CN103870995A - High and cold sand land vegetation recovery potential estimation method - Google Patents
High and cold sand land vegetation recovery potential estimation method Download PDFInfo
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Abstract
The invention discloses a high and cold sand land vegetation recovery potential estimation method. The method comprises the following steps that according to growth conditions of different types of sand land in high and cold areas, a vegetation recovery target of the high and cold areas is determined; a hierarchical structure model of vegetation recovery potential estimation of the different types of sand land is built by using an analytic hierarchy process; a judgment matrix, a hierarchical single-row sequence table and a hierarchical total-row sequence table are built by means of the hierarchical structure model of vegetation recovery potential estimation of the sand land; comprehensive evaluation calculation is conducted on the vegetation recovery potential of the different types of sand land by means of a fuzzy comprehensive evaluation method. According to the high and cold sand land vegetation recovery potential estimation method, the good and bad degree comprising 15 evaluation factors and total evaluation of the vegetation recovery potential can be respectively output, and a scientific decision support method can be provided for making of a vegetation recovery policy of the different types of high and cold sand land in different areas of the Qinghai-Tibet Plateau.
Description
Technical field
The present invention relates to ecological protection and recovery technology field, relate in particular to a kind of alpine sandy land revegetation potential evaluation method.
Background technology
Carrying out revegetation Potential Evaluation is to carry out the on the spot basis of (degeneration sandy land and Engineering Disturbance district) ecological recovery practice of solid difficulty, when facing an ecosystem of having degenerated, what first consider is to determine that it is restored to the ability of certain target ecosystem, assesses the size of revegetation potentiality.It is to make impaired ecosystem restoration arrive the perfect condition before disturbing that American Natural Resources Council (UNRC), Cairns and Peng Shaolin etc. emphasize to recover.But owing to lacking the restriction of understanding, release time to ecosystem historical development of oversize, the too high current conditions of expense, this perfect condition can not reach.In revegetation Potential Evaluation, conventionally to use the information of frame of reference to define the target of recovery, and then determine by tolerance Community Characters of Degenerate and with reference to " distance " between group the revegetation potentiality that recovers location, evaluate the state recovering.
In recent years, some comprehensive evaluation models are applied to China mining area, Transitional Agro-pastoral, in the revegetation Potential Evaluation in the dissimilar regions such as Northwestern Guizhou Province Karst Regional, particularly by analogy investigation method, recovery extent and the resume speed of having predicted Qinghai-Tibetan Railway species richness along the line and vegetation cover degree, obtained good effect.But existing research at present not yet relates to variations of the bio-diversity in alpine sandy land revegetation process under the stress conditions of habitat, succession of community mechanism, psammophytes dominant population spatial framework and with the response relation of spatial and temporal heterogeneity of soil moisture etc., but this carries out prerequisite and foundation that high and cold river valley sand ground revegetation potential comprehensive is assessed just.
At present, the research and practice that the revegetation of the Qinghai-Tibet extremely frigid zones degeneration desertification ecosystem is relevant with reconstruction, mainly concentrates on basin, middle part, Tibet " two rivers, a river ", Qinghai-Tibet Railway and three river sources areas and the Caidamu Basin etc.Research shows, due to unique puna and harsh natural conditions, it is very difficult on Qinghai-Tibet active sand dune, only recovering with natural force, sand-protecting barrier is manually set after revegetation can start very soon.From the eighties in 20th century, autonomous region near Qushui County, Lhasa, Shannan Prefecture Zetang Zhen, to the east of Lang Sai Ling Hesangye town, Zhanang County, Luo Cun is to areas such as Duo Pozhang townshiies, Naidong County, overcome the adverse condition such as height above sea level, rainfall amount be few, dry, by building forests for windbreak and sand-fixation, agricultural protection forest and the measure such as trees have been planted to fix the sand, carry out the continuous exploration of the work of defending and controlling sand, the hazards of sand storms that alleviates traffic main artery, airport port has been played to certain positive role.
But, above-mentioned practice is operated in when having accumulated abundant sandstorm prevention practice experience, what is more important, many bottleneck problems that high and cold river valley sand ground ecological recovery urgent need solves are found, outstanding behaviours is in the following aspects: the one, and high and cold shifting of sand dunes land type is various, the critical area that the mobile sand ground of sand ground and hillside is sandstorm control flows on the riverbank of both sides, river valley, due to habitat conditions restriction, its revegetation mechanism is completely different with the good river shoal of moisture condition sand ground, urgently carries out dissimilar sand ground revegetation Potential Evaluation; The 2nd, urgently set up target, evaluation index and evaluation criterion that alpine sandy land manually promotes revegetation, build alpine sandy land revegetation potential comprehensive assessment models under the stress conditions of habitat, for carrying out the revegetation Potential Evaluation supplying method foundation of the dissimilar sand ground in high and cold river valley and zones of different.
Summary of the invention
The object of the present invention is to provide a kind of alpine sandy land revegetation potential evaluation method, to address the above problem.In order to achieve the above object, technical scheme of the present invention is achieved in that
A kind of alpine sandy land revegetation potential evaluation method, comprises the steps:
For the habitat conditions of the dissimilar sand ground of extremely frigid zones, determine its revegetation target;
Use analytical hierarchy process, set up the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation;
Utilize the hierarchy Model of described sand ground revegetation Potential Evaluation, development of judgment matrix, Mode of Level Simple Sequence list and the total sorted lists of level;
Use Field Using Fuzzy Comprehensive Assessment, carry out dissimilar sand ground revegetation potential comprehensive evaluation and calculate.
