CN107392356A - A kind of rectangle grid construction method for managing field - Google Patents
A kind of rectangle grid construction method for managing field Download PDFInfo
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- CN107392356A CN107392356A CN201710509683.7A CN201710509683A CN107392356A CN 107392356 A CN107392356 A CN 107392356A CN 201710509683 A CN201710509683 A CN 201710509683A CN 107392356 A CN107392356 A CN 107392356A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/043—Optimisation of two dimensional placement, e.g. cutting of clothes or wood
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Mining
Abstract
The invention discloses a kind of rectangle grid construction method for managing field, using the soil sampling point data obtained in big Tanaka as data, the rectangle grid subregion based on Semi-variance analysis and two-value linear programming is established.The present invention improves existing management partition method, determines optimal management Grid size, ensures the homogenieity of division result and improve the efficiency that regular grid structure calculates.The inventive method can carry out rectangular sub-area using different soils key element, be contrasted with existing crop field environmental management partition method, improved efficiency, application, universality and accuracy improve.
Description
Technical field
The present invention relates to a kind of management grid structure for the rectangle grid construction method, especially large area field for managing field
Build, it is specifically a kind of by carrying out utilizing secondary line after Semi-variance analysis obtains optimal Grid size to soil trace element
Property integer programming carry out rectangle grid subregion method.
The invention discloses a kind of rectangle grid construction method for managing field, belongs to field management in accurate agricultural and leads
Domain, the management subregion for crop field are built.
Background technology
At present, management partition analysis is that field is divided into the similar management subregion of multiple environmental key-elements according to soil attribute
Technology, it is the basis for realizing accurate farming.For field management subregion, selection can directly affect the soil ring of crop yield
Border key element ability meaningful, such as soil acidity or alkalinity, soil moisture content, soil nutrient.
Most of existing management partition analysis is analyzed for Non-surveillance clustering, what classification was often determined and generated by clustering algorithm
Division result is the subregion of not rectangle.The convenience of operability and the fertilising of under-developed area peasant household in view of agricultural machinery,
Division result is that rectangle grid is more particularly suitable.Partition management by carrying out rectangle grid to crop field can save fertilizer, save
Labour simultaneously reduces environmental pollution.However, there is also some problem for existing rectangular sub-area result.First, in most of situation
Under, fully do not carry out subregion calculating using data；Secondly, different size of Grid size can cause different division results,
Need to find most suitable Grid size.
The content of the invention
The purpose of the present invention is to be directed to the nonstandard problem of farmland partition management, proposes that a kind of novel rectangular grid subregion is retouched
Paint method.Semi-variance analysis has been used and the optimal size that manages subregion grid carried out during grid interpolation by this method
Judge, and quadratic linear integer programming method is improved.
Technical scheme steps are as follows used by the present invention solves above-mentioned technical problem：
S101 is sampled：Algorithm chooses N (h) sampled point in research field, and obtains soil environment information；Select a certain soil
Earth environmental key-element is the foundation key element of grid-based management field, is designated as Z；
S102 determines optimal Grid size：The Z variables semivariance variation figure of sampled point is drawn, a variety of semivariances are evaluated in fitting
Model, optimal semivariance model is determined, using the change journey a of optimal semivariance model into optimal Grid size；
S103 interpolation：Scope using the minimum enclosed rectangle of field as management field, the grid for being a*a with size are split
The range of management, using common kriging method to soil environment key element Z interpolation, that is, calculate the property value of all grid；
S104 rectangle grid example generates：All examples (rectangle management subregion) that may be present are generated according to interpolation result
And a homography C consistent with example number is established, store all example internal grids soil key elements with homography C
Z variance；
The optimal grid example selections of S105：Optimum partition example is determined with two-value integer program algorithm, and remembers viFor decision-making
Variable, target are that the variation of regional compartmentalization inner space is comprehensive minimum, by solving, obtain optimum partition example, that is, manage field
Rectangle grid structure result.
Specifically, in step S101：Factor data needed for actual management includes soil nitrogen concentrations data, the soil organism
Content, content of soil available phosphor, Soil Available potassium content etc..
Specifically, step S102 is specially：
S1021, the factor data obtained using sampling draw the semivariance variation function figure on γ (h), and its formula is：
Wherein, h is semivariance variation figure independent variable, and n (h) represents the number of pairs of sampled point during at intervals of h, and Z (x) is to adopt
The value of sampling point；
S1022, it is fitted using a variety of semivariance theoretical models to obtain the semivariance curve of each model, is tested by intersecting
The method of card assesses each model；Select mean value error close to 0 and model of the mean square deviation close to 1 as optimal models, and determine
The change journey a of optimal semivariance model carries out soil key element Z interpolation into optimal Grid size.
The selection mean value error close to 0 and model of the mean square deviation close to 1 as optimal models, following formula meter can be passed through
Calculate：Min [a Shu x-0 Shu+b (1-y)], ab is weight, and x, y are respectively mean value error and mean square deviation.
Preferably, a=b=1.
