CN108984995A - A kind of ecology garden landscape design method of evaluation simulation - Google Patents
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Abstract
The present invention provides a kind of ecology garden landscape design methods based on evaluation simulation, which comprises the steps of: obtains climatic data, hydrographic data and the terrain data in target plot.The physical model in target plot is established according to climatic data, hydrographic data and terrain data.Physical model is subjected to grid dividing and is separated into calculating grid model.Building Markov model is iterated calculating to grid model is calculated, to obtain the physical descriptor in each target plot.It is multiple Land units by target Parcel division, to obtain the unit physical descriptor of each Land unit.Unit physical descriptor is matched with environmental variance needed for the growth of landscape plant, to obtain the matching degree of unit physical descriptor and environmental variance, further according to the height of matching degree to obtain the plot scoring of each Land unit, further select to be suitable for plant that each Land unit is planted from plant library according to the height that plot is scored.
Description
Technical field
The present invention relates to evaluation analog analysing methods, and in particular to a kind of ecology garden landscape of evaluation simulation
Design method belongs to landscape planning design field.
Background technique
It is phytobiocoenose about the relationship between the dynamic process and the external environment factor and phytobiocoenose of phytobiocoenose
Major issue in ecological development process causes the extensive concern of ecologists.Plant is more sparse for landscaped area, more
In spot block distribution, and change in time and space amplitude is larger, and landscape ecology system is particularly significant, in addition the interference of mankind's activity, plant
Feature is significant for stablizing for landscaped area ecological environment, can play the role of conserving water and soil.
It influences ornamental plant Distribution Pattern and dynamic factor includes biology and abiotic, interaction pass therebetween
It is sufficiently complex.It is relatively more about the research herded to Vegetation Effect, and about the climatic factor pair under long period sequence
The research of waterfront Vegetation Effect is less.Natural process, mankind's activity are affecting always the development and change of garden landscape pattern.It is special
Be not constantly increase in population, social-economic structures are in today of continuous adjustment variation, people's Land use systems different to landscape,
Different understanding is all changing landscape pattern.
Common Landscape Design selects landscape plant, planted plant and plot according to design experiences by designer's
Matching degree it is not high, gardens lack it is ecological.The present invention is corresponding using detrended correspondence analysis and model by Markov model
The dynamic change for analyzing two kinds of sort method simulation and forecast landscaped area landscape patterns, to Garden Plant Community feature and weather because
The correlation of son is analyzed, and the landscape plant of suitable plot plantation is selected, it is intended to provide theory for ecology Landscape Design
Foundation.
Summary of the invention
To solve the above problems, present invention employs following technical solutions:
The present invention provides a kind of ecology garden landscape design methods based on evaluation simulation, are suitable for mesh for selecting
The landscape plant of mark plot plantation simultaneously designs ecology garden landscape, which comprises the steps of:
Step S1 obtains the climatic data in target plot；
Step S2 obtains the hydrographic data in target plot；
Step S3, obtains the terrain data in target plot, which contains at least two level of detail；
Step S4, terrain data and hydrographic data are imported into modeling software to establish the physical model in target plot and
According to the initial physical condition and boundary of climatic data and hydrographic data setting physical model；
Physical model is carried out grid dividing and is separated into calculating grid model by step S5；
Step S6 will calculate grid model and import evaluation simulation software, by building Markov model to calculating net
Lattice model is iterated calculating, to obtain the physical descriptor in target plot；
Target Parcel division is multiple Land units, to be obtained often according to the physical descriptor in target plot by step S7
The unit physical descriptor of a Land unit；
Step S8 passes through the progress of environmental variance needed for growth of the computer to unit physical descriptor and landscape plant
Match, to obtain the matching degree of unit physical descriptor and environmental variance, the height further according to matching degree is to obtain each plot
The plot of unit is scored, and further select to be suitable for plant that each Land unit is planted from plant library according to the height that plot is scored
Object, to complete the design of ecology garden landscape.