Preferably, described utilization analytical hierarchy process, sets up the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation, specifically comprises the steps:
Select weather conditions information, topographic condition information, soil regime information, recover the basic index of these four aspects of presence information as the mobile sand ground revegetation Potential Evaluation in high and cold river valley;
According to the basic index of the mobile sand ground revegetation Potential Evaluation in described high and cold river valley, and adopt analytical hierarchy process to build the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation; Fuzzy evaluation is divided into three levels, i.e. destination layer (A), rule layer (B) and indicator layer (C), wherein:
Described destination layer (A) is the highest level of hierarchical structure, realizes the mobile sand ground revegetation Potential Evaluation value in high and cold river valley; Described rule layer (B) is the Major Systems level of guaranteeing that overall goal realizes, is divided into weather conditions information B1, topographic condition information B2, soil regime information B3, recovers presence information B4; Described indicator layer is the most basic hierarchical structure, comprises weather conditions information B1, topographic condition information B2, soil regime information B3, recovers the concrete factor of evaluation of presence information B4;
Wherein: described weather conditions information B1 comprises the factor of evaluation set of annual precipitation C1, average temperature of the whole year C2, year sunshine time C3; Described topographic condition information B2 comprises the factor of evaluation set of height above sea level C4, gradient C5, slope aspect C6; Described soil regime information B3 comprises the factor of evaluation set of soil moisture C7, P in soil H value C8, soil organism C9, total soil nitrogen C10, soil texture C11, sand dune ground temperature C12; The suitable biological species of described recovery presence information B4 is selected the factor of evaluation set of C13, fence fencing C14, floor treatment C15;
Described factor of evaluation set is: B1={C1, C2, C3}, B2={C4, C5, C6}, B3={C7, C8, C9, C10, C11, C12}, B4={C13, C14, C15}; A={B1, B2, B3, B4}.
Preferably, utilize the hierarchy Model of described sand ground revegetation Potential Evaluation, development of judgment matrix, Mode of Level Simple Sequence list and the total sorted lists of level, specifically comprise the steps:
Indicator layer from the hierarchy Model of described sand ground revegetation Potential Evaluation starts, the importance of the basic index of the rule layer according to the each factor of evaluation in indicator layer to upper level, adopt manner of comparison between two to form Judgement Matrix, adopt root method to obtain weighted value the normalization computing of each factor of evaluation, by calculating the weight sets (B-C) of indicator layer to rule layer after consistency check: W21, W22, W23, W24; The weighted value of the each factor of evaluation calculating is set up to Mode of Level Simple Sequence list;
Rule layer from the hierarchy Model of described sand ground revegetation Potential Evaluation, according to the importance of the destination layer of each basic index to upper level in rule layer, adopt manner of comparison between two to form Judgement Matrix, adopt root method to obtain weighted value the normalization computing of each basic index, by calculating the weight sets (A-B) of rule layer to destination layer: W1 after consistency check; The weighted value of the each basic index calculating is set up to Mode of Level Simple Sequence list;
Indicator layer is multiplied each other with respect to the weighted value of destination layer with rule layer with respect to the weighted value of rule layer, obtain each factor of evaluation shared weights W in high and cold river valley flows sand ground revegetation Potential Evaluation value; The each factor of evaluation calculating shared weight in high and cold river valley flows sand ground revegetation Potential Evaluation value is set up to the total sorted lists of level.
Preferably, described utilization Field Using Fuzzy Comprehensive Assessment, carries out dissimilar sand ground revegetation potential comprehensive evaluation and calculates, and specifically comprises the steps:
For default comment threshold value corresponding to different stage of each factor of evaluation;
The shared weight scope in multistage comment threshold value in sand ground revegetation Potential Evaluation value that flows in high and cold river valley according to each factor of evaluation, determines each factor of evaluation sand ground revegetation Potential Evaluation information that flows in high and cold river valley;
Determine subordinate function:
Determining after the corresponding comment rank that 15 factors of evaluation flow in sand ground revegetation Potential Evaluation information in high and cold river valley respectively, set up evaluation criterion system and the interval list in 5 grades thereof, and establish the subordinate function of 5 comment ranks of each factor of evaluation;
The interval intermediate value of choosing each factor of evaluation in described evaluation criterion system and the interval list in 5 grades thereof as index in standard value at different levels, utilize described subordinate function to calculate i the standard value Sij of index in j level, i=1,2,3 ..., 15; J=1,2 ..., 5;
Wherein, the subordinate function type of above-mentioned 15 factors of evaluation can be divided into 3 classes, that is: (1) annual precipitation C1, soil moisture C7, soil organism C9, total soil nitrogen C10, slope aspect C6, soil texture C11, fence fencing C14, suitable biological species select C13, floor treatment C15 to belong to ring mo(u)ld bottom half for the subordinate function of grade 1;
(2) height above sea level C4, gradient C5 belong to ring mo(u)ld top half for the subordinate function of grade 1;
(3) average temperature of the whole year C2, year sunshine time C3, soil pH value C8, sand dune ground temperature C12 belong to symmetric form for the subordinate function of grade 1;
Set up fuzzy evaluation matrix:
Obtain the degree of membership that each factor of evaluation belongs to different comment ranks, set up fuzzy evaluation matrix R;
Have i if participate in the index of revegetation Potential Evaluation, revegetation Potential Evaluation standard is made up of j rank, because revegetation potentiality situation and revegetation potential classification standard are all fuzzy, therefore it is proper to carry out partition level boundary by degree of membership;
