Method for generating a 3D model using new building elements determined from values of a multi-dimensional and multiple

Abstract

A method for generating a 3D model at a city location (U) using new construction elements determined by values of multi-dimensional and multivariate environmental data sets, comprising the steps of:-retrieving a 3D geographic data set of the city location with topographic shapes and possibly architectural and / or vegetation shapes; retrieving or calculating a plurality of independent environmental scalar and / or vector data sets at the urban location, the environmental data sets corresponding to a plurality of environmental fields in solar radiation energy, wind speed, noise pressure level and / or visibility ratio of free volume / area or target object; -generating a 3D model of the city location based on values of the 3D geographic data set and values of the environmental data set; projecting the 3D model onto a 2D view and displaying the 2D view on a display in order to display values from the 3D geographic data set and values from the environmental data set at a plurality of sensor points; displaying a plurality of graphical user control elements on the display, wherein at least one graphical user element allows one to be selected in at least two of the environmental data sets; selecting a set of environmental data; receiving a first filtering command input by a user with one of said graphical user control elements for defining a filtering threshold to be applied to the selected environmental data set; generating a filtered 3D model, wherein values of the 3D model that do not reach a filtering threshold on the set of environmental data are excluded; receiving a first transformation command input by a user with one of said graphical user control elements for defining a first transformation to be applied to the filtered model, generating a first transformed 3D model comprising construction elements whose position, orientation and shape are determined by the position and scalar or vector values of the filtered 3D model; and displaying the 2D projection of the transformed 3D model.

Description

Technical Field

[0001] The present invention relates to the field of computer-implemented generation of 3D models of urban locations. Background Art

[0002] The concept of healthy and sustainable architecture in urban environments is one of our society's major challenges. Physical properties related to sunlight, views, noise, airflow, pollution, and other environmental factors are crucial for human comfort, health, and sustainability. To fully understand these physical phenomena, accurate environmental analysis of local urban environments is crucial.

[0003] Over time, site analysis has become a defining phase of the architectural design process, dedicated to studying a site's context and its climatic, geographical, historical, legal, and infrastructural aspects. Long before the advent of computer technology, designers and engineers developed tools to analyze and plot site-related information. Regarding environmental information, a typical approach involves retrieving meteorological data in the form of time-based graphs, where variables such as temperature, humidity, solar radiation, wind speed, and rainfall are plotted over annual or daily cycles.

[0004] Of these graphical tools, sun path diagrams are probably the most widespread and exist in a range of different configurations based on several types of geometric projections. Some tools, such as psychometric or bioclimatic diagrams, also allow for the setting of these climate variables related to human comfort.

[0005] Today, many of these methods are integrated with meteorological databases within architectural 3D modeling programs, so that, given a site's geographic location, representations like sun-path diagrams, radiation cubes, or wind rose diagrams can be retrieved with a simple click. Following the site analysis phase, architects / planners typically integrate the resulting information into a graphical sketch, often a topographical view, that sets the environmental features of interest relative to the site's physical characteristics based on the plot, topography, and built environment. This representation is often used as a starting point for developing an environmental strategy during the conceptual design phase.

[0006] Generally speaking, these graphical tools are well-suited for studying environmental resources on simple sites. In fact, if the environmental resources are fairly evenly distributed across the site, the analysis can be simplified to a single entity, usually the center point of the parcel.

[0007] However, if the object of study is a more complex urban site and / or located in a non-trivial terrain environment, most of these tools will be insufficient, especially in the presence of close obstacles.

[0008] To address this issue, numerous software tools have been developed. They allow for the analysis of environmental resources based on digital simulations, information about the surrounding environment, and early sketches of architectural solutions. However, these early-design building simulation optimization software solutions suffer from a chicken-and-egg problem: running environmental simulations (e.g., related to sunlight, sight lines, airflow, or noise propagation) always requires surface-based digital sketches of the building, while the goal is to conceive the building based on the simulation results. Consequently, the associated single-objective or multi-objective heuristic processes are highly dependent on the initial constraints set by the user and can only work within a very limited scope.

[0009] Similarly, recent AI-driven generative solutions for automated simulation optimization or AI-driven ambient building configurators are also highly self- and / or past-referenced. Therefore, even if they help achieve some results more quickly, they rarely help users generate truly innovative and improved solutions, as they remain deeply tied to the initial definitions and constraints set by the user and to old design and decision-making paradigms. Furthermore, AI-based solutions are often based on black-box systems, so users do not fully understand what should lead to the performance of the proposed solution.

[0010] Software attempts have been made to move beyond the "early design" phase of recent software solutions and back to the "pre-design" phase of traditional graphical tools. Some of these attempts are based on a bottom-up approach, where the values ​​of different environmental variables are determined for a set of volumetric sensor points representing the empty space of the site. However, these attempts have failed to produce groundbreaking solutions, primarily due to the lack of simple methods to handle the very high degree of variability and dimensionality.

[0011] To address the need for a comprehensive joint assessment of several environmental resources across both temporal and spatial dimensions, and to assess the critical potential of urban sites directly from the characteristics of the resources present in the empty space and time of each distinct site, a comprehensive volumetric site analysis method is proposed. This technique is based on the recent availability of ultra-high-resolution 3D geographic datasets with precise information on the shape of terrain, buildings, and vegetation. Based on this data, additional environmental datasets can be retrieved or calculated through simulations, added to the geographic dataset, and then displayed to the user through a 3D visualization framework.

[0012] Within this visualization framework, a series of volumetric environmental fields are then represented in 3D. Typical variables in this environmental dataset relate to, for example, solar radiation, visibility, wind, and noise. The goal of this environmental information is to provide key recommendations tailored to local conditions for architectural design, construction engineering, energy technology, land planning, urban planning, and real estate objectives. Therefore, it is a technical tool used during the pre-design phase of a project.

[0013] However, this technique still does not provide practical usability due to the enormous amount of data generated and the complexity of its representation and interpretation. The results generated by the described process can have both scalar (v) and vector (vx, vy, vz) structures and constitute complex multidimensional (x, y, z, t) and multivariate (v, u, w, ...) data sets that are very difficult to interpret. Moreover, given the amount of information and the variety of parameters involved, a direct, comprehensive and interconnected understanding of these data sets is beyond human capabilities, and the correlation between the different variables and their parameters and the investigation objectives is extremely difficult to establish.

[0014] Furthermore, these methods fail to generate practical decisions and design recommendations, such as specific suggestions for planning cities, designing buildings, or designing construction elements based on these environmental datasets.

[0015] Below we list some identified prior art documents in the related field.

[0016] US2022 / 0198084A1 relates to solar panel positioning software. It describes irradiance heat maps at various locations, such as on a rooftop. A threshold value can be entered through a user interface, allowing the system to recommend one or more suitable panel placements. However, the document fails to account for the shape of the terrain and is therefore not applicable to mountainous areas, where mountains cast shadows on buildings. Furthermore, it does not consider other environmental data sets besides solar irradiance.

[0017] US2021 / 0110156A1 is very similar to US2022 / 0198084A1, although it does take into account the effects of adjacent buildings, trees, etc. on solar irradiance.

[0018] L. Jiaming et al. published “An open-source 3D solar radiation model integrated with a geographicInformation System" is another document that is relevant only to solar irradiance modeling.

