CN107423504A - Based on the hilly area Evaluation of Land Readjustment Potentiality method for improving enabling legislation - Google Patents

Based on the hilly area Evaluation of Land Readjustment Potentiality method for improving enabling legislation Download PDF

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CN107423504A
CN107423504A CN201710599917.1A CN201710599917A CN107423504A CN 107423504 A CN107423504 A CN 107423504A CN 201710599917 A CN201710599917 A CN 201710599917A CN 107423504 A CN107423504 A CN 107423504A
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王大国
罗斌
郑雪平
徐兵
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Southwest University of Science and Technology
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Abstract

The invention discloses a kind of based on the hilly area Evaluation of Land Readjustment Potentiality method for improving enabling legislation, establish hilly area exploiting potential for arable land model, propose improved FAHP Entropy enabling legislations simultaneously, and after using compatibility verifying its superiority, hilly area Evaluation of Land Readjustment Potentiality model measure layer index weights are calculated, and Cultivated Land Consolidation Potential composite index is have studied from comprehensive evaluation.The present invention enters row interpolation classification to Arable Land Potential composite index using Arcgis softwares simultaneously, draws the distribution situation of Arable Land Potential grade in Yanting administrative region；Matlab software building Arable Land Potential three-dimensional DEM models are used by foundation of Cultivated Land Consolidation Potential composite index, and analysis of partition are carried out in four principal directions based on three-dimensional DEM models.Finally on the basis of the classification of Arcgis composite indexes interpolation, the analysis of Arable Land Potential three-dimensional DEM model facetizations etc., arrange exploitation for hilly area Reserved Cultivated Land Resources and provide theory support.

Description

Based on the hilly area Evaluation of Land Readjustment Potentiality method for improving enabling legislation
Technical field
The invention belongs to Evaluation of Land Readjustment Potentiality technical field, and in particular to a kind of to be ploughed based on the hilly area for improving enabling legislation The design of ground Consolidation Potential method.
Background technology
Since reform and opening-up, economy is advanced by leaps and bounds, and China turns into second-biggest-in-the-world economy, not while economic development It is disconnected to corrode, damage and take the resistance to arable land with existence.It is especially regional in Southwestern China, because of topography and geomorphology and the limit of natural conditions System, originally available to be extremely limited with the high quantity of cultivated land of yield, the constantly flat cultivated land resource of extruding landform is expanded again in city. Therefore southwestern knob Cultivated Land Consolidation Potential Selection Method is studied, formulating southwest grain security decision-making to science has weight Want practical guided significance.
In Evaluation of Land Readjustment Potentiality research, existing method has：(1) comprehensive benefit evaluation of land consolidation is built System, using the weight of analytic hierarchy process (AHP) (AHP) evaluation index, Land Consolidation Project is studied.(2) city-building is established Land used renovates Potential Evaluation model, is quantified using Fuzzy AHP (FAHP) and GIS, qualitatively carries out Urban Construction Land_use Renovate Potential Evaluation.(3) on the basis of Cultivated Land Consolidation Potential analysis indexes system is built, with reference to entropy assessment (Entropy) and Comprehensive evaluation is evaluated Cultivated Land Consolidation Potential.(4) commented in the endogenous variable and exogenous variable for establishing influence Arable Land Potential On the basis of valency index system, ask rule layer index weights and Entropy to seek measure layer index weights using AHP, it is whole to inquire into soil Potentiality are managed, provide following Arable Land Consolidation suggestion.
In other evaluation methods, in addition to：(1) AHP-Entropy enabling legislations, AHP-Entropy enabling legislations are by AHP For solving the subjective weight of rule layer and measure layer, Entropy solves the objective weight of measure layer, then solves AHP Measure layer weight and Entropy solve measure layer weight carries out simple combination and obtains measure layer comprehensive weight, finally AHP is solved Rule layer subjectivity weight and comprehensive weight be combined to obtain measure layer final weight.(2) improved AHP-Entropy assign power Method, improved AHP-Entropy enabling legislations can preferably hold the important journey of rule layer relative to AHP-Entropy enabling legislations Degree and order, take into full account dominating role of the measure layer to equal rule layer, with entering using the Studies on Index Selections result of Entropy methods Row comparative analysis, it was demonstrated that superiority, the robustness of improved AHP-Entropy enabling legislations.(3) FAHP-Entropy enabling legislations, FAHP is used to solve measure layer and rule layer subjectivity weight, Entropy is used for the objective weight for solving measure layer, seeks FAHP The measure layer subjectivity weight of solution is combined to obtain measure layer complex weight with the Entropy measure layer objective weights solved, finally By FAHP rule layer weight and the complex weights solved be combined measure layer final weight, this method do not consider same criterion The contact between measure layer under layer, it is isolated to treat as between the index in layer.
