CN115758890A - Intelligent monitoring method and system for sponge city - Google Patents
Intelligent monitoring method and system for sponge city Download PDFInfo
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- CN115758890A CN115758890A CN202211468844.XA CN202211468844A CN115758890A CN 115758890 A CN115758890 A CN 115758890A CN 202211468844 A CN202211468844 A CN 202211468844A CN 115758890 A CN115758890 A CN 115758890A
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Abstract
The invention discloses a method and a system for intelligently monitoring a sponge city, wherein the technical scheme of the invention utilizes a cellular automaton model to simulate and deduce the rainwater absorption condition of the sponge city in the future time, sets a water absorption area in the city as seed cells, utilizes city construction activities, water absorption capacity and weather conditions as influence factors of the cellular automaton model, and can accurately deduce the rainwater absorption condition of the sponge city in the future time through the continuous development of tissue cells in a tissue development mode so as to send out an early warning signal; the disaster early warning can not be carried out in advance by solving the existing manual prejudgment, the timeliness is lacked, the manual prejudgment mode is lacked in accuracy and efficiency, the technical problem that effective help can not be provided for the monitoring of the smart sponge city is solved, the manual prejudgment strategy under the traditional mode is replaced, early warning disasters can be carried out on the smart sponge city in advance, and the timeliness, the accuracy and the efficiency of monitoring the smart sponge city are improved.
Description
Technical Field
The invention relates to the field of urban big data processing, in particular to a sponge urban intelligent monitoring method and system.
Background
The sponge city is a new generation of city rainfall flood management concept, and refers to a city which can be like a sponge and has good elasticity in the aspects of adapting to environmental changes, coping with natural disasters caused by rainwater and the like, and the city can also be called as a water elasticity city. In sponge cities, rainwater can supplement groundwater, lakes and the like through water permeability subsurface infiltration, greenbelt stagnation and the like. In addition, a large amount of rainwater is recycled through the rainwater collecting device, the flow discarding device, the filtering device, the transmission device and the storage device, so that the urban can absorb rainwater impact caused by flood to the maximum extent, and the life safety of people and animals and plants in the urban is protected. Based on this, how accurately to predict the sponge city on the rainwater volume of holding to infer the risk that the sponge city will face, so that the professional carries out the plan processing to the calamity risk, guarantee people's life and property safety.
In the prior art, a risk early warning strategy of a sponge city on rainwater holding capacity is observed through the flood condition of a worker city at present, and then manual prejudgment is performed by combining the future rainwater condition. The manual pre-judging mode can only send out early warning when the maximum rainwater holding capacity of the city exceeds the maximum limit and a problem occurs after the flood occurs; the disaster early warning can not be carried out in advance, the timeliness is lacked, the manual prejudging mode is lacked in accuracy and efficiency, and effective help can not be provided for monitoring of the smart sponge city.
The Cellular Automata (CA) is a grid dynamics model with discrete time, space and state, and the spatial interaction and time causal relationship are local, and has the capability of simulating the time-space evolution process of a complex system. The cellular automata model can deduce the occurrence condition of an event, but since the cellular automata model is commonly used in ecological and economic deductions in the past, how to utilize the cellular automata model to deduce and early warn the rainwater holding capacity of a sponge city, realize the real-time monitoring of the occurrence of disasters and solve the problem that the cellular automata model still needs to make compatible breakthrough efforts in the deduction of the disasters of the sponge city. The necessary influence factors of the sponge city on the rainwater holding capacity and the development deduction of the sponge city on the rainwater disaster are researched, and the deduction strategy fitting the cellular automata model is researched, so that the cellular automata model can be suitable for the intelligent monitoring of the sponge city.
In the face of the change of ecological environment, a sponge city monitoring strategy with higher practicability is researched, and the method has important significance for the survival of human ecological civilization. Based on the circumstances, urgent need for a sponge city wisdom monitoring strategy on the market at present to solve current artifical judgement and can't accomplish to carry out calamity early warning in advance, lack the ageing, in addition artifical mode of judging in advance lacks accuracy and efficiency, can't provide the technical problem of effective help to the control in wisdom sponge city.
Disclosure of Invention
The invention provides a smart monitoring method and a smart monitoring system for a sponge city, which are used for replacing a manual prejudgment strategy in a traditional mode, realizing early warning of disasters for the sponge city and improving timeliness, accuracy and efficiency of monitoring the smart sponge city.
In order to solve the technical problem, an embodiment of the present invention provides an intelligent monitoring method for a sponge city, including:
acquiring three-dimensional data of a target sponge city, establishing a space model corresponding to the target sponge city according to the three-dimensional data, and establishing a cellular automata model based on the space model;
determining the development time of a cellular automata model, acquiring future weather data corresponding to the development time of the target sponge city, and dividing the target sponge city into a plurality of tissue plates in the space model according to the future weather data and the topography of the target sponge city;
acquiring planning data of a target sponge city, determining a water absorption area of the target sponge city in each tissue plate according to the planning data, taking each water absorption area as a seed cell of a cellular automaton model, and taking an area except the water absorption area in each tissue plate as a tissue cell of the cellular automaton model;
acquiring city construction activities of a target sponge city in each tissue plate within the development time, and taking the city construction activities as first influence elements; calculating the total water absorption capacity of each tissue plate in unit time according to the water absorption capacity of each water absorption area in unit time, and taking the total water absorption capacity as a second influence element; determining rainfall data of each tissue plate in the development time according to the future weather data, and taking the rainfall data as a third influence element;
inputting the first influence element, the second influence element and the third influence element into a cellular automaton model, determining whether the seed cellular is alive according to the first influence element, and when the seed cellular is determined to be alive, controlling the tissue cellular to develop within the development time according to the second influence element and the third influence element, and meanwhile, adjusting the second influence element according to the first influence element;
and determining a development red line in the spatial model, selecting a tissue development mode, and stopping development and sending out an early warning signal when the development of the tissue cellular reaches the development red line or the starting time of the tissue development mode reaches the development time.