[0019] Murshed Syed Monjur et al., “Modelling, validation and Quantification of Climate and other Sensitivities of Building Energy Model on 3D City Models” does consider more than one environmental dataset but fails to publicly filter the data, especially when the amount of data to be displayed is very large.

[0020] “Towards a sensitive UrbanWind Representation in Virtual Reality” by Giraldo Gabriel et al., published on April 6, 2022, describes wind vector representation in virtual volumes. Summary of the Invention

[0021] Therefore, most existing techniques involve the analysis of a single environmental parameter, usually involving the surface of a 3D roof / building / city model, sometimes used to optimize the placement of components on an existing building or building design.

[0022] The purpose of the present invention is to provide a new method for displaying and interacting with multidimensional and multivariate datasets corresponding to environmental variables of urban locations, and generating 3D models based on these interactions, thereby providing users with specific decision suggestions and / or practical design recommendations.

[0023] According to the present invention, this object is achieved by the objects of the attached independent claim and is further described in the dependent claims.

[0024] The present invention provides an advantage over what is known in the art in that high-level dimensions and variables, along with their potential dependencies and / or their relationship to the specific goals of a project, can be easily manipulated, combined, selected, processed, transformed and displayed to generate appropriate design recommendations for construction elements.

[0025] According to one aspect, the present invention relates to a method comprising the following steps:

[0026] a) Retrieve a 3D geographic dataset of the urban location with the shape of the terrain and possibly the shapes of buildings and / or vegetation;

[0027] b) retrieving or calculating a plurality of independent environmental scalar and / or vector data sets at the urban location, the environmental data sets corresponding to a plurality of environmental fields of solar radiation energy, wind speed, noise sound pressure level and / or free volume / area or visibility ratio of target objects;

[0028] c) generating a 3D model of the city location based on the values ​​of the 3D geographic dataset and the values ​​of the environment dataset;

[0029] d) projecting the 3D model onto a 2D view and displaying the 2D view on a display so as to display values ​​from the 3D geographic dataset and values ​​from the environment dataset at a plurality of points;

[0030] e) displaying a plurality of graphical user control elements on said display, wherein at least one graphical user element allows selection of one of at least two of said environment data sets;

[0031] f) Select an environmental dataset;

[0032] g) receiving a first filter command input by a user using one of said graphical user control elements for defining a first filter threshold to be applied to the selected environmental data set;

[0033] h) generating a filtered 3D model, wherein values ​​of the 3D model that do not meet a first filtering threshold on the environment dataset are excluded;

[0034] q) receiving a first transformation command input by a user using one of the graphical user control elements for defining a first transformation to be applied to the filtered model and generating a first transformed 3D model comprising construction elements whose positions, orientations and shapes are determined by the positions and scalar or vector values ​​of the filtered 3D model;

[0035] r) Displaying the 2D projection of the transformed 3D model.

[0036] Structural elements may include walls, roofs, ceilings, slabs, openings, shelters, balconies, facades, complete buildings, urban infrastructure, etc.

[0037] This method may include the following features:

[0038] 1. The environmental variables of this method are related to the open space represented by 3D sensor points;

[0039] 2. Analysis of multi-layer environmental information;

[0040] 3. A combination of such multiple environment variables; and / or

[0041] 4. Filtering and / or transformation of combined datasets.

[0042] To facilitate the selection and filtering of the environment dataset, the method preferably comprises the following step i): before displaying the transformed 3D model, displaying a 2D projection of the filtered 3D model. The filtered 3D model preferably does not include any generated construction elements and primarily comprises the shape of the terrain and the selected and filtered environment dataset.

[0043] The transformed 3D model includes the shape of the terrain and the newly generated construction elements. It may or may not include the display of the environment dataset.

[0044] Between steps h) and q), the method may further comprise the following steps:

[0045] j) repeating steps f) to h) or f) to i) for at least a second independent environmental data set;

[0046] k) combining values ​​of two or more different filtered independent environmental data sets to generate a combined environmental data set at the location;

[0047] l) Generating a combined 3D model of an urban location, said combined 3D model integrating values ​​of said 3D geographic dataset and values ​​of said combined environment dataset.

[0048] Thus, the method provides an iterative, interactive, multi-level and cross-correlated filtering and combining method for processing multi-dimensional environment datasets and generating a 3D model using construction elements whose position, orientation and shape depend on the selected filtered environment dataset.

[0049] Thus, for example, several data sets (eg solar radiation and noise level) can be selected, filtered and displayed successively, combining the values ​​of these different filtered data sets.

[0050] Combining the values ​​of two different environmental data sets may include, for example:

[0051] normalizing the values ​​of the two different environmental data sets; and / or

[0052] weighting the values ​​of the first and second environmental data sets of the two different environmental data sets; and / or

[0053] Logical and / or arithmetic combinations are applied between the weighted values.

[0054] Between steps 1) and q), the method may further comprise the following steps:

[0055] m) projecting the combined 3D model onto a 2D view and displaying the 2D view on a display so as to show values ​​from the geographic dataset and values ​​from the combined environment dataset at a plurality of points.

[0056] The method described in the above steps may further comprise the following steps between steps 1) and q):

[0057] n) receiving a filter command input by a user using one of said graphical user control elements for defining a filter threshold to be applied to the combined environment data set;

[0058] o) generating a filtered combined 3D model, wherein values ​​of the combined 3D model that do not meet a previous filtering threshold on the combined environment dataset are excluded;

[0059] p) Displaying a 2D projection of the filtered combined 3D model.

[0060] Thus, for example, several data sets (eg solar radiation and noise level) can be selected, filtered and displayed in succession, the values ​​of these different filtered data sets combined, and the combination then filtered.

[0061] After step r), the method may further comprise the following steps:

[0062] s) generating a second transformed 3D model comprising construction elements whose positions, orientations and shapes are determined by the positions and scalar or vector values ​​of the filtered or combined 3D models;

[0063] t) combining the first and second transformed 3D models into a combined transformed 3D model;

[0064] u) Displaying a 2D projection of the combined transformed 3D model.

[0065] Therefore, the combination between 3D models may be performed after generating the transformed model.

[0066] The above steps a) to u) are preferably performed chronologically in the alphabetical order shown.

[0067] In some embodiments, the order of some steps is changed.

[0068] Some steps, such as those indicated in the dependent claims, are optional and may be omitted in some embodiments.

[0069] You can add additional steps to this method. Some steps may be executed multiple times.

[0070] The generation of the transformed 3D model may be based on one or more commands input by the user for defining the type of construction elements to be generated depending on one or more selected filtered or combined environment data sets.

[0071] The generation of the transformed 3D model may include generating 3D cells whose positions, orientations, and shapes are determined by the positions and scalar or vector values ​​of the filtered or combined 3D model.

[0072] For example, a cell may correspond to a room and may be generated at a location where the environmental dataset exhibits the most favorable values.

[0073] The method may include the step of receiving parameters and constraints to define the construction element. Those constraints may be input by a user. The method may generate suggestions for construction elements based on the positions and scalar or vector values ​​of the filtered or combined 3D model and the parameters and constraints.

[0074] The approach is multi-level in that it allows filtering of the dataset both at the level of the independent environmental datasets and at the level of the combined environmental datasets.