The content of the invention
The invention aims to solve existing Evaluation of Land Readjustment Potentiality method not considering under same rule layer Contact between measure layer, the problem of compatibility is not high, it is proposed that a kind of based on the hilly area for improving FAHP-Entropy enabling legislations Evaluation of Land Readjustment Potentiality method.
The technical scheme is that：It is including following based on the hilly area Evaluation of Land Readjustment Potentiality method for improving enabling legislation Step：
S1, hilly area exploiting potential for arable land model is established according to regional arable land situation to be evaluated, the evaluation model includes one Individual destination layer, m rule layer and l measure layer, wherein 1≤l≤m；
S2, measure layer index weights C={ θ are calculated using Entropy enabling legislations1,θ2,...,θl}；
S3, rule layer index weights A={ β are calculated using FAHP enabling legislations1,β2,...,βmAnd measure layer index power Weight B={ χ1,χ2,...,χl}；
S4, weight A, B, the C being calculated according to step S2-S3, calculated using FAHP-Entropy enabling legislations are improved To final weight η={ ω of measure layer index1,ω2,...,ωl}；
S5, according to final weight η, regional Cultivated Land Consolidation Potential synthesis to be evaluated is calculated using comprehensive evaluation and referred to Number, and be ranked up；
S6, enter row interpolation classification to regional Cultivated Land Consolidation Potential composite index to be evaluated using Arcgis softwares；
S7, regional Arable Land Potential three-dimensional DEM models to be evaluated are established using Matlab softwares, and carry out analysis of partition；
S8, combining step S6 Arcgis composite index interpolation classification results and step S7 potentiality three-dimensional DEM models Analysis of partition result, comprehensive sub-areas suggestion is provided to regional Cultivated Land Consolidation Potential to be evaluated.
Wherein, step S4 specifically include it is following step by step：
S41, the measure layer that measure layer index weights B and the Entropy enabling legislation that FAHP enabling legislations are calculated is calculated referred to Mark weight C and carry out integrated treatment, obtain measure layer index comprehensive weightWherein
S42, the corresponding relation according to measure layer and rule layer, the comprehensive weight of each index of measure layer is represented againAnd respectively to the comprehensive of the measure layer under each rule layer Weight is closed to normalize：
In formulak∈{l1,l2,...,lm, liRepresent the measure number of plies included under i-th of rule layer Mesh, i=1,2 ..., m；
It is S43, η " and rule layer index weights A is corresponding mutually multiplied：
ω ' in formulaij=βiω″ij, j=1,2 ..., k, k ∈ { l1,l2,...,lm}；
S44, η ' is expressed as to η '={ ω ' again1,ω′2,...,ω′l, and after being normalized η= {ω1,ω2,...,ωl, wherein
The beneficial effects of the invention are as follows：The present invention both considers rule layer during to Evaluation of Land Readjustment Potentiality Subjective assessment and objective data combination, it is also considered that the relative importance of different measure layer, taken into account FAHP- The advantages of Entropy enabling legislations and improved AHP-Entropy enabling legislations.Simultaneously by the present invention in that being weighed with compatibility to each assign The superiority of method is checked, demonstrates compatibility of the present invention apparently higher than single subjectivity or objectivity enabling legislation, has steady Strong property, superiority and representativeness.In addition the present invention is first by reserved resources storage level, every mu of grain yield, mechanization of agriculture water Equality index, which introduces, is used as a metrics evaluation Cultivated Land Consolidation Potential, and is write using Matlab integrated for Arable Land Potential first The three-dimensional DEM figures of value, and analysis of partition has been carried out, react inherent potential quality characteristic.
Brief description of the drawings
Fig. 1 show provided in an embodiment of the present invention based on the hilly area Evaluation of Land Readjustment Potentiality method stream for improving enabling legislation Cheng Tu.
Fig. 2 show Yanting County hilly area exploiting potential for arable land model schematic provided in an embodiment of the present invention.
Fig. 3 show Arable Land Potential distribution map in Yanting County provided in an embodiment of the present invention.
Fig. 4 show Yanting County Arable Land Potential three-dimensional DEM model schematics provided in an embodiment of the present invention.
Fig. 5 show Yanting County Arable Land Potential three-dimensional DEM subdivision graphs provided in an embodiment of the present invention.
Embodiment
The illustrative embodiments of the present invention are described in detail referring now to accompanying drawing.It should be appreciated that shown in accompanying drawing and What the embodiment of description was merely exemplary, it is intended that explain the principle and spirit of the present invention, and not limit the model of the present invention Enclose.
The embodiments of the invention provide a kind of based on the hilly area Evaluation of Land Readjustment Potentiality method for improving enabling legislation, such as Fig. 1 It is shown, comprise the following steps S1-S6：
S1, hilly area exploiting potential for arable land model is established according to regional arable land situation to be evaluated, the evaluation model includes one Individual destination layer, m rule layer and l measure layer (1≤l≤m), include l under each rule layeri(i=1,2 ..., m) is individual to be arranged Apply layer, and l1+l2+…+lm=l.