As a preferred scheme, the step of acquiring three-dimensional data of a target sponge city, establishing a spatial model corresponding to the target sponge city according to the three-dimensional data, and constructing a cellular automaton model based on the spatial model specifically includes:
acquiring three-dimensional data of a target sponge city, wherein the three-dimensional data comprises city airspace data, city land area data and land topography data;
determining a development red line of a target sponge city according to the urban airspace data and the urban land data, and selecting a plurality of reference points on the development red line;
based on a plurality of reference points, performing space-time alignment on the urban airspace data and the urban land data so as to construct a space model corresponding to the target sponge city;
and adjusting the space model according to the land topography data to optimize the space model.
As a preferred scheme, the step of dividing the target sponge city into a plurality of tissue plates in the spatial model according to the future weather data and the topography of the target sponge city specifically includes:
acquiring future weather data of a target sponge city, and judging rainfall of the target sponge city in each region in a space model according to the future weather data;
acquiring land topography data of a target sponge city, and judging a rainwater confluence point formed by rainfall of each region under the influence of different topography according to the land topography data;
in the space model, the target sponge city is divided into a plurality of corresponding tissue plates according to the area range of each rainwater confluence point.
As a preferred scheme, the step of obtaining planning data of a target sponge city, determining a water absorption area of the target sponge city in each tissue plate according to the planning data, taking each water absorption area as a seed cell of a cellular automaton model, and taking an area except the water absorption area in each tissue plate as a tissue cell of the cellular automaton model specifically includes:
acquiring planning data of a target sponge city, wherein the planning data comprises urban sewer data, rainwater collection facility construction data and natural water area data;
respectively determining the holding capacity of the urban sewer and the rainwater collection facility in each organization plate according to the urban sewer data and the rainwater collection facility construction data, and taking the water absorption areas corresponding to the urban sewer and the rainwater collection facility with the holding capacity reaching a capacity threshold value as seed cells of a cell automata model; meanwhile, according to the data of the natural water area, the water absorption area corresponding to the natural water area in each tissue plate is used as a seed cell of a cell automaton model;
and respectively determining the position of each seed cell in the space model, and taking the positions except the seed cells in the space model as organization cells of the cellular automaton model.
Preferably, the step of determining whether the seed cell survives according to the first influencing element specifically includes:
determining city construction types and construction duration according to the city construction activities, and determining organization plates correspondingly influenced by the city construction activities according to the city construction types;
setting a positive growth value or a negative growth value for all seed cells in the affected tissue plates according to the city construction type and the construction duration;
setting an initial development probability for each seed cell in the space model, and adjusting the initial development probability corresponding to each seed cell according to a positive growth value or a negative growth value set for each seed cell in an affected tissue plate;
and when the adjusted development probability reaches a preset probability threshold, determining that the seed cells are alive.
Preferably, the step of controlling the development of the tissue cellular unit within the development time according to the second influencing element and the third influencing element specifically comprises:
extracting the rainfall of each tissue plate in unit time from the rainfall data according to the third influence elements, and calculating the rainfall of each tissue cell in the same tissue plate in unit time according to the land topography data corresponding to each tissue plate to generate a rainfall distribution sequence;
extracting the total water absorption of each tissue plate in the second influencing elements in unit time, and determining the development area of the tissue cells in unit time according to the total water absorption and the rainfall distribution sequence; to control the development of the tissue cells within the development time.
As a preferred scheme, the step of adjusting the second influence element according to the first influence element specifically includes:
when the city construction type and the construction duration in the first influence element set all the seed cells in the influenced tissue plates to be positive growth values, the total water absorption capacity of each tissue plate in the second influence element in unit time is multiplied;
and when the city construction type and the construction time length in the first influence element set all the seed cells in the influenced tissue plates as negative growth values, reducing the total water absorption of each tissue plate in the second influence element by a multiple in unit time.
Preferably, after determining the development red line in the spatial model, the method further comprises:
when the seed cells in the tissue plate are set as a negative growth value and the adjusted development probability of the seed cells is lower than a preset probability threshold value, determining that the seed cells are not alive;
when the seed cellular in the tissue plate is set as a negative growth value and the adjusted development probability of the seed cellular is not lower than a preset probability threshold, taking the absolute value of the negative growth value as a multiple, expanding the development probability of the seed cellular by a corresponding multiple, and controlling the seed cellular to develop within the development time;
and selecting a spontaneous growth mode, and stopping the development and sending out an early warning signal when the seed cellular is determined to be non-viable, or the development of the seed cellular reaches the development red line, or the starting time of the spontaneous growth mode reaches the development time.
