CN102637227A - Land resource assessment factor scope dividing method based on shortest path - Google Patents
Land resource assessment factor scope dividing method based on shortest path Download PDFInfo
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Abstract
A land resource assessment factor scope dividing method based on a shortest path includes: dispersing an assessment space range of land resource; setting up a road network dataset based on a road network of the assessment space range, wherein the road network dataset comprises network nodes and network edges; dividing the assessment space range into a plurality of assessment subareas; searching the assessment subarea of each grid in a grid set G; inquiring the network node and the assessment factor contained by each obtained assessment subarea; searching the network nodes to centralize the closest assessment factor of each network node; searching the closest assessment factor of each grid in the grid set G; and combining the grids with same closest assessment factors to obtain a corresponding assessment factor scope.
Description
Technical field
The invention belongs to Evaluation for Soil Resources factor action scope partitioning technology field, particularly relate to a kind of Evaluation for Soil Resources factor action scope division methods based on shortest path.
Background technology
(1) Evaluation for Soil Resources technology
China is as populous nation, and land resource is rare relatively, how rationally to utilize the soil, realizes that sustainable using of land resources is the current problem that presses for solution.The technological means of employing science and method are estimated the quality of land resource, are to promote land resource rationally to utilize, improve the necessary ways that the soil utilizes output.
Definition according to the FAO of FAO (Food and Agriculture Organization of the United Nation); Evaluation for Soil Resources is meant the process that the soil is assessed to the specific effect of utilizing mode to show; Comprise that aspect attributes such as form to the soil, soil, vegetation, weather carry out quality comprehensive and identify, thereby distinguish and more different soil utilizes mode to suitability degree that evaluation objective showed.Relevant document: [1] FAO.Land Evaluation.Towards a revised framework.2007..Using for reference on the basis of advanced foreign technology, China has formed that the soil that comprises to farming land and construction land grades, the land valuation system that meets current national conditions demand of deciding grade and level, appraisal, appraisal of land suitability etc.
When estimating the land resource quality; The land resource quality there is the object such as various factors entity such as business service center, country fair, iirigation water source, road network of appreciable impact, is defined as " the Evaluation for Soil Resources factor " (abbreviating " the evaluation factor " as).Different according to the spacial influence characteristic of estimating the factor, mainly can be divided into " the point-like factor ", " the wire factor " and " the planar factor ".Wherein, " the planar factor " (edaphic condition, geologic condition etc.) only limit to the coverage of this evaluation factor to the spatial dimension of land resource quality influence, and its action scope is exactly the area of space of this evaluation factor in the Evaluation for Soil Resources scope; Then there are stronger relation in " the point-like factor ", " the wire factor " with space length to the influence of land resource quality, mainly show as the influence of estimating factor pair land resource quality and constantly weaken along with the increase of space length.Therefore, for a plurality of evaluation factors in the range of value, a certain soil always receives the influence apart from its nearest evaluation factor.This rule spatially shows as the different evaluation factor and has different space behavior territories (reach).Can distinguish analyse through space buffer for the influence of " the wire factor " (mainly comprising the irrigation canals and ditches of Traffic Net, the agricultural land of urban land in estimating in estimating etc.) and obtain its action scope.Land resource quality in its buffer zone scope is influenced by it, otherwise not influenced by it.And to " the point-like factor " in the land resource quality assessment (school, business service center in the evaluation of urban land; Water source during agricultural land is estimated, country fair etc.) the division relative complex then of action scope; Its main cause is: the influence of point-like factor pair land resource quality often depends on certain particular network structure (Traffic Net, irrigation canals and ditches network etc.); Its action intensity is not along the air line distance decay, but decays along network path distance.Therefore, when dividing its action scope, need to adopt dividing mode usually based on path distance.What the present invention relates to is to design to " the point-like factor " the action scope division methods in the land resource quality assessment, and " the evaluation factor " that hereinafter is mentioned mainly refers to " the point-like factor ".
(2) Evaluation for Soil Resources factor action scope partitioning technology
The method of dividing about " the point-like factor " action scope both at home and abroad at present mainly can be divided into following 3 types:
1) according to the round structure of Ke Lesi Teller " center geographical says "; Principle according to the equilibrium covering; Adopt formula
to calculate the action scope of each point-like factor, wherein D is that the radius of influence, the n of the factor are the area of range of value for number, the S that estimates the factor.This method is calculated simple, is the method that is widely used at present, also is the method for recommending in the current domestic relevant Evaluation for Soil Resources rules.Relevant document: [2] State Administration for Quality Supervision and Inspection and Quarantine. urban land deciding grade and level rules (GB/T 18507-2001) [S] .2001 that grades; Relevant document: [3] Ministry of Land and Resources. farming land deciding grade and level rules (TD/T1005-2004) [S] .2003.Yet this method does not consider to estimate the spatial distribution state of the factor, can not response factor to the characteristic of land resource quality influence along with the path distance decay, computational accuracy is low, factor action scope is divided unreasonable.