In the embodiment of the present invention, Sichuan Province Mianyang City Yanting County is chosen as area to be evaluated.Yanting is located at Mianyang southeast Square, on Jia Lingjiang River, Fujiang River watershed, border of the county basin trunk river has Fujiang River tributary Zi Jiang, Mi Jiang, Tuan Jiang, Yong Jiang and beech small stream river, Northern height low, the whole county territory area 1647.6km in south is totally presented in physical features2, 36 small towns.Yanting County landform is with hills, mountain region peace Based on original, based on hills Yi Zhongqiu, high mound, middle mound area 77.9km2, high mound is 282.78km2, hills accounts for whole county area 31.18%；Mountain region is to corrode and degrade based on low mountain, low mountain area 1156.73km2, mountain region accounts for the 60.92% of whole county area； Plain is based on valley plain, Plain area 130.19km2, Plain accounts for the 7.9% of whole county area.Cut-off 2015, Yanting County Total area under cultivation is 36925hm2, account for the 22.45% of territory area, wherein field 13017hm2, account for 35.25% always to plough, nonirrigated farmland 23908hm2, account for 64.74% always to plough.Therefore, Yanting County can be used as hilly area to represent, and carry out hilly area Evaluation of Land Readjustment Potentiality Analysis.
Yanting County is influenceed by composite factors such as geographical position, natural conditions, economic conditions, and cultivated land resource presents following special Point：(1) mountain region is more, and causing sloping upland, farmland quality is poor, and middle-and-low-yielding fields are more than great.(2) each small towns farmland types (field) Proportional imbalance, the more paddy fields in county domain southwest region, northern more nonirrigated farmlands.(3) rural area arable land infrastructure is poor, fund guarantee is not in place, Arable Land Consolidation special fund implements project, and each department acting on its own, decentralization in investment, does not concentrate.(4) land use is comminuted, standby money of ploughing Source is limited.
According to county's feelings of Yanting, the endogenous variable of influence Yanting exploiting potential for arable land and many fingers of exogenous variable are chosen Mark, hilly area exploiting potential for arable land model is established, carry out Yanting County exploiting potential for arable land, as shown in Figure 2.
S2, measure layer index weights C={ θ are calculated using Entropy enabling legislations1,θ2,...,θl, specifically step by step It is as follows：
S21, provided with a objects to be evaluated, l items index to be evaluated, structure raw data matrix X=(xij)a×l。
S22, normalized matrix R=(r are calculated according to raw data matrix Xij)a×l, wherein 1≤i≤l, 1≤j≤ A, rij∈[0,1]。
In the embodiment of the present invention, data matrix X is standardized using extremum method, if selecting relatively large person to be excellent Index, then：
rij=(xij-min{xij})/(max{xij}-min{xij}) (1)
If selecting relatively small person as excellent index,：
rij=(max { xij}-xij)/(max{xij}-min{xij}) (2)
S23, the entropy of i-th of index of definition areWhereinK=1/lna；When dijWhen=0, dij lndij=0.
S24, according to entropy HiThe entropy weight θ of i-th of index is calculatedi, calculation formula is：
0≤θ in formulai≤ 1,According to the index entropy weight θ of all measure layersiComposition measure layer index weights C= {θ1,θ2,...,θl}。
In the embodiment of the present invention, the measure layer index weights C being calculated using Entropy enabling legislations is as shown in table 1：
Table 1
S3, rule layer index weights A={ β are calculated using FAHP enabling legislations1,β2,...,βmAnd measure layer index power Weight B={ χ1,χ2,...,χl}。
Wherein, calculation criterion layer index weights A method is specially：
A31, according to FAHP enabling legislations, using 0.1~0.9 scale, build preferential judgment matrix F=(fij)m×m.Each scale Explanation it is as shown in table 2：
Table 2
Scale Explanation
0.5 One index and another index are of equal importance
0.6 One index is somewhat more important than another index
0.7 One index is substantially more important than another index
0.8 Much more important than another index of one index
0.9 One index is more extremely important than another index
0.1,0.2,0.3,0.4 fji=1-fij
A32, it transform preferential judgment matrix F as fuzzy consistent judgment matrix T=(tij)m×m, t in formulaij=(ti-tj)/2m + 0.5,I=1,2 ..., m, m be rule layer index number.
A33, sum row normalization weight sets W={ (w) according to fuzzy consistent judgment matrix T calculating1×m}T。
A34, fuzzy consistent judgment matrix T is converted into reciprocal matrix E=(eij)m×m, e in formulaij=tij/tji。
A35, will be with row normalization weight sets W as initial vector V0, it is iterated using formula (4)：
If | | | Vk+1||∞-||Vk||∞Then iteration terminates |≤ε, in formulaε is assigned error, this hair 0.0001 is taken in bright embodiment.