[0075] Filtering can also be cross-correlated, in that the effects of these different filters applied at multiple levels can be directly correlated, and constraints such as thresholds, averages, projections, etc. can be updated in real time as the filtering process proceeds to generate the final result.

[0076] The unexpected hidden patterns revealed by this approach allow the generation of highly impactful added value that is very specifically targeted to the user's architectural, engineering, planning or real estate goals. Examples of such goals could be the definition of building forms, their exterior surfaces, their interior subdivisions, energy and plant issues, the planning of urban areas, the identification of plots of land with specific environmental properties or the valuation of real estate.

[0077] Depending on the environmental dataset, this method can be used to represent spatial points that simultaneously have the highest solar radiation energy, the lowest wind speed, the lowest traffic noise sound pressure level, and the highest or best visibility, for example, in urban locations. Structural elements such as rooms, facades, balconies, complete buildings, urban areas, or territorial infrastructure may be proposed at these locations.

[0078] For example, this can be used by architects and urban planners to identify good sites, or to plan urban development, construction, or renovation. In another use case, this can also be used, for example, to plan the installation of photovoltaic panels on a building to optimize solar energy production while using the PV surface as a noise or solar shield, and also to avoid placing the PV surface in a location exposed to strong winds. In another use case, this can be used to position a balcony in a place that has good nighttime solar access, a high lake view, low nighttime traffic noise, and airflow within an ideal speed range.

[0079] The method allows for the generation and display of a 3D model of an urban location including a new construction element, wherein the location, position and orientation of the construction element are determined based on values ​​of a filtered and / or combined 3D model generated from a 3D geographic dataset and values ​​of one or more independent, multidimensional, multivariate environmental datasets.

[0080] For purposes of this disclosure, a multidimensional dataset is a set of data values ​​that may have scalar (v) and vector (vx, vy, vz) structures and multiple dimensions (e.g., such as (x, y, z, t)).

[0081] For the purposes of this disclosure, a multivariate data set is a set of data values ​​of different physical properties (u, v, w), possibly quantified in different units of measurement.

[0082] For the purposes of this disclosure, an environmental dataset is a dataset representing environmental variables, such as solar radiation, wind speed and direction, visibility, noise level, and the like.

[0083] For the purposes of this disclosure, a scalar data set is a set of scalar values, such as sampled and digitized values, representing an ambient field of an area or volume of interest.

[0084] For the purposes of this disclosure, a vector dataset is a set of vectors, such as sampled and digitized vectors, that represent an ambient field of an area or volume of interest. The value of each vector depends on all of its components, and therefore also on its magnitude and direction.

[0085] For purposes of this disclosure, combining values ​​of two different environmental data sets may involve performing a logical and / or arithmetic combination between each pair of corresponding scalar or vector values ​​from the two data sets.

[0086] Because datasets are multivariate, values ​​in different environmental datasets may have different units of measurement. For example, one dataset corresponding to scalar values ​​in a solar radiation energy field may include values ​​in J / m² / y, while a second dataset corresponding to a wind speed field may include values ​​reported in m / s.

[0087] Thus, for each point, the combined environmental data set may include logical and arithmetic combinations between values ​​from the two different data sets, possibly including values ​​expressed in different units.

[0088] Combining values ​​reported in different units may include a step of normalizing the values ​​to convert them into numbers without any units. In one embodiment, combining values ​​may include a step of normalizing each value, such as by reporting them within a range from 0 (minimum value) to 100 (maximum value) or any other standardized interval.

[0089] Combining the values ​​may include the step of weighting each value, for example by multiplying the scalar and / or vector value of each point by a weighting scalar factor. The weighting factor may be set by the user, or predefined.

[0090] Combining values ​​may include performing logical combinations such as AND, OR, XOR, or NOT combinations.

[0091] Combining values ​​may include performing arithmetic combinations, such as multiplication, addition, averaging, differencing, etc., between values ​​from two or more different sets of environmental data.

[0092] Combining values ​​from different environmental datasets, which may have been pre-filtered, can also allow these values ​​to simply and simultaneously affect different structural elements of the jointly transformed 3D model without the values ​​being mathematically combined. For example, a lake view can determine the orientation of a window as a structural element, while the average direction of summer radiation can affect the overhang on the window. In this way, values ​​from two or more different environmental datasets determine one or different structural elements of the same 3D model.

[0093] The filtering may be input using a graphical user control element, such as any control on a graphical user interface (GUI), such as a button, a slider, a knob, a text entry box, and the like.

[0094] At least some of the different 3D models may be time-dependent models, ie, dynamic models, where the value of each point may change over time (hour of the day, month of the year, etc.).

[0095] The method may include the steps of receiving a specific time input by a user and displaying a modified view, wherein the value of each point corresponds to the value of the specific received time.

[0096] The method may comprise the steps of receiving a user input of a time interval and displaying a modified view wherein the value of each point corresponds to the average or sum of the values ​​of that point during the time interval.

[0097] The method may comprise the steps of receiving a coordinate interval input by the user and displaying only the values ​​of the environment dataset for points lying within the interval.The coordinate interval may comprise a range in one or several dimensions (x, y and / or z).

[0098] The method may comprise the steps of receiving a resolution value selected by said user, and adjusting the spatial distance between points according to said resolution.

[0099] A filter threshold can be a numerical threshold applied to a scalar value in a dataset or to the magnitude of a vector in a vector dataset.

[0100] A filtering threshold may be a numerical threshold applied to the number of cells of the area / volume to be displayed at the location of each sensor point.

[0101] A filter threshold can be a lower bound, an upper bound, or a range between a lower and an upper bound.

[0102] A filtering threshold can be applied to an entire area or an entire volume, or it can be applied independently to specific sub-parts of them, such as smaller areas within a larger area (e.g. independently to municipalities within a larger area) or smaller volumes within a larger volume (e.g. independently to all points located at the same level of the volume).

[0103] One filter may involve reducing the region / volume of interest to a boundary encompassing the region / volume (eg, showing a boundary of a land area, a boundary of a building volume, or a boundary of a floor slab, etc.) using, for example, a convex hull and / or a concave hull.

[0104] Other types of filters can be applied. For example, in a vector field, a threshold can be used to filter out only vectors pointing in a specific direction or range of directions.

[0105] Other filters may replace the displayed scalar value, magnitude, or direction with an average value across a region, volume, and / or time interval.

[0106] Other filters may allow deciding whether to display a scalar value, the magnitude of a vector or the ratio between these two values, for example using a color or grayscale gradient.

[0107] The method may comprise the step of projecting the vectors of the vector data set along a specific direction or on a specific plane.

[0108] For example, such a method may include projecting the vector along its mean direction.

[0109] For example, such an approach may comprise projecting the vector onto a horizontal plane. This may, for example, allow for the orientation of vertical surfaces, such as windows or vertical surfaces of a facade.

[0110] For example, the method may comprise the step of projecting the vectors of one of the vector datasets onto a vertical plane having a horizontal orientation defined by the user. This may allow, for example, to recover the ideal vertical tilt of photovoltaic panels for an urban building project having a defined / constrained main building facade orientation.