2) the evaluation factor action scope division methods of scheming based on Voronoi.This method is divided into several Voronoi polygons according to the spatial distribution state of estimating the factor with the land valuation spatial dimension, and the scope that the Voronoi polygon that each factor generates covers is exactly the action scope that changes the factor.Relevant document [4]: Hu Shiyuan; The expansion of Liu Yao woods .Voronoi figure and the application [J] in the land grading influencing radius is confirmed thereof. the Chinese soil science; 2004 (03). this method is calculated relative complex; But its computation process has considered to estimate the space distribution of the factor, and is more reasonable with respect to traditional simple algorithmic approach, can the whole evaluation region of complete covering.Yet, adopt this method to estimate the division of factor action scope and still do not consider the path factor, thereby can not reflect the characteristic of factor pair land resource quality influence along with the path distance decay, have certain limitation.
3) based on the Voronoi drawing method of path distance.This method is the basis with the network, carry out Voronoi when dividing with network on shortest path apart from replacing conventional space line Euclidean distance.With respect to preceding 2 kinds of methods, this method can the reflected appraisal factor influence the characteristic along path attenuation, also is the highest method of accuracy in the present practical application.Relevant document [5]: Zhu Guorui; Tang Xu; Wang Ping. based on the point-like of effect characteristics deciding grade and level factor analysis [J]. Wuhan University's journal (information science version) 2004 (03). relevant document [6]: thank to Shunping County, Feng Xuezhi, Lu Wei. the Voronoi face territory figure based on the road network analysis makes up algorithm [J]. mapping journal .2010.39 (01) yet.; This method need adopt grid cell, raster cell or vector grid that the land valuation scope is dispersed usually, divides the action scope of estimating the factor on this basis.Because the Evaluation for Soil Resources scope can reach tens of square kilometres usually, and in order to obtain higher computational accuracy, when it was dispersed, the size of grid cell, raster cell or vector grid was generally 50-100 rice.Therefore calculate the pixel that relates to or meshes number and can reach hundreds thousand ofly, and need carry out path query repeatedly, its calculated amount is huge.Single evaluation factor action scope partition process for 1 medium-sized city promptly need be calculated 3-4 hour, and the Evaluation for Soil Resources process is usually directed to 10-20 the evaluation factor, and visible its computation process is very consuming time.Therefore, must give full play to the newest fruits of computer software and hardware development, improve counting yield.
(3) parallel computing
Parallel computation (being also referred to as high-performance calculation, supercomputing) is the calculating of under parallel computing platform, carrying out.Adopt the fundamental purpose of parallel computation to be to improve speed and the scale that computing machine solves problem.Relevant document [7]: cypress. the data directory technical research [D] on the parallel computing platform. the .2011. of China Science & Technology University is along with the fast development of computer hardware technique; Advanced persons such as grid, polycaryon processor, cluster, desktop supercomputer, cloud computing calculate facility and successively occur, for the speed of finding the solution and the efficient that improves the large-scale calculations problem provides the important techniques support.In addition, the CPU on the personal computer also develops (examining to more multinuclear number development from double-core, four nuclears, eight) towards the direction of multinucleation day by day, makes that the hardware cost of parallel computation is cheaper.On the other hand, the appearance of multiple programming standards such as OpenMP, MPICH, OpenMPI, MapReduce also greatly reduces the threshold of parallel software development.Therefore, how making full use of the computing power of multi-core CPU, improve the speed of finding the solution and the efficient of large-scale calculations problem, is the subject matter that faces during following program development and science are calculated.
But, there is not the relevant art scheme to occur as yet in Evaluation for Soil Resources factor action scope partitioning technology field.
Summary of the invention
To the poor efficiency that exists in the existing Evaluation for Soil Resources factor action scope division methods, problem such as consuming time based on shortest path; The present invention improves existing division methods; And design meets the spatial data decomposition strategy of concurrent operation requirement, the parallelization that realization Evaluation for Soil Resources factor action scope is divided.Fully excavate the resource potential of multi-core computer on this basis, improve the efficient of Evaluation for Soil Resources factor action scope partition process, shorten working hours.
