CN110019633A - Line density statistical method and system based on ArcGIS secondary development - Google Patents
Line density statistical method and system based on ArcGIS secondary development Download PDFInfo
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Abstract
The present invention discloses a kind of line density statistical method and system based on ArcGIS secondary development, applies in ArcGIS spatial analysis tool.By statistics starting point coordinate and terminal point coordinate using the midpoint coordinates of the n-th simple line as the center of circle, using the numerical value of m-th of search radius as the number of the simple line in the area of space that radius is constituted, obtain n-th of first statistical results of m group, the value of m is followed successively by from 1 to M, the value of n is followed successively by from 1 to N, m-th of min cluster result with conspicuousness is calculated according to N number of first statistical result of Principle of Statistics and m group, Statistics of Density is carried out to N bars of simple line according to N number of first statistical result of M min cluster result and m group, obtains density result set.This method and system are applied in ArcGIS spatial analysis tool, can solve the technical issues of ArcGIS spatial analysis tool lacks line density statistical tool.
Description
Technical field
The present invention relates to the beginning and the end (Origin-Destination, OD) line process fields more particularly to one kind to be based on
The line density statistical method and system of ArcGIS secondary development.
Background technique
OD matrix is for one of strategical planning and the most important information source of transportation network management.Traditionally, city
Planning and traffic engineering are investigated by family investigation questionnaire or every 5-10 generaI investigation carried out and road to develop OD Matrix Estimation
Method.In recent years, the improvement of big data and trace facility allows to collect a large amount of travel data for mobile object.However,
Due to a large amount of intersections of OD flow and overlapping, in the previous research of OD matrix, based on the point to administrative or traffic space unit
Statistics becomes difficult to recognize rapidly because data volume increases.
The geospatial analysis software ArcGIS of complete function is weaker for the processing function of OD line, only calculates there are two types of related
Method, first is that line density is analyzed, second is that OD matrix calculates or track generates.The former goes to calculate OD in grid according to the setting of grid
The length of line is analyzed as OD line density, and result interpretation is excessively poor.Because what it was counted is one virtual through overfrequency
Secondary and length, rather than actual route.The OD matrix of the latter calculates, and realization is relatively simple, but also only increases the one of OD line
A little association attributes can not understand its spatial relation representation, especially when analyzing mass data.The track OD is raw
At realizing also relative difficulty in ArcGIS, if studied a question about traffic analysis, the extraction of this actual path is very heavy
It wants.But if we concern the field of space relationship or special attention, such as find contact most close employment and
Residence centre, then the Statistics of Density tool of OD line is then even more important, and this is exactly to be lacked in ArcGIS spatial analysis tool
's.
Summary of the invention
The main purpose of the present invention is to provide a kind of line density statistical method and systems, can solve in the prior art
The technical issues of ArcGIS spatial analysis tool lacks line density statistical tool.
To achieve the above object, first aspect present invention provides a kind of line density statistics side based on ArcGIS secondary development
Method, which is characterized in that the method is applied in ArcGIS spatial analysis tool, which comprises
Step 101, obtain simple Single-wire data collection, and according to the numerical value of minimum search radius, radius incrementss numerical value and
The numerical value of cycle-index calculates the numerical value of m-th of search radius according to pre-set radius formula, and the letter Single-wire data collection includes N
Item has the simple line of starting point coordinate and terminal point coordinate, and the N is positive integer, and the value of the m is followed successively by from 1 to M, the M
For positive integer；
Step 102, starting point coordinate and terminal point coordinate are counted using the midpoint coordinates of the n-th simple line as the center of circle, with m-th
The numerical value of search radius is the number of the simple line in the area of space that radius is constituted, and obtains n-th first statistics knots of m group
Fruit, the value of the n are followed successively by from 1 to the N；
Step 103, it is calculated according to N number of first statistical result of Principle of Statistics and m group with conspicuousness
M-th of min cluster result；
Step 104, simple described in N articles according to N number of first statistical result of M min cluster result and m group
Line carries out Statistics of Density, obtains density result set.
To achieve the above object, second aspect of the present invention provides a kind of line density department of statistic based on ArcGIS secondary development
System, which is characterized in that the system is applied in ArcGIS spatial analysis tool, the system comprises:
Computing module is obtained, for obtaining simple Single-wire data collection, and according to the numerical value of minimum search radius, radius incrementss
Numerical value and cycle-index numerical value, according to pre-set radius formula calculate m-th of search radius numerical value, it is described letter Single-wire data
Collection include N item have starting point coordinate and terminal point coordinate simple line, the N be positive integer, the value of the m be followed successively by from 1 to
M, the M are positive integer；
First statistical module is being circle with the midpoint coordinates of the n-th simple line for counting starting point coordinate and terminal point coordinate
The heart obtains n-th of m group using the numerical value of m-th of search radius as the number of the simple line in the area of space that radius is constituted
One statistics is as a result, the value of the n is followed successively by from 1 to the N；
Computing module is shown for being calculated to have according to N number of first statistical result of Principle of Statistics and m group
M-th of min cluster result of work property；
Statistics of Density module, for according to N number of first statistical result of M min cluster result and m group to N articles
The simple line carries out Statistics of Density, obtains density result set.