Specifically, in step S1022 a variety of semivariance theoretical models include linear model, spherical model, exponential model and
Gauss model.
Specifically, step S104 is specially：According to interpolation result, all rectangle grid examples are generated, establish Correlation Moment
Battle array C={ cij, wherein, if example i grid coverages j, cij=1, otherwise cij=0；And calculate each example i internal grids
Soil key element variable variance
Specifically, step S105 is specially：
S1051, optimum partition example determined with two-value integer program algorithm, and remember vi∈ { 0,1 } is decision variable, target
Made a variation for regional compartmentalization inner space comprehensive minimum, two-value integral linear programming byDetermine；
S1052, maximum mesh threshold value LX and minimum grid threshold value LN is set to ensure the efficiency and operable of agricultural machinery practice
Property, its constraint formulations is：
A relative variable is introduced simultaneously to improve to original method, so as to ensure the homogenieity of division result, its
Constraint formulations are
WhereinIt is all example population variances, α is the suitable index of variability for ensureing subregion homogenieity, and N is example quantity, α
Span [0.5,1), niRepresent the sampled point number in example i.
Beneficial effects of the present invention
The management subregion grid size of the inventive method design is can accurately to show the spatial distribution form of soil attribute
Full-size, optimize rectangular mesh management subregion in example generate.Compared with the method not improved, the inventive method computing
Speed is greatly speeded up, and is to be applied in Production of Large Fields more economically and efficiently method.
Brief description of the drawings
The method flow schematic diagram that it is the present invention that Fig. 1, which is,.
Fig. 2 is the interpolation result figure of the present invention.
Fig. 3 is each grid nitrogen content schematic diagram of the present invention.
Fig. 4 is the management grid structure result schematic diagram of the present invention.
Embodiment
With reference to embodiment, the invention will be further described, but protection scope of the present invention not limited to this：
As shown in Figure 1.
Collection measures multiple sampled point soil nitrogen concentrations data in crop field in the present embodiment, makes semivariance variation figure and profit
Go out the Grid size of most suitable semivariance model with four kinds of models fittings, it is determined that carrying out grid interpolation after most suitable grid scope.
Finally all examples are calculated using two-value integral linear programming, the rectangle grid for completing management field is described.
S101 is sampled：The present embodiment 2012 in the arable land of 41 pieces of Jiangsu Rugao (nearly 70,000 square metres) be randomly provided
As shown in Fig. 2 gathering total nitrogen content of soil data in the present embodiment, (Z variables=full nitrogen contains 136 sampled points (N (h)=136)
Measure, Z can be soil organic matter content, content of soil available phosphor, Soil Available potassium content etc. in other embodiments).
S102 calculates Grid size：Draw the semivariogram of total nitrogen content of soil.Utilize four kinds of semivariance theoretical model (lines
Property model, spherical model, exponential model and Gauss model) it is fitted to obtain the semivariance curve of each model.Tested using intersection
The mean value error that demonstration obtains Gauss model is -0.004, and mean square deviation is -0.012；The mean value error of spherical model is -0.003,
Variance is -0.007；The mean value error of doughnut model is -0.003, and mean square deviation is -0.009；The mean value error of exponential model for-
0.001, mean square deviation is -0.003.Therefore exponential model is optimality model in the present embodiment, and it becomes journey as 35.075m, this reality
The optimal Grid size for applying example is 35m (a=35m).
S103 interpolation：35m*35m grid is drawn in research area, the property value of all grid is calculated using Kriging regression
(in the present embodiment be total nitrogen content of soil numerical value), as a result as shown in Fig. 2 the different numberings of grid to represent different soil complete
Nitrogen content is horizontal, and Fig. 2 is the grid of 3 rows 18 row, and Fig. 3 represents the soil nitrogen concentrations of each grid, the Soil Nitrogen of each grid shown in Fig. 3
The same following table of content：
S104 examples generate：According to interpolation result, all rectangle grid examples (rectangle management subregion) are generated, establish phase
Close Matrix C={ cij, wherein, if example i grid coverages j, cij=1, otherwise cij=0.And calculate each example i soil
Key element variable variance, the present embodiment grid number are 3*18, and total rectangle grid instance number mesh is 1026.
S105 management grid structures：Optimum partition example is determined with two-value integer program algorithm, and remembers ViFor decision variable,
Target is that the variation of regional compartmentalization inner space is comprehensive minimum, two-value integral linear programming byDetermine (Represent each real
The soil key element variable variance of example i internal grids)；Maximum LX and minimum LN number of grids threshold value are set to ensure that agricultural machinery is put into practice
Efficiency and operability.Its constraint formulations is：
A relative variable is introduced simultaneously to improve to original method, so as to ensure the homogenieity of division result, its
Constraint formulations are
WhereinIt is all example population variances, N is example quantity.α is the suitable index of variability for ensureing subregion homogenieity,
0.8 is taken in the present embodiment.
Fig. 4 show the present embodiment optimal rules grid Managed Solution when LX takes 10, the LN to take 0, and what 1-10 was represented is this reality
The regulation management division result obtained under the conditions of example is applied, different subregions can use different cultivation management schemes.