[0111] One of the environmental data sets may represent visibility in different directions. Free visibility from a point may be indicated as a percentage of an unobstructed area or volume surrounding the point, for example, as a fraction of a horizontal circle surrounding the point, as a fraction of a sphere, or as a fraction of a spherical sector.

[0112] Target visibility can be represented by the ratio between the field of view occupied by the target object and the global field of view. For example, the field of view of a landscape with water objects is generally preferred over that of a landscape with industrial objects.

[0113] The method may comprise the step of filtering points in one of said filtered or combined data sets according to the values ​​of its neighbouring points.

[0114] Control elements can be used to filter points not only based on their own value, but also based on the values ​​of their neighboring points (e.g., only select elements for which a certain condition is valid for at least two of their neighboring points).

[0115] The method may comprise the step of receiving a command input by a user using said graphical user control element, the command being for hiding points that may be modified by future obstacles inside the volume itself, i.e. keeping only points on the volume boundary that will have constant values, independent of content that will potentially be inserted inside the volume.

[0116] The method may comprise the step of receiving a command input by the user using the graphical user control element to display only points close to a user-specified object, i.e., only retaining points below a given distance (e.g., 1 m) from the surface of the object (e.g., an existing building).

[0117] The method may comprise the step of saving and / or restoring a set of selection, filtering and / or combination parameters as a preset. Thus, the preset may be easily retrieved and applied to different environmental data sets and / or different urban locations.

[0118] The graphical user interface may include buttons that allow the user to visualize the geometric operators used to generate the environmental dataset results. These geometric operators may assist the user in the filtering process and may include, for example, sun rays, lines of sight, wind streamlines, sound propagation lines, target objects, obstacle objects, emission objects, intersection points, reflection points, and diffraction points.

[0119] The graphical user interface may comprise controls to display a single spatial sector of a set of said geometric operators (eg a ray or lines) and / or also to display an aggregated result of a selection of these sectors.

[0120] The graphical user interface may include 2D camera images of the 3D model, which may be constructed with different types of projections and from different viewpoints, allowing visualization of detailed information related to the shape and / or value of each of these said geometric operators and assisting the user in the interpretation and / or filtering process.

[0121] The graphical user interface may include a 2D color or grayscale heat map that allows visualization of detailed information related to the shape and / or value of each of these geometric operators and assists the user in the interpretation and / or filtering process and in identifying global and / or local maxima and minima of the values ​​of the operators. A 2D slider located above these 2D camera images or heat maps may assist the user in selecting a particular geometric operator or a series of such operators.

[0122] The method may comprise the step of calculating a transformed 3D model comprising a schematic representation of construction elements whose positions, positions and orientations are determined based on the values ​​of the filtered or combined 3D model.

[0123] A 2D projection of the transformed 3D model can then be displayed.

[0124] The step of computing the transformed 3D model is called transformation.Transformation allows the user to transform the abstract or semi-abstract visual representation of the filtered and / or combined 3D model into a refined schematic representation associated with a specific proposal including construction elements.

[0125] Structural elements may include rooms, walls, roofs, solar panels, shelters, shutters, balconies, windows, etc.

[0126] The transformed 3D model can include construction elements based on a cell scheme. A cell scheme can include multiple aggregations of basic cells, each representing, for example, a single room or an entire building. Basic cells are created at locations that meet certain conditions from a dataset or a combination of datasets. Additional construction elements, such as balconies and openings, can be added to some cells; their location and orientation are determined based on the context dataset.

[0127] Construction elements may also include single-building plans (which represent a draft of the entire building level), and / or multi-building plans, and / or infrastructure plans.

[0128] The invention also relates to a computer program product comprising instructions for causing a computer to carry out the method according to one of the preceding claims, when the program is executed by the computer. BRIEF DESCRIPTION OF THE DRAWINGS

[0129] Exemplary embodiments of the present invention are disclosed in the specification and illustrated by the following drawings:

[0130] ● Figure 1 Shown is a 2D representation of a 3D volume corresponding to a geographic dataset of an urban location with terrain and building shapes.

[0131] ● Figure 2 showing the same representation with a plurality of graphical user control elements for selecting: environmental data sets to be displayed, combinations between environmental data sets to be displayed, filters to be applied, a representation type to be used, and a transformation type to be applied including associated parameters;

[0132] ● Figure 3 Shown is a 2D representation of a terrain surface from a 3D geographic dataset of an urban location.

[0133] ● Figure 4a –4e shows various 3D visualization elements used to represent environmental values ​​on a 2D view.

[0134] ● Figures 5a-5d Different methods of reducing the directional part of a tensor are shown.

[0135] ● Figures 6A-6FDifferent examples of proposed buildings comprising construction elements generated by the described method are shown.

[0136] Figures 1 to 3 Geographic data source: Swiss Federal Office of Topography. DETAILED DESCRIPTION

[0137] For the purposes of this disclosure, an urban location U designates any site or area where an environmental analysis is required or has been performed, with the goal of retrieving decisions and / or design recommendations related to the location, amount, size, direction and / or form of a specific target intervention. An urban location U may designate a 2D or 3D area of ​​land or a 3D volume of a site (see Figure 1 Targeted interventions in urban locations are typically related to:

[0138] ■ Land planning, urban planning or urban design: zoning, urban development planning, public space and infrastructure, mobility infrastructure, energy plants, etc.;

[0139] ■ Real estate strategies and projects: site selection, valuation, design of large urban developments, use, function, and distribution of buildings or residential units;

[0140] ■ The location, orientation, proportions and form of the building, its external building surfaces and building components: transparent surfaces, windows, openings, facades, roofs, external sunshades, balconies, wind shields, sun shields, acoustic shields, viewing shields, photovoltaic surfaces, thermal surfaces, wind turbines, ventilation inlets and outlets, heat exchangers, etc.;

[0141] ■ The use and functional distribution within the building: the shape and location of the residential units, the shape of the land plan, the size of the rooms, etc.

[0142] According to one aspect, the method of the present invention can be used in the pre-design or pre-decision phase, that is, as a simulation method suitable for generating and displaying a 3D model of an urban location U, taking into account environmental data. Although the original model of the urban location can include existing and planned objects, the method does not require the pre-modeling of planned urban objects; rather, it can be used before the conception process to retrieve important environmental suggestions for starting the conception process in a new way. Thus, the urban location U can be any vacant space in a city or abroad, or it can also be an existing space or area to be modified, renovated, rebuilt, etc.

[0143] According to one aspect, the method relies on discretizing the unoccupied space of a site / area into a matrix 11 of sensor points (which can be displayed as voxels). At each of these points, different physical properties of the environment (e.g. solar radiation, airflow, noise, visibility, etc.) are calculated or retrieved. These environmental values ​​have scalar (v) or vector (v x , v y , vz) The structure is stored as a dataset based on the four spatiotemporal dimensions (x, y, z, t) of the area / volume. This environmental data is then combined with a geographic model of the location into a 3D model that the user can access through visualization on a display. The different values ​​of each sensor point can be represented by, for example, different colors, numbers, arrows, etc. ( Figures 1 to 3 (not shown in the figure). An urban location is defined at least by the 3D shape of the ground (which may be flat in some cases) and may be completed by the 3D shapes of buildings and / or the 3D shapes of associated vegetation.