The present invention provides a kind of line density statistical method and system based on ArcGIS secondary development, applies in ArcGIS sky
Between in analysis tool.By statistics starting point coordinate and terminal point coordinate using the midpoint coordinates of the n-th simple line as the center of circle, with m
The numerical value of a search radius is the number of the simple line in the area of space that radius is constituted, and obtains n-th first statistics knots of m group
Fruit, the value of m are followed successively by from 1 to M, and the value of n is followed successively by from 1 to N, according to N number of first statistics of Principle of Statistics and m group
As a result m-th of min cluster with conspicuousness is calculated as a result, according to N number of the first of M min cluster result and m group
Statistical result carries out Statistics of Density to the simple line of N item, obtains density result set.This method and system are applied to ArcGIS sky
Between in analysis tool, can solve the technical issues of ArcGIS spatial analysis tool lacks line density statistical tool.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those skilled in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.
Fig. 1 shows for the process of the line density statistical method based on ArcGIS secondary development a kind of in first embodiment of the invention
It is intended to；
Fig. 2 is the flow diagram of the refinement step of step 103 in first embodiment of the invention；
Fig. 3 is the flow diagram of the refinement step of step 104 in first embodiment of the invention；
Fig. 4 is the area of space constituted in first embodiment of the invention based on the simple line of nth and m-th of search radius
Schematic diagram；
Fig. 5 shows for the structure of the line density statistical system based on ArcGIS secondary development a kind of in second embodiment of the invention
It is intended to；
Fig. 6 is the structural schematic diagram of the refinement module of computing module 203 in second embodiment of the invention；
Fig. 7 is the structural schematic diagram of the refinement module of Statistics of Density module 204 in second embodiment of the invention.
Specific embodiment
In order to make the invention's purpose, features and advantages of the invention more obvious and easy to understand, below in conjunction with the present invention
Attached drawing in embodiment, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described reality
Applying example is only a part of the embodiment of the present invention, and not all embodiments.Based on the embodiments of the present invention, those skilled in the art
Member's every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
Since the technical issues of ArcGIS spatial analysis tool lacks line density statistical tool exists in the prior art.
In order to solve the above-mentioned technical problem, the present invention proposes a kind of line density statistical method based on ArcGIS secondary development
And system, it applies in ArcGIS spatial analysis tool.By statistics starting point coordinate and terminal point coordinate with the n-th simple line
Midpoint coordinates is the center of circle, using the numerical value of m-th of search radius as the number of the simple line in the area of space that radius is constituted, is obtained
N-th of first statistical results of m group, the value of m are followed successively by from 1 to M, and the value of n is followed successively by from 1 to N, according to Principle of Statistics
M-th of min cluster with conspicuousness is calculated as a result, according to M min cluster with N number of first statistical result of m group
As a result Statistics of Density is carried out to N bars of simple line with N number of first statistical result of m group, obtains density result set.By this method
And system is applied in ArcGIS spatial analysis tool, be can solve ArcGIS spatial analysis tool and is lacked line density statistical tool
Technical problem.
Referring to Fig. 1, for a kind of line density statistical method based on ArcGIS secondary development in first embodiment of the invention
Flow diagram.Specifically, this method is applied in ArcGIS spatial analysis tool, this method comprises:
Step 101, obtain simple Single-wire data collection, and according to the numerical value of minimum search radius, radius incrementss numerical value and
The numerical value of cycle-index, the numerical value of m-th of search radius is calculated according to pre-set radius formula, and simple Single-wire data collection includes N item tool
There is the simple line of starting point coordinate and terminal point coordinate, N is positive integer, and the value of m is followed successively by from 1 to M, and M is positive integer；
Further, radius formula are as follows:
rm=r1+(i-1)Δr
Wherein, rmIndicate m-th of search radius, r1It indicates minimum search radius, also illustrates that the 1st search radius, i indicate
Cycle-index, Δ r indicate radius incrementss.
