CN101916458A - Multi-scale estimation predication method of geographic model - Google Patents
Multi-scale estimation predication method of geographic model Download PDFInfo
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Abstract
The invention discloses a multi-scale estimation predication method of a geographic model, which overcomes the application problem of single scale of the geographic model by applying a geographic information system rasterization calculation method based on the development scale of the geographic model. Based on an Arc GIS Engine platform, the multi-scale estimation predication method achieves the coupling of the geographic information system components technology and the geographic model, fully develops the advantages of geographic information system components in a spatial data processing and the advantages of the computer in a batch data processing calculation, and carries out the quantitative simulation estimation on scientific problems involved in the geographic spatial scale by combining with the geographic model. The multi-scale estimation predication method is simple and easy to realize, belongs to a united innovation over multiple disciplines, can be applicable to the crossing research fields of hydrological simulation, meteorological simulation and the like, can be extended or popularized to multi-scale estimation related to the geographic spatial scale models, and overcomes the application and popularization problem of the geographic model.
Description
Technical field
The present invention relates to Geographic Information System spatial data treatment technology and model dimension technical field, particularly a kind of multi-scale estimation predication method of geographic model.
Background technology
A lot of geographic models all are the modeling at a certain particular space scope when development research, this particular space scope is called the model development yardstick in the present invention, when this geographic model is departing under the condition of self research and development yardstick when carrying out analog computation, the science that causes with regard to being faced with the change of geographic model internal logic departs from and computational accuracy disappearance problem, yet the research at the geographic model particular dimensions is always limited with correction, therefore, how to realize that the multiple dimensioned analog computation of geographic model becomes the difficult point problem of model application.
Summary of the invention
The object of the present invention is to provide a kind of multi-scale estimation predication method of geographic model.
The multi-scale estimation predication method of this geographic model provided by the invention comprises the steps:
(1) selects geographic model according to subject area practical problems to be solved;
(2) determine the specific object meaning of each parameter representative in subject area of comprising in the selected geographic model, i.e. the attribute data of subject area;
(3) according to selected geographic model, collect the thematic maps of the pairing Geographic Information System grid format of each attribute data in the arrangement subject area, if there is not ready-made thematic maps about each attribute data correspondence in the subject area, then attribute data in the collection research subject area and the spatial data that matches, the thematic maps that is the theme with each attribute data of subject area with the making of Geographic Information System drafting instrument;
(4) based on the Geographic Information System component platform, call good function of Geographic Information System component package and class definition grid cell size according to the development scale of selected geographic model, subject area is divided into several foursquare grids;
(5) based on the Geographic Information System component platform, programming realizes reading the numerical value of each attribute data of the interior correspondence of each grid cell in each thematic maps;
(6) programming realizes the computational logic of selected geographic model, the numerical value of each attribute data in each grid cell that step (5) is read is composed each parameter to selected geographic model, obtain result of calculation, programming deposits result of calculation in the corresponding grid cell automatically;
(7) with two kinds of forms of result of calculation classification figure and the output of result of calculation numerical value the result of calculation of step (6) is expressed demonstration.
The present invention is based on the Geographic Information System component platform, realized the coupling of Geographic Information System component technology and geographic model, given full play to advantage and computing machine the advantage on batch data processing calculating of Geographic Information System assembly on spatial data is handled, the problem in science that relates to the geographical space yardstick has been carried out the quantification analog computation in conjunction with geographic model.The present invention is based on the development scale of geographic model own, utilization Geographic Information System rasterizing Calculation Method has solved the application limitation of the single yardstick of geographic model, thereby has realized the Multi-Scale Calculation of geographic model, has solved the application problem of geographic model.The present invention is simple and direct and be easy to realize that belong to the multidisciplinary innovation of uniting, described computing method can be applicable to crossing research fields such as hydrological simulation, meteorological simulation, and can transplant or be generalized to the various geographical space yardstick models that relate to and carry out multiple dimensioned calculating.
Description of drawings
Fig. 1 is the multi-scale estimation predication method process flow diagram of geographic model.
Fig. 2 reads the grid cell property value and embeds selected geographical Model Calculation synoptic diagram.
Fig. 3 is a Lake Dongting area soil coefficient of efficiency thematic maps.
Fig. 4 is a Lake Dongting area Rice Production potentiality distribution thematic map.