Correspondingly, another embodiment of the present invention further provides an intelligent monitoring system for sponge city, including: the system comprises a three-dimensional data module, a tissue plate module, a water absorption area module, an influence element module, a development control module and an early warning signal module, wherein each module is as follows:
the three-dimensional data module is used for acquiring three-dimensional data of a target sponge city, establishing a space model corresponding to the target sponge city according to the three-dimensional data, and establishing a cellular automata model based on the space model;
the tissue plate module is used for determining the development time of the cellular automaton model, acquiring future weather data corresponding to the development time of the target sponge city, and dividing the target sponge city into a plurality of tissue plates in the space model according to the future weather data and the topography of the target sponge city;
the water absorption area module is used for acquiring planning data of a target sponge city, determining a water absorption area of the target sponge city in each tissue plate according to the planning data, taking each water absorption area as a seed cell of a cellular automaton model, and taking an area except the water absorption area in each tissue plate as a tissue cell of the cellular automaton model;
the influence element module is used for acquiring city construction activities of the target sponge city in each tissue plate within the development time, and taking the city construction activities as first influence elements; calculating the total water absorption capacity of each tissue plate in unit time according to the water absorption capacity of each water absorption area in unit time, and taking the total water absorption capacity as a second influence element; determining rainfall data of each tissue plate in the development time according to the future weather data, and taking the rainfall data as a third influence element;
the control development module is used for inputting the first influence element, the second influence element and the third influence element into a cellular automaton model, determining whether the seed cellular is alive according to the first influence element, controlling the tissue cellular to develop within the development time according to the second influence element and the third influence element when the seed cellular is determined to be alive, and meanwhile adjusting the second influence element according to the first influence element;
the early warning signal module is used for determining a development red line in the space model, selecting a tissue development mode, and stopping development and sending an early warning signal when the development of tissue cells reaches the development red line or the starting time of the tissue development mode reaches the development time.
As a preferred scheme, the three-dimensional data module is specifically configured to: acquiring three-dimensional data of a target sponge city, wherein the three-dimensional data comprises urban airspace data, urban land area data and land topography data; determining a development red line of a target sponge city according to the urban airspace data and the urban land data, and selecting a plurality of reference points on the development red line; based on a plurality of reference points, performing space-time alignment on the urban airspace data and the urban land domain data so as to construct a space model corresponding to the target sponge city; and adjusting the space model according to the land topography data to optimize the space model.
As a preferred scheme, the tissue plate module is configured to divide the target sponge city into a plurality of tissue plates in the spatial model according to the future weather data and the topography of the target sponge city, and specifically includes: acquiring future weather data of a target sponge city, and judging rainfall of the target sponge city in each region in a space model according to the future weather data; acquiring land topography data of a target sponge city, and judging a rainwater confluence point formed by rainfall of each region under the influence of different topography according to the land topography data; in the space model, the target sponge city is divided into a plurality of corresponding tissue plates according to the area range of each rainwater confluence point.
As a preferred scheme, the water absorption area module is specifically used for: acquiring planning data of a target sponge city, wherein the planning data comprises urban sewer data, rainwater collection facility construction data and natural water area data; respectively determining the holding capacity of the urban sewer and the rainwater collection facility in each organization plate according to the urban sewer data and the rainwater collection facility construction data, and taking the water absorption areas corresponding to the urban sewer and the rainwater collection facility with the holding capacity reaching a capacity threshold value as seed cells of a cell automata model; meanwhile, according to the data of the natural water area, the water absorption area corresponding to the natural water area in each tissue plate is used as a seed cell of a cell automaton model; and respectively determining the position of each seed cell in the space model, and taking the positions except the seed cells in the space model as organization cells of the cellular automaton model.
Preferably, the controlling and developing module is configured to determine whether the seed cell survives according to the first influencing element, and specifically includes: determining city construction types and construction duration according to the city construction activities, and determining organization plates correspondingly influenced by the city construction activities according to the city construction types; setting a positive growth value or a negative growth value for all seed cells in the affected tissue plates according to the city construction type and the construction duration; setting an initial development probability for each seed cell in the space model, and adjusting the initial development probability corresponding to each seed cell according to a positive growth value or a negative growth value set for each seed cell in an affected tissue plate; and when the adjusted development probability reaches a preset probability threshold, determining that the seed cells are alive.
Preferably, the development control module is configured to control the development of the tissue cellular unit in the development time according to the second influencing element and the third influencing element, and specifically includes: extracting the rainfall of each tissue plate in unit time from the rainfall data according to the third influence elements, and calculating the rainfall of each tissue cell in the same tissue plate in unit time according to the land topography data corresponding to each tissue plate to generate a rainfall distribution sequence; extracting the total water absorption of each tissue plate in the second influence elements in unit time, and determining the development area of the tissue cells in unit time according to the total water absorption and the rainfall distribution sequence; to control the development of tissue cells during said development time.
As a preferred scheme, the step of adjusting the second influence element according to the first influence element by the control development module specifically includes: when the city construction type and the construction duration in the first influence element set all the seed cells in the influenced tissue plates to be positive growth values, the total water absorption capacity of each tissue plate in the second influence element in unit time is multiplied; and when the city construction type and the construction time length in the first influence element set all the seed cells in the influenced tissue plates as negative growth values, reducing the total water absorption of each tissue plate in the second influence element by a multiple in unit time.
Preferably, after determining the development red line in the spatial model, the early warning signal module is further configured to: when the seed cells in the tissue plate are set to be a negative growth value and the adjusted development probability of the seed cells is lower than a preset probability threshold, determining that the seed cells do not survive; when the seed cellular in the tissue plate is set as a negative growth value and the adjusted development probability of the seed cellular is not lower than a preset probability threshold, taking the absolute value of the negative growth value as a multiple, expanding the development probability of the seed cellular by a corresponding multiple, and controlling the seed cellular to develop within the development time; and selecting a spontaneous growth mode, and stopping the development and sending out an early warning signal when the seed cellular is determined to be non-viable, or the development of the seed cellular reaches the development red line, or the starting time of the spontaneous growth mode reaches the development time.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program; wherein the computer program, when running, controls the device on which the computer readable storage medium is located to execute the sponge city intelligent monitoring method according to any one of the above items.
