CN116229001A - A method and system for generating a three-dimensional digital map of a city based on spatial entropy - Google Patents

Abstract

The invention provides a space entropy-based city three-dimensional digital map generation method and system, and relates to the field of artificial intelligence city design. The urban three-dimensional digital map generation method comprises the steps of constructing a three-dimensional space digital map taking a land function block as a unit, measuring and displaying the space entropy of the block unit, collecting crowd vitality and public emotion data, secondarily judging the land to be updated and displaying the land to be early-warned, adjusting and checking the space entropy, feeding back and updating the space entropy, splicing the adjusted urban three-dimensional digital map, printing and outputting the three-dimensional digital map for planning, designing and managing personnel to refer to a large-scale urban three-dimensional digital map image manufacturing and displaying technology based on the space entropy, realizing accurate expression of the urban feature of a large scale with a wide range, realizing instant display of the urban feature of the whole range and quick disclosure of basic rules, and improving the working efficiency and accuracy of judging the urban feature of the urban feature.

Description

A method and system for generating urban three-dimensional digital map based on spatial entropy

Technical Field

The present invention relates to the field of artificial intelligence urban design technology, and in particular to a method and system for generating a three-dimensional urban digital map based on spatial entropy.

Background Art

Urban landscape plays a guiding role in establishing the city image, improving the city quality and optimizing the urban space environment. At present, the research and practice on urban landscape focus on two aspects: one is to analyze and summarize the content and elements of urban landscape to guide urban planning and construction and architectural design; the other is to study the specific practical experience of urban landscape construction. As an important variable to characterize the complexity of urban space, spatial entropy can be introduced to systematically and accurately measure the multi-dimensional urban landscape characteristic indicators of plot units, and guide the efficient screening of urban landscape remediation units, in order to achieve a practical breakthrough in the identification of urban landscape characteristics and the screening of remediation units.

Summary of the invention

1. Technical issues to be solved

In view of the shortcomings of the prior art, the present invention provides a method and system for generating a three-dimensional urban digital map based on spatial entropy, and provides an automated and intelligent image production and display technology for updating urban features based on spatial entropy, thereby achieving accurate expression of large-scale urban features with a wide range of areas and quantities, and improving the efficiency and accuracy of determining urban features.

(II) Technical solution

To achieve the above objectives, the present invention is implemented through the following technical solutions:

In a first aspect, a method for generating a three-dimensional digital map of a city based on spatial entropy is provided, comprising:

Obtain the three-dimensional oblique photography data of the target city, translate it into geographic information vector data and enter it into the geographic information platform; after completing the data verification, perform data superposition processing to build a basic sand table of the city's three-dimensional digital map; and identify the type of plot unit through POI data, and divide the target city into geographic space units based on land use function plots;

A spatial entropy measurement method is constructed to measure the building volume scale entropy, building structure form entropy, and building facade surface entropy of different types of land plot units; the natural break point method is used to obtain the spatial entropy value types of different types of plot units, and different types of spatial entropy digital map entropy value result layers and entropy value type layers are established, and the image results of the three-dimensional digital map of the target city are displayed according to the functional parameter settings of the digital layer;

Collect detailed urban design plans at the plot level in the target area and perform vector processing, build a spatial entropy sample library, automatically match samples in the spatial entropy sample library according to the spatial attributes of the plot units, calculate the six types of spatial entropy values of the samples, use the sample spatial entropy value range as the spatial entropy threshold judgment standard, mark the urban plots that do not meet the spatial entropy threshold as possible plots to be updated and display them in a hierarchical manner, collect population vitality data and public sentiment data in the target area as secondary judgment conditions for updating plots, determine the warning plots to be updated and add labels for display;

Build a city three-dimensional digital map sensor to recognize user voice and action, build a spatial entropy adjustment instruction library, adjust the building height, building area, and building color, and review whether the adjustment content meets the specifications through the relevant specifications of the target city design style, and feedback and update the adjusted spatial entropy in the three-dimensional digital map;

The three-dimensional digital map of the city after adjusting the spatial entropy is spliced and printed out, including the entropy values of various spatial entropies of the warning plot units before and after adjustment, the bird's-eye view before and after the three-dimensional digital map is updated, and the spatial entropy values and bird's-eye view after adjustment of the spatial entropy of the warning plot units exceeding the threshold, for reference by planning and design and management personnel.

Preferably, the three-dimensional oblique photography data of the target city is obtained, and the geographic information vector data is translated and entered into the geographic information platform; after completing the data verification, the data is superimposed to construct the basic sand table of the three-dimensional digital map of the city; and the land unit type is identified through the POI data, and the target city is divided into geographic space units based on land use function plots, which specifically includes:

Geographic information basic data collection: use the laser radar point cloud data collection system to obtain the three-dimensional oblique photography data of the target city, and load the deep learning digital interpretation interface of the digital map to translate the three-dimensional oblique photography data into the geographic information platform.

Constructing a 3D digital map of the city, verifying geographic information, converting the 3D oblique photography data of the target city and the verified geographic information vector data into a unified CGCS2000 coordinate system, superimposing the data according to the geographic coordinates, and making a 3D digital map of the city based on the geographic information platform;

The plot unit type is delineated by loading the POI data collection and land use identification interface of the digital map, collecting the POI data of the target city, and assigning different POI reference land area values to different types of POI data. The POI types are classified according to the plot unit type. The dominant plot type with the largest total area of the corresponding POI type in the plot unit is the land use function of the plot unit. The specific calculation formula is as follows:

Among them, i represents the type represented by the POI, Fi represents the number of POIs of the i-th type in the plot unit, _Si represents the reference land area value assigned to the POI, m represents the total number of POI types in the plot unit, and n represents the total number of POI types under the corresponding type of the plot unit. The land use function of the plot unit is finally determined by comparing the C values of different types.

Preferably, the method for constructing spatial entropy measurement measures the building volume scale entropy, building structure form entropy, and building facade surface entropy of different types of land plot units; the natural break point method is used to obtain the spatial entropy value types of different types of land plot units, and different types of spatial entropy digital map entropy value result layers and entropy value type layers are established, and the image results of the three-dimensional digital map of the target city are displayed according to the function parameter settings of the digital layer, specifically including:

Spatial entropy index measurement: measure the three types of spatial entropy indexes closely related to architectural style, namely building volume scale entropy, building structure form entropy, and building facade surface entropy. Load the index calculation module to calculate the units of each block in the target city.

The building volume scale entropy includes building height entropy and building base area entropy, the building structure form entropy includes building main structure form entropy and building roof form entropy, and the building facade skin entropy includes building facade color entropy and building facade material entropy;

The basic formula of the spatial entropy index system is:

Among them, H(X) represents the result of measuring the spatial entropy of the object, n represents the total number of types of the corresponding measurement standard, and _Pi represents the probability of the corresponding classification when X takes i;

Identification and display of spatial entropy types: for different types of spatial entropy values obtained by calculation, the natural break point method is used to divide the plot units into three categories: "high entropy", "medium entropy" and "low entropy". The spatial entropy database interface is loaded in the digital map, and the spatial matching of the target city's geographic information vector data and spatial entropy data is established according to the geographic coordinates. Different types of spatial entropy digital map entropy value result layers and entropy value type layers are established, and the image results of the target city's three-dimensional digital map are displayed according to the function parameter settings of the digital layer.