A36, by Vk+1Rule layer index weights A is obtained after normalization：
Calculating measure layer index weights B method specifically includes：
B31, according to FAHP enabling legislations, using 0.1~0.9 scale, build preferential judgment matrix F=(fij)l×l。
B32, it transform preferential judgment matrix F as fuzzy consistent judgment matrix T=(tij)l×l, t in formulaij=(ti-tj)/2l + 0.5,I=1,2 ..., l, l be measure layer index number.
B33, sum row normalization weight sets W={ (w) according to fuzzy consistent judgment matrix T calculating1×l}T。
B34, fuzzy consistent judgment matrix T is converted into reciprocal matrix E=(eij)l×l, e in formulaij=tij/tji。
B35, will be with row normalization weight sets W as initial vector V0, it is iterated using formula (4)：
If | | | Vk+1||∞-||Vk||∞Then iteration terminates |≤ε, in formulaε is assigned error, this hair 0.0001 is taken in bright embodiment.
B36, by Vk+1Measure layer index weights B is obtained after normalization：
In the embodiment of the present invention, the rule layer index weights A and measure layer index that are calculated using FAHP enabling legislations are weighed Weight B is as shown in table 3：
Table 3
S4, weight A, B, the C being calculated according to step S2-S3, calculated using FAHP-Entropy enabling legislations are improved To final weight η={ ω of measure layer index1,ω2,...,ωl, it is specifically as follows step by step：
S41, the measure layer that measure layer index weights B and the Entropy enabling legislation that FAHP enabling legislations are calculated is calculated Index weights C carries out integrated treatment, obtains measure layer index comprehensive weightWherein
S42, the corresponding relation according to measure layer and rule layer, the comprehensive weight of each index of measure layer is represented againAnd respectively to the comprehensive of the measure layer under each rule layer Weight is closed to normalize：
In formulak∈{l1,l2,...,lm, liRepresent the measure number of plies included under i-th of rule layer Mesh, i=1,2 ..., m.
It is S43, η " and rule layer index weights A is corresponding mutually multiplied：
ω ' in formulaij=βiω″ij, j=1,2 ..., k, k ∈ { l1,l2,...,lm}。
S44, η ' is expressed as to η '={ ω ' again1,ω′2,...,ω′l, and after being normalized η= {ω1,ω2,...,ωl, wherein
In the embodiment of the present invention, the final weight of measure layer index is calculated using improvement FAHP-Entropy enabling legislations η is as shown in table 3.
The superiority of FAHP-Entropy enabling legislations is improved for checking, is tested using enabling legislation compatibility.N is assigned The compatibility of power method refers to the enabling legislation and the arithmetic mean of instantaneous value of the Spearman coefficient of rank correlations of remaining each enabling legislation, i.e.,：
In formuladinlFor the difference of sequence of i-th of index between two kinds of enabling legislations of n and l, M is index sum, and h is the quantity of enabling legislation, and the compatibility that certain assigns power method is big, then the representativeness of this enabling legislation is strong, assesses As a result more representative, robustness.Data of the embodiment of the present invention come from table 3, calculate to obtain FAHP enabling legislations (method 1), Entropy Enabling legislation (method 2), FAHP-Entropy enabling legislations (method 3), improve the Spearman of FAHP-Entropy enabling legislations (method 4) successively Coefficient of rank correlation, that is, have：R12=-0.0196, R13=0.8015, R14=0.8382, R23=0.1642, R24=0.1642, R34=0.9314.According to formula (10), the compatibility that each enabling legislation is calculated is as shown in table 4：
Table 4
As shown in Table 4, R4>R3>R1>R2, that is, the compatibility of FAHP-Entropy enabling legislations is improved apparently higher than single subjectivity Property or objectivity enabling legislation, demonstrate robustness, the superiority of improved FAHP-Entropy enabling legislations.
S5, according to final weight η, regional Cultivated Land Consolidation Potential synthesis to be evaluated is calculated using comprehensive evaluation and referred to Number, and be ranked up.The formula for calculating regional Cultivated Land Consolidation Potential composite index to be evaluated is：
ω in formulaiRepresent the final weight of i-th of index, ciThe standard value of i-th of index is represented, by formula (1) or (2) Each index r obtainedijObtained after standardization.
S6, enter row interpolation classification to regional Cultivated Land Consolidation Potential composite index to be evaluated using Arcgis softwares.
The situation of change of Cultivated Land Consolidation Potential, is entered using inverse distance weighted interpolation method between reflection Yanting County different zones Row Arable Land Consolidation composite index interpolation analysis, and be overlapped with Yanting County administrative region, Yanting County Arable Land Potential distribution map is obtained, As shown in figure 3, the Arable Land Consolidation composite index situation of change of Yanting difference administrative region as shown in Figure 3, through calculating whole county arable land Comprehensive potential index between 0.5614-0.1017, with《County land Renovation and planning works out code》(TD/135-2013) be according to According to being classified by Arcgis softwares to Yanting County Cultivated Land Consolidation Potential, as shown in table 5.