The present invention provides a kind of ecology garden landscape design methods based on evaluation simulation, can also have in this way
Feature, wherein unit physical descriptor includes multiple individual event unit physical descriptors, and each individual event unit physical descriptor and environment become
Corresponding item environment variable is matched in amount, so that the individual event unit physical descriptor scoring of each Land unit is obtained,
It is added each individual event unit physical descriptor scoring of Land unit to obtain plot scoring.
The present invention provides a kind of ecology garden landscape design methods based on evaluation simulation, can also have in this way
Feature, wherein individual event unit physical descriptor be each Land unit temperature, wind speed, humidity and air pressure.
The present invention provides a kind of ecology garden landscape design methods based on evaluation simulation, can also have in this way
Feature, wherein climatic data include by the firsthand information of the weather system in meteorologic instrument target plot obtained and
The data reorganized according to firsthand information.
The present invention provides a kind of ecology garden landscape design methods based on evaluation simulation, can also have in this way
Feature, wherein terrain data is the remote sensing image in the target plot obtained by satellite remote sensing technology.
The present invention provides a kind of ecology garden landscape design methods based on evaluation simulation, can also have in this way
Feature, wherein hydrographic data include multiple individual event hydrographic datas in target plot obtained by observation and copmputing laboratory with
And it according to the maximum value of the obtained individual event hydrographic data of individual event hydrographic data, minimum value, average value, total amount, graph and waits
It is worth line, individual event hydrographic data is precipitation, evaporation capacity, water level, flow and the silt content in target plot.Invention action and effect
The ecology garden landscape design method of evaluation simulation according to the present invention, due to obtaining the gas in target plot
Data, hydrographic data and terrain data are waited, therefore terrain data and hydrographic data can be imported modeling software to establish
The physical model in target plot and initial physical condition and the boundary that physical model is set according to climatic data and hydrographic data.
Since terrain data contains at least two level, various virtual scene demands needed for can satisfy evaluation simulation.
Since physical model is carried out grid dividing and is separated into calculating grid model, it can will calculate grid model and import calculating
Numerical simulation software, and calculating is iterated to grid model is calculated by building Markov model, to obtain target plot
Physical descriptor.Due to being multiple Land units by target Parcel division, can be obtained according to the physical descriptor in target plot
To the unit physical descriptor of each Land unit.Due to using computer to be iterated calculating, what is calculated is more efficient, knot
Fruit is more acurrate.The environmental variance as needed for the growth to unit physical descriptor and landscape plant carries out matching scoring, energy
Enough height score according to plot select to be suitable for plant that each Land unit is planted from plant library, to complete ecological garden
The design of landscape.Due to carrying out matching scoring by computer, matching is scored more efficient, as a result more acurrate.
Detailed description of the invention
Fig. 1 is the satellite remote sensing schematic diagram of the ecology garden landscape design method of evaluation simulation of the invention；
Fig. 2 is the physical model schematic diagram of the embodiment of the present invention；
Fig. 3 is the flow diagram of the ecology garden landscape design method of evaluation simulation of the invention；
Fig. 4 is the calculating grid model schematic diagram of the embodiment of the present invention；
Fig. 5 is the Parcel division schematic diagram of the embodiment of the present invention；
Fig. 6 is the wind speed profile schematic diagram in the target plot of the embodiment of the present invention；
Fig. 7 is that the plot scoring of the ecology garden landscape design method of evaluation simulation of the invention matches with plant and shows
It is intended to；
In figure, 10- island in river；The waters 20-；The land 30-.
Specific embodiment
In order to be easy to understand the technical means, the creative features, the aims and the efficiencies achieved by the present invention, tie below
Attached drawing is closed to be specifically addressed the ecology garden landscape design method of evaluation simulation of the invention.
As shown in Fig. 2, the target plot in the present embodiment includes island in river 10, waters 20 and land 30.