The functional parameter settings of the digital layer include: the digital map layer can be displayed in layers or in superposition through the display setting function of the digital map layer; the entropy value units with the same result or the same type can be linked for viewing through the hyperlink function of the digital map layer; the statistical chart function of the digital map layer can record the statistical characteristic chart results of a certain type of entropy value result; and the real scene retracing function of the digital map layer can roam to the specific plot unit when viewing different types of spatial entropy layers to view the corresponding type characteristics under the three-dimensional oblique photography real scene image.

Preferably, the detailed urban design scheme at the plot level of the target area is collected and vectorized, a spatial entropy sample library is constructed, samples in the spatial entropy sample library are automatically matched according to the spatial attributes of the plot units, six types of spatial entropy values of the samples are calculated, the sample spatial entropy value range is used as the spatial entropy threshold judgment standard, the urban plots that do not meet the spatial entropy threshold are marked as possible plots to be updated and displayed in a graded manner, the population vitality data and public sentiment data of the target area are collected as secondary judgment conditions for updating the plots, and the warning plots to be updated are determined and labeled for display, which specifically includes:

The spatial entropy sample library is constructed to collect detailed urban design plans at the plot level in the target area, and the design plan content is intelligently translated into three-dimensional vector data, which is entered into the three-dimensional digital map to construct the spatial entropy sample library of the target area, calculate the land use functions of all plots and the normalized boundary shape index, perimeter, and area three spatial attribute values, and annotate them in the form of labels;

Spatial entropy threshold matching and judgment, calculate the three major spatial attribute values of the target plot unit, automatically match the unique sample data with the same land use function and the smallest spatial attribute difference in the spatial entropy sample library, and then calculate the six categories of spatial entropy values of the matching sample using the spatial entropy measurement method. The maximum and minimum values of the six categories of spatial entropy values of the sample are used as the judgment criteria for the six categories of spatial entropy thresholds of the target plot unit.

The spatial attribute difference formula is as follows:

Among them, Cn, Ln, Sn are the normalized shape index, perimeter, and area values of the sample plots, respectively; Cx, Lx, Sx are the normalized shape index, perimeter, and area values of the sample plots, respectively;

Extraction of over-threshold plots and display of possible updated plot units. The six types of spatial entropy thresholds obtained by matching and judging the spatial entropy thresholds are used as the judgment criteria. Plots exceeding the threshold range are extracted and the spatial entropy type labels exceeding the threshold are added. The spatial entropy values exceeding the range of the extracted plots are standardized. Then, the severity of the six types of spatial entropy thresholds exceeding the range are divided into three levels: severe, medium, and slight using the natural discontinuity method. The extracted plots are labeled with severity labels and marked as possible plot units to be updated. They are classified and displayed in different colors in the three-dimensional digital map.

The verification of crowd location and emotion data and the determination results of early warning updated plots are displayed. Crowd vitality data and public emotion data are collected and loaded into the three-dimensional digital map through spatial association. Based on these two types of data, a secondary determination is made on the plot units that may be updated. The plots that meet the determination conditions are marked as early warning plot units to be updated and displayed in the three-dimensional digital map.

Preferably, the three-dimensional digital map sensor of the city is built, the user's voice and action are recognized, a spatial entropy adjustment instruction library is constructed, the building height, building area and building color are adjusted, and the adjustment content is examined through the relevant specification conditions of the target city design style to see whether it meets the specification, and the adjusted spatial entropy is fed back and updated in the three-dimensional digital map, specifically including:

User command voice and action recognition, loading a VR interactive adjustment module based on interactive instructions for urban landscape update in a three-dimensional digital map, including a voice recognition system, a motion recognition wearable device equipped with an inertial sensor, and a handheld control system, recognizing user voice and user behavior through data transmission calculation, wherein the user voice recognition includes "forward", "turn right", "turn left", "check update warning plot", "check update demand level", "adjust building color space entropy", "adjust building area space entropy", "adjust building height space entropy", "confirm", "check", "yes", "no"; wherein the user behavior includes four actions: user walking, eye turning, arm pointing, and finger button touching;

Construction of spatial entropy adjustment instruction library: Based on the recognized voice and action, the spatial entropy adjustment instruction library is constructed to complete the functions of free walking and browsing space in the three-dimensional digital map, selecting to view detailed information of the plot, displaying the spatial entropy value, viewing the update warning plot information, viewing the update demand level, adjusting the spatial entropy of the building volume scale, adjusting the spatial entropy of the building structure form, and adjusting the spatial entropy of the building facade surface. When the user confirms to make a certain type of spatial entropy adjustment, the constructed spatial entropy sample library is used as the training set for deep learning. According to the threshold range of the type of spatial entropy corresponding to the plot, new building model data within the threshold range is automatically and randomly generated. If the user is not satisfied, he can repeat the update through the adjustment instruction;

Verification and feedback of standard conditions: collect design standard conditions related to the urban appearance of the target area, and conduct intelligent review of the randomly generated data after the user's selection and adjustment according to the standard conditions. If the review is passed, it will be input into the data update system of the three-dimensional digital map. If the review is not passed, it will be randomly generated again until it passes the review and then fed back to the user. Among them, the design standard conditions related to urban appearance include the building height, building density, volume ratio, building roof type, building color, and building material control requirements in the overall urban design of the target area.

Preferably, the three-dimensional digital map of the city after adjusting the spatial entropy is spliced and printed out, including the entropy values of various spatial entropies of the warning plot units before and after adjustment, the bird's-eye view before and after the three-dimensional digital map is updated, and the spatial entropy values and bird's-eye view of the spatial entropy of the warning plot units exceeding the threshold after adjustment, for reference by planning and design and management personnel, specifically including:

Update the generation and standard verification of the city's three-dimensional digital map, combine the adjusted plot data with the unadjusted plot data through spatial superposition, generate updated three-dimensional digital map data, and conduct final verification of the combined data according to the building sunlight spacing and building fire protection spacing specifications in the regulatory detailed plan;

The output of urban three-dimensional digital map data is to print out the updated urban three-dimensional digital map data after splicing and verification and the data before updating. The output data includes the model bird's-eye view of the urban three-dimensional digital map before and after updating, the model bird's-eye view of the style and land unit before and after updating, the spatial entropy value of the style and land unit before and after adjustment, and the spatial entropy type of the land unit to be updated that exceeds the threshold for warning, for reference by planning and design and management personnel.

