CN110413666A - A kind of multi-source heterogeneous data integration method of farmland quality - Google Patents
A kind of multi-source heterogeneous data integration method of farmland quality Download PDFInfo
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Abstract
The invention discloses a kind of multi-source heterogeneous data integration methods of farmland quality, comprising: changes assessment data with obtaining farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality；Farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality are changed into assessment data, conversion process is carried out according to unified database association rule, the multi-source heterogeneous data integration model based on Spatial Data Modeling standard criterion GML is constructed, and is managed collectively by data management system；Overall merit is carried out to farmland quality data by contribution rate method.The invention proposes a kind of multi-source heterogeneous data integration models of the farmland quality based on GML, utilize the multi-source heterogeneous Data Integration process of the model, the data such as MapGIS data, ArcGIS data, picture grid are converted to unified GML data format, thus easily and effectively integrated and shared according to integrated rule in a network environment；Farmland quality data normalization is pushed, to improve data analysis application efficiency.
Description
Technical field
The present invention relates to quality management of cultivated land technical fields, and it is whole to more particularly relate to a kind of multi-source heterogeneous data of farmland quality
Conjunction method.
Background technique
Quality management of cultivated land is one of core content of land management, and tightening quality control is returned in land management essence
The objective requirement of appearance.Wherein, the management for reinforcing farmland quality has very heavy for improving plough production capacity, Ensuring Food Safety
The meaning wanted.China requires to adhere to most stringent of Conservation Institutions of Cultivated Land and most stringent of system of saving the area, and puts forth effort to reinforce arable land
Arable land red line is firmly observed in quantity, quality, ecology " Trinity " protection, and promotion formation protection is more strong, it is more suitable to execute
Freely, more efficient cultivated land protection new frame is managed.
Currently, the existing farmland quality data type in China is more.The sampling point data of existing reflection soil physico-chemical property,
There are the planar data for reflecting regional farmland quality；The difference of different industries and department due to application and demand, farmland quality data
There is also larger differences.Such as agricultural and the monitoring point in rural area portion are the monitoring indexes using regional economy characteristic as foundation of layouting
Stress soil physico-chemical property；The monitoring point of Environmental Protection Department stresses soil pollutant using administrative law enforcement site as foundation of layouting
Monitoring report；The standard site that the monitoring point of Ministry of Natural Resources is set up with farming land quality grading is foundation of layouting, monitoring
Content includes soil environment index, orographic factor and the water project situation of farming land, stresses the economic value and life that reflect farming land
Production level etc..Standard is different when due to monitoring point arrangement, and monitored data analysis is different, and in the quantity and precision of monitoring network
On there are larger difference, be difficult to accomplish that inter-sectional Data Integration is reported and shared.In addition, existing on the monitoring content of part certain
Repeatability causes the waste of supervision resource.Therefore, it needs to integrate the farmland quality data resource of multi-source, establishes system
One monitoring system, to make to monitor sampling point quantity configuration optimization, monitoring content is more comprehensively efficient.The integration of farmland quality big data
The inter-trade data fusion such as territory, agricultural and environmental protection is helped to realize, complete shared data set or rasterizing atlas is formed, subtracts
Few repetitive operation, improves farmland quality data precision.It is whole with the cross-cutting data such as meteorology, remote sensing, environment, national economy simultaneously
Close, establish one with farmland quality safety and protection for core include mass data is effectively managed, efficient analysis and
Easy-to-use comprehensive big data system can be used, standardization, Visualization Service are provided, China's land arrangement potential pattern structure can be promoted
It builds, ensures national food security.
Existing farmland quality data are related to sampling point, peasant household, small towns etc. from agricultural, territory, environmental protection and each department of statistics
Different scale, since data production, storage, the mode called have diversity, there has been no a kind of data integration methods at present, will
Multi-source farmland quality data carry out integration application, to influence the efficient utilization of farmland quality big data.It is summed up, matter of ploughing
Amount big data integration is primarily present following several problems:
1. data production method diversity.