If Rij represents the revegetation potential value of i kind index and can be evaluated as the possibility of j kind grade, so just form the fuzzy relationship matrix r between revegetation Potential evaluation index and grade; According to evaluation object measured value and the evaluation criterion value of sand ground revegetation of flowing, and subordinate function algorithm, determine the fuzzy relationship matrix r of alpine sandy land revegetation Potential evaluation index layer;
Wherein, m represents that evaluation index counts i=1,2 ..., 15; N represents that revegetation potentiality rank is j=1,2,3,4,5; The degree of membership of i to j, their relation is subordinate function;
Build model of fuzzy synthetic evaluation:
Set up model of fuzzy synthetic evaluation:
Wherein,
be fuzzy synthesis operational symbol, in fuzzy mathematics, be called fuzzy operator; Fuzzy operator has various ways, and wherein the most frequently used situation is " get and get greatly little operator " and " take advantage of with and operator ";
Weight sets W21, W22, W23, W24 and W1 that binding hierarchy analytic approach is definite, based on model of fuzzy synthetic evaluation, build alpine sandy land revegetation potentiality fuzzy overall evaluation rule layer model, and obtain the fuzzy relation matrix list that rule layer is evaluated;
The fuzzy relation matrix list of evaluating according to described rule layer, obtain the degree of membership value of the corresponding different brackets under rule layer mesoclimate conditional information B1, topographic condition information B2, these four different conditions constraints of soil regime information B3, recovery presence information B4, judge the capacity of water of revegetation potentiality under four different conditions according to described degree of membership value;
The fuzzy relation matrix of described rule layer evaluation is:
Weather conditions:
Topographic condition:
Soil regime:
Recover present situation:
Determine alpine sandy land revegetation potentiality fuzzy overall evaluation destination layer model, and obtain the fuzzy relation matrix list that destination layer is evaluated:
The fuzzy relation matrix list of evaluating according to described destination layer, obtain in destination layer the degree of membership value of 15 corresponding different brackets of factor of evaluation that four conditions specifically comprise, judge under four conditions the capacity of water of revegetation potentiality under concrete factor of evaluation according to degree of membership value corresponding to described factor of evaluation;
The fuzzy relation matrix of described destination layer evaluation is:
Preferably, the mobile sand ground revegetation Potential Evaluation information in described high and cold river valley comprises five comment ranks; Be followed successively by strong i.e. I level, more i.e. II level, generally i.e. III level, weak i.e. IV level, very weak i.e. V level.
Compared with prior art, the advantage of the embodiment of the present invention is:
A kind of alpine sandy land revegetation potential evaluation method provided by the invention; analyze its principle known: use the method for zone-by-zone analysis, building revegetation Potential Evaluation model can provide for environmental protection and Eco-environmental Forestry worker the essential information of ecological recovery object as a decision support tool.The revegetation Potential Evaluation model of setting up based on this research, this method is being divided the succession of community stage and is being determined on the basis of recovering target, from four constraint conditions (being weather conditions information B1, topographic condition information B2, soil regime information B3, recovery presence information B4), choose 15 evaluation indexes (being factor of evaluation), carried out mobile sand ground revegetation Potential Evaluation.In the time carrying out revegetation potentiality grade classification by fuzzy mathematics, overcome the ambiguity of information, solve in revegetation process, quantitatively and the quantification problem of qualitative index, tentatively set up the mobile sand ground revegetation potential comprehensive evaluation model in high and cold river valley.According to 15 factors of evaluation (being desired value) of weather conditions, topographic condition, soil regime and four aspects of recovery present situation of specifying, through calculating, can calculate respectively the degree of membership value of output to these four aspects in rule layer; And the degree of membership value of 15 factors of evaluation that in destination layer, it comprises; Can obtain the size of the revegetation potentiality under four different conditions (four different aspects) and 15 factors of evaluation of fuzzy overall evaluation according to the size of above-mentioned degree of membership value; The size of above-mentioned revegetation potentiality can be used for user serve as assessment data, and guides and affects assessment and the formulation of user to alpine sandy land revegetation policy.
Brief description of the drawings
The schematic flow sheet of the alpine sandy land revegetation potential evaluation method that Fig. 1 provides for the embodiment of the present invention;
In the alpine sandy land revegetation potential evaluation method that Fig. 2 provides for the embodiment of the present invention, the structural relation schematic diagram of hierarchy Model of sand ground revegetation Potential Evaluation flows in high and cold river valley.
Embodiment
Also by reference to the accompanying drawings the present invention is described in further detail below by specific embodiment.
Referring to Fig. 1, the embodiment of the present invention provides a kind of alpine sandy land revegetation potential evaluation method, comprises the steps:
Step S100, for the habitat conditions of the dissimilar sand ground of extremely frigid zones, determine its revegetation target;
Step S200, use analytical hierarchy process, set up the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation;
Step S300, utilize the hierarchy Model of described sand ground revegetation Potential Evaluation, development of judgment matrix, Mode of Level Simple Sequence list and the total sorted lists of level;
Step S400, utilization Field Using Fuzzy Comprehensive Assessment, carry out dissimilar sand ground revegetation potential comprehensive evaluation and calculate.