[0144] A city location can be represented by a 3D geographic dataset, i.e., a set of numerical values ​​representing the shape of the terrain 10 and possible buildings and / or vegetation. The 3D geographic dataset representing the city location can be collected from a geographic data provider, retrieved from a cartographic database, retrieved from architectural plans, and / or retrieved from 2D or 3D images. This dataset can at least represent the shape of the terrain. Existing buildings and / or planned buildings and / or vegetation can also be represented by this dataset.

[0145] For example, a 3D geographic dataset may represent the three-dimensional contours of the ground 10, including hills, slopes, inclines, mountains, and any other terrain that can be considered. The presence of natural or man-made objects, such as trees, rivers, buildings, and infrastructure that already exist in urban locations, may also be considered.

[0146] Figure 1 An example of a representation of a city location U of a 3D geographic dataset on a display is shown. In this example, the 3D geographic dataset is represented by a mesh of triangular surfaces. The 3D geographic dataset itself is stored in a computer memory as a set of values, such as a set of sampled values.

[0147] The method of the present invention also requires one or more environmental scalar and / or vector datasets for an urban location. Environmental datasets are numerical representations of environmental fields, such as solar radiation energy, wind speed, noise sound pressure level, and / or free volume / area or visibility ratios of target objects. Environmental datasets can be static or dynamic, i.e., change over time.

[0148] The environmental data sets may be already available and retrieved, for example, from a database. They may be physically determined on site, for example through appropriate observations or measurements. They may be calculated, for example, using known simulation or prediction tools. Each environmental data set includes or can be used to determine values ​​of the environmental field at a plurality of points in an urban location.

[0149] Different environmental data sets may correspond to different environmental fields, such as annual, monthly or hourly solar radiation energy or time, and / or wind speed, direction, pressure, turbulence intensity, and / or noise sound pressure level, and / or visibility of open space (the free part of the volume or area around the observation point), and / or visibility of target objects (lakes, green areas, monuments, ugly industrial areas, etc.). These environmental data sets can be obtained for a single background or multiple background scenarios (current or future, with or without vegetation, etc.).

[0150] Some environmental data sets may correspond to a set of environmental scalar values ​​at different points of an area / volume. For example, an environmental data set may indicate the noise level at different points of an area / volume.

[0151] Some environmental data sets may correspond to a set of environmental vector values ​​at different points of an area / volume. For example, an environmental data set may indicate the amplitude and direction of wind or solar energy at different points of the area / volume.

[0152] Different data sets may indicate values ​​in different units. For example, noise levels may be indicated in decibels; solar energy may be expressed in J / m 2 / y; wind speed is indicated in m / s; and visibility is indicated in percentage.

[0153] The values ​​of the environmental data set may be normalized, for example by expressing it on a scale with a minimum value (eg, 0) and a maximum value (eg, 100). As will be described below, normalization allows data sets with values ​​in different units of measurement to be combined.

[0154] To perform the combination, the values ​​of different environment datasets can be weighted by multiplying them by a scalar weighting value. The weighting value can represent the importance of a particular dataset relative to other datasets. The weighting value applied to a particular dataset can be predefined, user-defined, and saved in or restored from a preset.

[0155] The values ​​of different environment data sets, which may have been pre-filtered, may also be combined by virtue of the fact that they simultaneously affect different construction elements of the joint 3D model without the values ​​being mathematically or logically combined. This combination may involve priority rules.

[0156] Each environmental dataset can be selected and independently filtered, manipulated, and displayed. The filtering process can be iterative. For example, a first filter can be applied to an environmental dataset to produce a filtered 3D model. Then, a second filter can be applied to the filtered 3D model to produce a second filtered 3D model to which two different filters have been applied.

[0157] Two different environmental datasets can be combined into a single combined environmental dataset by combining the possibly normalized and possibly weighted values ​​of each dataset at each sampling point in the region / volume. The user can select the environmental datasets they wish to combine. Thus, at each sampling point, the combined environmental dataset stores values ​​based on a combination of different environmental variables. For example, the combined environmental dataset might indicate a combined value at each point that indicates the amount of solar energy and wind speed on a standardized scale.

[0158] In another example, two different environmental datasets that have been previously filtered are simply jointly displayed, independently contributing to the generation of the overall 3D model.

[0159] The combined environment datasets can be filtered, manipulated, and displayed individually and / or independently of the original environment datasets. Thus, the method is multi-stage, as it allows for filtering and potentially transforming the datasets at both the level of the individual environment datasets and the level of the combined environment dataset. The interactive filtering process can also be iterative. Furthermore, the filtering can also be interdependent, i.e., a filter applied to one environment dataset can automatically affect any other filter applied to that dataset or to the combined environment dataset into which that environment dataset is combined.

[0160] Furthermore, it is possible to enter some predefined basic parameters, corresponding to the characteristics of the analysis you wish to perform or the intervention you aim to implement. For example, the number of floors of urban buildings to be implemented, or the minimum surface area of ​​the ground to be occupied, or the main orientation of urban objects, or the minimum surface area of ​​solar panels to be distributed, or the maximum acceptable sound level. These basic parameters can be determined by basic project requirements, project constraints, regulations, generated by specific standards, generated by client requests, or derived from any other source. Therefore, these basic parameters represent the original constraints that should be considered when evaluating urban locations.

[0161] The values ​​of the 3D geographic dataset and the environmental dataset (including the combined environmental dataset) can be combined to generate a combined 3D model of the urban location. The combined 3D model combines the values ​​of the 3D geographic dataset and the values ​​of the environmental dataset at different points in the area / volume of the location. Thus, the combined 3D model of the location indicates geographic parameters of the environment (ground, buildings, vegetation, etc.) and one or more environmental values ​​and / or combined environmental values ​​at multiple points in the area / volume.

[0162] The 3D model or filtered 3D model or combined 3D model is then projected onto a 2D view, which can be displayed on a display, such as a computer monitor, such as Figure 2The interface may include graphical user interface elements 20-23 to select, combine, filter and transform visualizations and other commands, such as to set the 2D view by scaling, rotating, shifting, etc. the projection plane. Figure 2 In the example of FIG, the underlying 3D geographic dataset includes the ground 10, buildings 13 and a grid of orthogonal sensor points represented by voxels 11, while an environmental dataset is represented on the view using a grayscale or texture 110 at each point or voxel 11.

[0163] Such a visual representation allows, for example, to easily identify the most sun-irradiated part of a city location, or the most sun-irradiated part at a specific time of day or as an average over a time interval.For example, the solar radiation in summer can be represented according to such a graphical representation.

[0164] Thus, the displayed 2D view shows values ​​from the geographical dataset (topography and possible buildings and / or vegetation of the environment) at a number of points, as well as values ​​or directions of a selected or combined environment dataset.

[0165] The display may be part of a computer comprising a keyboard and / or other input means, a processor, a memory and a computer program for calculating and presenting the 2D views. The computer program may comprise a graphical user interface allowing the user to select the environment data set or combination of environment data sets he wants to display, manipulate them and filter them.

[0166] Environmental datasets (including combined environmental datasets) can be represented by various visualization elements 23 on the 2D view. For example, the magnitude of scalar values ​​and vector values ​​can be represented by colored voxels ( Figure 4a ), points, polygonal packages or surfaces, grayscale levels or numbers next to each sampling point or voxel 11. The direction of the vector value can be displayed using arrows and / or directional surfaces (respectively Figure 4b 、 4c ) or oriented volume ( Figure 4d and 4e ) etc. to display.