As shown in FIG. 1 to FIG. 7, ecology garden landscape design method in the present embodiment includes the following steps:
Step S1, the firsthand information of the weather system in the target plot obtained by meteorologic instrument simultaneously carry out firsthand information
Reorganization, to obtain the climatic data in target plot；
Step S2 obtains the individual event hydrographic data in target plot and according to individual event hydrology number by observing and calculating research
According to the maximum value, minimum value, average value, total amount, graph and the isopleth that acquire each individual event hydrographic data is calculated, to obtain
The hydrographic data in target plot.Individual event hydrographic data includes the precipitation in target plot, evaporation capacity, water level, flow and containing sand
Amount；
Step S3 obtains the satellite remote sensing figure in target plot by satellite remote sensing technology, to obtain tool, there are two details
The terrain data of level；
Terrain data and hydrographic data are imported modeling software, establish the physical model in target plot in proportion by step S4,
And according to the initial physical condition and boundary of climatic data and hydrographic data setting physical model；
Physical model is carried out grid dividing and is separated into calculating grid model by step S5；
Step S6 will calculate grid model and import evaluation simulation software, by building Markov model to calculating net
Lattice model is iterated calculating, to obtain the plot physical descriptor in target plot；
Target Parcel division is multiple Land units, to be obtained often according to the physical descriptor in target plot by step S7
The unit physical descriptor of a Land unit；
Step S8 uses ring needed for growth of the big data algorithm to unit physical descriptor and landscape plant by computer
Border variable is matched, to obtain the matching degree of unit physical descriptor and environmental variance, further according to matching degree height to
The plot scoring of each Land unit is obtained, further selects to be suitable for each plot from plant library according to the height that plot is scored
The plant of unit plantation, to complete the design of ecology garden landscape.
Wherein, the quality of the calculating grid model in step S5 can satisfy the required precision that more limit members calculate, and calculate net
The quality of lattice model is higher, and the precision of calculated result is higher.
Markov model in step S6 is the present status and trend using a certain variable, predicts the variable future state
With the prediction technique of trend.Markov model basic principle, it is in variable prediction that the disease incidence division of studied variable is several
Time is divided into several periods by observation interval, then calculates the transfer number between each state by state, determines that probability shifts square
Battle array, is made prediction by maximum transfer probability in matrix；Research variable draws matched influence degree by it in Analysis of Policy Making
It is divided into multiple and different matching status, in conjunction with the development of each state mutual transition probability analog variable within a certain period of time
Journey, according to it is stateful on matching result and resource consumption pass through operation repeatedly, to variable development final result and medical expense
It makes prediction；It is that the natural history of certain variable is divided into several states in variable screening measure evaluation, determines cycle period, point
Other analysis mode screening and not screening crowd, estimate the effect and expense of screening accordingly, and carry out incremental analysis.Markov model
Establishment step is state demarcation, probability calculating, transition probability matrix and prediction and examines.Markov model mathematic(al) structure λ
=(N, M, π, A and B), wherein N is model state number, and M is observation quantity in stateful observation sequence that may be present, π
For state probability, A is state-transition matrix, and B is observation sequence probability matrix.Markov model has been widely used for
Natural science, field of engineering technology.
Specific algorithm is as follows:
Given observation value sequence O, is determined by calculation a model λ, so that P (O | λ) it is maximum.
Algorithm steps:
Initial model 1. (to training pattern) λ 0,
2. based on λ 0 and observation value sequence O, training new model λ；
If 3. log P (X | λ)-log (P (X | λ 0) < Delta, illustrate that training having reached desired effect, algorithm terminates.
4. otherwise, enabling λ 0=λ, continue step 2 work, until condition meets.
Iterative calculation in step S6 refers to a kind of typical method in calculating, is applied to finding roots of complex functional equation, solving equations, square
Battle array seeks characteristic value etc..Its basic thought is Approach by inchmeal, first takes a coarse approximation, then public with the same recursion
Formula corrects this initial value repeatedly, until reaching predetermined accuracy and requiring.Using the environmental carrying capacity entropy weight based on risk entropy
Markov model constructs genetic projection pursuit model, and value-at-risk and time series are fitted, with diffusion of information opinion by each sample
Value-at-risk is divided into different brackets, using the calculation method assessment iterative calculation result of risk entropy.