In embodiments of the present invention, use the method for zone-by-zone analysis, building revegetation Potential Evaluation model can provide for environmental protection and Eco-environmental Forestry worker the essential information of ecological recovery object as a decision support tool.The revegetation Potential Evaluation model of setting up based on this research, this method is being divided the succession of community stage and is being determined on the basis of recovering target, from four constraint conditions (being weather conditions information B1, topographic condition information B2, soil regime information B3, recovery presence information B4), choose 15 evaluation indexes (being factor of evaluation), carried out mobile sand ground revegetation Potential Evaluation.In the time carrying out revegetation potentiality grade classification by fuzzy mathematics, overcome the ambiguity of information, solve in revegetation process, quantitatively and the quantification problem of qualitative index, tentatively set up the mobile sand ground revegetation potential comprehensive evaluation model in high and cold river valley.According to 15 desired values of weather conditions, topographic condition, soil regime and four aspects of recovery present situation of specifying, through calculating, can export respectively these four aspects and the good and bad degree of 15 indexs comprising and the overall assessment of revegetation potentiality.
In above-mentioned steps S200, described utilization analytical hierarchy process, sets up the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation, specifically comprises the steps:
Select weather conditions information, topographic condition information, soil regime information, recover the basic index of these four aspects of presence information as the mobile sand ground revegetation Potential Evaluation in high and cold river valley;
According to the basic index of the mobile sand ground revegetation Potential Evaluation in described high and cold river valley, and adopt analytical hierarchy process to build the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation; Fuzzy evaluation is divided into three levels, i.e. destination layer (A), rule layer (B) and indicator layer (C), wherein:
Described destination layer (A) is the highest level of hierarchical structure, realizes the mobile sand ground revegetation Potential Evaluation value in high and cold river valley;
Described rule layer (B) is the Major Systems level of guaranteeing that overall goal realizes, is divided into weather conditions information B1, topographic condition information B2, soil regime information B3, recovers presence information B4; Described indicator layer is the most basic hierarchical structure, comprises weather conditions information B1, topographic condition information B2, soil regime information B3, recovers the concrete factor of evaluation of presence information B4;
Wherein: described weather conditions information B1 comprises the factor of evaluation set of annual precipitation C1, average temperature of the whole year C2, year sunshine time C3; Described topographic condition information B2 comprises the factor of evaluation set of height above sea level C4, gradient C5, slope aspect C6; Described soil regime information B3 comprises the factor of evaluation set of soil moisture C7, P in soil H value C8, soil organism C9, total soil nitrogen C10, soil texture C11, sand dune ground temperature C12; The suitable biological species of described recovery presence information B4 is selected the factor of evaluation set of C13, fence fencing C14, floor treatment C15;
Described factor of evaluation set is: B1={C1, C2, C3}, B2={C4, C5, C6}, B3={C7, C8, C9, C10, C11, C12}, B4={C13, C14, C15}; A={B1, B2, B3, B4}.
In above-mentioned steps S300, utilize the hierarchy Model of described sand ground revegetation Potential Evaluation, development of judgment matrix, Mode of Level Simple Sequence list and the total sorted lists of level, specifically comprise the steps:
Indicator layer from the hierarchy Model of described sand ground revegetation Potential Evaluation starts, the importance of the basic index of the rule layer according to the each factor of evaluation in indicator layer to upper level, adopt manner of comparison between two to form Judgement Matrix, adopt root method to obtain weighted value the normalization computing of each factor of evaluation, by calculating the weight sets (B-C) of indicator layer to rule layer after consistency check: W21, W22, W23, W24; The weighted value of the each factor of evaluation calculating is set up to Mode of Level Simple Sequence list;
Rule layer from the hierarchy Model of described sand ground revegetation Potential Evaluation, according to the importance of the destination layer of each basic index to upper level in rule layer, adopt manner of comparison between two to form Judgement Matrix, adopt root method to obtain weighted value the normalization computing of each basic index, by calculating the weight sets (A-B) of rule layer to destination layer: W1 after consistency check; The weighted value of the each basic index calculating is set up to Mode of Level Simple Sequence list;
Indicator layer is multiplied each other with respect to the weighted value of destination layer with rule layer with respect to the weighted value of rule layer, obtain each factor of evaluation shared weights W in high and cold river valley flows sand ground revegetation Potential Evaluation value; The each factor of evaluation calculating shared weight in high and cold river valley flows sand ground revegetation Potential Evaluation value is set up to the total sorted lists of level.
In above-mentioned steps S400, described utilization Field Using Fuzzy Comprehensive Assessment, carries out dissimilar sand ground revegetation potential comprehensive evaluation and calculates, and specifically comprises the steps:
For the comment threshold value of the default multistage correspondence of each factor of evaluation;
The shared weight scope in multistage comment threshold value in sand ground revegetation Potential Evaluation value that flows in high and cold river valley according to each factor of evaluation, determines each factor of evaluation sand ground revegetation Potential Evaluation information that flows in high and cold river valley;
Determine subordinate function;
Set up fuzzy evaluation matrix;
Build model of fuzzy synthetic evaluation;
Set up model of fuzzy synthetic evaluation; Weight sets W21, W22, W23, W24 and W1 that binding hierarchy analytic approach is definite, based on model of fuzzy synthetic evaluation, build alpine sandy land revegetation potentiality fuzzy overall evaluation rule layer model, and obtain the fuzzy relation matrix list that rule layer is evaluated;
The fuzzy relation matrix list of evaluating according to described rule layer, obtain the degree of membership value of the corresponding different brackets under rule layer mesoclimate conditional information B1, topographic condition information B2, these four different conditions constraints of soil regime information B3, recovery presence information B4, judge the capacity of water of revegetation potentiality under four different conditions according to described degree of membership value;
The fuzzy relation matrix of described rule layer evaluation is:
Weather conditions:
Topographic condition:
Soil regime:
Recover present situation:
Determine alpine sandy land revegetation potentiality fuzzy overall evaluation destination layer model, and obtain the fuzzy relation matrix list that destination layer is evaluated:
The fuzzy relation matrix list of evaluating according to described destination layer, obtain in destination layer the degree of membership value of 15 corresponding different brackets of factor of evaluation that four conditions specifically comprise, judge under four conditions the capacity of water of revegetation potentiality under concrete factor of evaluation according to degree of membership value corresponding to described factor of evaluation;
The fuzzy relation matrix of described destination layer evaluation is:
Preferably, the mobile sand ground revegetation Potential Evaluation information in described high and cold river valley comprises five comment ranks; Be followed successively by strong i.e. I level, more i.e. II level, generally i.e. III level, weak i.e. IV level, very weak i.e. V level.