[0167] Available through Figure 2 Transformation is triggered by selecting a transformation filter in block 24. Transformation is the step of calculating and then displaying a transformed 3D model including construction elements. The position, shape, and orientation of the construction elements are determined based on the values ​​of the filtered or combined 3D model. Thus, the transformed 3D model includes specific design recommendations based on the data from the environment dataset.

[0168] First, the user may select in box 24 whether he wishes to apply a transformation filter and generate proposals based on a unit building solution, a single building solution, a multi-building solution, or an urban infrastructure solution.

[0169] If the user selects a cell building solution, he may decide to link the distribution of spatial cells (e.g. 3x3x3 meter rooms), and / or the determination of the transparency of the faces of such cells (intended as glass surfaces), or the distribution of some smaller openings on the faces of such cells, or the distribution of external shading and balconies around such cells, to different filtered or combined environmental datasets of his choice. In turn, the results of such a transformation may then be combined in a transformed 3D model comprising a plurality of construction elements. This will represent schematic suggestions regarding the determination of the position, orientation and shape of such construction elements based on the position and / or scalar values ​​and / or orientation values ​​of the selected environmental dataset and the parameters of different potential filters and combinations. Such a transformation may create 3x3x3m cells (of a size indicated by the user) and other construction elements at positions that are optimal for the selected environmental dataset, and with shapes and orientations that are optimal for the values ​​of the selected environmental dataset.

[0170] The user can select some constraints and parameters related to the construction element through the graphical user control elements on the GUI, such as:

[0171] Whether the orientation of the construction element (e.g., the visor surface) should be perpendicular to the direction of the environmental resource, or whether it should be orthogonal to the face of the cell (i.e., orthogonal to the grid of sensor points);

[0172] Whether the depth of construction elements (e.g., visor surfaces) should be free-formed by the environment dataset, or should have the same unit size, or should be a fixed value defined by the user (e.g., 1m); and / or

[0173] whether it should be horizontal, vertical, or both;

[0174] Whether it should be connected directly to the cell or separated by a user defined value (e.g. 1m).

[0175] The user can also specify whether the space between a cell and a construction element (e.g., a PV surface) should be left empty or filled with the cell volume, whether the surface should be placed outside the cell or inscribed into it, etc.

[0176] In a second example, if the user selects a single-building solution in box 24, he can define some general parameters that the building should have, such as the height and number of floors, as well as the dimensions of each floor (in square meters). He can then, for example, define that the exterior boundaries of each floor of the building will be determined by the location that grants the highest unobstructed view to the surrounding space (this will vary from floor to floor depending on the shape and height of surrounding obstacles). In a second step, he can then decide, for example, that the facades of these floors should be oriented towards both evening solar radiation and the lake view by linking them to the corresponding filtered combined environmental dataset. In a similar manner, he can also define the location, orientation, and shape of roofs, openings and transparent facades, balconies, and exterior surfaces by linking them to different filtered or combined environmental datasets of his choice based on his goals. All of these selections and links will then simultaneously determine the final transformed 3D model, which has construction elements corresponding to the proposal according to the selected parameters and constraints.

[0177] The same principles can also be applied on a larger scale to determine the position, orientation and shape of more complex structural elements such as multi-building settings or urban infrastructure.

[0178] The raw data (scalars and vector tensors) of the filtered and possibly combined environmental datasets are transformed into transformed 3D models, generating schematic representations of construction solutions associated with the 3D shapes of construction elements such as, for example, infrastructure, buildings, exterior building surfaces, transparent surfaces, windows, openings, facades, roofs, exterior sunshades, balconies, wind shields, sun shields, acoustic shields, viewing shields, photovoltaic surfaces, thermal surfaces, wind turbines, ventilation inlets / outlets, heat exchangers, etc. This transformation stage can occur before or after the potential combination of multiple environmental datasets, or even during both stages.

[0179] The location, shape, and orientation of building elements are determined so that the effect of the filtered environmental dataset on these elements is optimal, positive, a compromise, or otherwise corresponds to known requirements and / or user input. For example, a user may want as many balconies on a building as possible to have a view of the lake and receive evening sunlight. Therefore, these balconies would be located where the combination of filtered values ​​from these datasets is high.

[0180] For example, the transformation can detect groups of adjacent sensor points that meet specific optimization criteria (e.g., sufficient sunlight, low noise, field of view, etc.) and display them as a set of spatial cells of a predefined or selected size. These cells can then be further transformed to define additional building elements, for example, orienting their exterior facades in a direction corresponding to the orientation values ​​of the environmental dataset (e.g., toward the lake to optimize the lake view), or proposing balconies in the correct orientation, etc. These building cells and building elements can provide direct suggestions to the user for generating building elements, such as basic elements (rooms, walls, balconies, PV cells, etc.), complete buildings, groups of buildings, etc. The goal is to create suggestions that are directly generated by the selected filtering, combining, and transformation criteria and parameters, as well as data from the environmental dataset, thereby combining multiple data, objectives, optimizations, and trade-offs into a global suggestion.

[0181] The graphical user interface may have controls that allow the user to define certain parameters related to these design proposals, such as, for example: the size of the units, or the number and height of floors, and / or the geometrical rules of the building shape and / or construction elements.

[0182] In addition to these user-defined constraints, designs can satisfy implicit constraints. For example, construction elements can be adjacent to define a cohesive building, the first floor can be aligned with the ground, and elements can be aligned to create uniform floors, planes, ceilings, and so on.

[0183] Figure 6A An example of a facade design proposal that can be generated using the described method for a given urban location and a given set of environmental data is shown. In this example, the user specifies that a large opening (black) on the primary facade of a predefined building volume be located where the view is free and where winter radiation is high. Shades 200 (white) on the opening are distributed to prevent the summer sun from entering the building. Thermal panels 201 (narrow dashed lines) are positioned and oriented according to the winter solar radiation value. PV panels 202 (wide dashed lines) are positioned and oriented toward the annual solar radiation. Furthermore, on the secondary facades, additional PV panels 203 and openings are positioned and oriented toward the high evening solar radiation. The size of the units that make up the facade, as specified by the user or defined in the system, is 1x1x1m.

[0184] Figure 6BAnother example of an architectural design proposal that can be generated using the described method is shown. In this example, the user requires that the main opening 204 (narrow dashed line) be positioned and oriented toward the highest lake view, the PV panels 205 (wide dashed line) be positioned and oriented toward the highest annual radiation, the balcony 206 (white) be positioned in a location with the highest lake view, summer sun, and tranquility, and the sunshade 207 (white) be positioned and shaped to prevent morning radiation from entering the main transparent opening. The unit size, either user-indicated or system-defined, is 3x3x3m.

[0185] Figure 6C Another example of a building design proposal that can be generated by the described method is shown. In this example, the user requires that the main opening 208 be located at a location with the highest nighttime solar radiation and mountain views, the balcony 209 be located at a location with the highest lake views, and the roof 210 be shaped in the direction of the annual solar radiation.