The data means of production multiplicity that each department uses at present, such as remote sensing technology, GPS technology, survey, field exploring
Deng.The different data means of productions uses different software systems and data format.In addition, the data management software used is not
Together, the difficulty of data integration can be made to increase.Data production unit is different, the classification of same class data classification, attribute coding, data knot
Structure, data format etc. are also different.
2. data spatial resolution is different.
When collecting farmland quality data, the spatial resolution of collected data source and the spatial resolution of target data source are poor
It is different bigger, Data Matching or difficulty and uncertain bigger is integrated, the workload for eliminating data collision is also bigger.Arable land at present
Qualitative data spatial resolution differs greatly, scale bar Wan Junyou from 1:5000 to 1:50, vector data and raster data, face
Shape and dotted data have, and it is larger to integrate difficulty.
3. data call mode diversity
Currently, the calling of farmland quality related data is dependent on specific GIS software, as ArcGIS, MapGIS,
SuperMap etc..Different GIS software data call read-write modes are different, and data can only be in specific software or specific business system
It is used in system, once providing external use, can not just carry out complete data conversion.This is also that multi-source heterogeneous spatial data is integrated
The difficult point of analysis.
4. the time, there are larger differences
With the variation of time gradual change can occur for farmland quality, and the data different times of same sampling point are also different.
Current all types of farmland quality data need to handle data well due to the difference of acquisition time when carrying out arable land Data Integration
The problem of timing and data timely update.
Summary of the invention
The embodiment of the present invention provides a kind of multi-source heterogeneous data integration method of farmland quality, to solve above-mentioned background technique
The problem of.
The embodiment of the present invention provides a kind of multi-source heterogeneous data integration method of farmland quality, comprising:
Change assessment data with obtaining farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality；
Farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality are changed into assessment data, according to unification
Database association rule carries out conversion process, constructs the multi-source heterogeneous data integration model based on Spatial Data Modeling standard criterion GML,
And it is managed collectively by data management system；
Overall merit is carried out to farmland quality data by contribution rate method.
Further, the grading factors of the farmland quality grade data include: topsoil quality, the content of organic matter,
Ensurance probability of irrigation water, soil acidity or alkalinity, terrain slope, barrier layer are away from earth's surface depth, profile pattern, drainage condition.
Further, the farmland quality grade data type include: National Nature etc., country utilize etc., national economy
Deng.
Further, the evaluation points of the natural Productivity Evaluation of Cultivated Land data include: geomorphic type, landform positions, height above sea level,
Table gravel degree, effective soil layer thickness, quality configuration, ensurance probability of irrigation water, full nitrogen, available phosphorus, available potassium, obstacle channel type, obstacle
Layer position, barrier layer thickness.
Further, it is carried out using different observations of the Delphi method to the evaluation points of the natural Productivity Evaluation of Cultivated Land data
Marking, determines the weight of the natural Productivity Evaluation of Cultivated Land data evaluation factor；It specifically includes:
Cultivated-land composite index is determined using index and method, model formation is as follows:
IFI=∑ Fi×Ci(i=1,2,3 ..., n)
In formula: IFI represents cultivated-land composite index；FiFor i-th of factor value；CiFor the combining weights of i-th of factor；
In the cultivated land resource management information system of county domain, membership function model and level point are imported in thematic evaluation module
Model is analysed, Potential Productivity of Cultivated Land Function of Evaluation is selected to carry out the calculating of cultivated-land composite index；Referred to according to cultivated-land synthesis
Several changing rules is evaluated in cultivated land resource management system using accumulation curve staging, according to the prominent of the slope of curve
Height simultaneously determines the number of grade in conjunction with actual conditions and divides the critical point of composite index.
Further, change to the farmland quality farming land topsoil in assessment data to participate in evaluation and electing index, select location
The geologic setting value of band makees standard, after rejecting abnormalities data, by the 20% of data, 40%, 60%, 80% order statistics
Amount is divided into 5 grades, as grade scale；
Change to the farmland quality Soil Fertility Quality evaluation in assessment data, according to quality investigaton of cultivated lands soil nutrient and
PH grade scale is classified the measured value of soil nutrient index；
Change to the farmland quality single-factor soil environment quality assessment in assessment data, according to standard of soil environment quality
It is classified；
Change to the farmland quality assessment data in soil environment health element overall merit, choose Hg, Cd, Pb, As,
Cu, Zn, Cr, Ni8 Heavy Metallic Elements are evaluation index, calculate composite index using Nei Meiluofa, are carried out according to composite index
Classification.
