CN113592318A - Method and system for establishing urban green space optimal layout model - Google Patents

Method and system for establishing urban green space optimal layout model Download PDF

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CN113592318A
CN113592318A CN202110890565.1A CN202110890565A CN113592318A CN 113592318 A CN113592318 A CN 113592318A CN 202110890565 A CN202110890565 A CN 202110890565A CN 113592318 A CN113592318 A CN 113592318A
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周海珠
王清勤
狄彦强
李晓萍
王海
陈晨
魏兴
徐迎春
袁扬
赵力
吕慧芬
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Abstract

The invention provides a method and a system for establishing an optimal layout model of an urban green space, wherein the establishing method comprises the following steps: gridding a research area according to a geographical plan to obtain a gridding area plan, wherein the research area is an area where a green land needs to be arranged; establishing a green space cooling model and an urban canopy model according to the gridding area plan, and solving to obtain the urban heat island strength UHI; establishing an optimized model by taking the minimum urban heat island strength UHI as a target; solving the optimal solution of the optimization model by adopting a genetic algorithm; the urban heat island effect is increasingly serious along with the continuous high-speed development of cities by establishing an urban green land optimal layout model according to an optimal solution.

Description

Method and system for establishing urban green space optimal layout model
Technical Field
The invention relates to the field of urban green land, in particular to an urban green land optimal layout model establishing method and system.
Background
Because urban building groups are dense, a large amount of generated heat is not easy to dissipate, and asphalt ways and cement pavements are not covered by vegetation, and a large amount of solar illumination is easy to absorb, so that the urban area is heated up quickly and radiates a large amount of heat to the periphery and the atmosphere, the temperature of the urban area is generally higher than the temperature of the suburbs around at the same time, the high-temperature urban area is surrounded by the suburbs at low temperature, like islands in the waning sea, and the phenomenon is called as urban heat island effect by people. The urban heat island effect has negative influence on the life and ecological environment of people.
The urban green land has an obvious relieving effect on the urban heat island effect, the local air temperature above the green land is lower than the air temperature of the surface of the surrounding non-green land, a green land area with a certain area is equivalent to a local cold source, the temperature of the green land surrounding area is reduced under the influence, the temperature influence of the green land on the surrounding environment has strong correlation with the factors such as the scale and the type of the green land, and how to effectively relieve the urban heat island effect by arranging the urban green land.
Disclosure of Invention
In view of the above, the present invention is proposed to provide an urban green space optimization layout model building method and system that overcomes or at least partially solves the above problems.
According to one aspect of the invention, an optimal layout model building method for an urban green space is provided, and the building method comprises the following steps:
gridding a research area according to a geographical plan to obtain a gridding area plan, wherein the research area is an area where a green land needs to be arranged;
establishing a green space cooling model and an urban canopy model according to the gridding area plan, and solving to obtain the urban heat island strength UHI;
establishing an optimized model by taking the minimum urban heat island strength UHI as a target;
solving the optimal solution of the optimization model by adopting a genetic algorithm;
and establishing an optimal layout model of the urban green land according to the optimal solution.
Optionally, the gridding the research area according to the geographical plan to obtain the gridding area plan specifically includes:
obtaining a geographical plan of a study area;
marking out the locations of greens and streets on the geographic plan;
dividing the research area into a plurality of regular grids, and supplementing the regular grids at an irregular boundary to a supplemented research area in a square shape when the research area is in an irregular shape;
and numbering the grids according to a rule, taking the east-west direction as a column and taking the north-south direction as a row to obtain a plurality of numbered grids.
Optionally, the establishing a greenbelt cooling model and an urban canopy model according to the gridding area plan, and solving to obtain the urban heat island strength UHI specifically includes:
establishing a green space cooling model and an urban canopy model according to the gridding area plan;
calculating the heat island strength I under the current green space arrangement scheme of the research area according to the green space cooling model and the urban canopy modelUHI；
Solving according to the greenbelt cooling model and the urban canopy model of the research area to obtain the intensity delta T of the urban heat island at each time intervalUHT，t；
Based on the composite index component of the collected heat island intensity values UHI from 5 am to 7 pm,
the average UHI index for the daytime period is the heat island intensity
Figure BDA0003195720680000021
Optionally, the establishing an optimized model with the minimum urban heat island strength UHI as a target specifically includes:
the objective function is to minimize the intensity index of the urban heat island in the research area under the condition of arranging limited green space area, and the objective function min { I }UHI}；
The decision variable δi，jIf the grid (i, j) needs to be laid with greenbelts, the value is 0 or 1,0 represents that greenbelts are not laid, 1 represents that greenbelts are laid, and i, j is 1, 2.. N; if there is already a naturally occurring greenfield within the grid (i, j), no decision variables are required;
the limiting condition is that
Figure BDA0003195720680000031
∑Ai，jδi，j≤Stot (3)；
Figure BDA0003195720680000032
μ-3σ≤φ≤μ+3σ (5)；
The limiting condition is the total amount S of the limited green land area of the planning arrangement of the research areatot，Ai，jIs the area of the grid (i, j); phi is the green land cooling index of the green land grid, and the green land cooling index phi conforms to normal distribution and is within +/-3 sigma regions.