In a second aspect, a system for generating a three-dimensional digital map of a city based on spatial entropy is provided, the system comprising:

The basic data acquisition and display module is used to obtain the three-dimensional oblique photography data of the target city, translate it into geographic information vector data and enter it into the geographic information platform; after completing the data verification, the data is superimposed to build the basic sand table of the city's three-dimensional digital map; and the land unit type is identified through POI data, and the target city is divided into geographic space units based on land use function plots;

The spatial entropy measurement and display module is used to construct a spatial entropy measurement method to measure the building volume scale entropy, building structure form entropy, and building facade surface entropy of different types of land plot units; the natural break point method is used to obtain the spatial entropy value type of different types of land plot units, and different types of spatial entropy digital map entropy value result layers and entropy value type layers are established, and the image results of the target city's three-dimensional digital map are displayed according to the function parameter settings of the digital layer;

The spatial entropy threshold determination and early warning display module is used to collect detailed urban design plans at the plot level in the target area and perform vector processing, build a spatial entropy sample library, automatically match samples in the spatial entropy sample library according to the spatial attributes of the plot units, calculate the six types of spatial entropy values of the samples, use the sample spatial entropy value range as the spatial entropy threshold judgment standard, mark the urban plots that do not meet the spatial entropy threshold as possible plots to be updated and display them in a graded manner, collect the target area population vitality data and public sentiment data as secondary judgment conditions for updating plots, determine the warning plots to be updated and add labels for display;

The city three-dimensional space sandbox interactive display and adjustment module is used to build a city three-dimensional digital map sensor, recognize user voice and action, build a spatial entropy adjustment instruction library, adjust the building height, building area, and building color, and review whether the adjustment content meets the specifications through the relevant specifications of the target city design style, and feedback and update the adjusted spatial entropy in the three-dimensional digital map;

The result output module is used to combine and print out the three-dimensional digital map of the city after the spatial entropy is adjusted, including the entropy values of various spatial entropies of the warning plot units before and after adjustment, the bird's-eye view before and after the three-dimensional digital map is updated, and the spatial entropy values and bird's-eye view after the spatial entropy of the warning plot units exceeding the threshold is adjusted, for reference by planning and design management personnel;

The system is used to implement the method for generating a three-dimensional urban digital map based on spatial entropy.

In a third aspect, a terminal device is provided, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the memory stores a computer program capable of running on the processor, and when the processor loads and executes the computer program, the method for generating a three-dimensional digital map of a city based on spatial entropy is adopted.

In a fourth aspect, a computer-readable storage medium storing a computer program is provided, and when the program is executed by a processor, the method for generating a three-dimensional digital map of a city based on spatial entropy is implemented.

(III) Beneficial effects

(1) The present invention provides a method and system for generating a three-dimensional urban digital map based on spatial entropy. In terms of expression content, it focuses on the large-scale urban three-dimensional digital map image production and display technology based on spatial entropy for the first time. The building volume scale, building structure form, and building facade surface of the target urban plot unit are combined with urban three-dimensional oblique photography data and geographic information vector data in the form of spatial entropy to construct a three-dimensional digital map, thereby achieving accurate expression of large-scale urban features with a wide range of areas and quantities, and increasing the expression range from the original 1 square kilometer to more than 10 square kilometers.

(2) The present invention provides a method and system for generating a three-dimensional urban digital map based on spatial entropy. In applicable scenarios, a complete set of rigorous operational procedures are constructed, from the collection of basic geographic information data, the measurement of the spatial entropy indicator system, to the determination and early warning of the spatial entropy threshold, and then to the interactive display and adjustment of the three-dimensional space sandbox. The method and system can then perform spatial location, coupling analysis, threshold monitoring and interactive adjustment of large-scale urban features, thereby changing the basic functions of general urban maps, which are only readable, difficult to interact with, and low in information content, and expanding the scope of use of large-scale three-dimensional urban digital maps based on spatial entropy.

(3) The present invention provides a method and system for generating a three-dimensional urban digital map based on spatial entropy. In terms of practical efficiency, it realizes the real-time display of the overall urban landscape characteristics and the rapid revelation of the basic laws, thus avoiding the investment of a large amount of ineffective manpower and time costs in conducting basic surveys on urban landscape. It reduces the time required to determine the characteristics of urban landscape from one week to four hours, thus avoiding the uncontrollability and time consumption of the previous urban construction process of selecting urban landscape improvement units, and also improves the accuracy of the data.

(4) The present invention provides a method and system for generating a three-dimensional urban digital map based on spatial entropy. In terms of interactive means, the system is oriented towards the fields of urban planning and architectural design, and incorporates the main structure of the building, the roof form of the building, the building height, the building base area, the color of the building facade, and the material of the building facade into the visualized VR interactive adjustment module of the three-dimensional urban digital map, so that users can instantly experience and adjust the city's features when roaming the three-dimensional urban digital map. The interactive mode involves voice, gaze, pointing and touch, which is more humane and the display effect is more intuitive and obvious.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of a large-scale urban three-dimensional digital map generation process based on spatial entropy according to the present invention;

FIG2 is a schematic diagram of land coding for a three-dimensional digital map of a city according to the present invention;

3 is a schematic diagram showing the spatial entropy value and type of a three-dimensional digital map of a city according to the present invention;

4 is a schematic diagram showing a display of a spatial entropy early warning unit of a three-dimensional digital map of a city according to the present invention;

FIG5 is a schematic diagram of interactive adjustment of a three-dimensional digital map of a city according to the present invention;

FIG6 is a schematic diagram of a city three-dimensional digital map space entropy adjustment instruction library according to the present invention.

DETAILED DESCRIPTION

The following will be combined with the accompanying drawings of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

As shown in FIG1 , an embodiment of the present invention provides a method for generating a three-dimensional digital map of a city based on spatial entropy, comprising the following steps:

Step S1: Basic data collection and display

Acquire the three-dimensional oblique photography data of the target city, translate it into geographic information vector data and enter it into the geographic information platform; after completing the data verification, perform data superposition processing to build a basic sandbox for the city's three-dimensional digital map; and identify the plot unit type through POI data, and divide the target city into geographic space units based on land use function plots.

S11. Collection of basic geographic information data

Use a surveying drone equipped with a lidar point cloud data acquisition system with an accuracy of less than 10mm to obtain three-dimensional oblique photography data of the target city, and load the deep learning digital interpretation interface of the digital map to enter the geographic information vector data obtained by translating the three-dimensional oblique photography data into the geographic information platform.

In this embodiment, a surveying and mapping drone equipped with a laser radar point cloud data acquisition system with an accuracy of less than 10mm is used to obtain the three-dimensional oblique photography data of the target city, and the deep learning digital interpretation interface of the digital map is loaded, and the geographic information vector data obtained by translating the three-dimensional oblique photography data is stored in the ArcGIS spatial data storage database. Among them, the geographic information vector data includes the topographic information, road information, land boundary information, building information, and facility information data of the target city; among them, the building information data includes building height, base area, main structure form, roof form, facade color, and facade material data.

