A method for representing and interacting on a display with multidimensional and multivariate data sets corresponding to environmental variables for urban location selection.

Abstract

1. A method for representing on a display and interacting through filtering, combination and transformation of multidimensional and multivariate environmental datasets of an urban location (U), comprising the steps of: a) retrieving a 3D geographic dataset of the urban location along 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 datasets for said urban location, said environmental datasets corresponding to a plurality of environmental domains of solar radiant energy, wind speed, noise sound pressure level and / or free volume / area or visibility of target objects; c) generating a 3D model of the urban location based on values ​​of said 3D geographic dataset and values ​​of said environmental dataset; d) projecting said 3D model onto a 2D view and displaying said 2D view on a display to show values ​​from said 3D geographic dataset and values ​​of said environmental dataset at a plurality of points; e) displaying a plurality of graphical user control elements on said display, at least one of said graphical user elements allowing to select one of at least two of said environmental datasets; selecting one environmental dataset; g) receiving a first filtering command input by a user using one of the graphical user control elements to define a filtering threshold to be applied to the selected environmental dataset; h) generating a filtered 3D model in which 3D model values ​​on the environmental dataset that do not reach the filtering threshold are excluded; i) displaying a 2D projection of the first transformed 3D model; j) repeating steps f) to i) for at least a second independent environmental dataset; k) combining values ​​of two or more different filtered independent environmental datasets to generate a combined environmental dataset at the location; l)m) projecting the combined 3D model onto a 2D view and displaying the 2D view on a display to display values ​​from the geographic dataset and values ​​of the combined environmental dataset at a plurality of points; n) receiving a filtering command entered by a user using one of the graphical user control elements to define a filtering threshold to be applied to the combined environmental dataset; o) generating a filtered combined 3D model in which values ​​of the combined 3D model that do not reach a preceding filtering threshold on the combined environmental dataset are not displayed; and p) displaying a 2D projection of the filtered combined 3D model.

Description

[Technical Field]

[0001] The present invention relates to a method for representing and interacting with multiple data sets corresponding to environmental variables in urban location selection. [Background technology]

[0002] Designing healthy and sustainable buildings in urban environments is one of our society's most important challenges. Physical characteristics related to sunlight, views, noise, airflow, pollution, and other environmental factors are crucial to human comfort, health, and sustainability. Therefore, to fully understand these physical phenomena, it is important to conduct accurate environmental analyses of local urban contexts.

[0003] Over time, site analysis became a typical stage in the building design process, dedicated to studying the climatic, geographical, historical, legal, and infrastructural aspects as well as the environmental aspects of the site. Designers and engineers developed tools to analyze and map site-related information long before the advent of computer technology. With regard to environmental information, the typical approach consisted of retrieving meteorological data in the form of time charts in which variables such as temperature, humidity, solar radiation, wind speed, and rainfall were plotted over annual or daily cycles.

[0004] Of these graphic tools, the sun chart is perhaps the most widespread and exists in a range of different configurations according to several types of geometric projections. Furthermore, some tools, such as psychrometric or bioclimatic charts, allow the setting of these climate variables in relation to human comfort.

[0005] Today, many of these methods are integrated with meteorological databases within architectural 3D modeling programs, so that simply specifying the geographic location of a site makes it possible to retrieve representations such as sun maps, radiation maps, or wind roses with a simple click. After the site analysis stage, the architect / designer usually integrates the resulting relevant information in the form of a graphic sketch, typically a top-view, that sets out the environmental characteristics of the site in relation to the physical properties of the site in terms of zoning, topography, and the built environment. This representation is then often used as a starting point for developing an environmental strategy during the conceptual design stage.

[0006] Generally, these graphical tools are very suitable for studying the environmental resources of simple sites. In fact, if the environmental resources are fairly homogeneously distributed throughout the site, the analysis process can be simplified to a single entity, typically the center point of the plot.

[0007] However, when the subject of study is a more complex urban site and / or located in a critical geomorphological context, most of these tools are quite difficult to achieve, especially in the presence of nearby obstacles.

[0008] To address this issue, many software tools have been developed. These allow for the analysis of environmental resources based on digital simulations, information about the proximate situation, and early sketches of architectural solutions. However, these early design building simulation and optimization software suffer from a chicken-and-egg problem: surface-based digital building sketches always require environmental simulations (e.g., related to solar radiation, lines of sight, airflow, or noise propagation), while the goal is to design the building based on the results of the simulation. The associated single- or multi-objective heuristic processes are thus highly dependent on the initial constraints set by the user and can only function within very specific boundaries.

[0009] Similarly, more recent AI-powered automated simulation and optimization solutions or AI-powered environmental building configurators are also self-referential and / or retrospective. Thus, while they may help achieve some results faster, they can do little to assist users in generating truly innovative and better solutions because they are still deeply tied to the initial definitions and constraints set by the user and thus to old design and decision paradigms. Furthermore, AI-based solutions are often based on black-box systems, leaving users completely uninformed about what makes the proposed solution so performant.

[0010] There have been software attempts to move away from the "initial design" stage of modern software solutions to the "pre-design" stage of traditional graphics tools. Some of these attempts are based on a bottom-up approach, where different environmental variables are determined for a volumetric set of sensor points representing the open space of a site. However, these attempts have failed to produce breakthrough solutions due to the lack of a simple method for handling the inherently very high degree of variation and dimensionality.