The embodiment of the present invention further provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor, when executing the computer program, implements the sponge city intelligent monitoring method according to any one of the above items.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
according to the technical scheme, a cellular automata model is used for simulating and deducing the rainwater absorption condition of a sponge city in the future time, a water absorption area in the city is set as seed cells, urban construction activities, water absorption capacity and weather conditions are used as influence factors of the cellular automata model, and the rainwater absorption condition of the sponge city in the future time can be accurately deduced through continuous development of tissue cells in a tissue development mode so as to send an early warning signal; the disaster early warning can not be carried out in advance by solving the existing manual prejudgment, the timeliness is lacked, the manual prejudgment mode is lacked in accuracy and efficiency, the technical problem that effective help can not be provided for the monitoring of the smart sponge city is solved, the manual prejudgment strategy under the traditional mode is replaced, early warning disasters can be carried out on the smart sponge city in advance, and the timeliness, the accuracy and the efficiency of monitoring the smart sponge city are improved.
Drawings
FIG. 1: the invention provides a step flow chart of a sponge city intelligent monitoring method;
FIG. 2: the invention provides a structural schematic diagram of a sponge city intelligent monitoring system;
FIG. 3: the structure diagram of an embodiment of the terminal device provided by the embodiment of the invention is shown.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1, a flow chart of steps of a method for intelligently monitoring a sponge city according to an embodiment of the present invention includes steps 101 to 106, and the steps are as follows:
step 101, acquiring three-dimensional data of a target sponge city, establishing a space model corresponding to the target sponge city according to the three-dimensional data, and establishing a cellular automaton model based on the space model.
In this embodiment, the step 101 specifically includes: step 1011, acquiring three-dimensional data of a target sponge city, wherein the three-dimensional data comprises urban airspace data, urban land area data and land topography data; step 1012, determining a development red line of a target sponge city according to the urban airspace data and the urban land data, and selecting a plurality of reference points on the development red line; step 1013, based on a plurality of reference points, performing space-time alignment on the urban airspace data and the urban land domain data so as to construct a space model corresponding to the target sponge city; and 1014, adjusting the space model according to the land topography data to optimize the space model.
Specifically, in order to realize intelligent monitoring of the sponge city, a space model of the sponge city needs to be constructed first. The three-dimensional data mentioned in this step, i.e. all the geographic data including the universe of the sponge city, etc., needs to be built into the spatial model. In the step of determining the development red line through the urban airspace data and the urban land data, the horizon line can be selected as the development red line, namely when the rainwater overflows to the horizon line, the stratum is proved to be incapable of absorbing the rainwater, and the red line is triggered at the moment. It is understood that there are many choices of the developmental red line, which are custom set according to city size or user tolerance, and this step is not limited. In order to prevent the subsequent deduction process from being influenced by airspace and land areas in the space model, the space model is required to be aligned in the step and adjusted according to terrain data, so that some terrain with low or high bumps is adjusted.
Step 102, determining the development time of the cellular automaton model, acquiring future weather data corresponding to the development time of the target sponge city, and dividing the target sponge city into a plurality of tissue plates in the space model according to the future weather data and the topography of the target sponge city.
In this embodiment, in the step 102, according to the future weather data and the topography of the target sponge city, in the step of dividing the target sponge city into a plurality of tissue plates in the spatial model, the method specifically includes: step 1021, acquiring future weather data of the target sponge city, and judging rainfall of the target sponge city in each region in the space model according to the future weather data; step 1022, acquiring land topography data of a target sponge city, and judging a rainwater confluence point formed by rainfall of each region under the influence of different topography according to the land topography data; and 1023, dividing the target sponge city into a plurality of corresponding tissue plates according to the area range forming each rainwater confluence point in the space model.
Specifically, due to different terrains, when the rainwater meets the difference of terrains, the rainwater converges towards the low-lying areas, the water immersion condition of the high-lying areas is good, and the low-lying areas are serious. The rainfall of each area is predicted by using future weather data, the rainwater confluence point can be judged according to the difference of the terrain by analyzing the terrain of each area, and then the range area corresponding to each rainwater backflow point is divided to form the tissue plate block.
103, acquiring planning data of a target sponge city, determining a water absorption area of the target sponge city in each tissue plate according to the planning data, taking each water absorption area as a seed cell of a cellular automaton model, and taking an area except the water absorption area in each tissue plate as a tissue cell of the cellular automaton model.
In this embodiment, the step 103 specifically includes: step 1031, acquiring planning data of a target sponge city, wherein the planning data comprises urban sewer data, rainwater collection facility construction data and natural water area data; step 1032, respectively determining the holding capacity of the urban sewer and the rainwater collection facility in each organization plate according to the urban sewer data and the rainwater collection facility construction data, and taking the water absorption areas corresponding to the urban sewer and the rainwater collection facility with the holding capacity reaching a capacity threshold value as seed cells of a cellular automata model; meanwhile, according to the natural water area data, the water absorption area corresponding to the natural water area in each tissue plate is used as a seed cell of a cell robot model; and 1033, respectively determining the position of each seed cellular in the space model, and taking the positions except the seed cellular in the space model as organization cellular of the cellular automaton model.
Specifically, the water absorption area is a natural water area such as water permeable subsurface infiltration area and greenbelt area , and equipment such as a rainwater collection device, a flow discarding device, a filtering device, a transmission device and a storage device and urban sewers are used for storing rainwater. These devices or areas, which can act as sponges to absorb rain, are marked as seed cells for the cellular automata model. And other positions in the space model are used as the tissue cells, so that in the subsequent deduction process of the tissue cells, when the tissue cells exceed the red line, an early warning signal is sent.