Technical scheme provided by the invention is a kind of Evaluation for Soil Resources factor action scope division methods based on shortest path, may further comprise the steps:
Step 7.1 according to the lookup result of step 4, obtains the numbering PID that the subarea is estimated at grid g place, evaluation subarea, grid g place is designated as estimates subarea P;
Step 7.2 according to the Query Result of step 5, obtains to estimate the network node and the evaluation factor that subarea P is comprised; Comprised the evaluation factor if estimate subarea P, execution in step 7.3 does not comprise the evaluation factor if estimate subarea P, execution in step 7.4,
Step 7.3 compares grid g and estimates the air line distance of respectively estimating the factor that subarea P comprises, and notes the numbering FID of the nearest evaluation factor, and grid g processing is finished;
Step 7.4, traversal is estimated the all-network node that subarea P comprises, and the distance B of the nearest evaluation factor that writes down in computing grid g and each network node relatively and note the numbering FID with the nearest evaluation factor of grid g, finishes grid g processing; Carrying out calculation mode during traversal does; If the network node that traverses is J; Computing grid g and network node J apart from d1; Then according to the lookup result of step 6 obtain the nearest evaluation factor of network node J numbering FID and with the path distance d2=Dis of the nearest evaluation factor, calculate D=d1+d2;
And in the step 6, searching the nearest evaluation factor implementation of certain network node is that employing dijkstra's algorithm computational grid node and the path distance of estimating all evaluation factors in the spatial dimension therefrom obtain the nearest evaluation factor.
And the implementation of step 1 does, belongs to minimum outsourcing rectangle and averages and cut apart according to estimating spatial dimension, obtains some space partition zones, and each space partition zone is assigned to the grid that calculates create-rule on the different threads separately; Grid with each space partition zone merges at last, obtains the grid set G of whole evaluation spatial dimension.
And; The implementation of step 4 does; Search the evaluation subarea at each grid place among the grid set G, will estimate subarea set Ps and be divided into several evaluation subarea subclass, from grid set G, separate each and estimate the corresponding partition network grid of subarea subclass collection; Each is estimated the subarea subclass, and execution is stacked separately to different threads with respective partition grid subset allocation, obtains the partition network grid and concentrates each grid place to estimate the numbering PID in subarea; At last each stacked result who estimates the subarea subclass is merged, obtain the numbering PID in each evaluation subarea, grid place among the grid set G.
And; The implementation of step 5 does; To estimate subarea set Ps and be divided into several and estimate the subarea subclass, and each estimated subarea subset allocation to different threads, carry out space querying separately, and obtain to estimate and respectively estimate network node that the subarea comprises in the subclass of subarea and estimate the factor; At last each space querying result who estimates the subarea subclass is merged, obtain estimating the network node and the evaluation factor that each evaluation subarea comprises among the subarea set Ps.
And; The implementation of step 6 does; The network node ensemble average is divided into plurality of network node subclass; And be assigned on the different threads separately the nearest evaluation factor of each network node in the Network Search node subclass, in network node, note then the nearest evaluation factor numbering FID and with the path distance Dis of the nearest evaluation factor; Lookup result with each network node subclass merges at last, obtains network node and concentrates the nearest evaluation factor of each network node.
And the implementation of step 7 does, grid gathered G on average be divided into the plurality of grids subclass, and be assigned on the different threads and separately the grid in the grid subclass carried out substep 7.1～7.4, obtains the nearest evaluation factor of each grid in the grid subclass; Execution result with each grid subclass merges at last, obtains the nearest evaluation factor of each grid among the grid set G.
With respect to domestic and international existing evaluation factor action scope division methods based on shortest path, the present invention has designed again and has estimated the flow process that factor action scope is divided according to new data structure and the basic demand of calculating parallelization.The present invention also provides the data structure that is beneficial to the shortest path inquiry, reduces dependence and correlation degree between the data, make it more appropriate to parallel processing, also can improve the efficient of shortest path inquiry simultaneously.The present invention has also designed rational data decomposition strategy; Realized the parallelization of Evaluation for Soil Resources factor action scope division methods; Can give full play to the processing power of the parallel computers such as cluster of multinuclear personal computer, small-sized workstation, shared storage, increase work efficiency.Technical scheme of the present invention has simply, characteristics fast, can improve the operational efficiency of Evaluation for Soil Resources dotted factor action scope partition process preferably.
Description of drawings
The process flow diagram of Fig. 1 embodiment of the invention;
The discrete grid block synoptic diagram of Fig. 2 Evaluation for Soil Resources spatial dimension of the present invention;
The parallelization of the Evaluation for Soil Resources spatial dimension of Fig. 3 embodiment of the invention synoptic diagram that disperses;
The road network of Fig. 4 embodiment of the invention makes up synoptic diagram;
The evaluation area of space of Fig. 5 embodiment of the invention is cut apart synoptic diagram;
The network topology relation of Fig. 6 embodiment of the invention makes up synoptic diagram;
The evaluation subregion topology constructing synoptic diagram of Fig. 7 embodiment of the invention;
The nearest evaluation factor inquiry synoptic diagram of the network node of Fig. 8 embodiment of the invention;
The nearest evaluation factor querying method process flow diagram of the grid of Fig. 9 embodiment of the invention;
Trellis state design sketch after the nearest factor inquiry of the execution of Figure 10 embodiment of the invention;
The legend master data situation synoptic diagram of Figure 11 embodiment of the invention;
The legend range of value discretize of Figure 12 embodiment of the invention is synoptic diagram as a result;
The legend road network of Figure 13 embodiment of the invention makes up synoptic diagram as a result;
The legend range of value of Figure 14 embodiment of the invention is cut apart and is estimated subarea structure synoptic diagram as a result;
The legend of Figure 15 embodiment of the invention is estimated factor action scope results comparison diagram.