[0011] A comprehensive volumetric site analysis method has been proposed to simultaneously address the need for a joint assessment of multiple environmental resources in its full temporal and spatial dimensions, with the aim of enabling the assessment of the primary potential of urban land directly from the specificities of the resources present within all different site spaces in space and time. This technique is based on the recent availability of very high-resolution 3D geographic datasets, along with information about the exact geometry of the terrain, buildings, and vegetation. Based on this data, additional environmental datasets can be extracted or calculated through simulations and added to this geographic dataset, which can then be displayed to the user through a 3D visualization framework.

[0012] Within this visualization framework, a series of volumetric environmental domains are then represented in 3D. Typical variables of such environmental datasets relate, for example, to solar radiation, views, wind, and noise. The ultimate goal of this type of environmental information is to provide leading proposals that are perfectly adapted to local conditions in relation to the final goals of architectural design, construction engineering, energy technology, land planning, urban planning, and real estate. It is therefore a technical tool used during the pre-design phase of a project.

[0013] However, this technique still does not offer practical usability due to the sheer volume of data generated and the complexity of its representation and interpretation. The results generated through the described process constitute complex multidimensional (x, y, z, t) and multivariate (v, u, w, ...) datasets that can have both scalar (v) and vector (vx, vy, vz) structures and are very difficult to interpret. Furthermore, due to the amount of information and the multiplicity of parameters involved, a direct, comprehensive and connected understanding of these datasets is beyond the reach of humans, and establishing correlations between the different variables and their parameters of interest is extremely difficult.

[0014] Below, we list some identified existing prior art documents in the related field.

[0015] US Patent Application Publication No. 2022 / 0198084 relates to solar panel positioning software. It describes irradiance heat maps for various locations, such as on rooftops. A threshold value can be input on the GUI so that the system can recommend one or more suitable panel installations. This document fails to consider the shape of the terrain and is therefore not suitable for mountainous regions where mountains cast shadows on buildings. Furthermore, it fails to consider environmental data sets other than solar irradiance.

[0016] US Patent Application Publication No. 2021 / 0110156 is very similar to US Patent Application Publication No. 2022 / 0198084, but it does consider the effects of adjacent buildings, trees, etc. on solar irradiance.

[0017] L. Jiaming et al., "An open-source 3D solar radiation model integrated with a 3D, geographic information system," ENVIRONMENTAL MODELLING & SOFTWARE, published December 10, 2014, is another publication related solely to solar irradiance modeling.

[0018] 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 does not disclose filtering data, especially when the amount of data to be displayed is very large.

[0019] Giraldo Gabriel et al., "Towards a sensitive Urban Wind Representation in Virtual Reality," published April 6, 2022, describes the representation of wind vectors in a virtual volume. [Prior art documents] [Patent documents]

[0020] [Patent Document 1] US Patent Application Publication No. 2022 / 0198084 [Patent Document 2] U.S. Patent Application Publication No. 2021 / 0110156 [Non-patent literature]

[0021] [Non-Patent Document 1] L. Jiaming et al., "An open-source 3D solar radiation model integrated with a 3D, geographic information system," ENVIRONMENTAL MODELLING & SOFTWARE, published December 10, 2014 [Non-patent document 2] Murshed Syed Monjur et al., “Modelling, validation and Quantification of Climate and other Sensitivities of Building Energy Model on 3D City Models” [Non-patent document 3] Giraldo Gabriel et al., "Towards a sensitive Urban Wind Representation in Virtual Reality," published April 6, 2022 Summary of the Invention [Problem to be solved by the invention]

[0022] Therefore, the majority of existing prior art is concerned with the analysis of a single environmental parameter, often related to the surface of a 3D roof / building / city model, which is sometimes used to optimize the installation of components on an existing building or building design.

[0023] The object of the present invention is to provide a new method for displaying and interacting with complex, large, multidimensional and multivariate datasets corresponding to environmental variables in urban location selection, which provides significant advantages for the manipulation of such datasets. [Means for solving the problem]

[0024] According to the invention, this object is achieved by the objects of the attached independent claims and is further detailed in the dependent claims.

[0025] Over what is known in the art, the present invention offers the advantage that high-level dimensions and variables and their potential correlations and / or relationships to specific project goals can be easily manipulated, combined, reduced, processed, and displayed to extract useful information.

[0026] According to one aspect, the invention relates to a method comprising the steps of claim 1.

[0027] The method thus provides an iterative, interactive, multi-layered and interrelated filtering and combination method for processing multi-dimensional environmental datasets.

[0028] The method is multi-tiered as it allows filtering of datasets both at the level of the independent environmental datasets and at the level of the combined environmental datasets.

[0029] The filtering can also be interrelated, as the effects of these different filters applied at multiple levels can be directly combined, and constraints such as thresholds, averages, projections, etc. can be updated in real time along the filtering process to produce the final result.

[0030] The method may include the following features: 1. The environmental variables of the method relate to the void represented by the 3D sensor points; 2. Analysis of multiple layers of environmental information; 3. A combination of multiple such environmental variables; and / or 4. Filtering of combined datasets.

[0031] The unexpected and hidden patterns revealed by this method make it possible to generate highly impactful added value that is highly specific 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 internal subdivisions, energy and plant issues, urban area planning, the identification of parcels with specific environmental characteristics or real estate valuations.