Table 5
Yanting Cultivated Land Consolidation Potential is classified using the grade scale of table 5, REGION OF WATER INJECTION OILFIELDs at different levels are presented below as region spy Point：One-level REGION OF WATER INJECTION OILFIELD is distributed mainly on Zi Jiang, Tuan Jiang, Mi Jiang, beech small stream river bank bank, and integrated distribution is more significant.Two level Potential zoning It is in zonal distribution approximately along northwest to southeastern direction.Three-level Potential zoning is distributed around one-level Potential zoning in fragmentary shape.Level Four Potential zoning is located at Yanting County northwest, southwest, the face of the southeast three, dissipates distribution in fragmentary.
S7, regional Arable Land Potential three-dimensional DEM models to be evaluated are established using Matlab softwares, and carry out analysis of partition.
Based on the small towns administrative division map of Yanting County 36, each town government location is extracted as sample with Arcgis This click-through row interpolation is analyzed, and is assigned each small towns composite index to 36 sample points, is write program using Matlab and establish Yanting County Arable Land Potential three-dimensional DEM models, as shown in Figure 4.
Intuitively to react microscopic characteristics of the Yanting Arable Land Potential integrated value in four Main ways, Yanting County is ploughed latent Power three-dimensional DEM models specify Dong-west, north-south, the northwest-southeast, southwest-northeast four direction progress uniformly subdivision.Dong-west refers to Determine subdivision point and be located at 31.23 ° of north latitude, north-south specifies subdivision point to be located at 105.52 ° of east longitude, the southeast-northwest, two, northeast-southwest Direction is to carry out oblique subdivision, 3 D stereo coordinate be present, and selected subdivision point is located at the Central Symmetry point of Yanting County administrative line figure, Three-dimensional dividing is carried out, obtains Arable Land Potential three-dimensional DEM subdivision graphs, as shown in Figure 5.
Understand that Yun Xi towns Cultivated Land Consolidation Potential is maximum by northeast-southwestern subdivision line (Fig. 5 d), Liang He takes second place in town, on subdivision line Composite index of ploughing average value is 0.1922, and overall Cultivated Land Consolidation Potential is horizontal general.The southeast-northwest subdivision line (Fig. 5 c) is presented Mountain peak type is distributed, and first increases and gradually decreases afterwards, and Huang Dian towns Cultivated Land Consolidation Potential is maximum, and Bai Zi towns, golden Kong Zhen take second place, on subdivision line Composite index of ploughing average value is 0.3012, and overall Cultivated Land Consolidation Potential level is higher.Dong-western subdivision line (Fig. 5 a) understands cloud small stream Town Cultivated Land Consolidation Potential is maximum, and Huang Dian towns, self-employed tree cultivator town are taken second place, and composite index average value of being ploughed on subdivision line is 0.2585, overall Cultivated Land Consolidation Potential is horizontal general.North-south subdivision line (Fig. 5 b) is similar to the southeast-northwest subdivision line tendency, and Yun Xi towns arable land is whole Manage with the largest potentiality, Yulong town, Ma Yang townshiies take second place, and composite index average value of being ploughed on subdivision line is 0.3114, overall Arable Land Consolidation Potentiality level is higher.
S8, combining step S6 Arcgis composite index interpolation classification results and step S7 potentiality three-dimensional DEM models Analysis of partition result, comprehensive sub-areas suggestion is provided to regional Cultivated Land Consolidation Potential to be evaluated.
On to Arcgis composite indexes interpolation analysis, Arable Land Potential three-dimensional DEM model facetization analysis foundations, according to Yanting County's agricultural belt return draw, arable land is divided into 4 Arable Land Consolidation developing zones by the composite factor such as topography and geomorphology：
(1) southwestern river valley Cultivated Land Consolidation Potential area：REGION OF WATER INJECTION OILFIELD is located at Chinese catalpa river bank downstream, and the sedimentation in river is obvious, Causing region to plough, irrigated area is more, and based on river valley Pingba, territorial scope includes geomorphic type：Yun Xi towns, Liang He towns, new agriculture Township, Mao Gong townshiies, giant dragon town, Ma Yang townshiies, Liang Chahe townshiies, Bai Zi towns, Yulong town, Huang Xi townshiies.REGION OF WATER INJECTION OILFIELD is located at Yanting County and mainly passed through Ji development zone, leading action is played to whole county economy, land and water transportation facility is the main portal of external contacts, is northern deep mound The connection bridge in Arable Land Potential area and southern Qian Qiu Arable Land Potentials area.The REGION OF WATER INJECTION OILFIELD density of population is larger, and urban population is more, agricultural Population is relatively fewer, and arable land infrastructure is preferable, but middle-and-low-yielding fields ratio, transforming slope into terrace large percentage, and infrastructure has larger Space is improved, makes the region Cultivated Land Consolidation Potential big, Cultivated Land Consolidation Potential rank is set to I grade, category optimum Distribution Area.