1. Optionally, the calculating the optimal solution of the optimization model by using a genetic algorithm specifically includes:
for the decision variable deltai，jCarrying out encoding;
determining the population number N of an initial scheme according to the research area;
obtaining a plurality of chromosomes according to whether the grids are arranged in the green space and one chromosome corresponding to each grid;
obtaining the planting density and the green land cooling index in the growth state of local plants in each grid for selectively arranging the green land, and obtaining the green land cooling index corresponding to each chromosome;
carrying out fitness calculation on the chromosome according to the green space temperature reduction index;
after the fitness calculation is carried out on the chromosomes, the fitness is ranked from large to small, the heat island strength corresponding to the maximum fitness is the minimum, and the corresponding green space arrangement scheme has the best effect;
fitness is used to calculate the probability that an individual is used in a population;
Fit＝-{IUHI+γp·max[0，(∑Ai，jδi，j-Stot)]} (6)；
wherein, γpIs a penalty factor; gamma raypWhen a larger value is taken, the scheme exceeding the total area is effectively removed;
selecting, exchanging and mutating genetic genes of a plurality of chromosomes to obtain N first generation optimized chromosomes;
judging whether grid greenbelt settings corresponding to the N first generation optimized chromosomes reach an optimal value, if so, obtaining an optimal greenbelt arrangement grid scheme; otherwise, the iteration is continued until 200 iterations.
In another aspect of the present invention, there is also provided a system for building an optimized layout model of an urban green space, the system comprising:
the gridding processing module is used for gridding a research area according to the geographical plan to obtain a gridding area plan, wherein the research area is an area where a green land needs to be arranged;
the urban heat island strength solving module is used for establishing a green space cooling model and an urban canopy model according to the gridding area plan and solving to obtain the urban heat island strength UHI;
an optimization model building module, configured to build an optimization model with the goal of minimizing the urban heat island strength UHI;
the genetic algorithm module is used for solving the optimal solution of the optimization model by adopting a genetic algorithm;
and the optimized layout module is used for establishing an optimized layout model of the urban green land according to the optimal solution.
The method and the system for establishing the urban green land optimized layout model have increasingly serious urban heat island effect along with the continuous high-speed development of cities. The urban heat island is relieved, and the method is beneficial to inhibiting the spread of infectious diseases, reducing the emission of greenhouse gases and reducing the energy consumption of buildings. The planning layout of the urban artificial green land can effectively relieve the urban heat island effect.
The urban green land optimization layout model for relieving the urban heat island strength can combine a green land cooling model and an urban canopy model which are influenced by factors such as green land area, plant transpiration, solar radiation strength and the like under the condition of urban green land total quantity constraint, global optimization is carried out through a genetic algorithm, optimization efficiency is greatly improved, and an optimal layout scheme is rapidly provided for urban green land planning of tropical island cities. When planning urban green land, the urban green land can play the function of relieving urban heat island effect to the maximum, and has profound influence on energy conservation and environmental protection.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic diagram of a regional gridding process of an urban green space optimization layout model building method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a method for solving the urban heat island strength according to the present invention;
FIG. 3 is a typical solar heat island intensity curve for a city in summer according to an embodiment of the present invention;
fig. 4 is a flowchart of a genetic algorithm provided by an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The terms "comprises" and "comprising," and any variations thereof, in the present description and claims and drawings are intended to cover a non-exclusive inclusion, such as a list of steps or elements.
The technical solution of the present invention is further described in detail with reference to the accompanying drawings and embodiments.
A method for building an optimized layout model of an urban green land comprises the following steps:
as shown in fig. 1, performing gridding processing on a research area according to a geographical plan to obtain a gridded area plan, wherein the research area is an area where a green land needs to be arranged;
gridding the research area according to the geographical plan, and specifically obtaining the gridding area plan comprises the following steps: obtaining a geographical plan of a study area; marking the position of greens and streets on the geographical plan; dividing the research area into a plurality of regular grids, and supplementing the regular grids at the irregular boundary to the supplemented research area into a square shape when the research area is in an irregular shape; and numbering the grids according to a rule, taking the east-west direction as a column and taking the north-south direction as a row to obtain a plurality of numbered grids.
