CN102693161B - Concurrent land resource quality evaluation factor space quantifying method - Google Patents
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Abstract
The invention relates to a concurrent land resource quality evaluation factor space quantifying method which comprises performing concurrent discretization to an evaluated space region; layering land resource quality evaluation factors; and performing concurrent space quantifying to land resource quality evaluation factors. The concurrent land resource quality evaluation factor space quantifying method generally has the advantages of simplicity and quickness, and is applicable to being carried out on personnel computers with multiple CPUs (central processing units) and multiple cores, small work stations and computer clusters. The concurrent land resource quality evaluation factor space quantifying method plays an important practical significance in sufficiently playing hardware computing proficiency of a current computer, shortening land evaluation work time and increasing work efficiency.
Description
Technical field
The invention belongs to land resource quality assessment technical field, particularly relate to a kind of parallel land resource quality assessment factor space quantization method.
Background technology
(1) land resource quality assessment technology
Along with the arrival of 21 century, many global problems such as the population problem of facing mankind, Food Security are increasingly serious.China is as populous nation, and land resource is relatively rare, how rationally to utilize soil, and the sustainable use that realizes land resource is current problem in the urgent need to address.Therefore, adopting technological means and the method for science to evaluate the quality of land resource, is the necessary means that promotes that Rational Land utilizes.
According to the definition of the FAO of FAO (Food and Agriculture Organization of the United Nation), land resource quality assessment (referred to as " land valuation ") refers to soil for the process of specifically utilizing effect that mode shows to assess, comprise that the aspect attributes such as form to soil, soil, vegetation, weather carry out quality comprehensive evaluation, thereby distinguish and compare the suitability degree that land use pattern shows evaluation objective.Related documents: [1] FAO.Land Evaluation.Towards a revised framework.2007..On the basis of foreign advanced technology, China has formed including grading for the soil of farming land and construction land, the land valuation system that meets current national conditions demand deciding grade and level, appraisal, appraisal of land suitability, Evaluation of land intensive use, Land Degradation Evaluation etc.
(2) the land resource quality assessment factor and space quantization technology thereof
When evaluating land resource quality, land resource quality is had to the various factors entity of appreciable impact as objects such as business service center, country fair, iirigation water source, road networks, be defined as " the Evaluation for Soil Resources factor " (referred to as " evaluation factor ") or " Evaluation for Soil Resources index ".
Evaluate the factor scale (or size), the spatial dimension on land quality impact, evaluate the differences such as distance between the factor and soil, caused evaluate the factor spatially affect intensity difference.Therefore, when carrying out land valuation, need to be according to evaluating scale, the spacial influence scope of the factor, calculate the factor in evaluation region everywhere soil affect intensity, this process is referred to as to evaluate the space quantization of the factor.Related documents: [2] State Administration for Quality Supervision and Inspection and Quarantine. Urban Land Classification rules (GB/T 18507-2001) ［ S ］ .2001; Related documents: [3] Ministry of Land and Resources. Farmland Grading rules (TD/T1005-2004) ［ S ］ .2003.
When evaluating factor space and quantize, conventionally evaluation region need to be carried out discretely according to a certain size grid picture dot or vector grid, calculate on this basis and evaluate the factor in the intensity that affects at each grid place.Because land resource quality assessment scope can reach tens of square kilometres conventionally, in order to obtain higher computational accuracy, evaluation region carries out discrete conventionally according to the spacing of 50-100 rice, thereby relates to the data processing of hundreds thousand of grids, and calculated amount is huge.According to current evaluation factor quantification method, on the personal computer of current main-stream configuration, a single evaluation factor space for 1 medium-sized city is quantized to calculate, its process needs 1-2 hour conventionally.And Evaluation for Soil Resources process is usually directed to 10-20 the evaluation factor, its computation process is very consuming time as seen.Therefore, must give full play to the newest fruits of computer software and hardware development, improve counting yield.