[0032] Depending on the environmental dataset, this method may be used to represent, for example, a spatial point in a city location that simultaneously has the highest solar radiation energy, the lowest wind speed, the lowest traffic noise sound pressure level, and the highest or best visibility. This could be used, for example, by architects and urbanists to plan excellent site observations or urban development, construction, or renovation. In another use case, this could be used, for example, to plan the installation of photovoltaic panels on a building to optimize solar energy production while avoiding the installation of PV surfaces in locations exposed to high winds while also using the PV surfaces as noise or sun shelters. In another use case, this could be used to position a balcony in a location that simultaneously has good access to evening sunlight, a high lake view rate, low evening traffic noise, and airflow at speeds within an ideal range.

[0033] For purposes of this disclosure, a multidimensional dataset is a set of data values ​​that may have both scalar (v) and vector (vx, vy, vz) structure and multiple dimensions, e.g., (x, y, z, t), etc.

[0034] For purposes of this disclosure, a multivariate data set is a set of data values ​​for different physical properties (u, v, w), possibly quantified in different units of measurement.

[0035] For purposes of this disclosure, an environmental dataset is a dataset intended to represent environmental variables such as solar radiation, wind speed and direction, visibility, noise levels, and the like.

[0036] For purposes of this disclosure, a scalar dataset is a set of scalar values, for example, a set of sampled, digitized values ​​of an environmental region representing a region or volume of interest.

[0037] For purposes of this disclosure, a vector dataset is a set of vectors, e.g., a sampled, digitized set of vectors of an environmental region representing a region or volume of interest, where the value of each vector depends on all of its components and therefore both its dimension and direction.

[0038] For purposes of this disclosure, combining values ​​of two different environmental datasets involves performing a logical and / or arithmetic combination between each pair of corresponding scalar or vector values ​​from the two datasets.

[0039] Because the datasets are multivariate, it is possible that values ​​in different environmental datasets may have different units of measurement. For example, one dataset corresponding to scalar values ​​in the solar radiant energy domain may be expressed in J / m 2 It is believed that the first data set corresponding to the wind speed region could contain values ​​reported in m / s, while the second data set corresponding to the wind speed region could contain values ​​reported in m / s.

[0040] Thus, a combined environmental dataset is considered to potentially contain, for each point, values ​​that are a logical and arithmetic combination between values ​​from two different datasets, the values ​​of which may be expressed in different units.

[0041] It is contemplated that combining values ​​reported in different units may include normalizing the values ​​to convert them to unitless numbers. In one embodiment, it is contemplated that combining the values ​​may include normalizing each value, for example, by reporting them within a range of 0 (minimum) to 100 (maximum), or any other normalized interval.

[0042] It is contemplated that combining the values ​​may include weighting each value, such as by multiplying the scalar and / or vector values ​​at each point by a weighting scalar factor. It is contemplated that the weighting factors may be set by a user or may be predefined.

[0043] It is contemplated that combining values ​​may include performing a logical combination such as AND, OR, XOR or NOT combinations.

[0044] It is contemplated that combining values ​​may include performing arithmetic combinations, such as multiplication and addition, averaging, differences, etc., between values ​​from two or more different environmental data sets.

[0045] Combining values ​​from different environmental datasets, possibly pre-filtered, can also allow such values ​​to simply affect different parts of the joint 3D visual representation simultaneously, without being arithmetically combined.

[0046] The filtering may be entered using graphical user control elements such as buttons, sliders, rotary knobs, text entry boxes, or any other control on a graphical user interface (GUI).

[0047] It is believed that at least some of the different 3D models may be time-dependent, i.e. dynamic, models in which the values ​​at each point may vary over time (hour of the day, month, etc.).

[0048] The method may include receiving a specific time entered by a user and displaying a scene modified with values ​​at each point corresponding to the values ​​at the specific received time.

[0049] The method may include receiving a time interval entered by a user and displaying the scene modified with values ​​at this point corresponding to the average or sum of the values ​​at each point during said time interval.

[0050] The method may include receiving a coordinate interval entered by the user and displaying only values ​​of the environmental dataset for points that fall within the interval, where it is contemplated that a coordinate interval may include ranges for one or more dimensions (x, y and / or z).

[0051] The method may include receiving the user selected resolution value and adapting the spatial distance between points depending on the resolution.

[0052] One filtering threshold may be a numerical threshold applied to the scalar values ​​of the dataset or the dimensions of the vectors in a vector dataset.

[0053] One filtering threshold may be a numerical threshold applied to the number of area / volume units located at each sensor point location to be displayed.

[0054] A single filtering threshold may be a lower boundary, an upper boundary, or a range between the lower and upper boundaries.

[0055] A single filtering threshold may be applied to the entire region or volume, or may be applied independently to specific sub-portions thereof, such as smaller regions of a larger region (e.g., independently to municipalities of a larger region) or smaller volumes of a larger volume (e.g., independently to all points located at the same horizontal height of a volume).

[0056] One filter may involve, for example, reducing the area(s) / volume(s) in question to edges that enclose the area(s) / volume(s) using convex and / or concave hulls (e.g., displaying the edges of an area of ​​land, the edges of a building volume, or the edges of a floor slab, etc.).

[0057] Other types of filters may also be applied, for example, a threshold may be used within the vector domain to filter only vectors pointing in one particular direction or range of directions.

[0058] Other filters may replace displayed scalar values, dimensions or directions with average values ​​over areas, volumes and / or time intervals.

[0059] Other filters may allow for the determination of whether to display a scalar value, the dimension of a vector, or the ratio between these two values, for example using a color or grayscale gradient.