Step 102, starting point coordinate and terminal point coordinate are counted using the midpoint coordinates of the n-th simple line as the center of circle, with m-th
The numerical value of search radius is the number of the simple line in the area of space that radius is constituted, and obtains n-th first statistics knots of m group
Fruit, the value of n are followed successively by from 1 to N；
Step 103, the m with conspicuousness is calculated according to N number of first statistical result of Principle of Statistics and m group
A min cluster result；
Specifically, referring to Fig. 2, being the flow diagram of the refinement step of step 103 in first embodiment of the invention.It should
Refinement step includes:
Step 1031, configured significance value is obtained, and N number of first statistical result tested in m group is formed
Data distribution distribution situation；
Step 1032, it if the data distribution that N number of first statistical result in m group is formed meets normal distribution, is based on
M-th of min cluster result is calculated according to normal distribution formula in significance value；
Step 1033, if the data distribution that N number of first statistical result in m group is formed meets Pareto distribution, base
M-th of min cluster result is calculated according to Pareto formula in significance value.
Further, normal distribution formula are as follows:
Minlines=average (Nls)+r*SD (Nls)
Wherein, minlines indicates min cluster as a result, average indicates that mean function, Nls indicate the N in m group
A first statistical result, r are parameter relevant to significance value, and when significance value is 99%, r value is
2.58, when significance value is 95%, r value is that 1.96, SD indicates standard deviation function.
Further, Pareto formula are as follows:
Wherein, p be parameter relevant to significance value, when significance value be 99% when, p value for less than
0.01, when significance value is 95%, p value is less than 0.05, xmMin cluster is indicated as a result, x is indicated in m group
N number of first statistical result, α indicate regression coefficient, are a positive parameters.
Step 104, N bars of simple line is carried out according to N number of first statistical result of M min cluster result and m group close
Degree statistics, obtains density result set.
Specifically, referring to Fig. 3, being the flow diagram of the refinement step of step 104 in first embodiment of the invention.It should
Refinement step includes:
Step 1041, it counts starting point coordinate and terminal point coordinate is being with the midpoint coordinates of unlabelled a bars simple line
The center of circle obtains using the numerical value of b-th of search radius as the number of the unlabelled simple line in the area of space that radius is constituted
A-th of second statistical results of b group, a is positive integer and value is followed successively by from 1 to A, and A is that simple Single-wire data concentrates unlabelled letter
The numerical value of single line, wherein m-th of maximum cluster knot is calculated according to N number of first statistical result of Principle of Statistics and m group
It is minimum less than c-th poly- to search first satisfaction, c-th of maximum cluster result from the 1st into m-th maximum cluster result for fruit
C-th of search radius of class result condition, the initial value of b are c-1, one into M of c value 1；
Step 1042, the maximum object statistics of numerical value are extracted as a result, judging mesh from A the second statistical results of b group
Whether mark statistical result is greater than b-th of min cluster result；
Step 1043, if object statistics result be greater than b-th of min cluster as a result, if remember i=i+1, inquiry is united with target
The corresponding simple line of target of result is counted, marking starting point coordinate and terminal point coordinate is being circle with the midpoint coordinates of the simple line of target
The heart, using the numerical value of b-th of search radius as the unlabelled simple line and the simple line of target in the area of space that radius is constituted, and
Note object statistics result is i-th of density result, and the initial value of i is 0；
Step 1044, whether the numerical value for judging unlabelled simple line is 0, if the numerical value of unlabelled simple line is not 0,
1041 are then returned to step, if the numerical value of unlabelled simple line is 0, density result collection is obtained based on i density result
It closes；
Step 1045, if object statistics result be less than or equal to b-th of min cluster as a result, if when b be greater than 1 when, enable b=
B-1 returns to step 1041, when b is less than or equal to 1, obtains density result set based on i density result.
It is emphasized that the initial value of b is 1 one into M, the initial value of b is c-1, and the c-1 search radius is
It is obtained based on statistical nature.Specific manifestation are as follows: be calculated according to N number of first statistical result of Principle of Statistics and m group
M-th of maximum cluster result, since the value of m is followed successively by from 1 to M, a shared M maximum statistical result.From the 1st to
It in m-th maximum cluster result, successively searches, when occurring, first satisfaction, c-th of maximum cluster result is minimum less than c-th poly-
When c-th of search radius of class result condition, the initial search radius (for maximum search radius) of b-th of search radius is c-
1 search radius.That is, the initial value of b is c-1, one into M of c value 1.If in M maximum cluster result, without meeting c
C-th of search radius of a maximum less than c-th min cluster result condition of cluster result, then the initial value of b is M.