Embodiment
Geographic information system technology is based on geographical spatial data, adopt the geographic model analytical approach, spatial data and attribute data are gathered, manage, operate, analyzed and simulate, multiple space and dynamic geography information are provided in real time, thereby a new technology of service is provided for geographical correlative study and decision-making.In recent years, the component geographic information system technology becomes the focus of Geographic Information System Application and Development, this technology is based on the component object platform, provide one group to have certain standard communication interface, allow to stride the Geographic Information System assembly of language application, between the Geographic Information System assembly or and the other types assembly between can realize by standard communication mutual, and then utilize object oriented calculation machine programming language to carry out the exploitation of high-level applied logic, wherein Geographic Information System assembly ArcGIS Engine is exactly wherein one of outstanding representative, and it has multiple functional, it is long-range to upgrade, integration is good, be convenient to issue, advantage such as the powerful and software cost of stand-alone development performance is cheap.
The method of the invention is a platform with Geographic Information System assembly ArcGIS Engine exactly, realize the coupling of Geographic Information System component technology and geographic model, based on the development scale of geographic model itself, the method for utilization rasterizing solves the application problem of the single yardstick of geographic model.Rasterizing is in the Geographic Information System graphics pel to be shown a kind of technology that pixel shows that converts to, it is the process that the image table of vector format is shown as grating image, grid is the array of a rule, wherein each pixel is independent of each other, its distinguishing feature is that attribute is obvious, be the direct record attribute of data itself, the process of rasterizing is exactly that attributes such as the color of pel, the degree of depth and texture are composed to each pixel.The Geographic Information System raster data is widely used in space stack, space correlation and spatial analysiss such as simulation and contagion, therefore be a kind of very important data layout, provided by the present invention this utilize geographic model carry out multiple dimensioned estimation approach at be exactly the graphic file of grid format.
Fig. 1 is the multi-scale estimation predication method process flow diagram of geographic model, comprises the steps:
(1) select geographic model according to subject area practical problems to be solved, selected geographic model has been determined self yardstick of each parameter that model comprised and model;
(2) determine the specific object meaning of each parameter representative in subject area of comprising in the selected geographic model, i.e. the attribute data of subject area;
(3) required according to the calculating of selected geographic model, collect the thematic maps of each attribute data correspondence in the arrangement subject area, the thematic maps form is necessary for the Geographic Information System grid format, if there are not ready-made thematic maps data about each attribute data correspondence in the subject area, the spatial data that then needs each attribute data in the collection research subject area and match, the thematic maps that is the theme with each attribute data of subject area with the making of Geographic Information System drafting instrument;
(4) under C# programming language environment, carry out program development, call the function and the class of ArcGIS Engine assembly, development scale programming definition grid cell according to selected geographic model, subject area is divided into several foursquare grids, the development scale strict conformance of grid cell size and selected geographic model, so far the Model Calculation in whole zone just is transformed into and in each grid cell, carries out Model Calculation, both guaranteed the science of selected geographical Model Calculation on the yardstick, it has obtained application exceeding self to get on development scale again;
(5) under C# programming language environment, carry out program development, call function and class in the ArcGIS Engine assembly, the numerical value of pairing each attribute data in each grid cell scope in the thematic maps that reads each attribute data correspondence of programming;
(6) under C# programming language environment, carry out program development, the numerical value of the attribute data in each grid cell that step (5) is read is composed to each parameter in the selected geographic model, programming realizes the computational logic of selected geographic model, and then carry out Model Calculation, obtain result of calculation, programming deposits result of calculation in the corresponding grid cell automatically;
(7) with two kinds of forms of result of calculation classification figure and the output of result of calculation numerical value the result of calculation of step (6) is expressed demonstration.
Spatial data described in the above-mentioned steps (3) comprises survey region border map data and the regional inner boundary map datum that is complementary with attribute data, result of calculation classification figure in the step (7) is by appending attribute field and assignment as a result for each grid cell, obtain a thematic map that is the theme with geographic model result of calculation after resampling, obtain the figure of classification as a result of an image according to its gray-scale value of size design of the result of calculation value in each grid cell, the output of result of calculation numerical value is that various statistical functions as a result are set as required, be convenient to simulation result of calculation in the arbitrary region scope is added up, finally offer the user with the form of determining numerical result.