[0060] The method may include projecting the vectors of the vector data set along one particular direction or onto a particular plane.

[0061] For example, the method could involve projecting vectors along their average direction.

[0062] For example, the method could involve the projection of a vector onto a horizontal plane, which could make it possible to orient vertical surfaces, such as the surface of a window or facade.

[0063] For example, the method may include projecting one vector of the vector data set onto a vertical plane with a user-defined horizontal orientation, which could make it possible to derive, for example, an ideal vertical tilt of photovoltaic panels for an urban building project with a pre-defined / constrained orientation of the main building facade.

[0064] One of the environmental datasets may represent visibility in different directions. Free visibility from a point may be expressed as a percentage of the unobstructed area or volume around the point, for example as a fraction of a horizontal circle around the point, as a fraction of a sphere, or as a fraction of a spherical sector.

[0065] Target visibility may be expressed as the ratio between the field of view occupied by the target object and the full spherical field of view, e.g., landscape views with water objects are usually preferred over landscape views with industrial objects.

[0066] The method may include filtering a point in one of the combined data sets according to the values ​​of its neighboring points.

[0067] Control elements may be used to filter points not only on their own value but also according to the values ​​of their neighboring points (e.g., selecting only elements for which a certain condition is valid for at least two of their neighboring points).

[0068] The method may include receiving a command entered by a user using said graphical user control element to hide points that are considered to be susceptible to modification by future obstacles inside the volume itself, i.e., to keep only points on the boundary of the volume that will have a constant value independent of what is potentially inserted inside the volume.

[0069] The method may include receiving a command entered by a user using a graphical user control element to display only points close to an object defined by the user, i.e., to retain only points that are within a given distance (e.g., 1 m) from the surface of said object.

[0070] The method may include saving and / or retrieving a set of selection, filtering and / or combination parameters as a preset, so that the preset can be easily retrieved and applied to different environmental datasets and / or different urban location locations thereafter.

[0071] The graphical user interface may include buttons that allow the user to visualize the geometric operators that have been used to generate the resulting environmental dataset. These geometric operators that can assist the user in the filtering process may include, for example, sun rays, line of sight, airflow lines, sound propagation lines, target-object, obstacle-object, light-emitting-object, intersection points, reflection points, and diffraction points.

[0072] The graphic user interface may include a controller for displaying a single spatial sector of said set of geometric operators (e.g., a ray or a multiline) and / or for also displaying the results of a collection of selections of such sectors.

[0073] The graphic user interface may include 2D camera images of the 3D model, which may be constructed in different types of projections and viewed from different perspectives, making it possible to visualize detailed information related to the shape and / or values ​​of each of these geometric operators, assisting the user in the interpretation and / or filtering process.

[0074] The graphic user interface may include 2D color or grayscale heat maps that allow visualization of detailed information related to the shape and / or values ​​of each of these geometric operators, assisting the user in the interpretation and / or filtering process and in identifying global and / or local maxima and minima among the values ​​of the operators. 2D sliders placed over these 2D camera images or heat maps may assist the user in selecting such particular geometric operators or ranges of such operators.

[0075] Filtering transformations can allow users to convert the data used to generate abstract or semi-abstract visual representations into refined plans related to more concrete proposals for the design of buildings. The 3D design proposals can be based on cellular plans (i.e., composed of an aggregation of multiple cells of space representing, for example, a single room), and / or single-building plans (representing sketches at the level of the entire building), and / or multi-building and / or infrastructure plans.

[0076] The invention also relates to a computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method of one of the preceding claims.

[0077] Exemplary embodiments of the invention are disclosed herein and illustrated by the following drawings. [Brief explanation of the drawings]

[0078] [Figure 1] 1 illustrates a 2D representation of a 3D volume corresponding to a geographic dataset of a city location with terrain and building shapes. [Figure 2] 1 illustrates the same representation with several graphical user control elements for selecting which environmental datasets to display, which combinations between environmental datasets to display, which filters to apply, and which type of representation to use. [Figure 3] 1 illustrates a 2D representation of the terrain surface from a 3D geographic dataset of a city location. [Figure 4a] Illustrates various 3D visualization elements for realizing environmental values ​​on a 2D view. [Figure 4b] Illustrates various 3D visualization elements for realizing environmental values ​​on a 2D view. [Figure 4c] Illustrates various 3D visualization elements for realizing environmental values ​​on a 2D view. [Figure 4d] Illustrates various 3D visualization elements for realizing environmental values ​​on a 2D view. [Figure 4e] Illustrates various 3D visualization elements for realizing environmental values ​​on a 2D view. [Figure 5a] 1 illustrates different methods for reduction of the directional parts of a tensor. [Figure 5b] 1 illustrates different methods for reduction of the directional parts of a tensor. [Figure 5c] 1 illustrates different methods for reduction of the directional parts of a tensor. [Figure 5d] 1 illustrates different methods for reduction of the directional parts of a tensor.