S12. Construction of three-dimensional digital city maps

An electric vehicle is used to carry a backpack laser scanner with a scanning range of 200 meters and a camera resolution of more than 4K to perform geographic information correction. The three-dimensional oblique photography data of the target city and the geographic information vector data that have completed data verification are converted into a unified CGCS2000 coordinate system, and the data are superimposed according to the geographic coordinates. Relying on the geographic information platform, a three-dimensional digital map of the city is created.

In this embodiment, an electric vehicle is driven to carry a backpack laser scanner with a scanning range of 200 meters and a camera resolution of 4K or above to perform geographic information correction. The spatial adjustment tool in GIS is used to convert the three-dimensional oblique photography data of the target city and the geographic information vector data that has completed data verification into a unified CGCS2000 coordinate system, and the data is superimposed according to the geographic coordinates. Relying on the GIS geographic information platform, a three-dimensional digital map of the city is produced.

S13. Delineation of land unit types

By loading the POI data collection and land use identification interface of the digital map, the POI data of the target city is collected, and different types of POI data are assigned different POI reference land area values. The POI types are classified according to the plot unit type, and the dominant plot type with the largest total area of the corresponding POI types in the plot unit is the land use function of the plot unit.

In this embodiment, the POI data of the city is collected by loading the POI data collection and land use identification interface of the digital map, and different POI reference land area values are assigned to different types of POI data. The POI types are classified according to the plot unit type. The dominant plot type with the largest total area of the corresponding POI types in the plot unit is the land use function of the plot unit. The specific calculation formula is as follows:

Among them, i represents the type represented by the POI, Fi represents the number of POIs of the i-th type in the plot unit, _Si represents the reference land area value assigned to the POI, m represents the total number of POI types in the plot unit, and n represents the total number of POI types under the corresponding type of the plot unit. The land use function of the plot unit is finally determined by comparing the C values of different types.

After the land unit types are divided according to the identification results, all the land units in the city are coded in the form of "land code + number" without duplication. Among them, the POI reference land area is determined by taking the average of the statistical data of different types of urban construction land areas and structural sampling data in the target city; among them, the land unit types are based on the "Urban Land Classification and Planning and Construction Land Standards", including residential land, public service land, commercial land, industrial land, and logistics and warehousing land.

Step S2: spatial entropy measurement and display

A spatial entropy measurement method is constructed to measure the building volume scale entropy, building structure form entropy, and building facade surface entropy of different types of land plot units. The natural break point method is used to obtain the spatial entropy value types of different types of land plot units, and different types of spatial entropy digital map entropy result layers and entropy value type layers are established. The image results of the three-dimensional digital map of the target city are displayed according to the functional parameter settings of the digital layer.

S21. Spatial entropy index measurement

The three types of spatial entropy indicators closely related to architectural style, namely building volume scale entropy, building structure form entropy and building facade surface entropy, are measured, and the indicators calculation module is loaded to calculate the units of each block in the target city.

In this embodiment, three types of spatial entropy indicators closely related to architectural style are measured, namely, building volume scale entropy, building structure form entropy, and building facade skin entropy, and the entropy of each block in the city is calculated by loading the index calculation module. Among them, the building volume scale entropy includes the building height entropy and the building base area entropy, the building structure form entropy includes the building main structure form entropy and the building roof form entropy, and the building facade skin entropy includes the building facade color entropy and the building facade material entropy;

Among them, the basic formula of the spatial entropy index system is:

Among them, H(X) represents the result of measuring the spatial entropy of the measured object, n represents the total number of types of the corresponding measurement standard, and _Pi represents the probability of the corresponding classification when X takes i.

S22. Spatial entropy type identification and display

For the different types of spatial entropy values obtained by calculation, the natural break point method is used to divide the plot units into three categories: "high entropy", "medium entropy" and "low entropy". The spatial entropy database interface is loaded in the digital map, and the spatial matching of the target city's geographic information vector data and spatial entropy data is established according to the geographic coordinates. Different types of spatial entropy digital map entropy value result layers and entropy value type layers are established, and the image results of the three-dimensional digital map of the target city are displayed according to the functional parameter settings of the digital layer.

In this embodiment, for different types of spatial entropy values obtained by calculation, the natural break point method is used to divide the plot units into three categories of "high entropy", "medium entropy" and "low entropy"; the spatial entropy database interface is loaded in the digital map, and the spatial matching of the city's geographic information vector data and the spatial entropy data is established according to the geographic coordinates, and different types of spatial entropy digital map entropy value result layers and entropy value type layers are established, and the image results of the target city's three-dimensional digital map are displayed according to the functional parameter settings of the digital layer. Among them, the functional parameter settings of the digital layer include that the digital map layer can be displayed in layers or superimposed through the display setting function of the digital map layer, the same result or the same type of entropy value unit can be linked to view through the hyperlink function of the digital map layer, a certain type of entropy value result statistical feature chart result can be recorded through the chart statistics function of the digital map layer, and the corresponding type characteristics under the three-dimensional oblique photography real scene image can be roamed to the specific plot unit when viewing different types of spatial entropy layers through the real scene retracing function of the digital map layer.

Step S3: Determination of spatial entropy threshold and early warning display

Collect detailed urban design plans at the plot level in the target area and perform vector processing, build a spatial entropy sample library, automatically match samples in the spatial entropy sample library according to the spatial attributes of the plot units, calculate six types of spatial entropy values of the samples, use the sample spatial entropy value range as the spatial entropy threshold judgment standard, mark urban plots that do not meet the spatial entropy threshold as possible plots to be updated and display them in a graded manner, collect population vitality data and public sentiment data in the target area as secondary judgment conditions for updating plots, determine the warning plots to be updated and add labels for display.

S31. Construction of spatial entropy sample library

Collect detailed urban design plans at the plot level in the target area in the past five years, and intelligently translate the design content into three-dimensional vector data through a scanner with a resolution of more than 1000dpi, enter it into the three-dimensional digital map generated in step S1, and build a spatial entropy sample library of the target area. Then calculate the land use function of all plots and the normalized boundary shape index, perimeter, and area three major spatial attribute values, and mark them in the form of labels.

In this embodiment, detailed urban design plans at the plot level of the city in the past five years are collected, and the design content is intelligently translated into three-dimensional vector data through a scanner with a resolution of more than 1000dpi, and entered into the three-dimensional digital map generated in step S1 to build a spatial entropy sample library of the city. Then, the land use functions of all plots and the normalized three major spatial attribute values of boundary shape index, perimeter, and area are calculated and annotated in the form of labels. Among them, the spatial entropy sample library collects new data once a year, and deletes data older than 5 years for dynamic data updating.