Part that the present invention does not relate to is same as the prior art or can be realized using prior art.
Specific embodiment described herein is only that spirit of the present invention is illustrated.Technology belonging to the present invention is led
The technical staff in domain can be made various modifications or supplement to described specific embodiment or be replaced using similar mode
Generation, but without departing from the spiritual of the present invention or surmount scope defined in appended claims.
Claims (6)
1. a kind of rectangle grid construction method for managing field, it is characterised in that it comprises the following steps：
S101 is sampled：N (h) sampled point is chosen in research field, and obtains soil environment information；Select a certain soil environment will
Element is the foundation key element of grid-based management field, is designated as Z；
S102 determines optimal Grid size：The Z variables semivariance variation figure of sampled point is drawn, a variety of en differential modes are evaluated in fitting
Type, optimal semivariance model is determined, using the change journey a of optimal semivariance model into optimal Grid size；
S103 interpolation：Scope using the minimum enclosed rectangle of field as management field, the grid for being a*a with size split the pipe
Scope is managed, using common kriging method to soil environment key element Z interpolation；
S104 rectangle grid example generates：All examples that may be present are generated according to interpolation result, and establish one and example
The consistent homography C of number, all example internal grids soil key element Z variance is stored with homography C；
The optimal grid example selections of S105：Optimum partition example is determined with two-value integer program algorithm, and remembers viFor decision variable,
Target is that the variation of regional compartmentalization inner space is comprehensive minimum, by solving, obtains optimum partition example.
2. a kind of rectangle grid developing algorithm for managing field as claimed in claim 1, it is characterized in that：In step S101：It is actual
Factor data needed for management includes soil nitrogen concentrations data, soil organic matter content, content of soil available phosphor, soil available nitrogen
Content.
3. a kind of rectangle grid developing algorithm for managing field as claimed in claim 1, it is characterized in that：Step S102 is specially：
S1021, the factor data obtained using sampling draw the semivariance variation function figure on γ (h), and its formula is：
Wherein, h is semivariance variation figure independent variable, and n (h) represents the number of pairs of sampled point during at intervals of h, and Z (x) is sampled point
Value；
S1022, it is fitted using a variety of semivariance theoretical models to obtain the semivariance curve of each model, passes through cross validation
Method assesses each model；Select mean value error close to 0 and model of the mean square deviation close to 1 as optimal models, and determine optimal
The change journey a of semivariance model carries out soil key element Z interpolation into optimal Grid size.
4. a kind of rectangle grid developing algorithm for managing field as claimed in claim 3, it is characterized in that：It is a variety of in step S1022
Semivariance theoretical model includes linear model, spherical model, exponential model and Gauss model.
5. a kind of rectangle grid developing algorithm for managing field as claimed in claim 1, it is characterized in that：Step S104 is specially：
According to interpolation result, all rectangle grid examples are generated, establish correlation matrix C={ cij, wherein, if example i nerves of a covering
Lattice j, then cij=1, otherwise cij=0；And calculate the soil key element variable variance of each example i internal grids
6. a kind of rectangle grid developing algorithm for managing field as claimed in claim 1, it is characterized in that：Step S105 is specially：
S1051, optimum partition example determined with two-value integer program algorithm, and remember vi∈ { 0,1 } is decision variable, and target is area
The variation of domain subregion inner space is comprehensive minimum, two-value integral linear programming byDetermine；
S1052, maximum mesh threshold value LX and minimum grid threshold value LN is set to ensure the efficiency and operability of agricultural machinery practice, its
Constraint formulations are：
A relative variable is introduced simultaneously to improve to original method, and so as to ensure the homogenieity of division result, it is constrained
Formula is
WhereinIt is all example population variances, α is the suitable index of variability for ensureing subregion homogenieity, and N is example quantity, α value models
Enclose [0.5,1), niRepresent the sampled point number in example i.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109541172A (en) * | 2018-10-25 | 2019-03-29 | 北京农业信息技术研究中心 | The calculation method and device of soil attribute value |
| CN110658011A (en) * | 2019-11-05 | 2020-01-07 | 新疆农业科学院土壤肥料与农业节水研究所(新疆维吾尔自治区新型肥料研究中心) | County scale orchard soil quality sampling method |
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| CN102999927A (en) * | 2012-11-23 | 2013-03-27 | 中国科学院亚热带农业生态研究所 | Fine partition method of soil pollutant content spatial distribution |
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| CN102867115A (en) * | 2012-08-29 | 2013-01-09 | 南京农业大学 | Farmland division method based on fuzzy c-means clustering |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109541172A (en) * | 2018-10-25 | 2019-03-29 | 北京农业信息技术研究中心 | The calculation method and device of soil attribute value |
| CN110658011A (en) * | 2019-11-05 | 2020-01-07 | 新疆农业科学院土壤肥料与农业节水研究所(新疆维吾尔自治区新型肥料研究中心) | County scale orchard soil quality sampling method |
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Application publication date: 20171124 |