104, acquiring city construction activities of the target sponge city in each tissue plate within the development time, and taking the city construction activities as first influence elements; calculating the total water absorption capacity of each tissue plate in unit time according to the water absorption capacity of each water absorption area in unit time, and taking the total water absorption capacity as a second influence element; and determining rainfall data of each tissue plate in the development time according to the future weather data, and taking the rainfall data as a third influence element.
Specifically, in the subsequent adjustment of the development probability of the cell, we must consider each influencing element. For example: whether factors such as city construction activities, construction types and duration influence the existing water absorption area or not, including increasing water absorption and reducing water absorption; the water absorption capacity of each tissue plate in unit time; and the effect of future weather on rainfall.
Step 105, inputting the first influence element, the second influence element and the third influence element into a cellular automaton model, determining whether the seed cellular is alive according to the first influence element, controlling the tissue cellular to develop within the development time according to the second influence element and the third influence element when the seed cellular is determined to be alive, and adjusting the second influence element according to the first influence element.
Specifically, a large amount of data research shows that urban construction activities affect the existing water absorption areas, so that the urban construction activities in the development time need to be judged whether the existing water absorption areas lose the capacity of absorbing rainwater (i.e., whether the seed cells survive).
In the first aspect of this embodiment, in the step 105, determining whether the seed cell is alive according to the first influencing element specifically includes: determining city construction types and construction duration according to the city construction activities, and determining organization plates correspondingly influenced by the city construction activities according to the city construction types; setting a positive growth value or a negative growth value for all seed cells in the affected tissue plates according to the city construction type and the construction duration; setting an initial development probability for each seed cell in the space model, and adjusting the initial development probability corresponding to each seed cell according to a positive growth value or a negative growth value set for each seed cell in an affected tissue plate; and when the adjusted development probability reaches a preset probability threshold, determining that the seed cells are alive.
Specifically, the positive and negative growth values of the seed cells are determined by using the city construction type and the construction duration, and the set initial development probability is adjusted. In a specific adjustment step, the probability of development is scaled up if it belongs to a positive growth value, otherwise scaled down. It is understood that the specific adjustment strategy may vary according to the actual application and is not limited herein. By judging the adjusted development probability, the seed cells reaching the preset probability threshold are defined as survival and still have water absorption capacity.
In the second aspect of this embodiment, the step 105 of controlling the tissue cellular unit to develop within the development time according to the second influencing element and the third influencing element specifically includes: extracting the rainfall of each tissue plate in unit time from the rainfall data according to the third influence elements, and calculating the rainfall of each tissue cell in the same tissue plate in unit time according to the land topography data corresponding to each tissue plate to generate a rainfall distribution sequence; extracting the total water absorption of each tissue plate in the second influencing elements in unit time, and determining the development area of the tissue cells in unit time according to the total water absorption and the rainfall distribution sequence; to control the development of tissue cells during said development time.
Specifically, in the step of controlling development, we also need to determine the developmental area of the tissue cells. By utilizing rainfall data and topography data in the tissue plate, the rainfall in unit time at the position of each tissue cell, namely a low-lying region can be obtained, and the pressure of the rainfall is higher due to rainwater confluence. Thereby generating a rainfall distribution sequence formed by rainfall of different tissue cells in unit time for subsequently determining the development area of each tissue cell. The water uptake in the second influencing element is utilized, i.e., assuming: there is currently a tissue cell a, which has a water absorption of 100 ml/sec in its area, and actually has a rainfall of 120 ml/sec, which is equivalent to an actual water absorption of-20 ml/sec. A tissue cell b in which the area has a water absorption of 80 ml/sec and a rainfall of 70 ml/sec, corresponding to an actual water absorption of 10 ml/sec. The development area of the two tissue cells under the same tissue plate can be set according to the actual water absorption capacity in equal proportion. It is understood that, in practical applications, the formula for determining the development area or the definition rule may be adjusted according to practical situations, and is not limited herein.
In the third aspect of this embodiment, the step of adjusting the second influence element according to the first influence element in step 105 specifically includes: when the city construction type and the construction duration in the first influence element set all the seed cells in the influenced tissue plates to be positive growth values, the total water absorption capacity of each tissue plate in the second influence element in unit time is multiplied; when the city construction type and the construction duration in the first influence element set all the seed cells in the influenced tissue plates as negative growth values, the total water absorption capacity of each tissue plate in the second influence element in unit time is reduced by a multiple.
Specifically, as can be seen from the above steps, city construction activities may affect the water absorption area, so we need to set a positive or negative growth value for the seed cells to adjust the water absorption capacity of the seed cells.
And 106, determining a development red line in the spatial model, selecting a tissue development mode, and stopping development and sending out an early warning signal when the development of the tissue cellular reaches the development red line or the starting time of the tissue development mode reaches the development time.
Specifically, since the development red line of the target sponge city is determined in step 101, we only need to generate the development red line in the spatial model according to the red line. And selecting a tissue development mode, enabling the tissue cells to carry out development transformation under a preset condition, and sending out an early warning signal when the development reaches a red line, namely the rainwater is filled to the set red line.
In another embodiment, further comprising: step 107, after determining a development red line in the spatial model, when the seed cells in the tissue plate are set to be a negative growth value and the adjusted development probability of the seed cells is lower than a preset probability threshold, determining that the seed cells are not alive; when the seed cellular in the tissue plate is set as a negative growth value and the adjusted development probability of the seed cellular is not lower than a preset probability threshold, taking the absolute value of the negative growth value as a multiple, expanding the development probability of the seed cellular by a corresponding multiple, and controlling the seed cellular to develop within the development time; and selecting a spontaneous growth mode, and stopping the development and sending out an early warning signal when the seed cellular is determined to be non-viable, or the development of the seed cellular reaches the development red line, or the starting time of the spontaneous growth mode reaches the development time.