S32. Spatial entropy threshold matching and judgment

Calculate the three major spatial attribute values of the target plot unit, automatically match the unique sample data with the same land use function and the smallest spatial attribute difference in the spatial entropy sample library, and then calculate the six categories of spatial entropy values of the matching sample according to the method described in step S2, and use the maximum and minimum values of the six categories of spatial entropy values of the sample as the judgment criteria for the six categories of spatial entropy thresholds of the target plot unit,

In this embodiment, the three major spatial attribute values of the plot units in the city are calculated, and the unique sample data with the same land use function and the smallest spatial attribute difference in the spatial entropy sample library is automatically matched. Then, the six types of spatial entropy values of the matching samples are calculated according to the method described in step S2, and the maximum and minimum values of the six types of spatial entropy values of the samples are used as the judgment criteria for the six types of spatial entropy thresholds of the target plot units.

The spatial attribute difference formula is as follows:

Among them, Cn, Ln, Sn are the normalized shape index, perimeter, and area values of the sample plots, respectively; Cx, Lx, Sx are the normalized shape index, perimeter, and area values of the sample plots, respectively.

S33. Extraction of over-threshold plots and possible update of plot unit display

The six types of spatial entropy thresholds obtained by the method described in step S32 are used as judgment criteria, and plots exceeding the threshold range are extracted, and spatial entropy type labels exceeding the threshold are added, and the spatial entropy values of the extracted plots exceeding the range are standardized. Then, the severity of the exceeding of the six types of spatial entropy thresholds is divided into three levels: severe, medium, and slight using the natural interruption method. The above-mentioned extracted plots are annotated with severity labels and marked as plot units that may be updated, and are classified and displayed in different colors in the three-dimensional digital map.

The six types of spatial entropy thresholds obtained by the method described in step S32 are used as judgment criteria, and plots exceeding the threshold range are extracted, and spatial entropy type labels exceeding the threshold are added, and the spatial entropy values of the extracted plots exceeding the range are standardized. Then, the severity of the exceeding of the six types of spatial entropy thresholds is divided into three levels: severe, medium, and slight using the natural interruption method. The above-mentioned extracted plots are annotated with severity labels and marked as plot units that may be updated, and are classified and displayed in different colors in the three-dimensional digital map.

S34. Crowd location and emotion data verification and early warning update plot determination result display

Collect crowd vitality data and public sentiment data, load them into the three-dimensional digital map constructed in step S1 through spatial association, and make a secondary judgment on the possible plot units to be updated obtained in step S3.3 based on these two data, mark the plots that meet the judgment conditions as warning plot units to be updated, and display them in the three-dimensional digital map.

In this embodiment, crowd vitality data and public emotion data are collected, loaded into the three-dimensional digital map constructed in step S1 through spatial association, and the possible plot units to be updated obtained in S3.3 are secondarily determined based on the two data, and the plots that meet the determination conditions are marked as warning plot units to be updated, and displayed in the three-dimensional digital map. Among them, the crowd vitality data collects the crowd quantity slice data based on location services at 10 o'clock, 14 o'clock, 18 o'clock, and 20 o'clock every day in the city in the past year, and is converted into the crowd quantity data of the year through spatial association and quantity superposition, and is processed into coordinate crowd vitality data representing spatial vitality through kernel density. The public emotion data collects facial expression data of the past year through traffic cameras on various streets and cameras in public places in the city, and uses more than 100,000 groups of emotional words translated into high and low emotional values, combined with corresponding facial image data as deep learning training sets, and translates public facial expression data into emotional values through deep learning recognition, and is processed into coordinate public emotion data representing high and low public emotion values through kernel density. Among them, the population vitality data and public sentiment value data of each plot are grouped together according to the same land use function. After normalization, each group of data is divided into five levels according to the order of magnitude, namely high, medium-high, medium, medium-low, and low, using the natural interruption method, and displayed in different colors. The possible plot units to be updated with high population vitality values and high public sentiment values are judged as normal plot units, and the remaining possible plot units to be updated are judged as warning plot units to be updated, and labels are added for display.

Step S4: interactive display and adjustment of the city three-dimensional space sand table

Build a city three-dimensional digital map sensor, recognize user voice and movements, construct a spatial entropy adjustment instruction library, adjust the building height, building area, and building color, and review whether the adjustment content meets the specifications through the relevant specifications of the target city's design style, and feedback and update the adjusted spatial entropy in the three-dimensional digital map.

S41, user command voice and action recognition

A VR interactive adjustment module based on interactive instructions for updating urban landscape is loaded into the three-dimensional digital map, including a voice recognition system, a motion recognition wearable device equipped with inertial sensors, and a handheld control system, which recognizes user voice and user behavior through data transmission calculation.

In this embodiment, a VR interactive adjustment module based on interactive instructions for urban landscape update is loaded in the three-dimensional digital map, including a voice recognition system, a motion recognition wearable device equipped with inertial sensors, and a handheld control system. User voice and user behavior are recognized by conducting data calculations, wherein user voice recognition includes "forward", "turn right", "turn left", "check update warning plots", "check update demand levels", "adjust building color space entropy", "adjust building area space entropy", "adjust building height space entropy", "confirm", "check", "yes", and "no"; wherein the user behavior includes four actions: user walking, eye turning, arm pointing, and finger button touching.

S42, construction of space entropy adjustment instruction library

A spatial entropy adjustment instruction library is constructed based on the voice and action recognized in S41 to complete the functions of freely walking and browsing space in the three-dimensional digital map, selecting to view detailed information of the plot, displaying the spatial entropy value, viewing and updating the warning plot information, viewing and updating the demand level, adjusting the spatial entropy of the building volume scale, adjusting the spatial entropy of the building structure form, and adjusting the spatial entropy of the building facade surface. When the user confirms to make a certain type of spatial entropy adjustment, the spatial entropy sample library constructed in step S3 is used as a training set for deep learning. According to the threshold range of the spatial entropy of this type corresponding to the plot, new building model data within the threshold range is automatically and randomly generated. If the user is not satisfied, the adjustment instruction can be repeated to update.

In this embodiment, a spatial entropy adjustment instruction library is constructed according to the voice and action recognized in S41 to complete the functions of freely walking and browsing space in the three-dimensional digital map, selecting to view detailed information of the plot, displaying the spatial entropy value, viewing the update warning plot information, viewing the update demand level, adjusting the spatial entropy of the building volume scale, adjusting the spatial entropy of the building structure form, and adjusting the spatial entropy of the building facade surface. When the user confirms to perform a certain type of spatial entropy adjustment, the spatial entropy sample library constructed in step S3 is used as a training set for deep learning. According to the threshold range of the type of spatial entropy corresponding to the plot, new building model data within the threshold range is automatically and randomly generated. If the user is not satisfied, the update can be repeated through the adjustment instruction.

S43, Standard Conditions Verification and Feedback

Collect the design specifications and conditions related to the urban landscape of the target area, and conduct intelligent review of the randomly generated data after the user selects and adjusts it in step S42 according to the specifications and conditions. If the review is passed, it is input into the data update system of the three-dimensional digital map. If the review is not passed, it is randomly generated again until it is passed and then fed back to the user.