Further, described that farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality are changed into assessment number
According to according to unified database association rule progress conversion process, building is based on the multi-source heterogeneous of Spatial Data Modeling standard criterion GML
Data integration model, and be managed collectively by data management system；It specifically includes:
By MapGIS formatted data, the Shape format of ArcGIS, GeoDatabase formatted data, SuperMap format
Data storage is in database server；
By MapGIS formatted data, the Shape format of ArcGIS, GeoDatabase formatted data, SuperMap format
Data are converted into unified Shape format, generate standardized shapefile data, Yi Jitong by formulating database association rule
It crosses corresponding GML generator and is converted to GML formatted data, and be managed collectively by data management system；
Data management system externally provides the data access interface of standard and application program interacts, to data processing request
It is parsed, and parsing result is sent to each database server；Database server receives processing order, makes corresponding
Response, the data after format transformation are returned to by data management system by GML generator；Data management system is to returning the result number
It is believed that breath is integrated, the integrated and analysis of data is realized, and client application is returned to GML format.
Further, described that overall merit is carried out to farmland quality data by contribution rate method；It specifically includes:
By constructing farmland quality overall merit contribution rate computation model, farmland quality synthesis is calculated according to different purposes and is commented
Valence index:
POverall merit=a × PPoint etc.+b×PSoil fertility+c×PGround
Wherein, POverall meritFor farmland quality comprehensive evaluation index；PPoint etc.For utilization class index national in former post-boost control；PSoil fertility
For total score Value Data in former natural Productivity Evaluation of Cultivated Land result；PGroundEnvironmental index in achievement is assessed for original placeization；A is former post-boost control
The contribution coefficient of middle country's utilization class index；B is the contribution coefficient of total score Value Data in former natural Productivity Evaluation of Cultivated Land result；C is original
Groundization assesses the contribution coefficient of environmental index in achievement.
The embodiment of the present invention provides a kind of multi-source heterogeneous data integration method of farmland quality to be had compared with prior art
Beneficial effect is as follows:
The present invention establishes unified data standard specification, develops data integration and management tool based on standard criterion, branch
Hold the sustainable acquisition of data；Data, the standardization of interface, data quality control System Construction and the multi-source number based on unified standard
According to integration；On the basis of analyzing geographical markup language (GML) format character, it is more to propose a kind of farmland quality based on GML
Source Model of Heterogeneous Data Integration.Using the multi-source heterogeneous Data Integration process of the model, by MapGIS data, ArcGIS number
Unified GML data format is converted to according to data such as, picture grids, thus in a network environment easily and effectively according to integrated rule
Ground is integrated and is shared；By advanced and mature big data storage and processing technique, integration and the processing various farmland qualities in inside and outside
Related data, then in conjunction with expertise data, sensing data and other monitoring data etc., building farmland quality big data is flat
Platform reduces data redundancy and unnecessary data, farmland quality data normalization is pushed, to improve data analysis application efficiency.
Detailed description of the invention
Fig. 1 is the farmland quality big data multi-source heterogeneous Data Translation model provided in an embodiment of the present invention based on GML；
Fig. 2 is farmland quality big data platform schematic diagram provided in an embodiment of the present invention；
Fig. 3 is farmland quality comprehensive evaluation result provided in an embodiment of the present invention (factor method) and former Comparative result is analyzed；
Fig. 4 is farmland quality comprehensive evaluation result provided in an embodiment of the present invention (contribution rate method) and former Comparative result point
Analysis.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Referring to Fig. 1~4, the embodiment of the present invention provides a kind of multi-source heterogeneous data integration method of farmland quality, this method packet
It includes:
Step 1, change assessment data with obtaining farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality.
Step 2, farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality are changed into assessment data, according to
Unified database association rule carries out conversion process, constructs the multi-source heterogeneous data set based on Spatial Data Modeling standard criterion GML
Unified management is carried out at model, and by data management system
Step 3, overall merit is carried out to farmland quality data by contribution rate method.