Iterative calculation is to calculate completion automatically by evaluation simulation software, carries out the first iteration of more limits according to physical model,
Until the numerical convergence of iteration, to stationary value, specific finishing control is controlled by the residual error of each physical descriptor, when
Computer is automatically stopped calculating when each residual error is both less than preset threshold value.It can also be set by user in calculating process
Iterative steps terminate to iterate to calculate, iterative steps are mainly the change for relying on the calculating experience and observation physical descriptor of user
Change curve to determine.
Matching methods of marking in step S8 is as shown in table 1, can assign different environmental variances not in matching process
Same specific gravity, so that matched result is more in line with actual conditions, specifically:
1 plot grade form of table
A is weight coefficient when each unit physical descriptor calculates, and b is each unit physical descriptor and environmental physics variable
Matching degree, n is the quantity of unit physical descriptor.
In the present embodiment, unit physical descriptor is temperature, wind speed, humidity and the air pressure of Land unit, i.e. n=4.
Each Land unit is numbered, and to environmental variance needed for the growth of unit physical descriptor and landscape plant
Matching scoring is carried out, during matching scoring, the weight coefficient of each unit physical descriptor is different.
By taking the matching methods of marking in No. 1 plot and No. 1 plant as an example, the weight coefficient a of temperature1=0.7, the matching of temperature
Spend b1=0.8, the weight coefficient a of wind speed2=0.5, the matching degree b of wind speed2=0.9, the weight coefficient a of humidity3=0.9, humidity
Matching degree b3=0.7, the weight coefficient a of air pressure4=0.6, the matching degree b of air pressure4=0.8, then plot 1 is relative to plant 1
Plot scoring be are as follows:
Each Land unit is matched one by one with every kind of plant in plant library using big data algorithm by computer
Scoring, to obtain plot scoring of each Land unit relative to every kind of plant in plant library, the result to score according to plot
It chooses scoring highest one and is used as optimal solution, to select the plant of each Land unit plantation of optimum from plant library
Object.
In the present embodiment, plot scoring is subject to the different some physics of others and comments first standard, finally makes each plot
Physical environmental data.Satellite remote-sensing image figure classification results are analyzed using GIS software, are obtained not
With the landscape feature area data of period, counted based on each landscape feature area data of different times with Markov model
According to the area of following any one year various landscape types can be predicted, to learn the change that each landscape feature area occurs
Change, analyzes the development of landscape.
The key of Markov model is the determination of landscape transfer matrix and transition probability and the planning of ecoscape.Pass through
The physical environment in evaluation simulated ecological gardens obtains the physical environment characteristic distributions of this area, whole block is drawn
Point, and each sub- plot is appraised through comparison according to measurement standard into property and is given a mark, finally matched according to plant species library with the plot,
The landscape plant plantation for being most suitable for the plot is obtained, is finely adjusted on this basis, by Markov model simulation and forecast landscape lattice
The dynamic change of office provides a kind of ecology of evaluation simulation with this come landscape pattern's layout principle to green ecological gardens
Landscape Design method.
Embodiment action and effect
According to the ecology garden landscape design method that the evaluation of the present embodiment is simulated, due to obtaining target plot
Climatic data, hydrographic data and terrain data, therefore terrain data and hydrographic data can be imported modeling software to build
Found the physical model of each Land unit and according to climatic data and the initial physical condition of hydrographic data setting physical model
The boundary and.Since terrain data contains at least two level, various virtual fields needed for can satisfy evaluation simulation
Scape demand.Since physical model is carried out grid dividing and is separated into calculating grid model, grid model can will be calculated
Evaluation simulation software is imported, and calculating is iterated to grid model is calculated by building Markov model, to obtain
The physical descriptor in target plot.Due to being iterated calculating by computer, what is calculated is more efficient, as a result more acurrate.