Below embodiment of the present invention above steps is in the specific implementation elaborated:
The object of the invention is to: unclear for Qinghai-Tibet zones of different, dissimilar alpine sandy land revegetation potentiality, appraisal procedure is substantially blank, the problem such as ecological recovery, effective control of river valley sandstorm that has seriously restricted alpine sandy land, has proposed a kind of extremely frigid zones revegetation potential evaluation method.
1, evaluation object is determined and type division
Select 3 types of drifting sand land in beach, the mobile sand grounds of the mobile sand ground in riverbank and hillside, carry out the dissimilar mobile sand ground revegetation Potential Evaluation in high and cold river valley, middle reaches, the Yarlung Zangbo River, its basic condition is as follows:
(1) drifting sand land in beach: be distributed in the mobile sand ground on river island, valley flat, soil moisture is subject to the impact of rainfall, the rich withered variation of river level and river valley wind-sand activity simultaneously, and main Types comprises active sand dune, sand ribbon, cover Shahe beach and mild grit etc.
(2) sand ground flows on riverbank: be distributed in rank, river (platform) or mobile sand ground on river valley alluvial-proluvial fan, soil moisture mainly relies on rainfall recharge, be subject to the impact of river level variation less, main Types comprises crescent active sand dune, short sand ribbon, mild grit and trellis dune.
(3) the mobile sand ground in hillside: be distributed in the mobile sand ground on hillside, two sides, river valley, middle reaches, the Yarlung Zangbo River are mainly distributed in northern bank, soil moisture mainly relies on rainfall recharge, be not subject to the impact of river level variation, main Types comprise active sand dune, trellis dune and have certain slope grit etc.This type of sand ground gradient is large, also can mark off between windward slope, leeward slope and mound, and top of sand dune is not obvious, is often connected with leeward slope, windward slope.
2, revegetation target is determined
Dividing on the basis in vegetation succession stage (exposed sand, sparse draft, fill with careless transition and shrub community), according to vegetation succession sequence (pioneer stage, period of expansion and climax community), based on study area Physical geographic outline, determine the revegetation target of the dissimilar sand ground in high and cold river valley, the vegetation that is foundation energy self―sustaining covers and has the plant community of stable ecological functions.
3, revegetation Assessment Method on Potential
First use analytical hierarchy process, hierarchical structure, Judgement Matricies, Mode of Level Simple Sequence and consistency check thereof, the level of setting up revegetation Potential Evaluation always sort and consistency check, and by mathematical software MatLab programme computation layer minor sort and consistency check thereof.
Secondly use Field Using Fuzzy Comprehensive Assessment, carry out the evaluation of dissimilar mobile sand ground revegetation potential comprehensive.
4, build revegetation potential comprehensive evaluation model
A. choosing of evaluation index:
In order to make the revegetation Potential evaluation index system can be more scientific, objective and reasonably reflect the revegetation ability of the dissimilar mobile sand ground in high and cold river valley.Evaluation index choose process in should follow following principle.(1) substantivity: the factor of selection should play direct effect to revegetation.(2) ubiquity: in the process of revegetation, some factors vary is all identical for the reaction of revegetation.(3) feasibility: in the time selecting evaluation index, should select relatively to calculate better simply index.
Select the basic index (Fig. 2) of 4 aspects such as weather conditions, topographic condition, soil regime, recovery present situation as the mobile sand ground revegetation Potential Evaluation in high and cold river valley.Adopt analytical hierarchy process to build the hierarchy Model of dissimilar mobile sand ground revegetation Potential Evaluation, fuzzy evaluation is divided into three levels, i.e. destination layer (A), rule layer (B) and indicator layer (C).Factor of evaluation set is: B1={C1, C2, C3}, B2={C4, C5, C6}, B3={C7, C8, C9, C10, C11, C12}, B4={C13, C14, C15}; A={B1, B2, B3, B4}.
Destination layer is the highest level of hierarchical structure, realizes the dissimilar mobile sand ground revegetation Potential Evaluation in high and cold river valley; Rule layer is the Major Systems level of guaranteeing that overall goal realizes, is divided into weather conditions, topographic condition, soil regime, recovery present situation etc.; Indicator layer is the most basic hierarchical structure, comprises all factors of revegetation Potential Evaluation, and these factors are to evaluate the direct mensurable factor of the mobile sand ground revegetation potentiality in high and cold river valley.
B. determining of index weights:
Adopt analytical hierarchy process (AHP), by evaluation index relative importance comparison between any two, calculate weighted value, set up the weight sets W of each evaluation index in revegetation Potential Evaluation.
From indicator layer, the importance according to each index to last layer, adopts manner of comparison between two to form Judgement Matrix, obtains weights the normalization of each index, by obtaining the weight sets of indicator layer to rule layer after consistency check.Determine the weight sets of rule layer to destination layer with same method.Obtain weight sets W21, W22, W23, the W24 of indicator layer to rule layer by analytical hierarchy process, the weight sets W1 of rule layer to destination layer.