(3) parallel computing
Parallel computation (also referred to as high-performance calculation, supercomputing) is the calculating of carrying out under parallel computing platform.Adopt the fundamental purpose of parallel computation to be to improve speed and the scale of computing machine solution problem.Related documents [4]: cypress. the data directory technical research [D] on parallel computing platform. the .2011. of China Science & Technology University is along with the fast development of computer hardware technique, the advanced facility that calculates such as grid, polycaryon processor, cluster, desktop supercomputer, cloud computing successively occurs, for the speed that solves and the efficiency that improve large-scale calculations problem provide important technical support.In addition, the CPU on personal computer also, day by day towards the future development (from double-core, four cores, eight cores to more multinuclear number development) of multinucleation, makes the hardware cost of parallel computation cheaper.On the other hand, the appearance of the 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 that solves and the efficiency of large-scale calculations problem, is the subject matter facing during following program development and science are calculated.
Summary of the invention
For the poor efficiency existing in existing serial land resource quality assessment factor space quantization method, the problem such as consuming time, the present invention is by according to the feature of evaluating the related spatial data of factor quantification, in conjunction with computer hardware feature, design space data decomposition paralleling tactic, fully excavate the calculating potentiality of multi-core computer, improve and evaluate the efficiency that factor space quantizes, shorten working hours.
Technical scheme of the present invention is a kind of parallel land resource quality assessment factor space quantization method, comprises the following steps:
Step 1.1, according to the quantity N of computer CPU, the mode that adopts data laterally to decompose, is divided into N sub regions by evaluation space region;
Step 1.2, N sub regions is distributed to N cpu process, and each cpu process is separated into a sub regions grid of fixed size, and exports separately the discrete results in subregion, discrete results adopts the vector file of shp form to store, and obtains N discrete grid block vector file;
Step 2.1, establishes all soil quality evaluation factors and is divided into M class by spacial influence characteristic, and every class soil quality evaluation factor is stored in respectively in a data layer, obtains M and evaluates factor graph layer;
Step 2.2, is copied into M part by N discrete grid block vector file of step 1 gained, obtains N × M for storing the discrete grid block vector file of evaluating factor space quantized result;
Step 3.1, N × M discrete grid block file distributed to N cpu process by subregion, each cpu process calculates for the treatment of the quantification of the M class soil quality evaluation factor in a sub regions, and each cpu process adopts the communication between MPI implementation process in computation process; In each cpu process, adopt concurrent technique in OpenMP node to open up M thread, each thread carries out respectively a quantification of evaluating factor graph layer and calculates, and gained is evaluated factor quantification result and is deposited respectively corresponding discrete grid block vector file in;
Step 3.2, merges to the M comprising in every sub regions discrete grid block vector file in a file, obtains altogether N file;
Step 3.3, becomes a file by a gained N Piece file mergence in step 3.2, obtains final result of calculation.
And, in step 3.1, while carrying out the quantification calculating of an evaluation factor graph layer on arbitrary thread, arbitrary grid is carried out to following steps,
Step a, calculates respectively the space length between each soil quality evaluation factor in current grid and Evaluation: Current factor graph layer, and finds out the nearest soil quality evaluation factor, is designated as F;
Step b, the scaled index f of acquisition soil quality evaluation factor F, radius of action D,
Step c, calculating soil quality evaluation factor F affects strength S at current grid place, and computing formula is as follows:
Wherein, d is the space length of the current grid of soil quality evaluation factor F distance.
The present invention has simply generally, feature fast, is applicable to carry out on the individual calculus with many CPU, multinuclear, small-sized workstation and computer cluster.The present invention for give full play to current computer hardware calculate potential, shorten the land valuation working time, increasing work efficiency has important practical significance.With respect to the evaluation factor space quantization method of conventional serial, the problem that the present invention mainly solves has: (1) has been designed and has been applicable to the spatial data decomposition strategy that land valuation factor space quantizes: to evaluating the factor, carry out layering, range of value subregion, realized the parallelization of evaluating factor space quantization method; (2) make full use of many CPU, the multinucleation development trend of current computer hardware art, improve greatly counting yield, shorten working hours.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the embodiment of the present invention;
Fig. 2 is the attribute field structure of the discrete grid block vector file of the embodiment of the present invention;
Fig. 3 is the synthetic schematic diagram of the multithreading result of calculation of the embodiment of the present invention.