Specifically, in addition to the tissue development pattern, the cellular automata model can also deduce the development of seed cells through a spontaneous growth pattern. When the spontaneous growth mode is selected, what is deduced at this time is no longer the rain condition, but the development condition of the seed cells. The seed cells are affected by the affected elements, gradually lose water absorption capacity when subjected to negative growth for a long time, and decrease the water absorption capacity, otherwise, the rainwater in the area is increased. Therefore, the full irrigation condition of rainwater is deduced reversely by the spontaneous growth module and the water absorption capacity change of the seed cells, and when the full irrigation reaches a red line, an early warning signal is sent out.
According to the technical scheme, a cellular automaton model is used for simulating and deducing the rainwater absorption condition of the sponge city in the future time, a water absorption area in the city is set as a seed cellular, urban construction activities, water absorption capacity and weather conditions are used as influence factors of the cellular automaton model, and the rainwater absorption condition of the sponge city in the future time can be accurately deduced by organizing the cells under the continuous development of a tissue development mode so as to send out an early warning signal; the disaster early warning can not be carried out in advance by solving the existing manual prejudgment, the timeliness is lacked, the manual prejudgment mode is lacked in accuracy and efficiency, the technical problem that effective help can not be provided for the monitoring of the smart sponge city is solved, the manual prejudgment strategy under the traditional mode is replaced, early warning disasters can be carried out on the smart sponge city in advance, and the timeliness, the accuracy and the efficiency of monitoring the smart sponge city are improved.
Example two
Referring to fig. 2, a schematic structural diagram of a sponge city intelligent monitoring system according to another embodiment of the present invention includes: the system comprises a three-dimensional data module, a tissue plate module, a water absorption area module, an influence element module, a development control module and an early warning signal module, wherein each module is as follows:
the three-dimensional data module is used for acquiring three-dimensional data of a target sponge city, establishing a space model corresponding to the target sponge city according to the three-dimensional data, and establishing a cellular automaton model based on the space model.
In this embodiment, the three-dimensional data module is specifically configured to: acquiring three-dimensional data of a target sponge city, wherein the three-dimensional data comprises city airspace data, city land area data and land topography data; determining a development red line of a target sponge city according to the urban airspace data and the urban land data, and selecting a plurality of reference points on the development red line; based on a plurality of reference points, performing space-time alignment on the urban airspace data and the urban land data so as to construct a space model corresponding to the target sponge city; and adjusting the space model according to the land topography data to optimize the space model.
The tissue plate module is used for determining the development time of the cellular automaton model, acquiring future weather data corresponding to the development time of the target sponge city, and dividing the target sponge city into a plurality of tissue plates in the space model according to the future weather data and the topography of the target sponge city.
In this embodiment, the tissue plate module is configured to divide the target sponge city into a plurality of tissue plates in the spatial model according to the future weather data and the topography of the target sponge city, and specifically includes: acquiring future weather data of a target sponge city, and judging rainfall of the target sponge city in each region in a space model according to the future weather data; acquiring land topography data of a target sponge city, and judging a rainwater confluence point formed by rainfall of each region under the influence of different topography according to the land topography data; in the space model, the target sponge city is divided into a plurality of corresponding tissue plates according to the area range of each rainwater confluence point.
The water absorption area module is used for acquiring planning data of a target sponge city, determining a water absorption area of the target sponge city in each tissue plate according to the planning data, taking each water absorption area as a seed cell of a cellular automata model, and taking an area except the water absorption area in each tissue plate as an organization cell of the cellular automata model.
In this embodiment, the water absorption region module is specifically configured to: acquiring planning data of a target sponge city, wherein the planning data comprises urban sewer data, rainwater collection facility construction data and natural water area data; respectively determining the holding capacity of the urban sewer and the rainwater collection facility in each organization plate according to the urban sewer data and the rainwater collection facility construction data, and taking the water absorption areas corresponding to the urban sewer and the rainwater collection facility with the holding capacity reaching a capacity threshold value as seed cells of a cell automata model; meanwhile, according to the data of the natural water area, the water absorption area corresponding to the natural water area in each tissue plate is used as a seed cell of a cell automaton model; and respectively determining the position of each seed cell in the space model, and taking the positions except the seed cells in the space model as organization cells of the cellular automaton model.
The influence element module is used for acquiring city construction activities of the target sponge city in each tissue plate within the development time, and taking the city construction activities as first influence elements; calculating the total water absorption capacity of each tissue plate in unit time according to the water absorption capacity of each water absorption area in unit time, and taking the total water absorption capacity as a second influence element; and determining rainfall data of each tissue plate in the development time according to the future weather data, and taking the rainfall data as a third influence element.
And the control development module is used for inputting the first influence element, the second influence element and the third influence element into a cellular automaton model, determining whether the seed cellular is alive according to the first influence element, controlling the tissue cellular to develop within the development time according to the second influence element and the third influence element when the seed cellular is determined to be alive, and adjusting the second influence element according to the first influence element.
In the first aspect of this embodiment, the step of determining whether the seed cell is alive according to the first influencing element by the control development module specifically includes: determining city construction types and construction duration according to the city construction activities, and determining organization plates correspondingly influenced by the city construction activities according to the city construction types; setting a positive growth value or a negative growth value for all seed cells in the affected tissue plates according to the city construction type and the construction duration; setting an initial development probability for each seed cell in the space model, and adjusting the initial development probability corresponding to each seed cell according to a positive growth value or a negative growth value set for each seed cell in an affected tissue plate; and when the adjusted development probability reaches a preset probability threshold, determining that the seed cells are alive.