Further, in step 1045, if object statistics result be less than or equal to b-th of min cluster as a result, if when b it is big
When 1, b=b-1 is enabled, returns to step 1041.Every to execute the primary step, the numerical value of search radius can subtract one and half
Diameter incrementss.For example, it is 6 that M numerical value, which is 10, c numerical value, then the initial value of b is 5.Step 101 is to there is 10 search half in 103
Diameter participates in, and at step 104, a Statistics of Density is carried out according to the 5th search radius, if when object statistics result is less than or waits
When the 5th min cluster result, a Statistics of Density is carried out according to the 4th search radius, circulation executes, until unlabelled
Simple line number value is that 0 or the 1st search radius (for minimum search radius) has carried out a Statistics of Density.
It should be noted that referring to Fig. 4, to be searched in first embodiment of the invention based on the simple line of nth and m-th
The schematic diagram for the area of space that radius is constituted.Wherein, solid arrow indicates that simple line, dotted arrow indicate m-th of search radius,
Simple line where the starting point of dotted arrow indicates the simple line of nth, and circle of dotted line expression is with the midpoint coordinates of the simple line of nth
The center of circle counts starting point coordinate and terminal point coordinate in dotted line using the area of space that the numerical value of m-th of search radius is constituted as radius
The number of simple line in circle, the number are and n-th of first statistical results of m group, by taking Fig. 4 as an example, n-th of m group the
One statistical result is 5 (including the simple lines of nth).
Further, the present invention is manually entered numerical value, the radius of minimum search radius by operator in parameter selection
The numerical value of incrementss and the numerical value of cycle-index, get the numerical value of the minimum search radius, the numerical value of the radius incrementss and
After the numerical value of the cycle-index, the numerical value of m-th of search radius is calculated, and statistical disposition is carried out to the simple line of N item respectively, is obtained
N number of first statistical result of M group.
It is emphasized that the numerical value of radius incrementss can be 0, it can not also be 0, the numerical value of cycle-index can be
1, it can not also be 1, i.e. the present invention has two ways in parameter selection.One is operators to be manually entered minimum search half
The cycle-index that the radius incrementss and/or numerical value that numerical value, the numerical value of diameter are 0 are 1, at this time by radius formula it is found that rmValue
Constant is r1, illustrate the numerical value of search radius be it is constant, m be equal to 1.This method be suitable for have to simple line it is enough
In the case where solving or having clearly analysis purpose, the numerical value for specifying search for radius and significance value that can be directly subjective.Example
Such as, if it is desired to which on-job firmly line number finds strongest connection region in special bus routes are arranged, and can will search for half
Diameter is set as 500 meters, this is usually the coverage of bus stop, and min cluster result can be set to a bus
Minimum service number.Another kind be operator's radius incrementss that be manually entered the numerical value of minimum search radius, numerical value not be 0 and
Numerical value is not 1 cycle-index, to keep the numerical value of search radius variable.This method is suitable for not being very to the understanding of simple line
Under foot, or the indefinite situation of purpose of analysis, after the numerical value for specifying search for radius, the density result counted may not be
Optimal.At this point, using specified minimum search radius, numerical value be not 0 radius incrementss and numerical value be not 1 cycle-index
Mode realizes that the automation of search radius is extracted, and can count in the case where lacking priori knowledge and obtain ideal density knot
Fruit.
Further, it is calculated according to N number of first statistical result of Principle of Statistics and m group, target is that had
There is m-th of min cluster result of conspicuousness.It is embodied in through N number of first statistical result formation in test m group
The distribution situation of data distribution.In general, most of data distribution meets normal distribution, if therefore N number of first system in m group
The data distribution that meter result is formed meets normal distribution, then is calculated the according to normal distribution formula based on significance value
M min cluster result, wherein what significance value can manually select for operator, including 95% and 99% two values,
What significance value can also be manually entered for operator；If the data distribution that N number of first statistical result in m group is formed is not
Meet normal distribution, but meet power-law distribution, in general, most of OD line in space be all it is discrete, it is only a small number of
It flocks together.Therefore (one of power-law distribution) can be distributed using Pareto to test N number of first statistics in m group
As a result the data distribution formed, and m-th of min cluster result is calculated using Pareto formula.Wherein, Pareto formula
In α indicate regression coefficient, be a positive parameter, can be from power law model f (x)=cx-(α+1)In obtain, c indicate return system
Number.When search radius is smaller, the numerical value of the first statistical result is largely 1, α larger.With the increase of search radius numerical value,
Value is reduced for the quantity of 1 the first statistical result, and α reduces.When α is less than 1, the phase of the stochastic variable after Pareto distribution
Prestige value is infinity, wherein the tail portion being distributed has infinite region, and probability density function becomes nonsensical.Therefore, work as α
When less than 1, min cluster result is nothing, and cannot find center line.