Embodiment
The parallel land resource quality assessment factor space quantization method flow process of the present invention's design is shown in accompanying drawing 1, can adopt computer software technology to realize automatic operational scheme.Embodiment specific implementation process is as follows:
Step 1.1, according to the quantity N of computer CPU, the mode that adopts data laterally to decompose, is divided into N sub regions by evaluation space region.
If available CPU quantity is N, embodiment resolves into N sub regions by evaluation region, is designated as respectively { n1, n2, n3 ... nN}.
Step 1.2, N sub regions is distributed to N cpu process, and each cpu process is separated into a sub regions grid of fixed size, and exports separately the discrete results in subregion, discrete results adopts the vector file of shp form to store, and obtains N discrete grid block vector file.Shp form is a kind of vector data storage format that internationally famous Geographic Information System (GIS) software manufacturer ESRI company designs, and is the general vector storage format of current area of geographic information, is mainly used in storing the geography targets such as point, line, surface.
Embodiment opens N calculation procedure, and the range information of N sub regions is distributed to N process, and each process is carried out respectively the spatial discretization to subregion.The discretize of the land resource quality assessment ranged space is divided into evaluation region several grids exactly.Grid is less, and computational accuracy is higher, and calculated amount is larger; Otherwise computational accuracy is lower, calculated amount is less.Conventionally when carrying out Evaluation for Soil Resources, adopt the grid of 50*50 or 100*100 rice to carry out discrete to evaluation space region.All subregion in process separately, carry out discrete after, grid result is kept at respectively in independent shp file and is stored.As Fig. 2, the attribute field structure of grid file is wherein as shown in table 1, and example is as table 2:
Table 1
| Field name | Field type | Remarks |
| ID | Int | Record the ID of current grid |
| Line number | Int | The line number of current grid in whole evaluation space region |
| Row number | Int | The row number of current grid in whole evaluation space region |
| Effects of Factors intensity | Float | Certain factor is in the intensity that affects at current grid place |
Table 2
| ID | Line number | Row number | Effects of |
| 1 | 1 | 1 | 98.5 |
| 2 | 1 | 2 | 97.3 |
| 3 | 1 | 3 | 86.1 |
| ...... | ...... | ...... | 78.9 |
Step 2.1, establishes all soil quality evaluation factors and is divided into M class by spacial influence characteristic, and every class soil quality evaluation factor is stored in respectively in a data layer, obtains M data layer.
Embodiment is stored in land resource quality assessment factor data respectively in M figure layer and (is designated as { m1 according to thematic content, m2, m3 ... mM}), each figure layer represents the dissimilar factor, as bank's factor graph layer, hospital's factor graph layer, country fair factor graph layer etc.Evaluation factor graph layer data after layering storage is deposited in shared memory, so that the access of each process.The data preprocessing phase that this step quantizes as parallel land resource quality assessment factor space, can evaluate before factor quantification calculates and complete in advance in execution.Also can classify in advance, directly import classification results while carrying out technical solution of the present invention, those skilled in the art's design software, realizes every class soil quality evaluation factor is stored in respectively to a data layer.
Step 2.2, is copied into M part by N discrete grid block vector file of step 1 gained, obtains N × M for storing the discrete grid block vector file of evaluating factor space quantized result.
In embodiment, the naming rule of each discrete grid block vector file is regional number+evaluation factor type model.For example the grid file of file " n1-m5.shp " by name is used for preserving in the 1st sub regions, the 5th the result of calculation information that the evaluation factor space impact of evaluating in factor graph layer quantizes.