The area where greens are to be placed is simplified according to a geographical plan, as shown in fig. 1. Only the greens (including the body of water) and streets are marked on the plan, dividing the area of investigation into small "grids". When the region of interest is irregularly shaped, some of the lattices are supplemented at the irregular boundaries so that the region of interest is square.
The grids are numbered according to a rule, for example, the grid is arranged in the east-west direction as a column, and the grid is arranged in the north-south direction as a row. The more east, the larger the column number; the further south the row number is, the larger the number of rows, resulting in a number of bins (1, 1), (1, 2) … (i, j).
By modeling the research area and solving the green space cooling model and the urban canopy model, the urban heat island strength UHI can be obtained, as shown in fig. 2. However, this UHI value is a value for a certain time period, i.e., Δ TUHI，tIf hour accuracy is used, then UHI is a curve that progresses with hours, as shown in FIG. 3. To optimize UHI, a comprehensive UHl index is required to summarize the heat island strength under the current green space arrangement scheme, where the index is IUHIThe optimization aim is to minimize the intensity index of the urban heat island in the research area under the condition of arranging limited green land area, namely obtaining the urban heat island
min{IUHI}. During research, the main time periods when the greenbelt has influence are mainly researched, and the daytime time periods are mainly considered, because the transpiration effect of the plants is obviously enhanced under the condition of sunlight irradiation in the daytime, and the sunlight shielding effect of crowns of tall plants is also the daytime time periods. Here, the heat island intensity value I, which is the heat island intensity value in the period from 5 am to 7 pm, is used as the comprehensive index component of UHIUHIAnd the quality judgment index is used as a quality judgment index of the optimization objective function.
Establishing a green space cooling model and an urban canopy model according to the gridding area plan, and solving to obtain the urban heat island strength UHI; and establishing a green space cooling model and an urban canopy model according to the gridding area plan.
Calculating the heat island strength I under the current green space arrangement scheme of the research area according to the green space cooling model and the urban canopy modelUHI。
Solving according to the greenbelt cooling model and the urban canopy model of the research area to obtain the intensity delta T of the urban heat island at each time intervalUHT，t。
Based on the composite index component of the collected heat island intensity values UHI from 5 am to 7 pm,
the average UHI index for the daytime period is the heat island intensity
Figure BDA0003195720680000071
The establishment of the optimization model requires explicit objective functions, decision variables and constraints.
Establishing an optimized model by taking the minimum urban heat island strength UHI as a target; the objective function is min { I } of the minimum urban heat island intensity index in the research area under the condition of limited green space areaUHI}；
Decision variable deltai，jIf the grid (i, j) needs to be laid with greenbelts, the value is 0 or 1,0 represents that greenbelts are not laid, 1 represents that greenbelts are laid, and i, j is 1, 2.. N; if there is already a naturally occurring greenfield within grid (i, j), no decision variables are needed; if there are already naturally occurring greenbelts in the trellis, no decision variables are needed
With the proviso that
Figure BDA0003195720680000072
∑Ai，jδi，j≤Stot (3)；
Figure BDA0003195720680000073
μ-3σ≤φ≤μ+3σ (5)；
The limiting condition is the limited total green space area S of the planning arrangement of the research areatot，Ai，jIs the area of the grid (i, j); phi is the green land cooling index of the green land grid, and the green land cooling index phi conforms to normal distribution and is within a +/-3 sigma region.
The flow chart of the genetic algorithm for solving the optimal solution is shown in fig. 4, and the genetic algorithm is adopted for solving the optimal solution of the optimization model; for the decision variable deltai，jCarrying out encoding; and encoding the decision variables. For example, as shown in fig. 1, 25 grids for laying green are provided, and the 25 grids are already indicated by light green colors in fig. 1, such as (2, 6), (4, 6), and (7, 11). According to the front and rear columns and the sequence from small to large, whether the 25 grids are laid with green lands or not can be arranged into a 2-system number, the 1 st bit of the 2-system number indicates whether the grids (2 and 6) adopt the green land arrangement or not, if the number is 1, the green land arrangement is indicated, and if the number is 0, the green land arrangement is not indicated. If 10 grids are selected from the 25 grids to be laid on green land, the number of 1 in the 2-ary number is 10.