In a second aspect of this embodiment, the step of controlling the development of the tissue cellular unit in the development time according to the second influencing element and the third influencing element specifically includes: extracting the rainfall of each tissue plate in unit time from the rainfall data according to the third influence elements, and calculating the rainfall of each tissue cell in the same tissue plate in unit time according to the land topography data corresponding to each tissue plate to generate a rainfall distribution sequence; extracting the total water absorption of each tissue plate in the second influencing elements in unit time, and determining the development area of the tissue cells in unit time according to the total water absorption and the rainfall distribution sequence; to control the development of tissue cells during said development time.
In a third aspect of this embodiment, the step of adjusting the second influence element according to the first influence element by the control development module specifically includes: when the city construction type and the construction duration in the first influence element set all the seed cells in the influenced tissue plates to be positive growth values, the total water absorption capacity of each tissue plate in the second influence element in unit time is multiplied; and when the city construction type and the construction time length in the first influence element set all the seed cells in the influenced tissue plates as negative growth values, reducing the total water absorption of each tissue plate in the second influence element by a multiple in unit time.
The early warning signal module is used for determining a development red line in the space model, selecting a tissue development mode, and stopping development and sending an early warning signal when the development of tissue cells reaches the development red line or the starting time of the tissue development mode reaches the development time.
In another embodiment, the early warning signal module, after determining a developmental red line in the spatial model, is further configured to: when the seed cells in the tissue plate are set as a negative growth value and the adjusted development probability of the seed cells is lower than a preset probability threshold value, determining that the seed cells are not alive; when the seed cellular in the tissue plate is set as a negative growth value and the adjusted development probability of the seed cellular is not lower than a preset probability threshold, taking the absolute value of the negative growth value as a multiple, expanding the development probability of the seed cellular by a corresponding multiple, and controlling the seed cellular to develop within the development time; and selecting a spontaneous growth mode, and stopping the development and sending out an early warning signal when the seed cellular is determined to be non-viable, or the development of the seed cellular reaches the development red line, or the starting time of the spontaneous growth mode reaches the development time.
EXAMPLE III
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program; when the computer program runs, the computer program controls the device where the computer readable storage medium is located to execute the sponge city intelligent monitoring method according to any one of the above embodiments.
Example four
Referring to fig. 3, which is a schematic structural diagram of a terminal device according to an embodiment of the present invention, the terminal device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the intelligent monitoring method for sponge cities according to any one of the above embodiments when executing the computer program.
Preferably, the computer program may be divided into one or more modules/units (e.g., computer program) that are stored in the memory and executed by the processor to implement the invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used for describing the execution process of the computer program in the terminal device.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, etc., the general purpose Processor may be a microprocessor, or the Processor may be any conventional Processor, the Processor is a control center of the terminal device, and various interfaces and lines are used to connect various parts of the terminal device.
The memory mainly includes a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like, and the data storage area may store related data and the like. In addition, the memory may be a high speed random access memory, may also be a non-volatile memory, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card), and the like, or may also be other volatile solid state memory devices.
It should be noted that the terminal device may include, but is not limited to, a processor and a memory, and those skilled in the art will understand that the terminal device is only an example and does not constitute a limitation of the terminal device, and may include more or less components, or combine some components, or different components.
The above-mentioned embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, and it should be understood that the above-mentioned embodiments are only examples of the present invention and are not intended to limit the scope of the present invention. It should be understood that any modifications, equivalents, improvements and the like, which come within the spirit and principle of the invention, may occur to those skilled in the art and are intended to be included within the scope of the invention.
Claims (10)
1. A sponge city intelligent monitoring method is characterized by comprising the following steps:
acquiring three-dimensional data of a target sponge city, establishing a space model corresponding to the target sponge city according to the three-dimensional data, and establishing a cellular automata model based on the space model;
determining the development time of a cellular automaton model, acquiring future weather data corresponding to the development time of the target sponge city, and dividing the target sponge city into a plurality of tissue plates in the space model according to the future weather data and the topography of the target sponge city;
acquiring planning data of a target sponge city, determining a water absorption area of the target sponge city in each tissue plate according to the planning data, taking each water absorption area as a seed cell of a cellular automaton model, and taking an area except the water absorption area in each tissue plate as a tissue cell of the cellular automaton model;
acquiring city construction activities of the target sponge city in each tissue plate within the development time, and taking the city construction activities as first influence elements; calculating the total water absorption capacity of each tissue plate in unit time according to the water absorption capacity of each water absorption area in unit time, and taking the total water absorption capacity as a second influence element; determining rainfall data of each tissue plate in the development time according to the future weather data, and taking the rainfall data as a third influence element;
inputting the first influence element, the second influence element and the third influence element into a cellular automaton model, determining whether the seed cellular is alive according to the first influence element, and when the seed cellular is determined to be alive, controlling the tissue cellular to develop within the development time according to the second influence element and the third influence element, and meanwhile, adjusting the second influence element according to the first influence element;
and determining a development red line in the spatial model, selecting a tissue development mode, and stopping development and sending out an early warning signal when the development of the tissue cellular reaches the development red line or the starting time of the tissue development mode reaches the development time.
2. The intelligent monitoring method for the sponge city according to claim 1, wherein the step of obtaining the three-dimensional data of the target sponge city, establishing a spatial model corresponding to the target sponge city according to the three-dimensional data, and constructing the cellular automaton model based on the spatial model specifically comprises:
acquiring three-dimensional data of a target sponge city, wherein the three-dimensional data comprises urban airspace data, urban land area data and land topography data;
determining a development red line of a target sponge city according to the urban airspace data and the urban land data, and selecting a plurality of reference points on the development red line;
based on a plurality of reference points, performing space-time alignment on the urban airspace data and the urban land data so as to construct a space model corresponding to the target sponge city;
and adjusting the space model according to the land topography data to optimize the space model.