Due to being multiple Land units by target Parcel division, it is single that each plot can be obtained according to the physical descriptor in target plot
The unit physical descriptor of member.As match commenting with environmental variance needed for the growth of landscape plant to unit physical descriptor
Point, therefore can select to be suitable for plant that each Land unit is planted from plant library according to the height that plot is scored, thus complete
At the design of ecology garden landscape, due to carrying out matching scoring using big data algorithm by computer, matching scoring
It is more efficient, it is as a result more acurrate.
Since unit physical descriptor includes multiple individual event unit physical descriptors, each individual event unit physical descriptor can
Item environment variable corresponding with environmental variance is matched, so that the individual event unit physics for obtaining each Land unit becomes
Amount scoring is added each individual event unit physical descriptor scoring of Land unit to obtain plot scoring.
Since physical model is the diminution model for meeting computational accuracy and requiring established in proportion, the essence of physical model
Degree can be corresponding with computational accuracy, to save the consumption for calculating power.
The preferred embodiment of the present invention has been described in detail above.It should be appreciated that the ordinary skill of this field is without wound
The property made labour, which according to the present invention can conceive, makes many modifications and variations.Therefore, all technician in the art
Pass through the available technology of logical analysis, reasoning, or a limited experiment on the basis of existing technology under this invention's idea
Scheme, all should be within the scope of protection determined by the claims.
For example, the individual event physical descriptor in the present embodiment includes temperature, wind speed, humidity and the air pressure of Land unit,
In ecology garden landscape design method provided by the invention based on evaluation simulation, individual event physical descriptor can also include day
According to duration, geological characteristics and radiation etc., for designing the ecology garden landscape in the different plot of various conditions.
Claims (6)
1. a kind of ecology garden landscape design method based on evaluation simulation, the scape for selecting appropriate target plot to plant
It sees plant and designs ecology garden landscape, which comprises the steps of:
Step S1 obtains the climatic data in the target plot；
Step S2 obtains the hydrographic data in the target plot；
Step S3, obtains the terrain data in the target plot, and the terrain data contains at least two level of detail；
The terrain data and the hydrographic data are imported modeling software to establish the physics in the target plot by step S4
Model and initial physical condition and the boundary that the physical model is set according to the climatic data and the hydrographic data；
The physical model is carried out grid dividing and is separated into calculating grid model by step S5；
The calculating grid model is imported evaluation simulation software by step S6, by building Markov model to the meter
It calculates grid model and is iterated calculating, to obtain the physical descriptor in the target plot；
The target Parcel division is multiple Land units by step S7, to be obtained according to the physical descriptor each described
The unit physical descriptor of Land unit；
Step S8 is carried out by environmental variance needed for growth of the computer to the unit physical descriptor and the landscape plant
Matching, to obtain the matching degree of the unit physical descriptor and the environmental variance, further according to the matching degree height from
And the plot scoring of each Land unit is obtained, further selected from the plant library according to the height that the plot is scored
Select be suitable for each Land unit plantation plant, to complete the design of the ecology garden landscape.
2. the ecology garden landscape design method according to claim 1 based on evaluation simulation, it is characterised in that:
Wherein, the unit physical descriptor include multiple individual event unit physical descriptors, each individual event unit physical descriptor with
Corresponding item environment variable is matched in the environmental variance, to obtain the individual event unit of each Land unit
Physical descriptor scoring is added the individual event unit physical descriptor scoring of each of the Land unit to obtain the plot
Scoring.
3. the ecology garden landscape design method according to claim 2 based on evaluation simulation, it is characterised in that:
Wherein, the individual event unit physical descriptor is temperature, wind speed, humidity and the air pressure of each Land unit.
4. the ecology garden landscape design method according to claim 1 based on evaluation simulation, it is characterised in that:
Wherein, the climatic data includes the firsthand information by the weather system in the meteorologic instrument target plot obtained
And the data reorganized according to the firsthand information.
5. the ecology garden landscape design method according to claim 1 based on evaluation simulation, it is characterised in that:
Wherein, the terrain data is the remote sensing image in the target plot obtained by satellite remote sensing technology.