(1) Judgement Matricies
Comprehensive pertinent literature and the expert result of giving a mark obtains the judgment matrix of destination layer, rule layer and indicator layer.The each index of rule layer with respect to the judgment matrix of destination layer and weight in table 1.
Table 1: destination layer-rule layer (A-B) judgment matrix and result of calculation
λ as calculated
max=4.1560, depart from coincident indicator CI=0.0520, judge coincident indicator CR=0.0578<0.1.Weight by each index can find out, weather conditions and soil regime are larger on the sand ground revegetation Potential Evaluation impact of flowing of high and cold river valley.
(2) Mode of Level Simple Sequence
The method is first complicated evaluation problem stratification, according to the character of problem and the target that will reach, is different composing factors PROBLEM DECOMPOSITION.
Table 2: rule layer-indicator layer (B-C) judgment matrix and result of calculation
(3) level always sorts:
By each specific targets with respect to the weight of rule layer and rule layer with respect to the multiplied by weight of destination layer, can obtain each index shared weight (table 3) in high and cold river valley flows sand ground revegetation Potential Evaluation.In all indexs, the index that weight accounts for the first five is respectively annual precipitation, soil moisture, fence fencing, average temperature of the whole year, sand dune ground temperature.
To sum up, indicator layer is respectively weight sets W21, W22, W23, the W24 of rule layer, W21=(0.6483,0.2297,0.1220), W22=(0.3325,0.1396,0.5278), W23=(0.4628,0.0597,0.0994,0.0994,0.0494,0.2293), W24=(0.5396,0.2970,0.1634); The weight sets W1=(0.4041 of rule layer to destination layer, 0.0833,0.3188,0.1938).
Table 3: sand ground revegetation Potential evaluation index weight flows in high and cold river valley
C. the foundation of evaluation criterion:
(1) determining of comment collection:
Comment collection is the set that various evaluation results that estimator makes evaluation object form, and represents with V.Determining of evaluation criterion will be determined according to the actual requirements, being generally divided between 3 grades to 9 grades of grade, i.e. and comment collection V={V1, V2 ..., Vm} (3≤m≤9).In the dissimilar mobile sand ground revegetation Potential Evaluation in high and cold river valley, make V={I, II, III, IV, V}, each comment represent respectively strong, stronger, general, and a little less than, very weak }, they represent 5 grade sizes of revegetation potentiality from high to low.Weather conditions and topographic condition have determined the satisfaction degree of the mobile sand ground vegetation growth in high and cold river valley to genetic prerequisite, and soil regime and mankind's interfering activity have determined the satisfaction degree of vegetation growth to the condition day after tomorrow.If vegetation growth congenital and the day after tomorrow condition can be met preferably, think that vegetation growth is easier, the potentiality of revegetation are larger.
(2) foundation of evaluation criterion system:
Impact according to each index on the mobile sand ground revegetation potentiality in high and cold river valley, with reference to expert opinion, has determined evaluation criterion system and the interval (table 4) in 5 grades thereof.
Mobile sand ground revegetation Potential evaluation index interval, the high and cold river valley of table 4
Note: represent expert's scope of giving a mark.
D. determining of subordinate function:
Correct structure subordinate function is the key of fuzzy diagnosis.The establishment of subordinate function does not also have a set of ripe effective method at present, and most of establishment methods also rest on the basis of experience and experiment.The method difference of determining the degree of membership of each index to revegetation potentiality grade (comment collection), for different evaluation indexes, the statement of subordinate function also there are differences.Simple in order to calculate, all think linear change.Subordinate function U (x) can be divided into following 3 types:
(1) guard against mo(u)ld bottom half: x is larger, U (x) value is larger;
(2) guard against mo(u)ld top half: x is less, U (x) value is larger;
(3) symmetry: x and U (x) value is parabolic shape.
Wherein, the subordinate function type of above-mentioned 15 factors of evaluation can be divided into 3 classes, that is: (1) annual precipitation C1, soil moisture C7, soil organism C9, total soil nitrogen C10, slope aspect C6, soil texture C11, fence fencing C14, suitable biological species select C13, floor treatment C15 to belong to ring mo(u)ld bottom half for the subordinate function of grade 1;
(2) height above sea level C4, gradient C5 belong to ring mo(u)ld top half for the subordinate function of grade 1;
(3) average temperature of the whole year C2, year sunshine time C3, soil pH value C8, sand dune ground temperature C12 belong to symmetric form for the subordinate function of grade 1, and the type is middle suitably type.
According to the Pyatyi evaluation criterion of each index, determine the subordinate function of 5 ranks.In the embodiment of the present invention, the mobile sand ground revegetation in determined high and cold river valley is evaluated each index interval division in table 4.The interval intermediate value of choosing each index in table 4 in standard value (table 5) at different levels, obtains i the standard value Sij of index in j level, i=1,2,3 as index ..., 15; J=1,2 ..., 5.
Table 5: the standard value of sand ground revegetation evaluation index in each grade flows in high and cold river valley
(1) the subordinate function formula of ring mo(u)ld top half is:
Wherein,
be respectively the 1st grade, k(k=2,3,4) level, the subordinate function of the index i of the 5th grade.S
ikrepresent the standard value of index i k level.X
irepresent the measured value of index.
(2) the subordinate function formula of ring mo(u)ld bottom half is:
(3) the subordinate function formula of symmetric form is:
E. the foundation of fuzzy evaluation matrix:
In revegetation Potential Evaluation, need to make an appraisal on as if affect the various specific targets of revegetation.Utilize the theoretical foundation of fuzzy mathematics, by necessary computational analysis, obtain the degree of membership that each index belongs to the different comments of comment collection, set up fuzzy evaluation matrix R.