For being described as follows for above-mentioned steps 1:
It selects Counties to carry out for research, and then carries out provincial popularization and application.Survey region is set in Henan Province
XX county-level city, XX county-level city is located in the Yellow River, downstream boundary, conquers east to Henan former zone of transition positioned at the hills Yu Xi, geographical
Coordinate is conveniently situation and spy between 113 ° 20 ' 40 of east longitude " -113 ° 24 ' 10 ", 34 ° 45 ' 08 of north latitude " -34 ° 48 ' 22 "
Very, it is higher to account for the ratio in the structure of agricultural production for Farming.According to XX county-level city Land-use System achievement in 2015,
9.43 ten thousand hectares of the soil gross area of XX county-level city 2015, wherein 4.13 ten thousand hectares of arable land.Rely on current XX county-level city existing
Each department, all types of farmland quality data, using the Data Integration in big data, to the multi-source heterogeneous data of farmland quality
It is integrated, constructs farmland quality big data platform.
(1) farmland quality grade achievement
According to " farming land quality grading regulation (GB/T 28407-2012) ", XX county-level city standard cropping system is that the winter is small
Wheat-summer corn yields two crops a year, and benchmark crop is winter wheat, and formulations crop is summer corn, in the Index areas of division, first class index
The Loess Plateau Region directly under the jurisdiction of a municipal government at county level area XX, the two-level index area XX western hilly area in Henan directly under the jurisdiction of a municipal government at county level, grading factors and weight table are shown in
Table 1.
1 XX county-level city Farmland Grading factor of table and weight table
According to " farming land quality grading regulation (GB/T 28407-2012) ", XX county-level city farmland quality etc. is calculated
Other result is as follows: XX county-level city National Nature equal distribution is in 6-11 etc., and country is using equal distribution in 6-11 etc., national economy equal part
Cloth is in 5-10 etc..
(2) natural Productivity Evaluation of Cultivated Land data
Selection according to " Soil fertility investigation of cultivated land and quality evaluation technical regulation " (NY/T1634-2008) evaluation index is former
Then, in conjunction with the shallow massif mound of XX county-level city, with a varied topography, irrigation conditions difference is big, soil type is various, the different distribution of nutrient levels
Unequal current conditions summarize by the repeated multiple times tradeoff of expert group under the guidance for saving station expert, landforms have finally been determined
Type, landform positions, height above sea level, earth's surface gravel degree, effective soil layer thickness, quality configuration, ensurance probability of irrigation water, full nitrogen, available phosphorus, speed
13 effect potassium, obstacle channel type, barrier layer position, barrier layer thickness factors are XX county-level city natural Productivity Evaluation of Cultivated Land index, and adopt
With Delphi method, i.e. expert graded, organizes expert gives a mark to each evaluation index difference observation, is then repeatedly returned
It receives, feed back and summarizes, obtain the weight of each evaluation index.
Each evaluation points weight definitive result table of 2 XX county-level city productivity evaluation of table
The composite index in arable land is determined with index and Fa Lai, model formation is as follows:
IFI=∑ Fi×Ci(i=1,2,3 ..., n)
In formula: IFI represents cultivated-land composite index；FiFor i-th of factor value；CiFor the combining weights of i-th of factor.
Specific operation process: in county domain cultivated land resource management information system (CLRMIS), in " special topic evaluation " module
Membership function model and Analytic Hierarchy Process Model are imported, then selects " Potential Productivity of Cultivated Land evaluation " function to carry out cultivated-land comprehensive
The calculating of index.Finally according to the changing rule of composite index, accumulation curve staging is used in cultivated land resource management system
It is evaluated, the number of grade is determined according to the catastrophe point (inflection point) of the slope of curve and in conjunction with city's actual conditions and is divided comprehensive
XX county-level city city's cultivated-land is divided into Pyatyi by the critical point of hop index altogether.