Step 3.1, N × M discrete grid block file distributed to N cpu process by subregion, each cpu process calculates for the treatment of the quantification of the M class soil quality evaluation factor in a sub regions, and each cpu process adopts the communication between MPI implementation process in computation process; In each cpu process, adopt the capable technology of OpenMP multithreading to open up M thread, each thread carries out respectively the quantification of a class soil quality evaluation factor and calculates, and gained is evaluated factor quantification result and is deposited respectively corresponding discrete grid block vector file in.Result of calculation can be saved in the attribute field of corresponding discrete grid block vector file (shp file).MPI, Message Passing Interface, message passing interface, is the basic technology of communicating by letter between process in parallel computation; When multi-process on the large-scale cluster of shared drive is not parallel, can use the communication between this technology implementation process.OpenMP, (Open Multi-Processing) is a set of a set of directiveness annotation for multithread programs design.OpenMP is applicable to the multithreads computing on the multi-core computer of shared drive.
Embodiment starts N calculation procedure, as process in Fig. 11, process 2 ... process N.Each process is responsible for respectively an evaluation factor quantification calculation task of evaluating in subarea.For each process, open up M thread, each thread is responsible for calculating the space quantization calculation task of 1 evaluation factor graph layer in Evaluation: Current subarea simultaneously.Can be considered and need to process N × M sub regions grid chart layer.In each thread units, travel through the mesh object in its corresponding shp file, calculate and evaluate the affect intensity of the factor at each grid cell place, and result of calculation is deposited in the attribute field of grid chart layer correspondence.Wherein the shp file of current thread processing can be searched corresponding shp file according to the file designation rule Auto-matching of formulating in step 2.2.For example, the 5th No. 3 in-process thread is for the treatment of the 3rd the quantification calculation task of evaluating factor graph floor in the 5th sub regions, and the shp file of its read-write is by name " n5-m3.shp ".On each thread, the computing method process of evaluating factor space quantification is as follows:
Step a, calculates respectively the space length between current grid and each soil quality evaluation factor, and finds out the nearest soil quality evaluation factor, is designated as F; The land quality at this grid place is considered to be subject to the impact of soil quality evaluation factor F.
Step b, the scaled index f of acquisition soil quality evaluation factor F, radius of action D.Wherein, the scaled index f of son is for the scale (size) of the reflected appraisal factor self, and span is [0-100].Index is larger, and its impact on land quality is larger.Evaluate the radius of action D of the factor, for representing the spatially maximum magnitude to land resource quality influence of this factor.Radius of action can adopt the methods such as mode based on shortest path distance, Thiessen polygon to divide and calculate.The computing method of f and D have comparatively detailed elaboration in relevant technical regulation and Research Literature, and non-focal point of the present invention, repeat no more herein.
Step c, calculating soil quality evaluation factor F affects strength S at current grid place, and computing formula is as follows:
Wherein, d is the space length of the current grid of soil quality evaluation factor F distance.
Step 3.2, merges to the M comprising in every sub regions discrete grid block vector file in a file, obtains altogether N file.The quantized result of the different factors can be stored in respectively in different attribute fields.
M the evaluation factor space that each calculation procedure is responsible for calculating affects quantized result and deposits discrete grid block vector file and synthesize 1 destination file.For the M in each process shp file, in each file corresponding stored a certain class spacial influence of evaluating the factor quantize result of calculation.Take first file as main, increase M-1 field, by the intensity data that affects in M-1 shp file of residue, according to the position No. of grid, corresponding copies in field corresponding in first file.Carry out after this step, in the shp file in each process, will preserve the space quantization result of M the evaluation factor in corresponding evaluation subregion.Result of calculation composition principle on multithreading is shown in accompanying drawing 3, point thread i1, i2 in process i ... iM, respectively to the 1st evaluation factor graph layer, the 2nd evaluation factor graph layer in i sub regions ... evaluating factor graph layer for M quantizes, obtain the factor quantification result of i sub regions, wherein the achievement data structure of multithreading result of calculation after synthetic can be in Table 3, and the data instance after multithreading is synthetic can be in Table 4.