Have i if participate in the index of revegetation Potential Evaluation, revegetation Potential Evaluation standard is made up of j rank, because revegetation potentiality situation and revegetation potential classification standard are all fuzzy, therefore it is proper to carry out partition level boundary by degree of membership.If Rij represents that it (is the degree of membership of i to j that the revegetation potential value of i kind index can be evaluated as the possibility of j kind grade, their relation is subordinate function), so just form the fuzzy relationship matrix r between revegetation Potential evaluation index and grade.
In formula, m represents that evaluation index counts i=1,2 ..., 15; N represents that revegetation potentiality rank is j=1,2,3,4,5.
According to evaluation object measured value and the evaluation criterion value of the sand ground revegetation of flowing, and subordinate function algorithm, determine high and cold river valley drifting sand land in beach, riverbank the flow fuzzy relation matrix (table 6) of sand ground revegetation Potential evaluation index layer of sand ground and hillside that flows.
Table 6: the fuzzy relation matrix of indicator layer
F. the structure of model of fuzzy synthetic evaluation:
The principle of level fuzzy overall evaluation is: first start to evaluate from lowermost layer, and the evaluation result of every layer is considered as to the evaluation collection to last layer index, the index that forms high one deck is evaluated matrix, higher one deck is carried out to comprehensive evaluation, until top evaluation finishes.In the time building hierarchy Model, require the index of considering in each layer must meet independence, not Existence dependency relationship.Therefore the evaluation algorithms of every one deck is identical, and model of fuzzy synthetic evaluation is:
Wherein,
be fuzzy synthesis operational symbol, in fuzzy mathematics, be called fuzzy operator.Fuzzy operator has various ways, and wherein the most frequently used situation is " get and get greatly little operator " and " take advantage of with and operator ".
Weight sets W21, W22, W23, W24 and W1 that binding hierarchy analytic approach is definite, based on model of fuzzy synthetic evaluation, build the mobile sand ground revegetation potentiality fuzzy overall evaluation rule layer model in high and cold river valley as follows:
Weather conditions:
Topographic condition:
Soil regime:
Recover present situation:
The mobile sand ground revegetation potentiality fuzzy overall evaluation destination layer model in high and cold river valley is as follows:
Illustrate:
According to said method, for the dissimilar mobile sand ground revegetation potentiality in high and cold river valley, to the fuzzy relation matrix of rule layer evaluation, in table 7, the fuzzy relation matrix of destination layer evaluation is in table 8.According to maximum membership grade principle, determine the power of the dissimilar mobile sand ground revegetation potentiality in high and cold river valley.
From the evaluation result (table 7) of rule layer, the revegetation potentiality of the lower drifting sand land in beach of weather conditions constraint, the mobile sand ground in riverbank and the mobile sand ground in hillside are the degree of membership maximum (0.6483) of I grade, and both revegetation potentialities are strong.The degree of membership of the lower drifting sand land in beach of topographic condition constraint and the mobile sand ground revegetation potentiality III grade in riverbank is maximum (being respectively 0.5471 and 0.5629), and its revegetation potentiality is general; The degree of membership maximum (0.3167) of the mobile sand ground revegetation potentiality I grade in hillside, its revegetation potentiality is strong.The degree of membership maximum (0.2962) of the lower drifting sand land in beach revegetation potentiality II grade of soil regime constraint, its revegetation potentiality is stronger; The flow degree of membership maximum (0.5299) of sand ground revegetation potentiality IV grade of riverbank, its revegetation potentiality a little less than; The degree of membership maximum (0.4176) of the mobile sand ground revegetation potentiality III grade in hillside, its revegetation potentiality is general.The degree of membership maximum (0.7986) of recovering the lower drifting sand land in beach revegetation potentiality II grade of present situation constraint, its revegetation potentiality is stronger; The degree of membership maximum (0.6538) of the mobile sand ground revegetation potentiality III grade in riverbank, its revegetation potentiality is general; The degree of membership maximum (0.6297) of the mobile sand ground revegetation potentiality II grade in hillside, its revegetation potentiality is stronger.
From the evaluation result (table 8) of destination layer, the degree of membership maximum (0.2869) of drifting sand land in beach revegetation potentiality II grade, its revegetation potentiality is stronger; The flow degree of membership maximum (0.3296) of sand ground revegetation potentiality IV grade of riverbank, its revegetation potentiality a little less than; The degree of membership maximum (0.2884) of the mobile sand ground revegetation potentiality I grade in hillside, its revegetation potentiality is strong.
Table 7: the fuzzy relation matrix of rule layer
It should be noted that, degree of membership belongs to the concept in fuzzy evaluation functions: fuzzy overall evaluation is the highly effective Multifactor Decision Making method of one that the things to being subject to various factors is made thoroughly evaluating, be characterized in that evaluation result is not positive or negative utterly, but with incompatible an expression of fuzzy set.
It should be noted that, building revegetation Potential Evaluation model can provide for environmental protection and Eco-environmental Forestry worker the essential information of ecological recovery object as a decision support tool.The revegetation Potential Evaluation model of setting up based on this research, by the qualitative checking of actual conditions, show that this model evaluation result can reflect the revegetation potentiality of the dissimilar mobile sand ground in high and cold river valley objective and accurately, can be for exploitation extremely frigid zones sand ground revegetation Potential Evaluation System provide core technology support, thus can be country and local relevant departments carry out Qinghai-Tibet zones of different, dissimilar sand ground revegetation is put into practice that science decision foundation is provided.