(3) natural Productivity Evaluation of Cultivated Land data
Change evaluation work with studying the land quality in area to start in March, 2008, in January, 2009 completes comprehensively.Using net
Lattice method, scale bar at county level are 1:5 ten thousand.According to Henan Province's land quality GEOCHEMICAL SURVEY achievement data, the farming land in area is studied
Topsoil participates in evaluation and electing index, and the geologic setting value of location band is selected to make standard, after rejecting abnormalities data, mainly presses data
20%, 40%, 60%, 80% order statistic be divided into 5 grades, as grade scale, wherein available phosphorus, available potassium press Henan Province
Overall survey of soil standard executes.Soil Fertility Quality evaluation is according to Farmland Quality in Henan Province investigation soil nutrient and pH grade scale
The measured value of soil nutrient index is classified.Single-factor soil environment quality assessment is in land quality Geochemical Assessment
It is classified according to standard of soil environment quality.Soil environment health element overall merit be choose Hg, Cd, Pb, As, Cu,
8 Heavy Metallic Elements such as Zn, Cr, Ni are evaluation index, calculate composite index with Nei Meiluofa, are divided according to composite index
Grade.
(4) three kinds of data difference analysis
Since farmland quality grade data and cultivated-land data are using arable land figure spot as minimum unit, quantity is relatively more,
It is difficult to carry out relatively.Therefore by counting each administrative village country utilization class index average value, arable land by unit of administrative village
Soil fertility mean scores and soil environment health element overall merit mean scores carry out correlation analysis.Analyzing result indicates: administrative
Country, village utilization class index and cultivated-land mean scores are in significant related (r2=0.2242, p < 0.01n=283), but two
Data and soil environment health element overall merit score value are not significant related, main reason is that farmland quality grade data and
Cultivated-land data have certain repetition in evaluation index, but dramatically different with soil environment health assessment indicators, soil ring
Border health assessment focuses on the influence in terms of soil pollution more, and land quality Geochemical Assessment scale bar is smaller, entire county
Otherness in domain is smaller.
For being described as follows for above-mentioned steps 2:
Based on the considerations of making full use of available data, reducing repetitive operation, graph required for this paper and database money
Material is all to utilize on going result, and no longer carry out special data survey work.After on going result is uniformly processed, directly answer
It is evaluated for integrating.Three kinds of outcome datas graph element, in terms of there are significant difference (table 3), in order to can
It is enough reflected on same figure, has the premise of integration, first have to handle three kinds of data, unified figure rule, data
Library rule.
3 three kinds of farmland quality data characteristics of table
Farmland quality grade achievement, natural Productivity Evaluation of Cultivated Land achievement and groundization are assessed into achievement, formulate unified database rule
Then, database includes following field:
4 database standard field of table and format
GML (Geography Markup Language, Spatial Data Modeling standard criterion) is OGC (Open
Geospatial Consortium develops GIS-Geographic Information System association) formulate based on standing on any manufacturer, any in XML
The geographic information encoding standard of platform, transmission, storage and publication for geography information.Its with it is simple, open, cross-platform,
The characteristics such as be readily inspected and convert, spatial data and attribute data can be combined together, by vector data and raster data melt for
One can be used http protocol and carry out teletransmission, it is easy to accomplish the dynamic integrity of data.Multi-source heterogeneous data are converted to unification
GML data format, can easily and effectively be integrated according to integrated rule in a network environment and shared.By proposing a base
In the multi-source heterogeneous data integration model of GML/KML, by Mapgis formatted data, ArcGIS Shape format,
GeoDatabase formatted data, SuperMap formatted data etc. can be converted to GML lattice by corresponding GML generator
Formula data, and be managed collectively by data management system, realize somewhere administrative division data (MapGIS format) and soil benefit
Integrated analysis is superimposed with data (ArcGIS format).
For being described as follows for above-mentioned steps 3:
By using scheduling theory, natural Productivity Evaluation of Cultivated Land and ground appraisal procedure is divided, establishing qualitative and quantitative integration evaluation
Index system makes full use of the three kinds of data integrated, realizes the overall merit of farmland quality.The method mainly taken has factor
Method and contribution rate method.Wherein factor method, by establishing new comprehensive index system, is reappraised using original basic data
Farmland quality；And contribution rate method is the difference by three kinds of achievements depending on the application, assigns contribution rate respectively, so that being formed with purposes is to lead
To Evaluation for cultivated-land achievement.