3. The intelligent monitoring method for sponge city as claimed in claim 2, wherein said step of dividing the target sponge city into a plurality of tissue blocks in said spatial model according to said future weather data and topography of the target sponge city specifically comprises:
acquiring future weather data of a target sponge city, and judging rainfall of the target sponge city in each region in a space model according to the future weather data;
acquiring land topography data of a target sponge city, and judging a rainwater confluence point formed by rainfall of each region under the influence of different topography according to the land topography data;
in the space model, the target sponge city is divided into a plurality of corresponding tissue plates according to the area range of each rainwater confluence point.
4. The intelligent monitoring method for sponge city as claimed in claim 1, wherein the step of obtaining planning data of target sponge city, determining water absorption area of the target sponge city in each tissue plate according to the planning data, using each water absorption area as seed cell of cellular automata model, and using the area of each tissue plate except the water absorption area as tissue cell of cellular automata model specifically comprises:
acquiring planning data of a target sponge city, wherein the planning data comprises urban sewer data, rainwater collection facility construction data and natural water area data;
respectively determining the holding capacity of the urban sewer and the rainwater collection facility in each organization plate according to the urban sewer data and the rainwater collection facility construction data, and taking the water absorption areas corresponding to the urban sewer and the rainwater collection facility with the holding capacity reaching a capacity threshold value as seed cells of a cell automata model; meanwhile, according to the data of the natural water area, the water absorption area corresponding to the natural water area in each tissue plate is used as a seed cell of a cell automaton model;
and respectively determining the position of each seed cell in the space model, and taking the positions except the seed cells in the space model as organization cells of the cellular automaton model.
5. The intelligent monitoring method for sponge city as claimed in claim 2, wherein the step of determining whether the seed cell survives according to the first influencing element comprises:
determining city construction types and construction duration according to the city construction activities, and determining organization plates correspondingly influenced by the city construction activities according to the city construction types;
setting a positive growth value or a negative growth value for all seed cells in the affected tissue plates according to the city construction type and the construction duration;
setting an initial development probability for each seed cell in the space model, and adjusting the initial development probability corresponding to each seed cell according to a positive growth value or a negative growth value set for each seed cell in an affected tissue plate;
and when the adjusted development probability reaches a preset probability threshold, determining that the seed cells are alive.
6. The method for intelligently monitoring the sponge city as claimed in claim 5, wherein the step of controlling the development of the histiocyte in the development time according to the second and third influencing elements specifically comprises:
extracting the rainfall of each tissue plate in unit time from the rainfall data according to the third influence elements, and calculating the rainfall of each tissue cell in the same tissue plate in unit time according to the land topography data corresponding to each tissue plate to generate a rainfall distribution sequence;
extracting the total water absorption of each tissue plate in the second influencing elements in unit time, and determining the development area of the tissue cells in unit time according to the total water absorption and the rainfall distribution sequence; to control the development of tissue cells during said development time.
7. The method of claim 6, wherein the step of adjusting the second influencing element according to the first influencing element comprises:
when the city construction type and the construction duration in the first influence element set all the seed cells in the influenced tissue plates to be positive growth values, the total water absorption capacity of each tissue plate in the second influence element in unit time is multiplied;
and when the city construction type and the construction time length in the first influence element set all the seed cells in the influenced tissue plates as negative growth values, reducing the total water absorption of each tissue plate in the second influence element by a multiple in unit time.
8. The utility model provides a sponge city wisdom monitoring system which characterized in that includes: the system comprises a three-dimensional data module, a tissue plate module, a water absorption area module, an influence element module, a development control module and an early warning signal module, wherein each module is as follows:
the three-dimensional data module is used for acquiring three-dimensional data of a target sponge city, establishing a space model corresponding to the target sponge city according to the three-dimensional data, and establishing a cellular automata model based on the space model;
the tissue plate module is used for determining the development time of the cellular automaton model, acquiring future weather data corresponding to the development time of the target sponge city, and dividing the target sponge city into a plurality of tissue plates in the space model according to the future weather data and the topography of the target sponge city;
the water absorption area module is used for acquiring planning data of a target sponge city, determining a water absorption area of the target sponge city in each tissue plate according to the planning data, taking each water absorption area as a seed cell of a cellular automaton model, and taking an area except the water absorption area in each tissue plate as a tissue cell of the cellular automaton model;
the influence element module is used for acquiring city construction activities of the target sponge city in each tissue plate within the development time, and taking the city construction activities as first influence elements; calculating the total water absorption capacity of each tissue plate in unit time according to the water absorption capacity of each water absorption area in unit time, and taking the total water absorption capacity as a second influence element; determining rainfall data of each tissue plate in the development time according to the future weather data, and taking the rainfall data as a third influence element;
the control development module is used for inputting the first influence element, the second influence element and the third influence element into a cellular automaton model, determining whether the seed cellular is alive or not according to the first influence element, controlling the tissue cellular to develop within the development time according to the second influence element and the third influence element when the seed cellular is determined to be alive, and meanwhile, adjusting the second influence element according to the first influence element;
the early warning signal module is used for determining a development red line in the space model, selecting a tissue development mode, and stopping development and sending out an early warning signal when the development of tissue cells reaches the development red line or the starting time of the tissue development mode reaches the development time.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored computer program; wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the sponge city intelligent monitoring method of any one of claims 1-7.
10. A terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the sponge city intelligent monitoring method of any one of claims 1-7 when executing the computer program.
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