Embodiment
The division methods flow process based on the Evaluation for Soil Resources point-like factor action scope of shortest path of the present invention design is seen accompanying drawing 1, can adopt the computer software technology realization flow to move automatically by those skilled in the art.Wherein step (1)-(3) are the basic data pretreatment stage of whole flow process.The concrete implementation procedure of embodiment is following:
Grid adopts the vector rectangle to store.Grid is more little, and then computational accuracy is high more, and calculated amount is big more; Otherwise computational accuracy is low more, and calculated amount is more little.Usually when carrying out Evaluation for Soil Resources, adopt the grid of 50*50 or 100*100 rice to disperse to estimating area of space.Like Fig. 2, the evaluation spatial dimension of land resource is dispersed, obtain the grid set G of whole evaluation spatial dimension.
Because number of grid can reach hundreds thousand of in this step; Calculated amount is bigger; Normally therefore calculation procedure more consuming time in the Evaluation for Soil Resources process can be divided into several space partition zones by coordinate with estimating spatial dimension, again it is assigned to different thread (process) and goes up independent execution discrete operations; This data decomposition parallel processing has improved efficient; The discretize result of each thread (process) merges the most at last, just obtains the grid set G of whole evaluation spatial dimension, like Fig. 3: belong to minimum outsourcing rectangle and average and cut apart according to estimating spatial dimension; Obtain some space partition zones, and each space partition zone is assigned to the grid that calculates create-rule on the different threads separately; Grid with each space partition zone merges at last, obtains the grid set G of whole evaluation spatial dimension.Embodiment is cut apart by the horizontal direction equidistance of minimum outsourcing rectangle, also can adopt other schemes during practical implementation, for example cuts apart by the vertical direction equidistance.
Embodiment according to the road network in the evaluation spatial dimension of land resource, makes up the road network data collection in this step.The road network data collection can be used for calculating in the evaluation spatial dimension arbitrarily a bit to the shortest path distance between the evaluation factor; Mainly form, stored the length on adjacent with it node information, limit, the information such as direction of network on the network limit by network node and network limit.Network node has been stored adjacent with it network side information.The efficient of network struction is higher, makes up for the road network of a large size city also to be no more than 1 minute usually and can to accomplish.So step is as estimating the basic data preliminary work that factor action scope is divided, the interface that mainly provides by existing software (like ArcGIS) is realized, not as focal point of the present invention.Like Fig. 4, from the road network that network limit E1, E2, E3, E4, E5 constitute, the road network data collection of structure has also comprised network node N1, N2, N3, N4, N5, N6.
Embodiment is according to road network and the polygon of estimating spatial dimension, the evaluation spatial dimension of land resource is divided into several independently subregions, for the parallel basic data of carrying out of the data decomposition of subsequent step is prepared.Because this step is as the basic data preliminary work of estimating the division of factor action scope, and computation process is shorter, the interface that mainly provides by existing software (like ArcGIS) is realized, not as focal point of the present invention.Its ultimate principle is seen Fig. 5: according to road, cut apart estimating spatial dimension.
Embodiment carries out network topology in this step and makes up.It is stacked that the space is carried out in the evaluation subarea that obtains in grid that obtains dispersing in the step 1 and the step 3, obtains the numbering that the subarea is estimated at each grid element center place.Like Fig. 6: the subarea number of dividing based on road graticule is 1,2,3,4,5,6,7,8,9,10,11,12; Stacked by subregion decomposition and executed in parallel and step 1 gained original mesh (being grid set G) merges the grid that obtains after stacked at last.
During practical implementation, " PID " field can be set in gridding information, this numbering be stored in " PID " field of grid.
Because step 3 will have been estimated spatial dimension and be divided into a plurality of evaluations subarea.Therefore this step can be a unit to estimate the subarea through the mode of data decomposition also, is assigned to different thread (process) respectively and goes up execution separately.Embodiment searches the evaluation subarea at each grid place among the grid set G; To estimate subarea set Ps and be divided into several evaluation subarea subclass; From grid set G, separate each and estimate the corresponding partition network grid of subarea subclass collection; Each is estimated the subarea subclass, and execution is stacked separately to different threads with respective partition grid subset allocation, obtains the partition network grid and concentrates each grid place to estimate the numbering PID in subarea; At last each stacked result who estimates the subarea subclass is merged, obtain the numbering PID in each evaluation subarea, grid place among the grid set G.