(1) based on the farmland quality overall merit of factor method
When carrying out the building of farmland quality overall evaluation system using factor method, it then follows following principle (1) scientific principle: comment
Valence index system should choose the Main Factors that can most reflect farmland quality on the basis of scientific accurate；(2) dominance principle:
Comprehensive benefit is restricted by influence factors such as nature, society, economy, in numerous factors, the mechanism of the various factors and
The mode of action is different.Therefore, it should select representative, can directly reflect that the dominance of farmland quality main feature refers to
Mark；(3) operability principle: the design of index system, should consider as far as possible data easy obtaining property and can collectivity, follow letter
Principle clean, conveniently, effectively, practical；(4) comprehensive principle: all Multi-environment factors considered are measured comprehensively, are integrated
Analysis and evaluation, single analysis can be made by accomplishing is convenient for making comprehensive analysis again.
Farmland quality System of Comprehensive Evaluation see the table below.As can be seen from Table 5, Factor system selection relate to weather,
Topography and geomorphology, land occupation condition, 6 broad aspect of moisture condition, soil fertility and soil pollution, and the characteristics of according to three kinds of data, choosing
Select the corresponding factor.Then according to analytic hierarchy process (AHP) (AHP) the step of, the expert in relation to being engaged in the field, binding are consulted
Region farmland quality feature, establishes one, two, three evaluation unit from destination layer to indicator layer, then finds out in sequence each
Each index weights in evaluation unit.
Farmland quality overall evaluation system of the table 5 based on factor method
It is final to evaluate according to the weight of each factor in three kinds of data factor attributes and county domain farmland quality overall evaluation system
XX county-level city arable land comprehensive quality.Comprehensive quality point is ploughed from 0.0782-0.9463 by XX county-level city, using nature knick point method,
Farmland quality can be divided into 5 grades.
It is total by counting farmland quality comprehensive evaluation result, national utilization class index and cultivated-land using administrative village as unit
Then index utilizes linear regression analysis, obtain total score (factor method) and former national utilization class index and soil fertility combined index
Correlation.The farmland quality overall merit result and former farmland quality grade data and cultivated-land data calculated using factor method
Significant correlation is presented.Illustrate that farmland quality overall merit result can reflect the distribution trend of above two result；In addition from table 6
As can be seen that the standard error of farmland quality comprehensive evaluation result and national utilization class index is lower than soil fertility combined index, the side of explanation
Journey fitting degree wants slightly higher, and reason is that the farmland quality grade Factor Weight selected in factor method index system is larger.
6 farmland quality comprehensive evaluation result of table (factor method) linear regression analysis table
(2) the farmland quality overall merit based on contribution rate
By constructing farmland quality overall merit contribution rate computation model, farmland quality synthesis is calculated according to different purposes and is commented
Valence index:
POverall merit=a × PPoint etc.+b×PSoil fertility+c×PGround
Wherein, POverall meritFor farmland quality comprehensive evaluation index；PPoint etc.For utilization class index national in former post-boost control；PSoil fertility
For total score Value Data in former natural Productivity Evaluation of Cultivated Land result；PGroundEnvironmental index in achievement is assessed for original placeization；A is former post-boost control
The contribution coefficient of middle country's utilization class index；B is the contribution coefficient of total score Value Data in former natural Productivity Evaluation of Cultivated Land result；C is original
Groundization assesses the contribution coefficient of environmental index in achievement.The reason is that, if value is to utilize grade, soil fertility rank and environment grade
Although comprehensive evaluation index can be directly calculated, calculating is easier, because utilizing grade, soil fertility rank and environment grade
All it is integer grade, because by weights influence, it can only be decimal that grade, which is calculated, therefore, will lead to error increase.As a result table
It is bright, for the opposite error using primitive state utilization class index, soil fertility score value and environmental index, utilize other error such as integer
It is bigger.
The determination of factor contribution ratio is very crucial.Common hepjalus gonggaensis larvae model has: Multivariate Normal homing method, Ke
Cloth-Paul H. Douglas production function method.Multivariate Normal homing method is used for reference herein, determines contribution rate using least square method.By
Coefficient can be determined depending on the application in contribution rate, therefore when carrying out farmland quality overall merit using contribution rate, if partially
When being managed to agricultural production, then the contribution rate of P soil fertility is properly increased, final farmland quality comprehensive scores are calculated.