(2) northeast Qian Qiu Cultivated Land Consolidation Potentials area：REGION OF WATER INJECTION OILFIELD is located at the northeast traffic convenience of county domain, provincial highway S101, continuous west Cross and mistake at a high speed.Territorial scope includes：Fu Yi towns, Huang Dian towns, woods mountain area, self-employed tree cultivator town, anistree town, ternary township, Yongtai township, gold Anxiang, Daxing township of the Hui ethnic group.REGION OF WATER INJECTION OILFIELD is located at Zi Jiang tributary Mi Jiang, the upstream in rapid river, is that Yanting agricultural industry belt assembles ground, base This farmland protection area is larger.Through fund input for many years, Arable Land Consolidation is slightly shown in achievement, but still has part arable land to need to arrange, potentiality level It is not set to II grade, belongs to suitable Distribution Area.
(3) southeast Qian Qiu Cultivated Land Consolidation Potentials area：REGION OF WATER INJECTION OILFIELD is located at the county domain southeast, Xuanyuan Yellow Emperor, a legendary ruler's member prince wife-Lei ancestrals mound position It is the leading travel industry band in Yanting County in the region, landforms scope mainly includes：Five Dragons township, Ju Xi townshiies, Xi Ze townshiies, high lamp Town, golden Kong Zhen, Zong Hai township, dragon's fountain township, golden pheasant town, Zhe Gong townshiies.Zi Jiang tributary Yong Jiang, beech small stream river are through this REGION OF WATER INJECTION OILFIELD, physical features Overall flatter, transforming slope into terrace ratio has larger deposit space, is the main Reserved Cultivated Land Resources storehouse in Yanting County, and Arable Land Consolidation is dived Power rank is set to III grade, belongs to convenient Distribution Area.
(4) northwest Di Shanshen mounds Cultivated Land Consolidation Potential area：REGION OF WATER INJECTION OILFIELD is located at the county domain northwestward, and geomorphic type is mainly deep mound With low mountain, territorial scope includes：Tea-booth township, township of wading a river, Hei Ping towns, Jianhe township, Lai Long townshiies, Shi Niumiao townshiies, Shuan Bei townshiies, settle down Town.REGION OF WATER INJECTION OILFIELD entirety physical features is higher, possesses forestry band along the river, and forest land area is more, is the Yanting County primary timber place of production, and population is close Spend sparse, basic farmland area is few, is limited by the more mountains of geographical conditions, and agriculture as the foundation of the economy is poor, therefore the region Cultivated Land Consolidation Potential Minimum, potentiality rank are set to IV grade, and category least adapts to Distribution Area.
One of ordinary skill in the art will be appreciated that embodiment described here is to aid in reader and understands this hair Bright principle, it should be understood that protection scope of the present invention is not limited to such especially statement and embodiment.This area Those of ordinary skill can make according to these technical inspirations disclosed by the invention various does not depart from the other each of essence of the invention The specific deformation of kind and combination, these deform and combined still within the scope of the present invention.

Claims (8)

1. based on the hilly area Evaluation of Land Readjustment Potentiality method for improving enabling legislation, it is characterised in that comprise the following steps：
S1, hilly area exploiting potential for arable land model is established according to regional arable land situation to be evaluated, the evaluation model includes a mesh Layer, m rule layer and l measure layer are marked, wherein 1≤l≤m；
S2, measure layer index weights C={ θ are calculated using Entropy enabling legislations1,θ2,...,θl}；
S3, rule layer index weights A={ β are calculated using FAHP enabling legislations1,β2,...,βmAnd measure layer index weights B ={ χ1,χ2,...,χl}；
S4, weight A, B, the C being calculated according to step S2-S3, it is calculated and is arranged using improvement FAHP-Entropy enabling legislations Apply final weight η={ ω of layer index1,ω2,...,ωl}；
S5, according to final weight η, regional Cultivated Land Consolidation Potential composite index to be evaluated is calculated using comprehensive evaluation, and It is ranked up；
S6, enter row interpolation classification to regional Cultivated Land Consolidation Potential composite index to be evaluated using Arcgis softwares；
S7, regional Arable Land Potential three-dimensional DEM models to be evaluated are established using Matlab softwares, and carry out analysis of partition；
S8, combining step S6 Arcgis composite index interpolation classification results and step S7 potentiality three-dimensional DEM model facetizations Analysis result, comprehensive sub-areas suggestion is provided to regional Cultivated Land Consolidation Potential to be evaluated.