Fig. 2 is the synoptic diagram that reads grid cell property value and incorporation model calculating, SHAPE this algorithm of * MERGEFORMAT comprise outer circulation and two circulations of interior circulation, outer circulation is read each line data by judging outer circulation condition (X〉the row coordinate of first grid cell of the upper left corner in the subject area attribute data thematic maps), in cycle through judge in cycling condition (row-coordinate of first grid cell of the upper left corner in Y＜thematic maps) read each column data.Judge whether to meet interior cycling condition earlier, if meet, then read first grid cell (X, Y) property value, and it is embedded into selected geographic model calculates, reduce step-length, cycling condition in judging, return interior circulation, read second grid cell (X, property value Y-1), and it is embedded into selected geographic model calculates, continue to reduce step-length, cycling condition in continue judging, cycling condition in not satisfying and till circulating jumping out in, as if not meeting interior cycling condition, then directly jump out interior circulation, increase step-length, judge whether X value meets the outer circulation condition, then jump out outer circulation as if ineligible, loop ends, the property value of all grid cells in the subject area attribute data thematic maps are read and are embedded selected geographical Model Calculation and finish.
Embodiment:
Select Rice Production potentiality computation model for use, selecting Lake Dongting area (comprising Changde, Yueyang, four areas in Yiyang and Changsha) is subject area, and these regional Rice Production potentiality are carried out analog computation.
The function expression of selected Rice Production potentiality computation model is Y
Q=CeQkGX, wherein
Y Q Be the Rice Production potentiality
(kg/ 666.7 m2), i.e. the result of calculation of model;
eBe the efficiency of light energy utilization, it is an occurrence at specific subject area, can regard constant as in this example; Q is the photosynthetic effective radiant energy of the sun during estimating
(J/ cm2d),Because the Lake Dongting area scope is less relatively, same value is got in whole zone, so can will should be worth as constant in the example;
kBe the unit conversion coefficient, can regard constant as in this example;
cBe economic coefficient, it has corresponding occurrence at Different Crop, and paddy rice is 0.45, can regard constant as in this example;
GBe fate breeding time, i.e. crop growth time is day to calculate the simulation deadline, input value during for analog computation, so can regard constant as in this example from transplanting for this value of paddy rice; X is the soil coefficient of efficiency, various places differ greatly, and are model parameter or independent variable, because c, e, k, G, Q in the selected Rice Production potentiality computation model parameter are constants, so the attribute data of present embodiment subject area Lake Dongting area has only the soil coefficient of efficiency, promptly selected model Y
Q=Parameter X among the ceQkGX.
Fig. 3 is selected Rice Production potentiality computation model Y
Q=The Lake Dongting area soil coefficient of efficiency thematic maps of the pairing Geographic Information System grid format of parameter X among the ceQkGX (soil coefficient of efficiency).If do not have ready-made, satisfactory Lake Dongting area soil coefficient of efficiency thematic maps, then need at first compile Lake Dongting area various places soil coefficient of efficiency attribute data, Lake Dongting area data boundary and the geographical frontier map datum that is complementary with soil coefficient of efficiency attribute data, Lake Dongting area various places soil coefficient of efficiency attribute data wherein, theoretically, this data correspondence regional the smaller the better, promptly to Model Calculation, the thematic map that goes out based on administrative village level attribute data creating more can guarantee the precision of analog computation than the thematic map of making based on administrative villages (towns) level attribute data, if soil coefficient of efficiency attribute data is administrative village rank data, its geographical frontier map datum must have corresponding border, administrative village so, so that make thematic maps.After above data preparation is collected and finished, use Geographic Information System Thematic Cartography software, produce the Lake Dongting area soil coefficient of efficiency thematic maps of grid format, see Fig. 3.
According to the development scale of subject area and selected geographic model, the size of programming definition grid cell is for the Rice Production potentiality computation model Y in this example
Q=CeQkGX, its development scale is 50m * 50m, therefore under C# programming language environment, carry out program development, call the function and the class of ArcGIS Engine assembly, programming definition grid cell size is 50m * 50m, Lake Dongting area is divided into the foursquare grid of several 50m * 50m, so far the Model Calculation of whole Lake Dongting area just is transformed into Model Calculation to each 50m * 50m grid cell, both guaranteed selected model Y on the yardstick
Q=The science that ceQkGX calculates has obtained application exceeding on the development scale of self again.