Table 3
Table 4
| ID | Line number | Row number | F1 | F2 | F3 | F4 | ...... | |
| 1 | 1 | 1 | 98.5 | 73.5 | 84.7 | 88.1 | 90.2 | 60.3 |
| 2 | 1 | 2 | 97.3 | 81.9 | 89.8 | 78.3 | 83.6 | 84.6 |
| 3 | 1 | 3 | 86.1 | 92.7 | 69.5 | 63.6 | 77.2 | 53.8 |
| ...... | ...... | ...... | 78.9 | 79.4 | 57.9 | 40.3 | 92.1 | 90.3 |
Wherein, if to the 1st evaluation factor graph layer, the 2nd evaluation factor graph layer, the 3rd evaluation factor graph layer, the 4th evaluation factor graph layer in i sub regions ... evaluate the nearest soil quality evaluation factor F finding when factor graph layer quantizes, be designated as the factor 1, the factor 2, the factor 3, the factor 4 for M ... factor M.F1, F2, F3, F4 ... FM is respectively to the 1st evaluation factor graph layer, the 2nd evaluation factor graph layer, the 3rd evaluation factor graph layer, the 4th evaluation factor graph layer in i sub regions ... evaluate factor graph layer for M and quantize the intensity that affects obtaining.
Step 3.3, becomes a file by a gained N Piece file mergence in step 3.2, obtains final result of calculation.
Embodiment synthesizes final complete result of calculation by the result of calculation in N process.Take first node as host node, the data Replica in N-1 shp file of residue can be obtained to the result of calculation that in whole evaluation region, the impact of M evaluation factor space quantizes in first node.
Specific embodiment described herein is only to the explanation for example of the present invention's spirit.Those skilled in the art can make various modifications or supplement 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 (2)
1. a parallel land resource quality assessment factor space quantization method, is characterized in that, comprises the following steps:
Step 1, to the evaluation space region discretize that walks abreast, comprises following sub-step,
Step 1.1, according to the quantity N of computer CPU, the mode that adopts data laterally to decompose, is divided into N sub regions by evaluation space region;
Step 1.2, N sub regions is distributed to N cpu process, and each cpu process is separated into a sub regions grid of fixed size, and exports separately the discrete results in subregion, discrete results adopts the vector file of shp form to store, and obtains N discrete grid block vector file;
Step 2, land resource quality assessment, because of sublayering, comprises following sub-step,
Step 2.1, establishes all soil quality evaluation factors and is divided into M class by spacial influence characteristic, and every class soil quality evaluation factor is stored in respectively in a data layer, obtains M and evaluates factor graph layer;
Step 2.2, is copied into M part by N discrete grid block vector file of step 1 gained, obtains N × M for storing the discrete grid block vector file of evaluating factor space quantized result;
Step 3, land resource quality assessment factor parallel spatial quantizes, and comprises following sub-step,
Step 3.1, N × M discrete grid block vector file distributed to N cpu process by subregion, each cpu process calculates for the treatment of the quantification of the M class soil quality evaluation factor in a sub regions, and each cpu process adopts the communication between message passing interface MPI implementation process in computation process; In each cpu process, adopt concurrent technique in OpenMP node to open up M thread, each thread carries out respectively a quantification of evaluating factor graph layer and calculates, and gained is evaluated factor quantification result and is deposited respectively corresponding discrete grid block vector file in;
Step 3.2, merges to the M comprising in every sub regions discrete grid block vector file in a file, obtains altogether N file;
Step 3.3, becomes a file by a gained N Piece file mergence in step 3.2, obtains final result of calculation.
2. the land resource quality assessment factor space quantization method walking abreast as claimed in claim 1, is characterized in that: in step 3.1, while carrying out the quantification calculating of an evaluation factor graph layer on arbitrary thread, arbitrary grid is carried out to following steps,
Step a, calculates respectively the space length between each soil quality evaluation factor in current grid and Evaluation: Current factor graph layer, and finds out the nearest soil quality evaluation factor, is designated as F;
Step b, the scaled index f of acquisition soil quality evaluation factor F, radius of action D,
Step c, calculating soil quality evaluation factor F affects strength S at current grid place, and computing formula is as follows:
Wherein, d is the space length of the current grid of soil quality evaluation factor F distance.
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