[0079] Geodata source for Figures 1–3: Swiss Federal Office of Topography swisstopo. DETAILED DESCRIPTION OF THE INVENTION

[0080] For the purposes of this disclosure, urban location U refers to any site or area where an environmental analysis needs to be or has been performed with the aim of deriving decisions and / or design proposals related to the location, amount, size, direction and / or form of intervention for a specific purpose. Urban location U can refer to a 2D or 3D area of ​​land or a 3D volume of land (see FIG. 1). The interventions targeted in urban location U typically relate to: ■ Land planning, urban planning or urban design (zoning, urban development plans, public spaces and infrastructure, mobility infrastructure, energy plants, etc.); ■ Real estate strategies and projects (site observation, evaluation, design of large-scale urban developments, use, function, distribution of buildings or living units); ■ The location, orientation, proportions and form of the building; ■ External building surfaces and building components (transparent surfaces, windows, openings, facades, roofs, external awnings, balconies, wind shelters, sun shelters, noise shelters, view shelters, photovoltaic surfaces, thermal surfaces, wind turbines, ventilation hatches, heat exchangers, etc.); ■ Distribution of uses and functions within the building (shape and location of living units, shape of floor plan, sizing of rooms, etc.).

[0081] According to one embodiment, the method of the present invention can be used as a simulation method adapted to generate and display a 3D model of an urban location U at a pre-design or pre-decision stage, i.e., taking into account environmental data. Although the original model of the urban location may include existing and planned objects, the method does not require pre-modeling of planned urban objects; rather, it can be used to extract crucial environmental proposals, prior to the conception process, that should be used to start the conceptual process in a new way. Thus, the urban location U can be any vacant space within a city or abroad, or an existing space or area to be modified, renovated, renovated, etc.

[0082] According to one embodiment, the method relies on discretizing the unoccupied space of a site / area into a matrix of sensor points, or voxels 11. 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 ​​can be expressed as scalars (v) or vectors (v x , v y , v z) structure and stored as a dataset according to 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 to form a 3D model, which the user can access through visualization on a display. Different values ​​at each sensor point may be represented, for example, by different colors, numbers, arrows, etc. (not shown in Figures 1-3). The location of the city is defined at least by the 3D shape of the ground (which may in some cases be flat), and may be complemented by the 3D shapes of buildings and / or the 3D shapes of associated vegetation.

[0083] The location of the city may be represented by a 3D geographic dataset, i.e., a set of numbers representing the shape of the terrain and possibly buildings and / or vegetation. The 3D geographic dataset representing the location of the city can be collected from geodata providers, retrieved from map databases, from architects' designs, and / or from 2D and 3D images. This dataset may represent at least the shape of the terrain. Existing and / or proposed buildings and / or vegetation may also be represented by this dataset.

[0084] For example, the 3D geographic dataset may represent a three-dimensional profile of the ground surface 10, including hills, slopes, slopes, mountains and any other terrain that may be considered. The presence of natural or man-made objects such as trees, rivers, buildings and infrastructure already present in the city site selection may also be taken into account.

[0085] An example of a representation on a display of a city location U according to a 3D geographic dataset is shown in Figure 1. In this example, the 3D geographic dataset is represented by a mesh of triangular surfaces. The 3D geographic dataset itself is stored as a set of values, e.g., a set of sampled values, in computer memory.

[0086] The method of the present invention also requires multiple environmental scalar and / or vector datasets in urban location. The environmental datasets are numerical representations of multiple environmental domains such as solar radiation, wind speed, noise sound pressure level, and / or free volume / area or visibility of target objects. The environmental datasets can be static or dynamic, i.e., they change over time.

[0087] The environmental datasets may already be available and may be retrieved, for example, from a database. They may be physically determined on the site, for example, by appropriate observations or measurements. They may be calculated, for example, using known simulation or prediction tools. Each environmental dataset may contain or be used to determine values ​​of environmental domains at multiple points in the city's location.

[0088] The different environmental datasets may correspond to different environmental regions, for example annual, monthly or hourly solar radiation or time, and / or wind speed, wind direction, air pressure, turbulence intensity, and / or noise sound pressure level, and / or visibility of open space (free part of the volume or area around the observation point), and / or visibility of target objects (lakes, green areas, monuments, unsightly industrial areas, etc.). These environmental datasets can be obtained for a single situation or for multiple situation scenarios (present or future, with or without vegetation, etc.).

[0089] Some environmental datasets may correspond to sets of environmental scalar values ​​at different points in an area / volume, for example, one environmental dataset may represent noise levels at different points in an area / volume.

[0090] Some environmental datasets may correspond to sets of environmental vector values ​​at different points in an area / volume, for example, one environmental dataset may represent the amplitude and direction of wind or solar energy at different points in an area / volume.

[0091] Different data sets may display values ​​in different units, for example, noise levels may be displayed in decibels, solar energy in J / m 2 / y units; wind speed in m / s units; and visibility in percentage units.

[0092] The values ​​of an environmental dataset can be normalized, such as by expressing them on a scale from a minimum value (e.g., 0) to a maximum value (e.g., 100). Normalization allows for the combination of datasets with values ​​having different units of measurement, as explained below.

[0093] To perform the combination, the values ​​of the different environmental datasets can be weighted by multiplication with a scalar weighting value. The weighting value can represent the importance of one particular dataset in relation to other datasets. The weighting value applied to one particular dataset can be predefined. It can be defined by the user. It can be saved in or retrieved from a preset.

[0094] Values ​​from different environmental data sets that may have been previously filtered are also combinable due to the fact that these values ​​simultaneously affect different parts of the joint visual representation without being mathematically combined, which may involve precedence rules.

[0095] Each of the environmental datasets can be selected, filtered, manipulated, and displayed independently. The filtering process can be iterative. For example, a first filter can be applied to the environmental dataset to produce a filtered 3D model. Then, a second filter can be applied to the filtered 3D model, resulting in a second filtered 3D model with two different filters applied.