In this embodiment, the design specification conditions related to the urban appearance of the target area are collected, and the data randomly generated after the user selects adjustment in step S42 is intelligently reviewed according to the specification conditions. If the review is passed, it is input into the data update system of the three-dimensional digital map. If the review is not passed, it is randomly regenerated until it passes the review and then fed back to the user. The design specification conditions related to the urban appearance include the building height, building density, floor area ratio, building roof type, building color, and building material control requirements in the overall urban design of the target area.

Step S5: Result output

The three-dimensional digital map of the city after adjusting the spatial entropy is spliced and printed out, including the entropy values of various spatial entropies of the warning plot units before and after adjustment, the bird's-eye view before and after the three-dimensional digital map is updated, and the spatial entropy values and bird's-eye view after adjustment of the spatial entropy of the warning plot units exceeding the threshold, for reference by planning and design and management personnel.

S51. Update the generation and standard verification of urban three-dimensional digital maps

In this embodiment, the adjusted plot data in step S4 is spliced with the unadjusted plot data through spatial superposition to generate updated three-dimensional digital map data, and the spliced data is finally checked according to the building sunlight spacing and building fire protection spacing specifications in the control detailed planning.

The adjusted plot data in step S4 is combined with the unadjusted plot data through spatial superposition to generate updated three-dimensional digital map data, and the combined data is finally checked according to the building sunlight spacing and building fire protection spacing specifications in the control detailed plan.

S52, city three-dimensional digital map data output

The updated urban three-dimensional digital map data after splicing and verification in step S51 is integrated with the data before updating and printed out. The output data includes the model bird's-eye view of the urban three-dimensional digital map before and after updating, the model bird's-eye view of the style and land unit before and after updating, the spatial entropy value of the style and land unit before adjustment and the spatial entropy value after adjustment, and the spatial entropy type of the land unit to be updated that warns that it exceeds the threshold, for reference by planning and design and management personnel.

In this embodiment, the updated city three-dimensional digital map data after splicing and verification in step S51 is aggregated with the data before the update and printed out. The output data includes the model bird's-eye view of the city's three-dimensional digital map before and after the update, the model bird's-eye view of the style and feature plot unit before and after the update, the spatial entropy value of the style and feature updated plot unit before and after adjustment, and the spatial entropy type of the warning plot unit to be updated that exceeds the threshold, for reference by planning designers and management personnel.

As another embodiment of the present invention, a system for generating a three-dimensional urban digital map based on spatial entropy is provided, the system comprising:

The basic data acquisition and display module is used to obtain the three-dimensional oblique photography data of the target city, translate it into geographic information vector data and enter it into the geographic information platform; after completing the data verification, the data is superimposed to build the basic sand table of the city's three-dimensional digital map; and the land unit type is identified through POI data, and the target city is divided into geographic space units based on land use function plots;

The spatial entropy measurement and display module is used to construct a spatial entropy measurement method to measure the building volume scale entropy, building structure form entropy, and building facade surface entropy of different types of land plot units; the natural break point method is used to obtain the spatial entropy value type of different types of land plot units, and different types of spatial entropy digital map entropy value result layers and entropy value type layers are established, and the image results of the target city's three-dimensional digital map are displayed according to the function parameter settings of the digital layer;

The spatial entropy threshold determination and early warning display module is used to collect detailed urban design plans at the plot level in the target area and perform vector processing, build a spatial entropy sample library, automatically match samples in the spatial entropy sample library according to the spatial attributes of the plot units, calculate the six types of spatial entropy values of the samples, use the sample spatial entropy value range as the spatial entropy threshold judgment standard, mark the urban plots that do not meet the spatial entropy threshold as possible plots to be updated and display them in a graded manner, collect the target area population vitality data and public sentiment data as secondary judgment conditions for updating plots, determine the warning plots to be updated and add labels for display;

The city three-dimensional space sandbox interactive display and adjustment module is used to build a city three-dimensional digital map sensor, recognize user voice and action, build a spatial entropy adjustment instruction library, adjust the building height, building area, and building color, and review whether the adjustment content meets the specifications through the relevant specifications of the target city design style, and feedback and update the adjusted spatial entropy in the three-dimensional digital map;

The result output module is used to combine and print out the three-dimensional digital map of the city after the spatial entropy is adjusted, including the entropy values of various spatial entropies of the warning plot units before and after adjustment, the bird's-eye view before and after the three-dimensional digital map is updated, and the spatial entropy values and bird's-eye view after the spatial entropy of the warning plot units exceeding the threshold is adjusted, for reference by planning and design management personnel;

The system is used to implement a method for generating a three-dimensional urban digital map based on spatial entropy in the above embodiment.

As another embodiment of the present invention, a device is provided, the device comprising:

one or more processors;

a memory for storing one or more programs,

When the one or more programs are executed by the one or more processors, the one or more processors execute a method for generating a three-dimensional digital map of a city based on spatial entropy in the above embodiment.

As another embodiment of the present invention, a terminal device is provided, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The device is characterized in that the memory stores a computer program capable of running on the processor, and when the processor loads and executes the computer program, a method for generating a three-dimensional urban digital map based on spatial entropy in the above-mentioned embodiment is adopted.

It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

Claims (9)

1. The city three-dimensional digital map generation method based on the space entropy is characterized by comprising the following steps of:

acquiring three-dimensional oblique photography data of a target city, translating to obtain geographic information vector data, and inputting the geographic information vector data into a geographic information platform; after finishing data verification, carrying out superposition processing on the data, and constructing a basic sand table of the urban three-dimensional digital map; identifying the type of the land block unit through POI data, and dividing the target city into geographic space units taking land function land blocks as units;

constructing a space entropy measurement method, and measuring the building body volume scale entropy, building structure form entropy and building elevation surface skin entropy of different types of land-used block units; obtaining the spatial entropy value types of different types of land block units by adopting a natural break point method, establishing an entropy value result layer and an entropy value type layer of different types of spatial entropy digital maps, and setting according to the functional parameters of the digital layers to display the image result of the three-dimensional digital map of the target city;

collecting a target regional land block level detailed city design scheme, carrying out vectorization treatment, constructing a spatial entropy sample library, automatically matching samples in the spatial entropy sample library according to space attributes of land block units, calculating six types of spatial entropy values of the samples, marking urban land blocks which do not meet the spatial entropy threshold as possible land blocks to be updated and displaying the land blocks in a grading manner, collecting target regional crowd vitality data and public emotion data as secondary judging conditions for updating the land blocks, judging the land blocks to be updated and adding labels for displaying;

Building a three-dimensional digital map sensor of a city, recognizing the voice and the action of a user, building a space entropy adjustment instruction library, adjusting building height, building area and building color, checking whether the adjustment content meets the specification or not through the related specification conditions of the design style of a target city, and carrying out feedback update on the adjusted space entropy in the three-dimensional digital map;

and splicing and printing out the urban three-dimensional digital map after the space entropy adjustment, wherein the urban three-dimensional digital map comprises various space entropy adjustment front and back entropy values of the early warning land parcel unit, a bird's eye view image before and after the three-dimensional digital map is updated, and a space entropy value and a bird's eye view image after the space entropy adjustment of the early warning land parcel unit exceeding a threshold value, and the space entropy value and the bird's eye view image are used for reference by planning design and management staff.