It is worth noting that, if the data distribution that N number of first statistical result in m group is formed meets other type data
Distribution can be calculated using corresponding distribution formula.The data distribution that N number of first statistical result tested in m group is formed
Distribution situation, and calculated using formula corresponding with the distribution situation, its purpose is to find suitable probability point
Cloth has the min cluster result of more highly significant level to extract.
Further, after obtaining that there is the min cluster result of conspicuousness, the simple line of N item is needed to carry out Statistics of Density.
The detailed process of Statistics of Density sees Fig. 3.It should be noted that step 102, count starting point coordinate and terminal point coordinate with
The midpoint coordinates of n-th simple line is the center of circle, using the numerical value of m-th of search radius as the simple line in the area of space that radius is constituted
Number, obtain n-th of first statistical results of m group, the value of n is followed successively by from 1 to N.In the M group that the step obtains, every group
N number of first statistical result between there may be be overlapped statistics the case where, for example, in m group in the 1st the first statistical result
The 1st bar of simple line, the 2nd bar of simple line, the 3rd bar of simple line and the 4th bar of simple line, the 2nd first statistics knot in m group are counted
The 1st bar of simple line, the 2nd bar of simple line, the 4th bar of simple line have been counted in fruit, the 5th bar of simple line and the 6th bar of simple line.Therefore,
The first statistical result that step 102 statistics obtains is inaccurate.Using in M group, every group of N number of first statistical result is calculated
To m-th of min cluster with conspicuousness as a result, N number of first statistical result pair based on M min cluster result and m group
The simple line of N item carries out Statistics of Density, obtains density result set.There is no be overlapped system between density result in the step 104
The case where meter.This is because in the area of space of the simple line of target unlabelled simple line and the simple line of target marked
Note, when so that counting next time, marked simple line is no longer participate in the process of Statistics of Density.
In embodiments of the present invention, by statistics starting point coordinate and terminal point coordinate with the midpoint coordinates of the n-th simple line
M group n-th is obtained using the numerical value of m-th of search radius as the number of the simple line in the area of space that radius is constituted for the center of circle
A first statistical result, the value of m are followed successively by from 1 to M, and the value of n is followed successively by from 1 to N, according to Principle of Statistics and m group
N number of first statistical result m-th of min cluster with conspicuousness is calculated as a result, according to M min cluster result and
N number of first statistical result of m group carries out Statistics of Density to N bars of simple line, obtains density result set.By this method and system
It is applied in ArcGIS spatial analysis tool, can solve ArcGIS spatial analysis tool and lack the technology of line density statistical tool and ask
Topic.
Referring to Fig. 5, for a kind of line density statistical system based on ArcGIS secondary development in second embodiment of the invention
Structural schematic diagram.Specifically, the system is applied in ArcGIS spatial analysis tool, which includes:
Computing module 201 is obtained, is increased for obtaining simple Single-wire data collection, and according to the numerical value of minimum search radius, radius
The numerical value of dosage and the numerical value of cycle-index calculate the numerical value of m-th of search radius, simple Single-wire data according to pre-set radius formula
Collection includes the simple line that N item has starting point coordinate and terminal point coordinate, and N is positive integer, and the value of m is followed successively by from 1 to M, and M is positive whole
Number；
Further, radius formula are as follows:
rm=r1+(i-1)Δr
Wherein, rmIndicate m-th of search radius, r1It indicates minimum search radius, also illustrates that the 1st search radius, i indicate
Cycle-index, Δ r indicate radius incrementss.
First statistical module 202 is being with the midpoint coordinates of the n-th simple line for counting starting point coordinate and terminal point coordinate
The center of circle obtains m group n-th using the numerical value of m-th of search radius as the number of the simple line in the area of space that radius is constituted
First statistical result, the value of n are followed successively by from 1 to N；
Computing module 203 is shown for being calculated to have according to N number of first statistical result of Principle of Statistics and m group
M-th of min cluster result of work property；
Specifically, referring to Fig. 6, being the structural representation of the refinement module of computing module 203 in second embodiment of the invention
Figure.The refinement module includes:
Test module 2031 is obtained, for obtaining configured significance value, and N number of first in test m group
The distribution situation for the data distribution that statistical result is formed；
First computing module 2032, if the data distribution for N number of first statistical result in m group to be formed meets normal state
Then m-th of min cluster result is calculated according to normal distribution formula based on significance value in distribution；
Second computing module 2033, if it is tired to meet pa for the data distribution that N number of first statistical result in m group is formed
Support distribution, then be calculated m-th of min cluster result according to Pareto formula based on significance value.