Embodiment estimates the subarea topology constructing in this step.The evaluation subarea that step 3 is obtained respectively with step 2 in network node and estimate the factor to carry out the space stacked, the network node that the query evaluation subarea comprises with estimate the factor.Like Fig. 7, establish and estimate subarea 5, estimate subarea 8 after parallel execution inquiry is calculated, estimating on the subarea 5 has network node 1,2,3,4; Estimating on the subarea 8 has network node 3,4,5,6,7,8, and contains the evaluation factor 1.
During practical implementation, can in the data structure of storage evaluation subarea information, " NIDs " field and " FIDs " field be set, network node be stored in " NIDs " field, estimate the factor and be stored in " FIDs " field.If it is a plurality of that the network node in certain evaluation subarea comprises, the mode that then adopts ", " to cut apart between the numbering NID of each network node is formed character string and is stored.If it is a plurality of that the evaluation factor also comprises, can adopt in the same way and store.
This step can adopt the paralleling tactic identical with step 4, will estimate subarea set Ps and be divided into several subclass, and each data centralization comprises one or several evaluation subareas.Be that a sub-set is distributed a thread, the evaluation subarea that antithetical phrase is concentrated is gone up at thread (process) one by one and is carried out space querying.For example, when 200 are estimated subareas and decompose 10 thread execution, have 10 sub-set with regard to one, each subclass comprises 20 polygons.Embodiment will estimate subarea set Ps and be divided into several and estimate the subarea subclass, each estimated subarea subset allocation to different threads, carry out space querying separately, obtain to estimate respectively to estimate network node that the subarea comprises in the subclass of subarea and estimate the factor; At last each space querying result who estimates the subarea subclass is merged, obtain estimating the network node and the evaluation factor that each evaluation subarea comprises among the subarea set Ps.
Embodiment inquires about the nearest evaluation factor apart from each network node, and will estimate the numbering FID of the factor at this node place record recently.During practical implementation; Can travel through each network node; Adopt existing dijkstra's algorithm (Di Jiesitela algorithm) to calculate the path distance of the current network node that traverses and all evaluation factors in the ergodic process, therefrom obtain the evaluation factor nearest apart from this network node.Like Fig. 8, to the nearest factor query script of a certain network node on the road network of having simplified do, the factor 1,2,3 of evaluation is arranged around the network node 1, through dijkstra's algorithm, it is to estimate factor 1 that inquiry obtains wherein nearest, and distance is 31.8.
During practical implementation; Field " FID " and " Dis " can be set in the data structure of storage networking node information, in the attribute field " FID " of network node, note the numbering (FID) of the evaluation factor nearest, storage networking node and the path distance (Dis) of estimating the factor in " Dis " field apart from it.
For a medium-sized city, its road network node scale is usually about 1000, and the process of the nearest evaluation factor inquiry of each network node is a relatively independent process, is fit to very much parallel processing.Therefore can adopt the parallel method of data decomposition, the network node collection is resolved into some subclass, and be assigned to upward executed in parallel of different threads (process).This step needn't be divided according to estimating the subarea.When embodiment searches the network node ensemble average is divided into plurality of network node subclass; And be assigned on the different threads separately the nearest evaluation factor of each network node in the Network Search node subclass, in network node, note then the nearest evaluation factor numbering FID and with the path distance Dis of the nearest evaluation factor; Lookup result with each network node subclass merges at last, obtains network node and concentrates the nearest evaluation factor of each network node.
Embodiment travels through grid set G.If the arbitrary grid that traverses is designated as g, carry out following substep:
Step 7.1 according to the lookup result of step 4, obtains the numbering PID that the subarea is estimated at grid g place, evaluation subarea, grid g place is designated as estimates subarea P;
Step 7.2 according to the Query Result of step 5, obtains to estimate the network node and the evaluation factor that subarea P is comprised; Comprised the evaluation factor if estimate subarea P, execution in step 7.3 does not comprise the evaluation factor if estimate subarea P, execution in step 7.4,
Step 7.3 compares grid g and estimates the air line distance of respectively estimating the factor that subarea P comprises, and notes the numbering FID of the nearest evaluation factor, and grid g processing is finished;
Step 7.4, traversal is estimated the all-network node that subarea P comprises, and the distance B of the nearest evaluation factor that writes down in computing grid g and each network node relatively and note the numbering FID with the nearest evaluation factor of grid g, finishes grid g processing; Carrying out calculation mode during traversal does; If the network node that traverses is J; Computing grid g and network node J apart from d1; Then according to the lookup result of step 6 obtain the nearest evaluation factor of network node J numbering FID and with the path distance d2=Dis of the nearest evaluation factor, calculate D=d1+d2.