6. the ecology garden landscape design method according to claim 1 based on evaluation simulation, it is characterised in that:
Wherein, the hydrographic data includes the individual event hydrology number in multiple target plot obtained by observation and copmputing laboratory
Accordingly and according to the maximum value of the obtained individual event hydrographic data of the individual event hydrographic data, minimum value, average value, total
Amount, graph and isopleth, the individual event hydrographic data be the precipitation in the target plot, evaporation capacity, water level, flow and
Silt content.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110245445A (en) * | 2019-06-21 | 2019-09-17 | 浙江城建规划设计院有限公司 | A kind of ecology garden landscape design method based on Computerized three-dimensional scenario simulation |
| CN110837911A (en) * | 2019-09-06 | 2020-02-25 | 沈阳农业大学 | Large-scale ground surface arthropod space distribution simulation method |
| CN111758503A (en) * | 2020-06-11 | 2020-10-13 | 北京天仁科技发展有限公司 | Lawn bed temperature adjusting device, control method, electronic device and storage medium |
| CN116702299A (en) * | 2023-08-02 | 2023-09-05 | 山东建筑大学 | Garden design method based on garden simulation |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050058971A1 (en) * | 2003-09-12 | 2005-03-17 | Nicholas Bugosh | Fluvial geomorphic landscape design computer software |
| CN102682202A (en) * | 2012-04-28 | 2012-09-19 | 清华大学 | Green space system community planning method for urban and rural ecological planning |
| CN103473613A (en) * | 2013-09-09 | 2013-12-25 | 武汉理工大学 | Landscape structure-surface temperature-electricity consumption coupling model and application thereof |
| CN106909899A (en) * | 2017-02-24 | 2017-06-30 | 中国农业大学 | A kind of analysis method and analysis system of wetland landscape evolution process |
-
2018
- 2018-09-28 CN CN201811136240.9A patent/CN108984995A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050058971A1 (en) * | 2003-09-12 | 2005-03-17 | Nicholas Bugosh | Fluvial geomorphic landscape design computer software |
| CN102682202A (en) * | 2012-04-28 | 2012-09-19 | 清华大学 | Green space system community planning method for urban and rural ecological planning |
| CN103473613A (en) * | 2013-09-09 | 2013-12-25 | 武汉理工大学 | Landscape structure-surface temperature-electricity consumption coupling model and application thereof |
| CN106909899A (en) * | 2017-02-24 | 2017-06-30 | 中国农业大学 | A kind of analysis method and analysis system of wetland landscape evolution process |
Non-Patent Citations (4)
| Title |
|---|
| 姚博: "风环境影响下的陕南山区小城镇空间布局方法研究 ——以丹凤县城龙驹寨镇为例", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
| 张玉娟: "长白山林区林场级尺度景观格局演化与模拟", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
| 杨勇: "关中地区土地利用动态模拟与优化配置研究", 《中国优秀博士学位论文全文数据库信息科技辑》 * |
| 郭立冬: "生态旅游村植物景观构建研究——以崇明县瀛东村为例", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110245445A (en) * | 2019-06-21 | 2019-09-17 | 浙江城建规划设计院有限公司 | A kind of ecology garden landscape design method based on Computerized three-dimensional scenario simulation |
| CN110837911A (en) * | 2019-09-06 | 2020-02-25 | 沈阳农业大学 | Large-scale ground surface arthropod space distribution simulation method |
| CN110837911B (en) * | 2019-09-06 | 2021-02-05 | 沈阳农业大学 | Large-scale ground surface arthropod space distribution simulation method |
| CN111758503A (en) * | 2020-06-11 | 2020-10-13 | 北京天仁科技发展有限公司 | Lawn bed temperature adjusting device, control method, electronic device and storage medium |
| CN111758503B (en) * | 2020-06-11 | 2022-03-01 | 北京天仁科技发展有限公司 | Lawn bed temperature adjusting device, control method, electronic device and storage medium |
| CN116702299A (en) * | 2023-08-02 | 2023-09-05 | 山东建筑大学 | Garden design method based on garden simulation |
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