[0186] Figure 6D Another example of a building design proposal that can be generated by the described method is shown. In this example, the user requires two facades 212 to be oriented horizontally in the direction with the highest free and green views, and one facade 213 to be oriented vertically in the direction of annual solar radiation.

[0187] Figure 6E Another example of a building design proposal that can be generated by the described method is shown. In this example, the user requires that the horizontal balcony slabs 215 be located at the highest free view and quiet position on each floor, and that the vertical transparent facades 216 be positioned to prevent solar radiation from entering the building through these facades from 10:00 to 15:00.

[0188] Figure 6F It shows how, for the same city location, changing the selected variables and combining and transforming parameters and constraints through a graphical user interface can lead to the calculation and display of different recommendations.

[0189] These recommendations may be based on unit plans that aggregate multiple units (such as individual rooms or building components) Figure 6A , 6B), or based on a single building scheme ( Figure 6C , 6D, 6E, 6F), or based on a multi-building solution, or based on an infrastructure solution (such as a solar park).

[0190] 3D models, filtered 3D models, combined 3D models, and transformed 3D models can include a very large number of sample points, for example, more than 1,000 points or more than 100,000 points. Multiple environmental values, including scalar and / or vector values, can be represented at each sensor point. Consequently, simultaneous 2D projection of the 3D model on a display is not possible, and multiple parallel or simultaneous 2D projections would be extremely difficult to interpret due to the large number of scalar and / or vector values ​​to be observed. Therefore, there is a need to reduce the number of environmental values ​​to be displayed and to correlate the content of different variables and dimensions with each other and with the requirements and constraints of the analysis at hand.

[0191] The first way to reduce the number of environmental values ​​to be represented is to increase the sampling step, i.e., to reduce the number of sampling points. However, reducing the sampling resolution may result in a less accurate representation of the 3D model. A graphical user interface command element (not shown) may be used to select the resolution.

[0192] Another way to reduce the number of environmental values ​​to be represented is to select the environmental datasets to be represented and exclude others. As an example, in Figure 2 The graphical user interface comprises an element 20 for selecting data to be calculated and displayed among the following data sets: solar radiation; noise level; and wind speed.

[0193] Another way to reduce the number of environmental values ​​to be represented is to combine different environmental data sets into a combined environmental data set, thereby reducing the number of visual elements to be displayed. Figure 2 The graphical user interface can include an element 21 for selecting the combination logic and the environmental datasets to be combined, so that the combined value of each point is represented by a single visualization element. Different types of environmental datasets with values ​​in different units of measurement can be combined. In addition to the combination shown in this example, many other combinations are possible. Furthermore, weighted combinations can be defined in the user interface, for example, to give one environmental dataset greater weight than another.

[0194] Another way to reduce the number of environment values ​​to be represented is to filter the environment datasets or combine them so that only values ​​that meet the filter criteria are displayed. For example, in Figure 2 1 , the graphical user interface includes an element 22 for selecting and / or controlling a filter to be applied to a selected environment dataset or a combined environment dataset. The filter applied to the environment dataset or the combined environment dataset can be associated with any type of graphical user interface control, such as a button, a slider, a knob, a text input box, etc.

[0195] Filtering can be based on a threshold, so that only values ​​above or below the threshold will be displayed. A special type of threshold-based filter is a Boolean filter for Boolean values; for example, you can choose to display only Boolean environment values ​​that are true or only values ​​that are false.

[0196] Threshold-based filters can be applied to scalar values. Threshold-based filters can also be applied to vector values. In the latter case, a scalar threshold can be applied to the magnitude of a vector, for example, to only display the value of the wind speed or any other vector magnitude above a given threshold in the dataset, and / or its direction, for example, to only display visualization elements for those points where the wind is blowing in a specific direction or range of directions.

[0197] A filtering threshold may be a numerical threshold applied to the scalar value of a scalar dataset, the magnitude of a vector of a vector dataset, or the number of sensor points (and associated voxels, oriented surfaces, arrows, etc.) to be displayed.

[0198] A filtering threshold can be applied globally to the entire region / volume of interest, or it can be applied independently to specific local parts of the region / volume. Vector field values ​​require a lot of computational work to represent them on a display. Therefore, it is technically necessary to reduce the amount of vector information and extract only the useful components.

[0199] Different vectors can be averaged, e.g. Figure 5a This is shown in the 2D reduction in [1]. In this example, three different vectors pointing in different directions are replaced by a vector pointing in the average direction and having the average length. The program can then also represent only one of these average vectors instead of representing all vectors.

[0200] like Figure 5b Different vectors can also be projected onto defined directions as shown in . In this example, three different vectors pointing into different directions are replaced by the projection of each vector onto their average direction. In another case, as Figure 5c As shown, such a vector may be projected onto a horizontal plane, for example to retrieve a suggestion for the horizontal orientation of an object to be distributed / sized, which object will in any case be vertical, such as a typical case such as a window or a wall.

[0201] Different vectors pointing in different directions can also be projected onto the vertical plane defined by the horizontal orientation given by the user, for example to determine the vertical tilt of a photovoltaic panel placed on a facade with a predetermined horizontal orientation, such as Figure 5d shown.

[0202] This projection can be used, for example, to align photovoltaic panels on a building. Assume that the orientation of the main facade of a future building has been determined (e.g., aligned along a main street). This filter allows this specific location orientation angle (the angle of the street in the horizontal plane) to be provided via the GUI, and then a vector is projected onto a vertical plane perpendicular to the main facade. This projection allows the ideal elevation angle (the angle in this vertical plane) to be determined, which must be tilted upwards if the photovoltaic panel is also to be aligned horizontally with the facade (i.e., have two edges parallel to the facade).

[0203] Therefore, selecting the environmental datasets to be displayed, their combinations, their filtering, and their transformations provides a very powerful means of reducing the amount of displayed data while still providing the user with the relevant information they need, for example, when planning a new construction at a location or trying to identify an ideal location within an area. However, it is often difficult to decide in advance which filters and combinations should be applied in a specific situation or project.

[0204] To facilitate the task of selecting the best filters, combinations and transformations, the method can therefore provide interactive and iterative filtering, wherein a user enters a first filtering command, the resulting filtered 3D model is calculated and the corresponding 2D view is displayed, and the user can enter and apply a second filtering command (or a modification of the first filtering command) in order to calculate a second filtered 3D model and display a new 2D view. This interactive and iterative filtering and / or transformation method is also multi-stage, with the final output resulting from applying a first filtering stage to the independent environment data sets (before combining) and a second filtering and / or transformation stage to the combined environment data set (after combining). The effects of different filters, combinations and transformations at different levels can also be interrelated, as the result will depend on the interaction and combined effects of the entire set of calculations applied to the selected environment data set.

[0205] Some data sets may be dynamic and change over time, such as the hour of the day, the month of the year, the season, etc. The method may include selecting a particular time and displaying a modified view where the value or direction of each point corresponds to the value or direction at that time. Alternatively or additionally, the user may enter a time interval so that the average or summed value for each point during the time interval will be calculated and displayed.

[0206] The user can enter a coordinate interval, such as a range for one of the coordinates X, Y, or Z. Then, only the values ​​of the environmental dataset for points within that coordinate interval will be displayed. For example, the user can decide to display solar energy only at the highest level of the volume to verify where solar panels can be placed on a roof.