[0096] Two different environmental datasets can be combined into one combined environmental dataset by combining possibly normalized and possibly weighted values ​​of each dataset at each sampling point of an area / volume. The user can select which environmental datasets they want to combine. At each sampling point, the combined environmental dataset thus stores values ​​according to a combination of different environmental variables. For example, the combined environmental dataset can display at each point one combined value that displays both the amount of solar energy and wind speed on a normalized scale.

[0097] In another example, two different environmental datasets that have previously been filtered are simply displayed together, independently contributing to the overall visual presentation.

[0098] With respect to the original environmental datasets, the combined environmental dataset can be filtered, manipulated, and displayed separately and / or independently. The method is therefore multi-layered, as it allows for filtering and possibly transforming datasets both at the level of the independent environmental datasets and at the level of the combined environmental dataset. The interactive filtering process can also be iterative. Moreover, filtering can be interrelated, i.e., a filter applied to one environmental dataset can automatically affect any other filters applied to such dataset or to the combined environmental dataset with which it is combined.

[0099] Furthermore, it is possible to input several predetermined basic parameters corresponding to the characteristics of an analysis to be performed or an intervention to be realized, such as the number of storeys of the city buildings to be realized, or the minimum surface of the ground to be occupied, or the main orientation of the city objects, or the minimum surface area of ​​the solar panels to be distributed, or the maximum acceptable sound level. Such basic parameters may be determined by the underlying project requirements, by project constraints, by regulations, may result from specific standards, arise from customer requests, or may originate from any source. Such basic parameters therefore appear as the original constraints to be taken into account in the evaluation of the city's location.

[0100] 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 values ​​of the 3D geographic dataset and values ​​of the environmental dataset at different points throughout the area / volume of the location. Thus, the combined 3D model of the location displays geographic parameters of the environment (ground, buildings, vegetation, etc.) and one or more environmental values, and / or combined environmental values, at multiple points of the area / volume.

[0101] The 3D model, or combined 3D model, is then projected onto a 2D view that can be displayed on a display, such as a computer display, as shown in Figure 2. The interface may include graphic user interface elements 20-23 for selecting, combining, filtering, and transforming visualizations and other commands for configuring the 2D view by projection plane, e.g., zooming, rotating, translating, etc. In the example of Figure 2, the underlying 3D geographic dataset includes ground 10, buildings 13, and a grid of orthogonal sensor points represented by voxels 11, while on top of this view an environmental dataset is represented using grayscale levels or textures 110 at each point or voxel 11.

[0102] Such a visual representation makes it possible, for example, to easily identify the parts of a city location that receive the most solar radiation, either at a particular time of day or as an average over a certain time interval. For example, solar radiation during the summer can be represented according to such a graphical representation.

[0103] The displayed 2D view therefore shows values ​​from the geographic dataset (terrain and possibly buildings and / or vegetation of the environment) and values ​​or directions of selected or combined environmental datasets at multiple points.

[0104] The display may be part of a computer that includes a keyboard and / or other input means, a processor, memory, and a computer program for computing and presenting the 2D view, the computer program including a graphic user interface that allows a user to select the environmental dataset or combined environmental datasets that they wish to view, manipulate, and filter.

[0105] Environmental datasets (including combined environmental datasets) may be represented on a 2D view using various visualization elements 23. For example, the dimensions of scalar and vector values ​​may be displayed as color voxels (FIG. 4a), points, polygonal shells or surfaces, gray levels, or numbers shown next to each sampling point or voxel 11, etc. The direction of vector values ​​may be displayed using arrows and / or oriented surfaces (FIGS. 4b and 4c, respectively), or using oriented volumes (FIGS. 4d and 4e), etc.

[0106] 3D models, and combined 3D models, may include a very large number of sampling points, for example, more than 1000 or more than 100,000. Multiple environmental values, including scalar and / or vector values, may be represented at each point. Therefore, due to the sheer number of scalar values ​​and / or vectors to observe, simultaneous 2D projections of the 3D model on a display may be impossible, and interpretation of multiple parallel or simultaneous 2D projections may be extremely difficult. Therefore, there is a need to reduce the amount of environmental values ​​to be displayed and to correlate the content of different variables and different dimensions with each other while also correlating that content with the requirements and constraints of the current analysis.

[0107] A first way to reduce the amount of environmental values ​​to be represented is to increase the sampling step, i.e., reduce the number of sampling points. However, reducing the sampling resolution may result in a less accurate representation of the 3D model. A graphic user interface command element (not shown) may be used to select the resolution.

[0108] Another way to reduce the amount of environmental values ​​to be represented is to select environmental data sets to be represented and exclude others. As an example, in Figure 2, the graphic user interface includes one element 20 for selecting which of the following data sets need to be calculated and displayed: solar radiation; noise level; and wind speed.

[0109] Another way to reduce the amount of environmental values ​​to be represented is to combine different environmental datasets into one combined environmental dataset, thereby reducing the amount of visual elements to be displayed. As an example, in FIG. 2, the graphic user interface can include an element 21 for selecting the combination logic and the environmental datasets to be combined, and for representing the combined value at each point with a single visualization element. It is possible to combine different types of environmental datasets with values ​​in different units of measurement. Many combinations other than those shown in this example are possible. Furthermore, weighted combinations can be defined in the user interface, for example, to give one environmental dataset more weight than another.