Further, normal distribution formula are as follows:
Minlines=average (Nls)+r*SD (Nls)
Wherein, minlines indicates m-th of min cluster as a result, average indicates that mean function, Nls indicate m group
In N number of first statistical result, r be parameter relevant to significance value, when significance value be 99% when, r value
It is 2.58, when significance value is 95%, r value is that 1.96, SD indicates standard deviation function；
Pareto formula are as follows:
Wherein, p be parameter relevant to significance value, when significance value be 99% when, p value for less than
0.01, when significance value is 95%, p value is less than 0.05, xmM-th of min cluster is indicated as a result, x indicates m
N number of first statistical result in group, α indicate regression coefficient, are a positive parameters.
Statistics of Density module 204, for according to N number of first statistical result of M min cluster result and m group to N articles
Simple line carries out Statistics of Density, obtains density result set.
Specifically, referring to Fig. 7, being the structure of the refinement module of Statistics of Density module 204 in second embodiment of the invention
Schematic diagram.The refinement module includes:
Second statistical module 2041, for counting starting point coordinate and terminal point coordinate with unlabelled a bars simple line
Midpoint coordinates be the center of circle, using the numerical value of b-th of search radius as the unlabelled simple line in the area of space that radius is constituted
Number, obtain a-th of second statistical results of b group, a is positive integer and value is followed successively by from 1 to A, and A is simple Single-wire data collection
In unlabelled simple line numerical value, wherein m is calculated according to N number of first statistical result of Principle of Statistics and m group
A maximum cluster result is searched first satisfaction, c-th of maximum cluster result and is less than from the 1st into m-th maximum cluster result
C-th of search radius of c-th of min cluster result condition, the initial value of b are c-1, one into M of c value 1；
Judgment module 2042 is extracted, for extracting the maximum object statistics of numerical value from A the second statistical results of b group
As a result, judging whether object statistics result is greater than b-th of min cluster result；
Inquire mark module 2043, for if object statistics result be greater than b-th of min cluster as a result, if remember i=i+1,
The simple line of target corresponding with object statistics result is inquired, marks starting point coordinate and terminal point coordinate in the simple line of target
Point coordinate is the center of circle, using the numerical value of b-th of search radius as the unlabelled simple line and mesh in the area of space that radius is constituted
Simple line is marked, and remembers that object statistics result is i-th of density result, the initial value of i is 0；
Judging treatmenting module 2044, for judging whether the numerical value of unlabelled simple line is 0, if unlabelled simple line
Numerical value be not 0, then return to the second statistical module 2041, if the numerical value of unlabelled simple line be 0, be based on i density knot
Fruit obtains density result set；
Obtain module 2045, for if object statistics result be less than or equal to b-th of min cluster as a result, if when b be greater than 1
When, b=b-1 is enabled, the second statistical module 2041 is returned, when b is less than or equal to 1, density knot is obtained based on i density result
Fruit set.
About the explanation of the embodiment of the present invention, the related description in relation to first embodiment of the invention is seen, here no longer
It repeats.
In embodiments of the present invention, by statistics starting point coordinate and terminal point coordinate with the midpoint coordinates of the n-th simple line
M group n-th is obtained using the numerical value of m-th of search radius as the number of the simple line in the area of space that radius is constituted for the center of circle
A first statistical result, the value of m are followed successively by from 1 to M, and the value of n is followed successively by from 1 to N, according to Principle of Statistics and m group
N number of first statistical result m-th of min cluster with conspicuousness is calculated as a result, according to M min cluster result and
N number of first statistical result of m group carries out Statistics of Density to N bars of simple line, obtains density result set.By this method and system
It is applied in ArcGIS spatial analysis tool, can solve ArcGIS spatial analysis tool and lack the technology of line density statistical tool and ask
Topic.
This method and system can be used for common OD data mining, including migration, phone, world commerce etc., with synthesis
Massive dataflow extracts Main Patterns, confirms known structure and finds unknown structure.Because this method and system can identify
Hot link between different zones, so this method and system can also be used to prediction the space passage and the space of status is closed
It is feature.
It should be noted that for the various method embodiments described above, describing for simplicity, therefore, it is stated as a series of
Combination of actions, but those skilled in the art should understand that, the present invention is not limited by the sequence of acts described because
According to the present invention, certain steps can use other sequences or carry out simultaneously.Secondly, those skilled in the art should also know
It knows, the embodiments described in the specification are all preferred embodiments, and related actions and modules might not all be this hair
Necessary to bright.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, there is no the portion being described in detail in some embodiment
Point, it may refer to the associated description of other embodiments.
The above are to a kind of line density statistical method and system based on ArcGIS secondary development provided by the present invention
Description, for those skilled in the art, thought according to an embodiment of the present invention, in specific embodiments and applications
It will change, to sum up, the contents of this specification are not to be construed as limiting the invention.