During practical implementation; Field " FID " and " Dis " can be set in the data structure of save mesh; The numbering FID that estimates the factor recently is stored in the attribute field " FID " of this grid, and with grid and estimate recently distance between the factor be stored in " Dis ' in the field.When searching the nearest evaluation factor of each grid among the grid set G, be stored in the information in the data structure, corresponding flow process such as Fig. 9 before also can utilizing:
The current grid g that traverses is begun to handle, comprise the grid numbering GID that provides this grid given;
Obtain the evaluation subarea P at grid g place according to " PID " property value of grid g;
According to estimating subarea P's " NIDs " and " FIDs " property value, obtain to estimate the network node collection N and evaluation factor set F that subarea P is comprised;
Judge whether estimate factor set F is empty; Be then to carry out 2., otherwise carry out 1..
1. for respectively estimating the air line distance of the factor among computing grid g and the evaluation factor set F, take out and the nearest evaluation factor of grid g, be designated as f.Deposit grid g and the air line distance of estimating factor f in grid at last " Dis " field, with the g of the FID property value storage network access lattice of estimating factor f " FID " field.Like Fig. 9 exemplified, estimating the subarea has network node 3,4,5,7..., and the evaluation factor 1 is wherein arranged, grid 1 is nearest with the air line distance of estimating factor 1, deposits grid 1 in " Dis " field.
2. respectively the air line distance d1 between each network node among computing grid g and the network node collection N, obtain each network node and its estimate recently the factor apart from d2, computing grid g apart from the distance B=d1+d2 that estimates the factor.Therefrom find out the network node n on the shortest path, with network node n's " FID " the numbering FID of the nearest evaluation factor of storing in the attribute is as the nearest evaluation factor f of grid g.Deposit grid g in grid g with the distance of estimating factor f at last " Dis " field, with the numbering FID storage network access lattice g's that estimates factor f " FID " field.Like Fig. 9 exemplified; Estimate the subarea network node 1,2,3,4 is arranged; Wherein do not estimate the factor; Grid is designated as d1 (1), d1 (2), d1 (3), d1 (4) respectively to the distance of network node 1,2,3,4; Network node 1 to the distance of the evaluation factor nearest with it be designated as d2 (1), network node 2 to the distance of the evaluation factor nearest with it be designated as d2 (2), network node 3 to the distance of the evaluation factor nearest with it be designated as d2 (3), network node 4 is designated as d2 (4) to the distance of the evaluation factor nearest with it; Find out the reckling among d1 (1)+d2 (1), d1 (2)+d2 (2), d1 (3)+d2 (3), d1 (the 4)+d2 (4) and deposit grid in " Dis " field, the corresponding network node " FID " factor numbering of storing in the attribute is as current nearest object f.
Calculate effect and see Figure 10: establishing has the factor 1,2 of evaluation in the road network under the original state; Through after the above query processing; In the trellis state that calculates; The nearest evaluation factor is all stored numbering 1 for the grid of estimating factor 1, and the nearest evaluation factor is all stored numbering 2 for the grid of estimating factor 2.
Because number of grid can reach hundreds thousand of usually; Serial is calculated shortest path one by one and is gone forward side by side walking along the street footpath distance relatively according to the conventional method; Efficient is very low, and the time that this computation process is consumed in Evaluation for Soil Resources factor action scope partition process can account for more than 80% of The whole calculations process usually.Because it also is relatively independent that each grid is searched the process of the nearest evaluation factor; Therefore can be divided into several subclass to grid being gathered G equally; And be assigned on the different threads and carry out above substep separately and decompose, to improve counting yield, shorten computing time.This step needn't be divided according to estimating the subarea.Embodiment gathers G with grid and on average is divided into the plurality of grids subclass, and is assigned on the different threads separately the grid in the grid subclass is carried out substep 7.1～7.4, obtains the nearest evaluation factor of each grid in the grid subclass; Execution result with each grid subclass merges at last, obtains the nearest evaluation factor of each grid among the grid set G.
Embodiment inquires about according to the numbering FID of the nearest evaluation factor of each grid among the step 7 gained grid set G, and the grid that the FID property value is identical merges, and can respectively be estimated factor action scope polygon, and the The whole calculations process finishes.Because during practical implementation, the inquiry in this step can be inquired about based on relational database fully, thereby efficient is higher, can accomplish so need not to carry out the parallelization operation.
The general data object that relates among the present invention has road network data collection (comprising network node and network limit), grid, evaluation subarea.For the purpose of the enforcement reference; The data structure of the present invention's suggestion is: 1) the road network data collection is the basis with Network Dataset (network data collection) data model of ESRI (company of U.S. environment system research institute), on this basis the data structure of network node is expanded; 2) mesh object is to the discrete rectangular node that obtains of Evaluation for Soil Resources spatial dimension according to fixing distance; 3) Evaluation for Soil Resources subarea makes up the polygon of sealing according to Evaluation for Soil Resources scope and road network, thereby whole evaluation region spatially is divided into several independently subareas, thereby prepares for the parallel data decomposition of carrying out of algorithm.