It is final to evaluate XX county-level city arable land comprehensive quality according to three kinds of data primitive attributes and respective contribution rate.It utilizes
Contribution rate method calculates XX county-level city arable land comprehensive quality point from 0.1266-0.9510, using nature knick point method, can will plough
Quality is divided into 5 grades.
By utilizing linear regression analysis, obtains total score (contribution rate method) and always refer to former national utilization class index and soil fertility
Several correlations.The farmland quality overall merit result and former farmland quality grade data and cultivated-land calculated using the method for weighting
Significant correlation is presented in data.Illustrate that farmland quality overall merit result (contribution rate method) can reflect the distribution of above two result
Trend；In addition as can be seen from Table 7, farmland quality comprehensive evaluation result (contribution rate method) and the standard error of soil fertility combined index are wanted
Significantly lower than national utilization class index, the standard error also than being calculated using factor method is low, and reason is in contribution rate
Calculating process in, due to being biased to agricultural production management, the contribution rate of cultivated-land wants slightly higher.
7 farmland quality comprehensive evaluation result of table (contribution rate method) linear regression analysis table
In conclusion the present invention uses the multi-source heterogeneous data integration model of farmland quality based on GML/KML, will be distributed over
Not commensurate, the multi-source heterogeneous data based on the different GIS softwares such as MapGIS, ArcGIS are converted to unified KML formatted data,
It realizes the integrated analysis of multi-source heterogeneous data and shares.Using this method, somewhere administrative division data (MapGIS is realized
Format) and land use data (ArcGIS format) superposition integrated analysis.The present invention utilize three kinds of stackable data, using because
Two methods of plain method and contribution rate method realize the overall merit of farmland quality data.Evaluation result shows that factor method passes through recombination
Assessment indicator system calculates new combined index, and combined index can preferably reflect the true distribution characteristics of former data, realizes a variety of plough
The integration of geological measuring data, but due to assessment indicator system to be rebuild, need certain professional knowledge；Contribution approach is directly applied,
The contribution rate that various factors is determined according to purposes eliminates and the complicated link such as constructs index system, determines weight, has higher
Operability.
Disclosed above is only several specific embodiments of the invention, and those skilled in the art can carry out the present invention
Various modification and variations without departing from the spirit and scope of the present invention, if these modifications and changes of the present invention belongs to the present invention
Within the scope of claim and its equivalent technologies, then the present invention is also intended to include these modifications and variations.
Claims (8)
1. a kind of multi-source heterogeneous data integration method of farmland quality characterized by comprising
Change assessment data with obtaining farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality；
Farmland quality grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality are changed into assessment data, according to unified data
Library rule carries out conversion process, constructs the multi-source heterogeneous data integration model based on Spatial Data Modeling standard criterion GML, and lead to
Data management system is crossed to be managed collectively；
Overall merit is carried out to farmland quality data by contribution rate method.
2. the multi-source heterogeneous data integration method of farmland quality as described in claim 1, which is characterized in that described farmland quality etc.
The grading factors of other data include: topsoil quality, the content of organic matter, ensurance probability of irrigation water, soil acidity or alkalinity, terrain slope,
Barrier layer is away from earth's surface depth, profile pattern, drainage condition.
3. the multi-source heterogeneous data integration method of farmland quality as described in claim 1, which is characterized in that described farmland quality etc.
Other data type include: National Nature etc., country utilize etc., national economy etc..
4. the multi-source heterogeneous data integration method of farmland quality as described in claim 1, which is characterized in that the cultivated-land is commented
The evaluation points of valence mumber evidence include: geomorphic type, landform positions, height above sea level, earth's surface gravel degree, effective soil layer thickness, quality configuration,
Ensurance probability of irrigation water, full nitrogen, available phosphorus, available potassium, obstacle channel type, barrier layer position, barrier layer thickness.