Claims (10)
1. a kind of line density statistical method based on ArcGIS secondary development, which is characterized in that the method is applied in ArcGIS
In spatial analysis tool, which comprises
Step 101, simple Single-wire data collection is obtained, and according to the numerical value of minimum search radius, the numerical value of radius incrementss and circulation
The numerical value of number, the numerical value of m-th of search radius is calculated according to pre-set radius formula, and the letter Single-wire data collection includes N item tool
There is the simple line of starting point coordinate and terminal point coordinate, the N is positive integer, and the value of the m is followed successively by from 1 to M, and the M is positive
Integer；
Step 102, starting point coordinate and terminal point coordinate are counted using the midpoint coordinates of the n-th simple line as the center of circle, is searched for m-th
The numerical value of radius is the number of the simple line in the area of space that radius is constituted, and obtains n-th of first statistical results of m group, institute
The value for stating n is followed successively by from 1 to the N；
Step 103, the m with conspicuousness is calculated according to N number of first statistical result of Principle of Statistics and m group
A min cluster result；
Step 104, according to N number of first statistical result of M min cluster result and m group the simple line described in N articles into
Line density statistics, obtains density result set.
2. the method according to claim 1, wherein the specific steps of the step 103 include:
Step 1031, configured significance value is obtained, and N number of first statistical result tested in m group is formed
Data distribution distribution situation；
Step 1032, it if the data distribution that N number of first statistical result in m group is formed meets normal distribution, is based on
M-th of min cluster result is calculated according to normal distribution formula in the significance value；
Step 1033, if the data distribution that N number of first statistical result in m group is formed meets Pareto distribution, base
M-th of min cluster result is calculated according to Pareto formula in the significance value.
3. the method according to claim 1, wherein the specific steps of the step 104 include:
Step 1041, starting point coordinate and terminal point coordinate are counted using the midpoint coordinates of unlabelled a bars simple line as the center of circle,
Using the numerical value of b-th of search radius as the number of the unlabelled simple line in the area of space that radius is constituted, b group is obtained
A the second statistical results, a is positive integer and value is followed successively by from 1 to A, and the A is that the simple Single-wire data concentration is not marked
The numerical value of the simple line of note, wherein m-th of maximum is calculated according to N number of first statistical result of Principle of Statistics and m group
Cluster result searches first and meets c-th of maximum cluster result less than c-th from the 1st into m-th maximum cluster result
C-th of search radius of min cluster result condition, the initial value of the b are c-1, one into the M of the c value 1；
Step 1042, the maximum object statistics of numerical value are extracted as a result, judging institute from A second statistical results of b group
State whether object statistics result is greater than b-th of min cluster result；
Step 1043, if the object statistics result be greater than b-th of min cluster as a result, if remember i=i+1, inquiry and institute
The simple line of the corresponding target of object statistics result is stated, marks starting point coordinate and terminal point coordinate in the simple line of the target
Point coordinate be the center of circle, using the numerical value of b-th of search radius as in the area of space that radius is constituted unlabelled simple line and institute
The simple line of target is stated, and remembers that the object statistics result is i-th of density result, the initial value of the i is 0；
Step 1044, whether the numerical value for judging unlabelled simple line is 0, if the numerical value of unlabelled simple line is not 0, is returned
Step 1041 described in receipt row obtains density result collection based on i density result if the numerical value of unlabelled simple line is 0
It closes；
Step 1045, if the object statistics result be less than or equal to b-th of min cluster as a result, if when b be greater than 1 when,
B=b-1 is enabled, returns and executes the step 1041, when b is less than or equal to 1, density result is obtained based on i density result
Set.
4. the method according to claim 1, wherein
The radius formula are as follows:
rm=r1+(i-1)Δr
Wherein, rmIndicate m-th of search radius, r1It indicates the minimum search radius, also illustrates that the 1st search radius, i
Indicate the cycle-index, Δ r indicates the radius incrementss.
5. according to the method described in claim 2, it is characterized in that,
The normal distribution formula are as follows:
Minlines=average (Nls)+r*SD (Nls)
Wherein, minlines indicates m-th of min cluster as a result, average indicates that mean function, Nls indicate m group
In N number of first statistical result, r be parameter relevant to significance value, when the significance value is
When 99%, r value is 2.58, and when the significance value is 95%, r value is that 1.96, SD indicates standard deviation function；
The Pareto formula are as follows:
Wherein, p is parameter relevant to significance value, and when the significance value is 99%, p value is small
In 0.01, when the significance value is 95%, p value is less than 0.05, xmIndicate the m min cluster knot
Fruit, x indicate N number of first statistical result in m group, and it is a positive parameter that α, which indicates regression coefficient,.