Embodiment has selected respectively the simplest decomposing scheme accordingly for step that can executed in parallel, also can adopt other decomposing schemes during practical implementation.The parallel number of concrete number, the active thread that decomposes subclass and actual operation ability etc. are relevant, and the user also can be provided with as the case may be.
In order to improve flow performing efficient, to reduce the dependence between the data, after the embodiment of the invention is expanded the data structure of 3 class objects (network node, grid, evaluation subarea), as shown in the table:
For the purpose of explanation invention effect; The present invention with the action scope partition process of the point-like factor " country fair " in certain urban land resource evaluation as legend, through writing computer program and on the personal computer of one 4 nuclear CPU, accomplishing parallel computation.Its basic data has: traffic route network, the position, country fair in Evaluation for Soil Resources scope, evaluation district.Shown in figure 11.Carry out successively according to process step provided by the present invention:
(1) according to the Evaluation for Soil Resources scope; Big or small generating mesh according to 100*100 rice; And generate the corresponding property field structure, and the result sees Figure 12: the attribute field structure comprises GID, Shape, PID, FID, Dis, the GID field is used for the numbering of save mesh; The Shape field has been used to store the X of the geometric object of grid, the Y coordinate.Geometric object is Polygon (polygon) model of ESRI.
(2) adopt the Network dataset network data collection model construction road network data collection of ESRI, and, the data structure of network node is expanded, add " FID " " Dis " field according to design of the present invention; The result sees Figure 13: the attribute field structure comprises NID, SHAPE, PID, FID, Dis, the numbering ID of NID field store current network node, and the Shape field is used for the X of storage networking node, the Y coordinate, point adopts point (Point) model of ESRI.
(3) carry out area of space according to road network and range of value and cut apart, and, add " FIDs " " NIDs " field according to design of the present invention; The result sees Figure 14: the attribute field structure comprises PID, SHAPE, FID, NIDs, FIDs, and the PID field store is estimated the subarea numbering, and the X of subarea all-network node, Y coordinate are estimated in the SHAPE storage.
(4) will estimate subarea set Ps and be divided into several evaluation subarea subclass, grid will be carried out data decomposition according to the evaluation subarea at its place, and be assigned to execution separately on the different threads, the PID numbering of estimating the subarea will be composed to its mesh object that comprises.
(5) will estimate subarea set Ps and be divided into several and estimate the subarea subclass, and be assigned on the different threads and carry out separately, calculate the network node and the evaluation factor respectively estimating to be comprised respectively in the subarea in.
(6) the network node collection is decomposed, and be assigned to execution separately on the different threads, the evaluation factor that each network node of computed range is nearest.Wherein the search of shortest path adopts dijkstra's algorithm to realize.
(7) set is decomposed to grid, is assigned on the different threads and carries out separately.According to grid and estimate the topological relation between subarea, network node, the evaluation factor, search the evaluation factor the shortest, and write down its FID with its path distance.
(8) " FID " according to mesh object inquires about, and the mesh object that will have identical FID property value merges, and finally obtains the evaluation factor action scope based on the shortest path distance.Shown in the result sees that (a) partly among Figure 15.
Wherein (4), (5) all are to decompose according to estimating the subarea.But the object that calculates is different, and the object data set of decomposition is different, and the foundation of decomposition all is the evaluation subarea according to the object place: what operated (4) is mesh object, and what operated (5) is to estimate the subarea.
Adopt prior art based on the evaluation factor results of air line distance shown in (b) part among Figure 15.With respect to the evaluation factor results based on air line distance, result obtained by the method for the present invention obviously meets real rule more.And through the parallel efficiency test, the method for the present invention's design is with respect to the traditional serial disposal route, and parallel efficiency can reach 70-80%, under multi-core environment, can amplitude shorten computing time, increases work efficiency.
Specific embodiment described herein only is that the present invention's spirit is illustrated.Person of ordinary skill in the field of the present invention can make various modifications or replenishes or adopt similar mode to substitute described specific embodiment, but can't depart from spirit of the present invention or surmount the defined scope of appended claims.