Utilize the grid cell of above-mentioned definition, call programming realization attribute data read functions among the Geographic Information System assembly ArcGIS Engine, make it to read the interior corresponding soil coefficient of efficiency property value of each grid cell in the Lake Dongting area soil coefficient of efficiency thematic maps.In fact, a grid cell may be corresponding to several different property values in the entity, at this moment just how the problem to the grid value is arranged, obtaining value method comprises the area method that is dominant, the central point method, length be dominant method and importance method, wherein the area method of being dominant is the value that the property value that occupies maximum area in the grid is decided to be this grid element, the central point method is with the value of the grid central point value as this grid element, the length method of being dominant is that grid element center is drawn a horizontal line, use the value of the property value of the shared the longest part of horizontal line then as this grid element, often outstanding some the main attribute of importance method, for these attributes, as long as in grid, occur, just the value of this attribute as this grid element.The obtaining value method of the corresponding attribute data of above-mentioned grid cell anyly all can bring certain error no matter adopt, but all belong to normal category, and is inevitable.
The present invention chooses the central point method and reads the soil coefficient of efficiency property value in corresponding each grid cell in the soil coefficient of efficiency thematic maps line by line, and the soil coefficient of efficiency property value that reads is embedded into Rice Production potentiality computation model Y
Q=Among the ceQkGX, the mode of incorporation model is at first to write selected model Y
Q=The computational logic program of ceQkGX is composed the soil coefficient of efficiency property value that is read to model Y afterwards
Q=The parameter X of ceQkGX obtains result of calculation, and programming is deposited into result of calculation in each corresponding grid cell, and wherein the attribute of raster data comprises grid size, line number, columns, projection information, grid scope, subsidiary property value or the like.
According to the subject area Lake Dongting area,, can obtain Lake Dongting area at selected geographic model Y each the pixel value addition of the grating image of Lake Dongting area
Q=The Rice Production potentiality analogue value under the ceQkGX condition by processing that soil coefficient of efficiency thematic map is resampled, obtains Rice Production potentiality distribution thematic map shown in Figure 4, can be used as the graph data of in-depth analysis.
Claims (4)
1. the multi-scale estimation predication method of a geographic model is characterized in that described method comprises the steps:
(1) selects geographic model according to subject area practical problems to be solved;
(2) determine the specific object meaning of each parameter representative in subject area of comprising in the selected geographic model, i.e. the attribute data of subject area;
(3) according to selected geographic model, collect the thematic maps of the pairing Geographic Information System grid format of each attribute data in the arrangement subject area, if there is not ready-made thematic maps about each attribute data correspondence in the subject area, then each attribute data in the collection research subject area and the spatial data that matches, the thematic maps that is the theme with each attribute data of subject area with the making of Geographic Information System drafting instrument;
(4) based on the Geographic Information System component platform, call good function of Geographic Information System component package and class definition grid cell size according to the development scale of selected geographic model, subject area is divided into several foursquare grids;
(5) based on the Geographic Information System component platform, programming realizes reading the numerical value of each attribute data of the interior correspondence of each grid cell in each thematic maps;
(6) programming realizes the computational logic of selected geographic model, the numerical value of each attribute data in each grid cell that step (5) is read is composed the corresponding parameter to selected geographic model, obtain result of calculation, programming deposits result of calculation in the corresponding grid cell automatically;
(7) with two kinds of forms of result of calculation classification figure and result of calculation numerical value output the result of calculation of step (6) is shown and express.
2. the multi-scale estimation predication method of geographic model according to claim 1 is characterized in that described spatial data comprises survey region border map data and the regional inner boundary map datum that is complementary with attribute data.
3. the multi-scale estimation predication method of geographic model according to claim 1, it is characterized in that the result of calculation classification figure in the described step (7) is by appending attribute field and assignment as a result for each grid cell, adopt the method that resamples, obtain a thematic map that is the theme with geographic model result of calculation, obtain the figure of classification as a result of an image according to its gray-scale value of size design of the result of calculation value in each grid cell; Result of calculation numerical value output in the described step (7) is that various statistical functions as a result are set as required, is convenient to simulation result of calculation in the arbitrary region scope is added up, and finally offers the user with the form of determining numerical result.
4. the multi-scale estimation predication method of geographic model according to claim 1 and 2, it is characterized in that described computing method are is platform with the Geographic Information System assembly, realize the coupling of Geographic Information System component technology and geographic model, based on the development scale of geographic model itself, utilization Geographic Information System rasterizing Calculation Method solves the yardstick problem of geographic model.
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| CN104978467B (en) * | 2015-07-23 | 2018-04-20 | 华中科技大学 | A kind of multidisciplinary design optimization subject decoupling method |
| CN105070185A (en) * | 2015-08-26 | 2015-11-18 | 中科宇图天下科技有限公司 | Automatic integration method of point element groups |
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| CN111651501A (en) * | 2020-06-01 | 2020-09-11 | 中南大学 | Spatial aggregation scale selection method for geographic big data |
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