6. a kind of line density statistical system based on ArcGIS secondary development, which is characterized in that the system is applied in ArcGIS
In spatial analysis tool, the system comprises:
Computing module is obtained, for obtaining simple Single-wire data collection, and according to the numerical value of minimum search radius, the number of radius incrementss
The numerical value of value and cycle-index calculates the numerical value of m-th of search radius, the letter Single-wire data Ji Bao according to pre-set radius formula
The simple line that N item has starting point coordinate and terminal point coordinate is included, the N is positive integer, and the value of the m is followed successively by from 1 to M, institute
Stating M is positive integer；
First statistical module, for counting starting point coordinate and terminal point coordinate using the midpoint coordinates of the n-th simple line as the center of circle, with
The numerical value of m-th of search radius is the number of the simple line in the area of space that radius is constituted, and obtains n-th first of m group systems
Meter is as a result, the value of the n is followed successively by from 1 to the N；
Computing module, for being calculated according to N number of first statistical result of Principle of Statistics and m group with conspicuousness
M-th of min cluster result；
Statistics of Density module, for according to N number of first statistical result of M min cluster result and m group described in N articles
Simple line carries out Statistics of Density, obtains density result set.
7. system according to claim 6, which is characterized in that the specific module of the computing module includes:
Test module is obtained, for obtaining configured significance value, and tests N number of first statistics in m group
As a result the distribution situation of the data distribution formed；
First computing module, if the data distribution for N number of first statistical result in m group to be formed meets normal state point
Then m-th of min cluster result is calculated according to normal distribution formula based on the significance value in cloth；
Second computing module, if the data distribution for N number of first statistical result in m group to be formed meets Pareto point
Then m-th of min cluster result is calculated according to Pareto formula based on the significance value in cloth.
8. system according to claim 6, which is characterized in that the specific module of the Statistics of Density module includes:
Second statistical module, for counting starting point coordinate and terminal point coordinate in the midpoint seat with unlabelled a bars simple line
It is designated as the center of circle, using the numerical value of b-th of search radius as the number of the unlabelled simple line in the area of space that radius is constituted, is obtained
To a-th of second statistical results of b group, a is positive integer and value is followed successively by from 1 to A, and the A is the simple line number
According to the numerical value for concentrating unlabelled simple line, wherein calculated according to N number of first statistical result of Principle of Statistics and m group
To m-th of maximum cluster result, from the 1st into m-th maximum cluster result, searches first and meet c-th of maximum cluster knot
C-th of search radius of less than c-th min cluster result condition of fruit, the initial value of the b are c-1, the c value 1 to institute
State one in M；
Judgment module is extracted, for extracting the maximum object statistics knot of numerical value from A second statistical results of b group
Fruit, judges whether the object statistics result is greater than b-th of min cluster result；
Inquire mark module, for if the object statistics result be greater than b-th of min cluster as a result, if remember i=i+1,
The simple line of target corresponding with the object statistics result is inquired, marks starting point coordinate and terminal point coordinate with the target letter
The midpoint coordinates of single line is the center of circle, using the numerical value of b-th of search radius as the unlabelled letter in the area of space that radius is constituted
Single line and the simple line of the target, and remember that the object statistics result is i-th of density result, the initial value of the i is 0；
Judging treatmenting module, for judging whether the numerical value of unlabelled simple line is 0, if the numerical value of unlabelled simple line is not
It is 0, then returns to second statistical module, if the numerical value of unlabelled simple line is 0, is obtained based on i density result close
Spend results set；
Obtain module, for if the object statistics result be less than or equal to b-th of min cluster as a result, if when b be greater than 1
When, b=b-1 is enabled, second statistical module is returned, when b is less than or equal to 1, density knot is obtained based on i density result
Fruit set.
9. system according to claim 6, which is characterized in that
The radius formula are as follows:
rm=r1+(i-1)Δr
Wherein, rmIndicate m-th of search radius, r1It indicates the minimum search radius, also illustrates that the 1st search radius, i
Indicate the cycle-index, Δ r indicates the radius incrementss.
10. system according to claim 7, which is characterized in that
The normal distribution formula are as follows:
Minlines=average (Nls)+r*SD (Nls)
Wherein, minlines indicates m-th of min cluster as a result, average indicates that mean function, Nls indicate m group
In N number of first statistical result, r be parameter relevant to significance value, when the significance value is
When 99%, r value is 2.58, and when the significance value is 95%, r value is that 1.96, SD indicates standard deviation function；
The Pareto formula are as follows:
Wherein, p is parameter relevant to significance value, and when the significance value is 99%, p value is small
In 0.01, when the significance value is 95%, p value is less than 0.05, xmIndicate m-th of min cluster knot
Fruit, x indicate N number of first statistical result in m group, and it is a positive parameter that α, which indicates regression coefficient,.
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