[0207] It is also possible to apply a filter command to only one such coordinate interval, or even to a single lower or upper boundary.

Claims

1. A method for generating a 3D model using new construction elements determined by values ​​of a multidimensional and multivariate environmental dataset of an urban location (U), comprising the following steps: a) Retrieve a 3D geographic dataset of the urban location with the shape of the terrain and possibly the shapes of buildings and / or vegetation; b) retrieving or calculating a plurality of independent environmental scalar and / or vector data sets at the urban location, the environmental data sets corresponding to a plurality of environmental fields of solar radiation energy, wind speed, noise sound pressure level and / or free volume / area or visibility ratio of target objects; c) generating a 3D model of the city location based on the values ​​of the 3D geographic dataset and the values ​​of the environment dataset; d) projecting the 3D model onto a 2D view and displaying the 2D view on a display so as to display values ​​from the 3D geographic dataset and values ​​from the environment dataset at a plurality of points; e) displaying a plurality of graphical user control elements on said display, wherein at least one graphical user element allows selection of one of at least two of said environment data sets; f) Select an environmental dataset; g) receiving a first filter command input by a user using one of said graphical user control elements for defining a first filter threshold to be applied to the selected environmental data set; h) generating a filtered 3D model, wherein values ​​of the 3D model that do not meet a first filtering threshold on the environment dataset are excluded; q) receiving a first transformation command input by a user using one of the graphical user control elements for defining a first transformation to be applied to the filtered model, generating a first transformed 3D model comprising construction elements whose positions, orientations and shapes are determined by the positions and scalar or vector values ​​of the filtered 3D model; r) Displaying the 2D projection of the transformed 3D model.

2. The method according to claim 1, further comprising: i) Displaying a 2D projection of the filtered 3D model.

3. The method according to claim 2, further comprising the following steps between steps h) and q): j) repeating steps f) to h) or f) to i) for at least a second independent environmental data set; k) combining values ​​of two or more different filtered independent environmental data sets to generate a combined environmental data set at the location; l) Generating a combined 3D model of an urban location, said combined 3D model combining values ​​of said 3D geographic dataset and values ​​of said combined environment dataset.

4. The method of claim 3 , wherein combining values ​​of two different environmental data sets comprises: normalizing the values ​​of the two different environmental data sets; and / or weighting the values ​​of the first environmental data set and the second environmental data set of the two different environmental data sets; and / or Logical and / or arithmetic combinations are applied between the weighted values.

5. The method according to claim 3 or 4, further comprising the following steps between steps 1) and q): m) projecting the combined 3D model onto a 2D view and displaying the 2D view on a display so as to show values ​​from the geographic dataset and values ​​from the combined environment dataset at a plurality of points.

6. The method according to any one of claims 3 to 5, further comprising the following steps between steps 1) and q): n) receiving an additional filter command input by a user using one of said graphical user control elements for defining a filter threshold to be applied to the combined environment data set; o) generating a filtered combined 3D model, wherein values ​​of the combined 3D model that do not meet a previous filtering threshold on the combined environment dataset are excluded; p) Displaying a 2D projection of the filtered combined 3D model.

7. The method according to claim 3, further comprising the following steps after step r): s) generating a second transformed 3D model comprising construction elements whose positions, orientations and shapes are determined by the positions and scalar or vector values ​​of the filtered or combined 3D models; t) combining the first and second transformed 3D models into a combined transformed 3D model; u) Displaying a 2D projection of the combined transformed 3D model.

8. The method according to any one of claims 1 to 7, wherein the generation of the transformed 3D model is based on commands input by a user, the commands being used to define one or more types of construction elements to be generated based on the selected filtered environment dataset.

9. The method according to any one of claims 1 to 8, wherein the generating of the transformed 3D model comprises generating 3D cells whose positions, orientations and shapes are determined by the positions and scalar or vector values ​​of the filtered 3D model.

10. The method according to any one of claims 1 to 9, further comprising the step of receiving user input of parameters and constraints of the construction element, and wherein the generation of the transformed 3D model comprises generating suggestions for construction elements based on the positions and scalar or vector values ​​of the filtered 3D model and the parameters and constraints.

11. The method according to any one of claims 1 to 10, wherein the 3D model is a time-dependent model, the method comprising the steps of: A specific time or time interval input by the user is received, and a value or direction of each point corresponding to the value at the specific time or the average or sum within the time interval is displayed.

12. The method according to any one of claims 1 to 11, comprising the steps of: A coordinate interval input by the user is received, and only the values ​​of the environment dataset of the points within the interval are displayed.

13. The method according to any one of claims 1 to 12, wherein a filtering threshold is applied to display only a sub-portion of the volume or region.

14. The method according to any one of claims 1 to 13, wherein one of the threshold values ​​is a numerical threshold applied to a scalar value of a data set or a modulus of a vector in a vector data set.

15. Method according to one of claims 1 to 14, wherein one of the filtering thresholds is applied to the entire region or volume, or independently to specific sub-portions thereof.

16. The method according to one of claims 1 to 15, wherein one of the filters involves reducing the region / volume of interest to the boundaries of the region / volume.

17. The method according to any one of claims 1 to 16, comprising the step of projecting a vector in the vector data set along a specific direction or plane.

18. The method according to any one of claims 1 to 17, comprising the steps of: Project the vectors of one of the vector datasets onto a horizontal plane or onto a vertical plane with a horizontal orientation defined by the user.

19. The method according to any one of claims 1 to 18, wherein one of the environmental data sets corresponds to the free visibility of each point of the data set in different directions.

20. The method according to any one of claims 1 to 19, comprising the steps of: The point is filtered based on the values ​​of neighboring points of the point in the environmental dataset.

21. The method according to any one of claims 1 to 20, comprising the steps of: A filter command is received, input by a user using the graphical user control element, the filter command being for averaging or summing scalar and directional values ​​of the environmental data set across a region, volume, or time interval.

22. The method according to any one of claims 1 to 21, comprising the step of receiving a command input by a user using the graphical user control element, said command being for hiding points that may be modified by future obstacles inside the volume itself, i.e. keeping only points on the volume boundary that will have constant values, independent of content that will potentially be inserted into the volume.

23. The method according to any one of claims 1 to 22, comprising the step of receiving a command input by a user using the graphical user control element to display only points whose distance from a user-specified object is less than a given distance.

24. The method according to one of claims 1 to 23, wherein combining the values ​​of two different environmental data sets involves performing a logical and / or arithmetic combination.

25. The method of one of claims 1 to 24, wherein combining values ​​of two different environment data sets involves determining a simultaneous influence on construction elements of the transformed 3D model without the values ​​being mathematically combined.

26. The method according to any one of claims 1 to 25, comprising the steps of: Save and / or restore a set of selection, filtering, and / or combination parameters as a preset.

27. The method according to any one of claims 1 to 26, comprising the steps of: Use the buttons on the graphical user interface to select the following items of results that have been used to generate the environmental data set: Sun Rays, Lines of Sight, Wind Streamlines, Sound Propagation Lines, Intersection Points, Reflection Points, and / or Diffraction Points.

28. A computer program product comprising instructions for causing a computer to carry out the method as claimed in any one of the preceding claims when the program is executed by the computer.

Images