2. The urban three-dimensional digital map generation method based on spatial entropy according to claim 1, characterized in that: the three-dimensional oblique photography data of the target city are obtained, geographic information vector data are obtained through translation, and the geographic information vector data are input into a geographic information platform; after finishing data verification, carrying out superposition processing on the data, and constructing a basic sand table of the urban three-dimensional digital map; and identifying the type of the land parcel unit by the POI data, and dividing the target city into geographic space units taking land parcel as a unit, wherein the method specifically comprises the following steps:

The method comprises the steps of collecting geographic information basic data, acquiring three-dimensional oblique photography data of a target city by using a surveying and mapping unmanned aerial vehicle of a laser radar point cloud data collecting system, loading a deep learning digital interpretation interface of a digital map, and inputting geographic information vector data obtained by translating the three-dimensional oblique photography data into a geographic information platform;

constructing a three-dimensional digital map of a city, verifying geographic information, converting three-dimensional oblique photographing data of a target city and geographic information vector data for completing data verification into a unified CGCS2000 coordinate system, carrying out data superposition processing according to geographic coordinates, and preparing the three-dimensional digital map of the city by depending on a geographic information platform;

the method comprises the steps of demarcating the types of land block units, acquiring target city POI data by loading POI data acquisition and land use identification interfaces of a digital map, giving different POI reference land use area values to different types of POI data, classifying the POI types according to the types of the land block units, and taking a dominant land block type with the largest area sum of the corresponding POI types in the land block units as a land use function of the land block units, wherein the specific calculation formula is as follows:

wherein i represents the type represented by the POI, fi represents the number of the i-th type POI in the block unit, S _i And representing the assigned POI reference land area value, wherein m represents the total number of POI types in the land block unit, n represents the total number of POI types under the corresponding type of the land block unit, and finally determining the land function of the land block unit by comparing the C values of different types.

3. The urban three-dimensional digital map generation method based on spatial entropy according to claim 2, characterized in that: the construction space entropy measurement method measures the building volume scale entropy, building structure form entropy and building elevation surface skin entropy of different types of land-used block units; the method comprises the steps of obtaining the spatial entropy value types of different types of land parcel units by adopting a natural break point method, establishing an entropy value result layer and an entropy value type layer of different types of spatial entropy digital maps, and displaying the image result of a three-dimensional digital map of a target city according to the functional parameter setting of the digital map layer, wherein the method specifically comprises the following steps:

measuring spatial entropy indexes, namely measuring spatial entropy indexes of three types of close relations between building body volume scale entropy, building structure form entropy and building facade surface entropy and building landscape, and measuring and calculating each land block unit of a target city through a loading index calculation module;

the building body measurement rule entropy comprises building height entropy and building substrate area entropy, the building structure form entropy comprises building main structure form entropy and building roof form entropy, and the building elevation surface entropy comprises building elevation color entropy and building elevation material entropy;

The basic formula of the spatial entropy index system is as follows:

wherein H (X) represents the result of measuring the spatial entropy of the object, n represents the total number of types of corresponding measurement standards, P _i Representing the probability of X under the corresponding classification when taking i;

identifying and displaying the spatial entropy types, and dividing the land parcel units into three types of high entropy, medium entropy and low entropy by adopting a natural break point method for the spatial entropy values of different types obtained through calculation; loading a space entropy database interface in the digital map, establishing space matching of geographic information vector data and space entropy data of a target city according to geographic coordinates, establishing a different type of space entropy digital map entropy value result layer and an entropy type layer, and setting according to functional parameters of the digital layer to display an image result of the three-dimensional digital map of the target city;

the setting of the functional parameters of the digital map layer comprises that the digital map layer can be displayed in a layered or overlapped mode through a display setting function of the digital map layer, the hyperlink function of the digital map layer can be used for linking and checking the same result or entropy value units of the same type, the chart statistics function of the digital map layer can be used for recording the statistical characteristic chart result of the entropy value result of a certain type, and the real scene re-tracing function of the digital map layer can be used for roaming to a specific block unit to check the corresponding type characteristic under the three-dimensional oblique photography real scene image when checking the space entropy layers of different types.

4. A method for generating a three-dimensional digital map of a city based on spatial entropy according to claim 3, wherein: the method comprises the steps of collecting a target regional land parcel level detailed city design scheme, carrying out vectorization processing, constructing a space entropy sample library, automatically matching samples in the space entropy sample library according to space attributes of land parcel units, calculating six types of space entropy values of the samples, marking urban land parcels which do not meet the space entropy threshold as possible land parcels to be updated and displaying the land parcels in a grading mode, collecting target regional crowd vitality data and public emotion data as secondary judging conditions for updating the land parcels, judging the land parcels to be updated and adding labels for displaying, and specifically comprises the following steps:

constructing a space entropy sample library, collecting a target regional land block level detailed city design scheme, intelligently translating the content of the design scheme into three-dimensional vector data, inputting the three-dimensional vector data into a three-dimensional digital map, constructing a target regional space entropy sample library, calculating land functions of all land blocks, and three space attribute values of a normalized boundary shape index, a normalized perimeter and a normalized area, and labeling the three space attribute values in a label form;

matching and judging the spatial entropy threshold value, calculating three large spatial attribute values of the target block unit, automatically matching the unique sample data with the same functions and the minimum spatial attribute difference value in the spatial entropy sample library, then calculating six types of spatial entropy values of the matched samples according to the spatial entropy measurement method of claim 2, taking the maximum value and the minimum value of the six types of spatial entropy values of the samples as judging standards of the six types of spatial entropy threshold values of the target block unit respectively,

Wherein, the formula of the spatial attribute difference value is as follows,

wherein Cn, ln and Sn are respectively the normalized shape index, perimeter and area value of the sample plot, and Cx, lx and Sx are respectively the normalized shape index, perimeter and area value of the sample plot;

extracting a super-threshold land block and displaying a possibly updated land block unit, taking six types of spatial entropy thresholds obtained by matching and judging the spatial entropy thresholds as judging standards, extracting a land block exceeding a threshold range, adding a spatial entropy type label exceeding the threshold, standardizing the spatial entropy value exceeding the range of the extracted land block, then respectively dividing the exceeding severity of the six types of spatial entropy thresholds into three grades of severity, medium and slight by a natural break method, marking the extracted land block with severity labels and marking the extracted land block as a possibly updated land block unit, and carrying out classified display by different colors in a three-dimensional digital map;

and (3) verifying crowd position and emotion data, displaying early warning updated land block judgment results, collecting crowd vitality data and public emotion data, loading the crowd vitality data and the public emotion data into a three-dimensional digital map through spatial association, carrying out secondary judgment on land block units possibly to be updated according to the crowd position and emotion data, marking land blocks meeting judgment conditions as the land block units to be updated for early warning, and displaying the land block units in the three-dimensional digital map.