5. the multi-source heterogeneous data integration method of farmland quality as claimed in claim 4, which is characterized in that use Delphi method pair
The different observations of the evaluation points of the natural Productivity Evaluation of Cultivated Land data are given a mark, and determine that the natural Productivity Evaluation of Cultivated Land data are commented
The weight of the valence factor；It specifically includes:
Cultivated-land composite index is determined using index and method, model formation is as follows:
IFI=∑ Fi×Ci(i=1,2,3 ..., n)
In formula: IFI represents cultivated-land composite index；FiFor i-th of factor value；CiFor the combining weights of i-th of factor；
In the cultivated land resource management information system of county domain, membership function model and step analysis mould are imported in thematic evaluation module
Type selects Potential Productivity of Cultivated Land Function of Evaluation to carry out the calculating of cultivated-land composite index；According to cultivated-land composite index
Changing rule is evaluated in cultivated land resource management system using accumulation curve staging, according to the catastrophe point of the slope of curve
And the number of grade is determined in conjunction with actual conditions and divides the critical point of composite index.
6. the multi-source heterogeneous data integration method of farmland quality as described in claim 1, which is characterized in that
Change to the farmland quality farming land topsoil in assessment data to participate in evaluation and electing index, selects the geological environment back of location band
Scape value makees standard, after rejecting abnormalities data, is divided into 5 grades by the 20% of data, 40%, 60%, 80% order statistic, as point
Grade standard；
Change to the farmland quality Soil Fertility Quality evaluation in assessment data, according to quality investigaton of cultivated lands soil nutrient and pH points
Grade standard is classified the measured value of soil nutrient index；
Change to the farmland quality single-factor soil environment quality assessment in assessment data, is carried out according to standard of soil environment quality
Classification；
Change to the farmland quality assessment data in soil environment health element overall merit, choose Hg, Cd, Pb, As, Cu, Zn,
Cr, Ni8 Heavy Metallic Elements are evaluation index, calculate composite index using Nei Meiluofa, are classified according to composite index.
7. the multi-source heterogeneous data integration method of farmland quality as described in claim 1, which is characterized in that described by farmland quality
Change assessment data to grade data, natural Productivity Evaluation of Cultivated Land data and farmland quality, is converted according to unified database association rule
Processing, construct the multi-source heterogeneous data integration model based on Spatial Data Modeling standard criterion GML, and by data management system into
Row unified management；It specifically includes:
By MapGIS formatted data, the Shape format of ArcGIS, GeoDatabase formatted data, the storage of SuperMap formatted data
There are in database server；
MapGIS formatted data, the Shape format of ArcGIS, GeoDatabase formatted data, SuperMap formatted data are turned
Unified Shape format is turned to, generates standardized shapefile data by formulating database association rule, and by corresponding
GML generator be converted to GML formatted data, and be managed collectively by data management system；
Data management system externally provides the data access interface of standard and application program interacts, and carries out to data processing request
Parsing, and parsing result is sent to each database server；Database server receives processing order, makes corresponding sound
It answers, the data after format transformation is returned to by data management system by GML generator；Data management system is believed data are returned the result
Breath is integrated, and realizes the integrated and analysis of data, and returns to client application with GML format.
8. the multi-source heterogeneous data integration method of farmland quality as described in claim 1, which is characterized in that described to pass through contribution rate
Method carries out overall merit to farmland quality data；It specifically includes:
By constructing farmland quality overall merit contribution rate computation model, farmland quality overall merit is calculated according to different purposes and is referred to
Number:
POverall merit=a × PPoint etc.+b×PSoil fertility+c×PGround
Wherein, POverall meritFor farmland quality comprehensive evaluation index；PPoint etc.For utilization class index national in former post-boost control；PSoil fertilityFor original
Total score Value Data in natural Productivity Evaluation of Cultivated Land result；PGroundEnvironmental index in achievement is assessed for original placeization；A is former post-boost control China
The contribution coefficient of family's utilization class index；B is the contribution coefficient of total score Value Data in former natural Productivity Evaluation of Cultivated Land result；C is original place
Assess the contribution coefficient of environmental index in achievement.
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| CN115266612A (en) * | 2022-07-27 | 2022-11-01 | 福建农林大学 | Southern hilly area cultivated land available phosphorus drawing method based on high-resolution environment variable |
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