Determining the population number N of an initial scheme according to a research area; by selecting different 0 or 1 for the grid, multiple chromosomes can be obtained. The total number of populations cannot be selected to be too large or too small, according to the usual settings of the GA algorithm. Too large a calculation load is too heavy, and too small a calculation load is not enough to quickly find an optimal solution. As a rule of thumb, an initial population number N of 60 is generally chosen.
Obtaining a plurality of chromosomes according to whether the grids are laid out in the green land or not; for each grid selected to lay the greenbelt, the greenbelt cooling index is given at the same time. According to research, the greenfield temperature reduction index of the greenfield conforms to normal distribution, so the operation process can be realized by using a generator of a normal distribution function. Its internal function can be directly adopted in Matlab environment: r ═ norm (mu, sigma), wherein the mu parameter represents the mean value, the sigma parameter represents the standard deviation, and the value of mu is obtained by taking a plurality of local greenbelts as samples through field examination of the research area, so as to obtain the greenbelt cooling under the normal planting density and growth state of the local plantsAnd obtaining an index. With no plant coverage as the position of μ -3 σ ═ 0, then
Figure BDA0003195720680000081
Acquiring the planting density and the green field temperature reduction index in the growth state of local plants in each grid with the green field selected to be arranged; calculating the fitness of the chromosome according to the green space cooling index;
fitness mainly considers an objective function and a constraint condition, and is used for calculating the probability of an individual being used in a group, and the function is shown as follows:
Fit＝-{IUHI+γp·max[0，(∑Ai，jδi，j-Stot)]} (6)
wherein, γpIs a penalty factor; gamma raypWhen a larger value is taken, the scheme exceeding the total area can be effectively eliminated. After the fitness of the chromosomes is calculated, the fitness of the chromosomes is ranked from large to small, and obviously, the maximum fitness means that the intensity of the heat island is minimum, namely, the scheme with the best effect of the green space arrangement scheme. In this step, the greenbelt cooling model and the urban canopy model of the research area need to be solved at the same time to obtain IUHIThis step requires a large amount of computational resources, preferably in parallel.
Selecting, exchanging and mutating genetic genes of a plurality of chromosomes to obtain N first generation optimized chromosomes; the traditional genetic algorithm has 3 basic operation modes: selecting; exchanging; and (5) carrying out mutation. Selecting: the top 5 highest ranked chromosomes are directly inherited as superior genes directly to the next generation. Exchanging: selecting 45 chromosomes to carry out gene exchange operation in a roulette mode; the interchange mode is to carry out pairing exchange on the genes with single or double positions. Mutation: carrying out mutation operation on all chromosomes with the probability of 1%; the mutation is made by changing the gene of a certain bit from 0 to 1 or from 1 to 0.
So doing, a new next generation population of 60 chromosomes will be generated.
Judging whether grid greenbelt settings corresponding to the N first generation optimized chromosomes reach an optimal value, and if so, obtaining an optimal greenbelt arrangement grid scheme; otherwise, the iteration is continued until 200 iterations. Judging the current optimization scheme: whether an optimum or maximum number of iterations has been found. Where setting reaches the optimal value scheme IUHILess than or equal to 0.1, and the maximum iteration times are 200. After the maximum number of iterations, there may be IUHISmaller schemes, but IUHIThe scheme is less than or equal to 0.1, and the optimization aim is considered to be fully met.
And establishing an optimal layout model of the urban green land according to the optimal solution.
In another aspect of the present invention, there is also provided a system for building an optimized layout model of an urban green space, the system comprising:
and the gridding processing module is used for gridding the research area according to the geographical plan to obtain a gridding area plan, wherein the research area is an area where a green land needs to be arranged.
And the urban heat island strength solving module is used for establishing a green space cooling model and an urban canopy model according to the gridding area plan and solving to obtain the urban heat island strength UHI.
And the optimization model building module is used for building an optimization model by taking the minimum urban heat island strength UHI as a target.
And the genetic algorithm module is used for solving the optimal solution of the optimization model by adopting a genetic algorithm.
And the optimized layout module is used for establishing an optimized layout model of the urban green land according to the optimal solution.
Has the advantages that:
the above embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, it should be understood that the above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (6)

1. A method for establishing an optimized layout model of an urban green land is characterized by comprising the following steps:
gridding a research area according to a geographical plan to obtain a gridding area plan, wherein the research area is an area where a green land needs to be arranged;
establishing a green space cooling model and an urban canopy model according to the gridding area plan, and solving to obtain the urban heat island strength UHI;
establishing an optimized model by taking the minimum urban heat island strength UHI as a target;
solving the optimal solution of the optimization model by adopting a genetic algorithm;
and establishing an optimal layout model of the urban green land according to the optimal solution.