[0110] Another way to reduce the amount of environmental data sets to be represented is to filter the environmental data sets or combined environmental data sets to display only values ​​that satisfy a filtering condition. As an example, in Figure 2, the graphic user interface includes one element 22 for selecting and / or controlling a filter to be applied to a selected environmental data set or combined environmental data set. The filter to be applied to the environmental data set or combined environmental data set can be associated with any type of graphic user interface controller, such as a button, a slider, a rotary knob, a text entry box, etc.

[0111] The filtering may be based on a threshold, such that only values ​​above or below the threshold are 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 values ​​that are false.

[0112] Threshold-based filters can be applied to scalar values. Threshold-based filters can also be applied to vector values. In that case, a scalar threshold can be applied to a vector dimension, for example, to display only values ​​for points in the dataset where the wind speed or any other vector dimension is higher than a given threshold, and / or to a direction, for example, to display visualization elements only for points where the wind is blowing in one particular direction or range of directions.

[0113] One filtering threshold may be a numerical threshold applied to scalar values ​​of a scalar data set, to the dimensions of vectors of a vector data set, or to sensor points (and associated voxels, oriented surfaces, arrows, etc.) to be displayed.

[0114] A filtering threshold may be applied globally to the entire region / volume of interest, or it may be applied independently to specific local parts of this region / volume. Vector region values ​​require a lot of computational effort to represent them on a display. Therefore, it is technically essential to reduce the amount of vector information and extract only the useful components.

[0115] Different vectors can be averaged, as illustrated by the 2D simplification in Figure 5a. In this example, three different vectors pointing in different directions are replaced by a vector of average length pointing in the average direction. Then, instead of representing all of these averaged vectors, the program can represent only one of them.

[0116] It is also possible to project different vectors in defined directions, as illustrated in Fig. 5b. In this example, three different vectors pointing in different directions are replaced by the projection of each vector in their average direction. In another case, as illustrated in Fig. 5c, such vectors could be projected onto a horizontal plane in order to extract a suggestion for the horizontal orientation of the object to be distributed / sized, which in any case would be vertical, as is typical for windows or walls, for example.

[0117] As illustrated in Figure 5d, it is also possible to project different vectors pointing in different directions onto the vertical plane defined by the horizontal orientation given by the user, for example to determine the vertical tilt of a photovoltaic panel to be installed on a facade with an already predetermined horizontal orientation.

[0118] This projection could be used, for example, to align photovoltaic panels on a building. Imagine that the orientation of the main facade of a future building has already been determined (e.g., aligned along a main street). Such a filter would provide this specific azimuthal orientation angle (the angle of the roadway on a horizontal plane) via a GUI, and then allow a vector to be projected onto a vertical plane perpendicular to this main facade. This projection would allow determining the ideal elevation angle (the angle on this vertical plane) at which these photovoltaic panels should be tilted upward if they are desired to remain horizontally aligned with the facade (with two edges parallel to this facade).

[0119] Thus, the selection of environmental datasets to display, their combination, and their filtering and transformation provide a powerful means for reducing the amount of data displayed, while still providing the relevant information a user needs when planning a new building, for example, at a site where the user is trying to identify an ideal site location within a territorial area. However, it is often difficult to determine in advance which filters and combinations to apply in a particular situation and project.

[0120] Thus, to facilitate this task of selecting the best filters and combinations, the method provides interactive and iterative filtering in which a first filtering command is entered by a user to calculate a second filtered 3D model and display a new 2D view, the resulting filtered 3D model is calculated, the corresponding 2D view is displayed, and a second filtering command (or a modification of the first filtering command) can be entered and applied by the user. This interactive and iterative filtering method is also multi-layered, with the final output resulting from the application of a first filtering level (pre-combination) to the independent environmental datasets and a second filtering (post-combination) to the combined environmental dataset. The effects of different filters at different levels may be interrelated in the sense that the results will be governed by the mutual and combinatorial effects of the entire set of filters applied to the selected environmental datasets.

[0121] Some of the data sets may be dynamic and change over time, such as by hour of the day, month, season, etc. The method may include selecting a particular time and displaying a modified view in which the value or direction at each point corresponds to the value or direction at that time. Alternatively or additionally, the user may input a time interval so that an average or sum of the values ​​at each point during the time interval is calculated and displayed.

[0122] 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 data set for points within that coordinate interval will be displayed. For example, the user may decide to display solar energy only on the highest level of a volume to see where solar panels could potentially be placed on a roof.

[0123] It is also possible to apply one filtering command to only one such coordinate interval, or even to a single lower or upper boundary. [Explanation of symbols]

[0124] 10 ground 11 Voxels 13 Building 20 Graphic User Interface Elements 21 Graphic User Interface Elements 22 Graphic User Interface Elements 23 Graphic User Interface Elements