2. Evaluation of Land Readjustment Potentiality method in hilly area according to claim 1, it is characterised in that the step S2 is specifically wrapped Include it is following step by step：
S21, provided with a objects to be evaluated, l items index to be evaluated, structure raw data matrix X=(xij)a×l；
S22, normalized matrix R=(r are calculated according to raw data matrix Xij)a×l, wherein 1≤i≤l, 1≤j≤a, rij ∈[0,1]；
S23, the entropy of i-th of index of definition areWhereinK=1/lna；Work as dij=0 When, dijlndij=0；
S24, according to entropy HiThe entropy weight θ of i-th of index is calculatedi, according to the index entropy weight θ of all measure layersiComposition measure layer Index weights C={ θ1,θ2,...,θl}。
3. Evaluation of Land Readjustment Potentiality method in hilly area according to claim 2, it is characterised in that the step S22 falls into a trap Calculate normalized matrix R=(rij)a×lFormula be：
If selecting relatively large person as excellent index,：
rij=(xij-min{xij})/(max{xij}-min{xij}) (1)
If selecting relatively small person as excellent index,：
rij=(max { xij}-xij)/(max{xij}-min{xij}) (2)。
4. Evaluation of Land Readjustment Potentiality method in hilly area according to claim 2, it is characterised in that the step S24 falls into a trap Calculate entropy weight θiFormula be：
<mrow> <msub> <mi>&amp;theta;</mi> <mi>i</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <msub> <mi>H</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>/</mo> <mrow> <mo>(</mo> <mi>l</mi> <mo>-</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <msub> <mi>H</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>
0≤θ in formulai≤ 1,
5. Evaluation of Land Readjustment Potentiality method in hilly area according to claim 1, it is characterised in that calculated in the step S3 Rule layer index weights A method specifically includes：
A31, according to FAHP enabling legislations, using 0.1~0.9 scale, build preferential judgment matrix F=(fij)m×m；
A32, it transform preferential judgment matrix F as fuzzy consistent judgment matrix T=(tij)m×m, t in formulaij=(ti-tj)/2m+ 0.5,I=1,2 ..., m, m be rule layer index number；
A33, sum row normalization weight sets W={ (w) according to fuzzy consistent judgment matrix T calculating1×m}T；
A34, fuzzy consistent judgment matrix T is converted into reciprocal matrix E=(eij)m×m, e in formulaij=tij/tji；
A35, will be with row normalization weight sets W as initial vector V0, it is iterated using formula (4)：
<mrow> <msup> <mi>V</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msup> <mo>=</mo> <mi>E</mi> <mfrac> <msup> <mi>V</mi> <mi>k</mi> </msup> <mrow> <mo>|</mo> <mo>|</mo> <msup> <mi>V</mi> <mi>k</mi> </msup> <mo>|</mo> <msub> <mo>|</mo> <mi>&amp;infin;</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow>
If | | | Vk+1||∞-||Vk||∞Then iteration terminates |≤ε, in formulaε is assigned error；
A36, by Vk+1Rule layer index weights A is obtained after normalization：
<mrow> <mi>A</mi> <mo>=</mo> <mo>{</mo> <msub> <mi>&amp;beta;</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>&amp;beta;</mi> <mn>2</mn> </msub> <mo>,</mo> <mn>...</mn> <mo>,</mo> <msub> <mi>&amp;beta;</mi> <mi>m</mi> </msub> <mo>}</mo> <mo>=</mo> <mo>{</mo> <mrow> <msubsup> <mi>V</mi> <mn>1</mn> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msubsup> <mi>V</mi> <mi>i</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>V</mi> <mn>2</mn> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msubsup> <mi>V</mi> <mi>i</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>,</mo> <mn>...</mn> <mo>,</mo> <msubsup> <mi>V</mi> <mi>m</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msubsup> <mi>V</mi> <mi>i</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> </mrow> <mo>}</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> <mo>.</mo> </mrow>
6. Evaluation of Land Readjustment Potentiality method in hilly area according to claim 1, it is characterised in that calculated in the step S3 Measure layer index weights B method specifically includes：
B31, according to FAHP enabling legislations, using 0.1~0.9 scale, build preferential judgment matrix F=(fij)l×l；
B32, it transform preferential judgment matrix F as fuzzy consistent judgment matrix T=(tij)l×l, t in formulaij=(ti-tj)/2l+ 0.5,I=1,2 ..., l, l be measure layer index number；
B33, sum row normalization weight sets W={ (w) according to fuzzy consistent judgment matrix T calculating1×l}T；
B34, fuzzy consistent judgment matrix T is converted into reciprocal matrix E=(eij)l×l, e in formulaij=tij/tji；
B35, will be with row normalization weight sets W as initial vector V0, it is iterated using formula (4)：
<mrow> <msup> <mi>V</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msup> <mo>=</mo> <mi>E</mi> <mfrac> <msup> <mi>V</mi> <mi>k</mi> </msup> <mrow> <mo>|</mo> <mo>|</mo> <msup> <mi>V</mi> <mi>k</mi> </msup> <mo>|</mo> <msub> <mo>|</mo> <mi>&amp;infin;</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow>
If | | | Vk+1||∞-||Vk||∞Then iteration terminates |≤ε, in formulaε is assigned error；
B36, by Vk+1Measure layer index weights B is obtained after normalization：