2. The method for building an optimized layout model of an urban green space according to claim 1, wherein the gridding the research area according to the geographical plan, and the obtaining of the gridded area plan specifically comprises:
obtaining a geographical plan of a study area;
marking out the locations of greens and streets on the geographic plan;
dividing the research area into a plurality of regular grids, and supplementing the regular grids at an irregular boundary to a supplemented research area in a square shape when the research area is in an irregular shape;
and numbering the grids according to a rule, taking the east-west direction as a column and taking the north-south direction as a row to obtain a plurality of numbered grids.
3. The method for building an optimized layout model of an urban green space according to claim 1, wherein the building a green space cooling model and a city canopy model according to the gridding area plan and solving to obtain the urban heat island strength UHI specifically comprises:
establishing a green space cooling model and an urban canopy model according to the gridding area plan;
calculating the heat island strength I under the current green space arrangement scheme of the research area according to the green space cooling model and the urban canopy modelUHI；
Solving according to the greenbelt cooling model and the urban canopy model of the research area to obtain the intensity delta T of the urban heat island at each time intervalUHT，t；
Based on the composite index component of the collected heat island intensity values UHI from 5 am to 7 pm,
the average UHI index for the daytime period is the heat island intensity
Figure FDA0003195720670000021
4. The method for building an optimized layout model of urban green space according to claim 1, wherein the building of the optimized model with the goal of minimizing the urban heat island intensity UHI specifically comprises:
the objective function is to minimize the intensity index of the urban heat island in the research area under the condition of arranging limited green space area, and the objective function min { I }UHI}；
The decision variable δi，jIf the grid (i, j) needs to be laid with greenbelts, the value is 0 or 1,0 represents that greenbelts are not laid, 1 represents that greenbelts are laid, and i, j is 1, 2.. N; if there is already a naturally occurring greenfield within the grid (i, j), no decision variables are required;
the limiting condition is that
Figure FDA0003195720670000022
∑Ai，jδi，j≤Stot (3)；
Figure FDA0003195720670000023
μ-3σ≤φ≤μ+3σ (5)；
The limiting condition is the total amount S of the limited green land area of the planning arrangement of the research areatot，Ai，jIs the area of the grid (i, j); phi is the green land cooling index of the green land grid, and the green land cooling index phi conforms to normal distribution and is within +/-3 sigma regions.
5. The method for building an optimized layout model of urban green space as claimed in claim 1, wherein said using genetic algorithm to find the optimal solution of said optimized model specifically comprises:
for the decision variable deltai，jCarrying out encoding;
determining the population number N of an initial scheme according to the research area;
obtaining a plurality of chromosomes according to whether the grids are arranged in the green space and one chromosome corresponding to each grid;
obtaining the planting density and the green land cooling index in the growth state of local plants in each grid for selectively arranging the green land, and obtaining the green land cooling index corresponding to each chromosome;
carrying out fitness calculation on the chromosome according to the green space temperature reduction index;
after the fitness calculation is carried out on the chromosomes, the fitness is ranked from large to small, the heat island strength corresponding to the maximum fitness is the minimum, and the corresponding green space arrangement scheme has the best effect;
fitness is used to calculate the probability that an individual is used in a population;
Fit＝-{IUHI+γp·max[0，(∑Ai，jδi，j-Stot)]} (6)；
wherein, γpIs a penalty factor; gamma raypWhen a larger value is taken, the scheme exceeding the total area is effectively removed;
selecting, exchanging and mutating genetic genes of a plurality of chromosomes to obtain N first generation optimized chromosomes;
judging whether grid greenbelt settings corresponding to the N first generation optimized chromosomes reach an optimal value, if so, obtaining an optimal greenbelt arrangement grid scheme; otherwise, the iteration is continued until 200 iterations.
6. An urban green space optimized layout model building system, characterized in that the building system comprises:
the gridding processing module is used for gridding a research area according to the geographical plan to obtain a gridding area plan, wherein the research area is an area where a green land needs to be arranged;
the urban heat island strength solving module is used for establishing a green space cooling model and an urban canopy model according to the gridding area plan and solving to obtain the urban heat island strength UHI;
an optimization model building module, configured to build an optimization model with the goal of minimizing the urban heat island strength UHI;
the genetic algorithm module is used for solving the optimal solution of the optimization model by adopting a genetic algorithm;
and the optimized layout module is used for establishing an optimized layout model of the urban green land according to the optimal solution.
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