5. The method for generating the urban three-dimensional digital map based on the spatial entropy according to claim 4, wherein the method comprises the following steps of: the method comprises the steps of constructing a three-dimensional digital map sensor of a city, recognizing voice and actions of a user, constructing a spatial entropy adjustment instruction library, adjusting building height, building area and building color, checking whether adjustment content meets specifications through relevant specification conditions of design and appearance of a target city, and carrying out feedback update on the adjusted spatial entropy in the three-dimensional digital map, wherein the method specifically comprises the following steps:

the method comprises the steps of user instruction voice and action recognition, loading a VR interaction adjustment module based on an urban landscape update interaction instruction in a three-dimensional digital map, wherein the VR interaction adjustment module comprises a voice recognition system, an action recognition wearable device carrying an inertial sensor and a handheld control system, and the user voice and user actions are recognized through conduction data calculation, and the user voice recognition comprises advancing, turning right, turning left, checking update early warning plots, checking update demand grades, adjusting building color space entropy, adjusting building area space entropy, adjusting building height space entropy, determining whether checking is yes or not; the user behavior comprises four actions of user walking, gaze steering, arm pointing and finger key touch;

The method comprises the steps of constructing a spatial entropy adjustment instruction library, constructing a spatial entropy adjustment instruction library according to recognized voices and actions, completing the functions of freely walking and browsing space, selecting and viewing detailed information of land parcels, displaying spatial entropy values, viewing and updating early warning land parcels information, viewing and updating demand levels, adjusting the dimensional spatial entropy of a building body, adjusting the spatial entropy of a building structure form and adjusting the spatial entropy of a building elevation surface, when a user confirms that certain type of spatial entropy adjustment is carried out, using the constructed spatial entropy sample library as a training set for deep learning, automatically randomly generating new building model data in a threshold range according to the type of spatial entropy threshold range corresponding to the land parcels, and repeatedly updating through adjustment instructions if the user is not satisfied;

and checking and feeding back standard conditions, namely collecting design standard conditions related to urban landscapes in a target area, carrying out intelligent examination on the data randomly generated after the user selects adjustment according to the standard conditions, inputting the data into a data updating system of the three-dimensional digital map if the examination is passed, and feeding back the data to the user again if the examination is not passed, wherein the design standard conditions related to the urban landscapes comprise the control requirements of building height, building density, volume rate, building roof type, building color and building material in the overall urban design of the target area.

6. The method for generating the urban three-dimensional digital map based on the spatial entropy according to claim 5, wherein the method comprises the following steps of: the method comprises the steps of splicing and printing out the urban three-dimensional digital map after the space entropy adjustment, wherein the urban three-dimensional digital map comprises entropy values before and after various space entropy adjustment of an early warning land parcel unit, aerial view images before and after three-dimensional digital map updating, and space entropy values and aerial view images after the space entropy adjustment of the early warning land parcel unit exceeding a threshold value, and the space entropy values and the aerial view images are used for reference by planning design and management staff, and specifically comprises the following steps:

updating the generation and standard check of the urban three-dimensional digital map, splicing the adjusted land block data and the unadjusted land block data through spatial superposition to generate updated three-dimensional digital map data, and finally checking the spliced data according to the building sunshine interval and building fireproof interval standard in the controlled detailed planning;

and outputting the urban three-dimensional digital map data, integrating the spliced and checked updated urban three-dimensional digital map data with the data before updating, and printing and outputting the integrated and checked updated urban three-dimensional digital map data, wherein the output data comprises model aerial views before and after updating the urban three-dimensional digital map, model aerial views before and after updating the landform units, space entropy values before and after adjusting the landform units, and space entropy types of the to-be-updated landform units exceeding a threshold value for reference by planning design and management staff.

7. A spatial entropy-based urban three-dimensional digital map generation system, the system comprising:

the basic data acquisition and display module is used for acquiring three-dimensional oblique photographic data of a target city, translating the three-dimensional oblique photographic data to obtain geographic information vector data and inputting the geographic information vector data into the geographic information platform; after finishing data verification, carrying out superposition processing on the data, and constructing a basic sand table of the urban three-dimensional digital map; identifying the type of the land block unit through POI data, and dividing the target city into geographic space units taking land function land blocks as units;

the spatial entropy measurement and display module is used for constructing a spatial entropy measurement method and measuring the building body volume scale entropy, the building structure form entropy and the building elevation surface skin entropy of the land parcel units of different types; obtaining the spatial entropy value types of different types of land block units by adopting a natural break point method, establishing an entropy value result layer and an entropy value type layer of different types of spatial entropy digital maps, and setting according to the functional parameters of the digital layers to display the image result of the three-dimensional digital map of the target city;

the space entropy threshold judging and early warning display module is used for collecting a target regional land block level detailed city design scheme, carrying out vectorization processing, constructing a space entropy sample library, automatically matching samples in the space entropy sample library according to space attributes of land block units, calculating six types of space entropy values of the samples, marking urban land blocks which do not meet the space entropy threshold as possible land blocks to be updated and displaying the possible land blocks in a grading manner, collecting target regional crowd activity data and public emotion data as secondary judging conditions for updating the land blocks, judging the land blocks to be updated and adding labels for displaying;

The urban three-dimensional space sand table interactive display and adjustment module is used for constructing an urban three-dimensional digital map sensor, identifying the voice and the action of a user, constructing a space entropy adjustment instruction library, adjusting building height, building area and building color, checking whether adjustment content meets the specification through the design and appearance related specification conditions of a target city, and carrying out feedback update on the adjusted space entropy in the three-dimensional digital map;

the result output module is used for splicing and printing out the urban three-dimensional digital map after the space entropy adjustment, and comprises various entropy values before and after the space entropy adjustment of the early-warning land block unit, a bird's eye view image before and after the three-dimensional digital map update, and the space entropy value and the bird's eye view image after the space entropy adjustment of the early-warning land block unit exceeding a threshold value, which are used for planning, designing and managing personnel to refer to;

the system is used for realizing the urban three-dimensional digital map generation method based on the spatial entropy according to any one of claims 1-6.

8. A terminal device comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, characterized in that the memory stores the computer program capable of running on the processor, and that the processor, when loading and executing the computer program, employs a spatial entropy based urban three-dimensional digital map generating method according to any of claims 1-6.

9. A computer readable storage medium storing a computer program, wherein the program when executed by a processor implements a spatial entropy based urban three-dimensional digital map generating method according to any one of claims 1-6.

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