a specific
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load and capacity, located in certain areas of the city, or urban areas with specific values for
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provision indicators. </p>
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<p>The system also allows you to choose the level of detail for displaying urban territories, from hexagonal
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cells with a side length of 200 meters to administrative districts</p>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/hex.jpg" />
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<figcaption>Display of indicators by 200m hexagonal cells in the Ramenki district </figcaption>
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</figure>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/square.jpg" />
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<figcaption>Display of indicators by 500m square cells in the Ramenki district </figcaption>
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</figure>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/diagram.jpg" />
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<figcaption>Provision diagram for all categories in a district </figcaption>
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</figure>
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</div>
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<div class="section">
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<figure>
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<img src="/images/city/shap.jpg" />
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<figcaption>Graph for interpreting the demand forecast for adult clinics </figcaption>
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</figure>
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</div>
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<div class="section">
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<a href="/en/contacts.html" class="contacts-link">Contact us if you are interested in a system like
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this<span class="arrow-diagonal">
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