Claims (7)
1. the Evaluation for Soil Resources factor action scope division methods based on shortest path is characterized in that, may further comprise the steps:
Step 1 disperses to the evaluation spatial dimension of land resource, obtains the grid set G of whole evaluation spatial dimension;
Step 2 makes up the road network data collection based on the road network of estimating spatial dimension, and the road network data collection comprises network node and network limit, and road network data concentrates the all-network node to constitute the network node collection;
Step 3 based on estimating spatial dimension and road network, will be estimated spatial dimension and be divided into several evaluation subareas, and the evaluation subarea set of formation is designated as Ps;
Step 4 is searched the evaluation subarea at each grid place among the grid set G, comprise to grid set G with estimate subarea set Ps and carry out stackedly, obtain the numbering PID that the subarea is estimated at each grid place;
Step 5 is carried out space querying respectively for each evaluation subarea among the evaluation subarea set Ps, obtains respectively to estimate the network node and the evaluation factor that the subarea comprises;
Step 6, the nearest evaluation factor of each network node in the Network Search nodal set, in network node, note then the nearest evaluation factor numbering FID and with the path distance Dis of the nearest evaluation factor;
Step 7 is searched the nearest evaluation factor of each grid among the grid set G, comprises traversal grid set G, for the following substep of any grid g execution wherein,
Step 7.1 according to the lookup result of step 4, obtains the numbering PID that the subarea is estimated at grid g place, evaluation subarea, grid g place is designated as estimates subarea P;
Step 7.2 according to the Query Result of step 5, obtains to estimate the network node and the evaluation factor that subarea P is comprised; Comprised the evaluation factor if estimate subarea P, execution in step 7.3 does not comprise the evaluation factor if estimate subarea P, execution in step 7.4,
Step 7.3 compares grid g and estimates the air line distance of respectively estimating the factor that subarea P comprises, and notes the numbering FID of the nearest evaluation factor, and grid g processing is finished;
Step 7.4, traversal is estimated the all-network node that subarea P comprises, and the distance B of the nearest evaluation factor that writes down in computing grid g and each network node relatively and note the numbering FID with the nearest evaluation factor of grid g, finishes grid g processing; Carrying out calculation mode during traversal does; If the network node that traverses is J; Computing grid g and network node J apart from d1; Then according to the lookup result of step 6 obtain the nearest evaluation factor of network node J numbering FID and with the path distance d2=Dis of the nearest evaluation factor, calculate D=d1+d2;
Step 8, according to the nearest evaluation factor of each grid among the step 7 gained grid set G, the grid that the nearest evaluation factor is identical merges, and is estimated factor action scope accordingly.
2. according to claim 1 based on the Evaluation for Soil Resources factor action scope division methods of shortest path; It is characterized in that: in the step 6; Searching the nearest evaluation factor implementation of certain network node does; Adopt dijkstra's algorithm computational grid node and the path distance of estimating all evaluation factors in the spatial dimension, therefrom obtain the nearest evaluation factor.
3. according to claim 1 or claim 2 based on the Evaluation for Soil Resources factor action scope division methods of shortest path; It is characterized in that: the implementation of step 1 does; Belong to minimum outsourcing rectangle and average and cut apart according to estimating spatial dimension; Obtain some space partition zones, and each space partition zone is assigned to the grid that calculates create-rule on the different threads separately; Grid with each space partition zone merges at last, obtains the grid set G of whole evaluation spatial dimension.
4. according to claim 1 or claim 2 based on the Evaluation for Soil Resources factor action scope division methods of shortest path; It is characterized in that: the implementation of step 4 does; Search the evaluation subarea at each grid place among the grid set G; To estimate subarea set Ps and be divided into several evaluation subarea subclass; Gather the corresponding partition network grid of each evaluation subarea subclass of separation collection the G from grid, each is estimated subarea subclass, and execution is stacked separately to different threads with respective partition grid subset allocation, and the numbering PID in subarea is estimated at concentrated each grid place of acquisition partition network grid; At last each stacked result who estimates the subarea subclass is merged, obtain the numbering PID in each evaluation subarea, grid place among the grid set G.
5. according to claim 1 or claim 2 based on the Evaluation for Soil Resources factor action scope division methods of shortest path; It is characterized in that: the implementation of step 5 does; To estimate subarea set Ps and be divided into several evaluation subarea subclass; Each is estimated subarea subset allocation to different threads, carry out space querying separately, obtain to estimate and respectively estimate network node that the subarea comprises in the subclass of subarea and estimate the factor; At last each space querying result who estimates the subarea subclass is merged, obtain estimating the network node and the evaluation factor that each evaluation subarea comprises among the subarea set Ps.
6. according to claim 1 or claim 2 based on the Evaluation for Soil Resources factor action scope division methods of shortest path; It is characterized in that: the implementation of step 6 does; The network node ensemble average is divided into plurality of network node subclass; And be assigned on the different threads separately the nearest evaluation factor of each network node in the Network Search node subclass, in network node, note then the nearest evaluation factor numbering FID and with the path distance Dis of the nearest evaluation factor; Lookup result with each network node subclass merges at last, obtains network node and concentrates the nearest evaluation factor of each network node.
7. according to claim 1 or claim 2 based on the Evaluation for Soil Resources factor action scope division methods of shortest path; It is characterized in that: the implementation of step 7 does; Grid is gathered G on average be divided into the plurality of grids subclass; And be assigned on the different threads separately the grid in the grid subclass is carried out substep 7.1 ~ 7.4, obtain the nearest evaluation factor of each grid in the grid subclass; Execution result with each grid subclass merges at last, obtains the nearest evaluation factor of each grid among the grid set G.
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