Claims

1. 1. A method for representing on a display and interacting through filtering and combination of multidimensional and multivariate environmental datasets of an urban location (U), comprising: a) retrieving a 3D geographic dataset of the urban location with the shape of the terrain and possibly the shape of buildings and / or vegetation; b) deriving or calculating a plurality of independent environmental scalar and / or vector data sets in said urban location, said environmental data sets corresponding to a plurality of environmental domains of solar irradiance, wind speed, noise sound pressure level, and / or free volume / area or visibility 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 environmental dataset; d) projecting the 3D model onto a 2D view and displaying the 2D view on a display to display values ​​from the 3D geographic dataset and values ​​of the environmental dataset at a plurality of points; e) displaying a plurality of graphical user control elements on said display, at least one of said graphical user elements enabling selection of one of at least two of said environmental data sets; f) selecting one environmental dataset; g) receiving a first filtering command entered by a user using one of said graphical user control elements to define a filtering threshold to be applied to a selected environmental data set; h) generating a filtered 3D model in which values ​​of the 3D model that do not reach a filtering threshold on the environmental dataset are excluded; i) displaying a 2D projection of the filtered 3D model; j) repeating f) through i) for at least a second independent environmental data set; k) combining values ​​of two or more different filtered independent environmental datasets to generate a combined environmental dataset for said location; l) generating a combined 3D model of the city's location, said combined 3D model combining values ​​of said 3D geographic dataset and values ​​of said combined environmental dataset; m) projecting the combined 3D model onto a 2D view and displaying the 2D view on a display to display values ​​from the geographic dataset and values ​​of the combined environmental dataset at a plurality of points; n) receiving a filtering command entered by a user using one of said graphical user control elements to define a filtering threshold to be applied to the combined environmental dataset; o) generating a filtered combined 3D model in which values ​​of the combined 3D model that do not meet a previous filtering threshold on the combined environmental dataset are excluded; p) displaying a 2D projection of the filtered combined 3D model; A method comprising:

2. The step of 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 and second of said two different environmental data sets; and / or applying logical and / or arithmetic combinations between said weighted values; The method of claim 1 , comprising:

3. 3. The method of claim 1 or 2, wherein the 3D model is a time-dependent model, the method including the step of receiving a specific time input by the user and displaying a value or direction at each point corresponding to the value at the specific time.

4. 4. The method of claim 1, wherein the 3D model is a time-dependent model, the method comprising the steps of receiving a time interval entered by the user and displaying a value at each point corresponding to an average or sum of the values ​​at that point over the time interval.

5. 5. A method according to any one of claims 1 to 4, comprising receiving a coordinate interval entered by the user and displaying only values ​​of the environmental data set for points within the interval.

6. The method of any one of claims 1 to 5, wherein a filtering threshold is applied to display only a sub-portion of the volume or region.

7. 7. The method of claim 1, wherein one said threshold is a numerical threshold applied to a scalar value of a data set or to a dimension of a vector in a vector data set.

8. 8. The method of claim 1, wherein one said threshold is a numerical threshold applied to the number of area or volume units located at each sensor point location to be displayed.

9. The method according to claim 1 , wherein one of the filtering thresholds is a lower boundary, an upper boundary or a range between two lower and upper boundaries.

10. 10. The method of claim 1, wherein one filtering threshold is applied to the entire region or volume, or independently to specific sub-portions thereof.

11. 11. The method of claim 1, wherein one said filter involves reducing the region(s) / volume(s) of interest to the edge(s) of the region(s) / volume(s).

12. 12. The method according to claim 1, wherein a filter allows for the decision of whether to display a scalar value, a vector dimension, or a ratio between these two values ​​using a color or grayscale gradient.

13. 13. A method according to any one of claims 1 to 12, comprising projecting vectors along one particular direction or plane into one of said vector data sets.

14. 14. The method of claim 1, comprising projecting a vector of the vector data set onto a horizontal plane or onto a vertical plane with a horizontal orientation defined by the user.

15. The method according to any one of claims 1 to 14, wherein one of the environmental data sets corresponds to free visibility from each point of the data set in different directions.

16. 16. A method according to any one of claims 1 to 15, comprising filtering points in one of the combined data sets according to values ​​of neighbouring points.

17. 17. A method according to any one of claims 1 to 16, comprising receiving a filtering command entered by a user using said graphical user control element to average or sum scalar and directional values ​​of said combined environmental dataset over an area, volume or time interval.

18. 18. A method according to any one of claims 1 to 17, comprising receiving a command entered by a user using said graphical user control element to hide points which are considered to be subject to modification by future obstacles within the volume itself, i.e. to keep only points on the boundary of the volume which will have a constant value independent of those which will potentially be inserted within the volume.

19. 19. A method according to any one of claims 1 to 18, comprising receiving a command entered by a user using said graphical user control element to display only points that are closer than a given distance to an object defined by the user.

20. 20. The method of any one of claims 1 to 19, wherein the step of combining values ​​of two different environmental data sets involves performing a logical and / or arithmetic combination.

21. 21. A method according to any one of claims 1 to 20, comprising the step of saving and / or retrieving sets of selection, filtering and / or combination parameters as presets.

22. 22. The method of any one of claims 1 to 21, including a graphic user interface with buttons that allow a user to visualize the geometric operators that have been used to generate the resulting environmental dataset.

23. 23. The method according to any one of claims 1 to 22, comprising a graphic user interface with a 2D camera image of the 3D model, which can be constructed using different types of projections and viewed from different viewpoints, making it possible to visualize detailed information related to the shape and / or values ​​of each of these geometric operators and to assist the user in the interpretation and / or filtering process.

24. 24. A method according to any one of claims 1 to 23, comprising a graphic user interface with a 2D colour or greyscale heat map that makes it possible to visualize detailed information relating to the shape and / or values ​​of each of these geometric operators and to assist the user in the interpretation and / or filtering process and in identifying global and / or local maxima and minima among the values ​​of the operators.

25. A computer program product comprising instructions which, when executed by a computer, cause the computer to carry out the method according to any one of claims 1 to 24.

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