<mrow> <mi>B</mi> <mo>=</mo> <mo>{</mo> <msub> <mi>&amp;chi;</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>&amp;chi;</mi> <mn>2</mn> </msub> <mo>,</mo> <mn>...</mn> <mo>,</mo> <msub> <mi>&amp;chi;</mi> <mi>l</mi> </msub> <mo>}</mo> <mo>=</mo> <mo>{</mo> <mrow> <msubsup> <mi>V</mi> <mn>1</mn> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <msubsup> <mi>V</mi> <mi>i</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>V</mi> <mn>2</mn> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <msubsup> <mi>V</mi> <mi>i</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>,</mo> <mn>...</mn> <mo>,</mo> <msubsup> <mi>V</mi> <mi>l</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <msubsup> <mi>V</mi> <mi>i</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> </msubsup> </mrow> <mo>}</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> <mo>.</mo> </mrow>
7. Evaluation of Land Readjustment Potentiality method in hilly area according to claim 1, it is characterised in that the step S4 is specifically wrapped Include it is following step by step：
S41, the measure layer index that measure layer index weights B and the Entropy enabling legislation that FAHP enabling legislations are calculated is calculated Weight C carries out integrated treatment, obtains measure layer index comprehensive weightWherein
S42, the corresponding relation according to measure layer and rule layer, the comprehensive weight of each index of measure layer is represented againAnd respectively to the comprehensive of the measure layer under each rule layer Weight is closed to normalize：
<mrow> <msup> <mi>&amp;eta;</mi> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msup> <mo>=</mo> <mo>{</mo> <msubsup> <mi>&amp;omega;</mi> <mn>11</mn> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mn>12</mn> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>,</mo> <mo>...</mo> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <mn>1</mn> <msub> <mi>l</mi> <mn>1</mn> </msub> </mrow> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>;</mo> <msubsup> <mi>&amp;omega;</mi> <mn>21</mn> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mn>22</mn> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>,</mo> <mo>...</mo> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <mn>2</mn> <msub> <mi>l</mi> <mn>2</mn> </msub> </mrow> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>;</mo> <mo>...</mo> <mo>;</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <mi>m</mi> <mn>1</mn> </mrow> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <mi>m</mi> <mn>2</mn> </mrow> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>,</mo> <mo>...</mo> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <msub> <mi>ml</mi> <mi>m</mi> </msub> </mrow> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msubsup> <mo>}</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow>
In formulak∈{l1,l2,...,lm, liRepresent the measure number of layers included under i-th of rule layer, i= 1,2,...,m；
It is S43, η " and rule layer index weights A is corresponding mutually multiplied：
<mrow> <msup> <mi>&amp;eta;</mi> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <mo>{</mo> <msubsup> <mi>&amp;omega;</mi> <mn>11</mn> <mo>&amp;prime;</mo> </msubsup> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mn>12</mn> <mo>&amp;prime;</mo> </msubsup> <mo>,</mo> <mo>...</mo> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <mn>1</mn> <msub> <mi>l</mi> <mn>1</mn> </msub> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>;</mo> <msubsup> <mi>&amp;omega;</mi> <mn>21</mn> <mo>&amp;prime;</mo> </msubsup> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mn>22</mn> <mo>&amp;prime;</mo> </msubsup> <mo>,</mo> <mo>...</mo> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <mn>2</mn> <msub> <mi>l</mi> <mn>2</mn> </msub> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>;</mo> <mo>...</mo> <mo>;</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <mi>m</mi> <mn>1</mn> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <mi>m</mi> <mn>2</mn> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>,</mo> <mo>...</mo> <mo>,</mo> <msubsup> <mi>&amp;omega;</mi> <mrow> <msub> <mi>ml</mi> <mi>m</mi> </msub> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>}</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>8</mn> <mo>)</mo> </mrow> </mrow>
ω ' in formulaij=βiω″ij, j=1,2 ..., k, k ∈ { l1,l2,...,lm}；
S44, η ' is expressed as to η '={ ω ' again1,ω′2,...,ω′l, and obtain η={ ω after being normalized1, ω2,...,ωl, wherein
8. Evaluation of Land Readjustment Potentiality method in hilly area according to claim 1, it is characterised in that calculated in the step S5 The formula of regional hilly area Cultivated Land Consolidation Potential composite index to be evaluated is：
<mrow> <mi>E</mi> <mi>S</mi> <mi>I</mi> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <msub> <mi>&amp;omega;</mi> <mi>i</mi> </msub> <mo>&amp;times;</mo> <msub> <mi>c</mi> <mi>i</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>9</mn> <mo>)</mo> </mrow> </mrow>
ω in formulaiRepresent the final weight of i-th of index, ciRepresent the standard value of i-th of index.
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