Therefore, this research, dividing the succession of community stage and determining on the basis of recovering target, has been chosen 15 evaluation indexes from four constraint conditions, has carried out mobile sand ground revegetation Potential Evaluation.In the time carrying out revegetation potentiality grade classification by fuzzy mathematics, overcome the ambiguity of information, solve in revegetation process, quantitatively and the quantification problem of qualitative index, tentatively set up the mobile sand ground revegetation potential comprehensive evaluation model in high and cold river valley.According to 15 factors of evaluation (i.e. 15 desired values) of weather conditions, topographic condition, soil regime and four aspects of recovery present situation of specifying, through calculating, can export respectively these four aspects and the good and bad degree of 15 factors of evaluation comprising and the overall assessment of revegetation potentiality.
Obvious above-mentioned alpine sandy land revegetation potential evaluation method, set up target, evaluation index and evaluation criterion that alpine sandy land manually promotes revegetation, build alpine sandy land revegetation potential comprehensive assessment models under the stress conditions of habitat, solve each factor of evaluation and obtain the mobile sand ground revegetation Potential evaluation index weight in high and cold river valley; Determine the comment threshold value for the default multistage correspondence of each factor of evaluation; The shared weight scope in multistage comment threshold value in sand ground revegetation Potential Evaluation value flows in high and cold river valley according to each factor of evaluation, determine each factor of evaluation in high and cold river valley flow sand ground revegetation Potential Evaluation information, the good and bad degree of 15 indexs that obtain comprising and the overall assessment of revegetation potentiality, it is significant.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (4)
1. an alpine sandy land revegetation potential evaluation method, is characterized in that, comprises the steps:
For the habitat conditions of the dissimilar sand ground of extremely frigid zones, determine its revegetation target;
Use analytical hierarchy process, set up the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation;
Utilize the hierarchy Model of described sand ground revegetation Potential Evaluation, development of judgment matrix, Mode of Level Simple Sequence list and the total sorted lists of level;
Use Field Using Fuzzy Comprehensive Assessment, carry out dissimilar sand ground revegetation potential comprehensive evaluation and calculate.
2. alpine sandy land revegetation potential evaluation method as claimed in claim 1, is characterized in that,
Described utilization analytical hierarchy process, sets up the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation, specifically comprises the steps:
Select weather conditions information, topographic condition information, soil regime information, recover the basic index of these four aspects of presence information as the mobile sand ground revegetation Potential Evaluation in high and cold river valley;
According to the basic index of the mobile sand ground revegetation Potential Evaluation in described high and cold river valley, adopt analytical hierarchy process to build the hierarchy Model of dissimilar sand ground revegetation Potential Evaluation; The hierarchy Model of described sand ground revegetation Potential Evaluation can be divided into three levels, i.e. destination layer (A), rule layer (B) and indicator layer (C), wherein:
Described destination layer (A) is the highest level of hierarchical structure, realizes the mobile sand ground revegetation Potential Evaluation value in high and cold river valley;
Described rule layer (B) is the Major Systems level of guaranteeing that overall goal realizes, is divided into weather conditions information B1, topographic condition information B2, soil regime information B3, recovers presence information B4; Described indicator layer is the most basic hierarchical structure, comprises weather conditions information B1, topographic condition information B2, soil regime information B3, recovers the concrete factor of evaluation of presence information B4;
Wherein: described weather conditions information B1 comprises the factor of evaluation set of annual precipitation C1, average temperature of the whole year C2, year sunshine time C3; Described topographic condition information B2 comprises the factor of evaluation set of height above sea level C4, gradient C5, slope aspect C6; Described soil regime information B3 comprises the factor of evaluation set of soil moisture C7, P in soil H value C8, soil organism C9, total soil nitrogen C10, soil texture C11, sand dune ground temperature C12; The suitable biological species of described recovery presence information B4 is selected the factor of evaluation set of C13, fence fencing C14, floor treatment C15, totally 15 set that factor of evaluation forms;
Described factor of evaluation set is: B1={C1, C2, C3}, B2={C4, C5, C6}, B3={C7, C8, C9, C10, C11, C12}, B4={C13, C14, C15}; A={B1, B2, B3, B4}.
3. alpine sandy land revegetation potential evaluation method as claimed in claim 2, is characterized in that,
Utilize the hierarchy Model of described sand ground revegetation Potential Evaluation, development of judgment matrix, Mode of Level Simple Sequence list and the total sorted lists of level, specifically comprise the steps:
Indicator layer from the hierarchy Model of described sand ground revegetation Potential Evaluation starts, the importance of the basic index of the rule layer according to the each factor of evaluation in indicator layer to upper level, adopt manner of comparison between two to form Judgement Matrix, obtain weighted value the normalization computing of each factor of evaluation, by calculating the weight sets (B-C) of indicator layer to rule layer after consistency check: W21, W22, W23, W24; The weighted value of the each factor of evaluation calculating is set up to Mode of Level Simple Sequence list;
Rule layer from the hierarchy Model of described sand ground revegetation Potential Evaluation, according to the importance of the destination layer of each basic index to upper level in rule layer, adopt manner of comparison between two to form Judgement Matrix, obtain weighted value the normalization computing of each basic index, by calculating the weight sets (A-B) of rule layer to destination layer: W1 after consistency check; The weighted value of the each basic index calculating is set up to Mode of Level Simple Sequence list;
Indicator layer is multiplied each other with respect to the weighted value of destination layer with rule layer with respect to the weighted value of rule layer, obtain each factor of evaluation shared weights W in high and cold river valley flows sand ground revegetation Potential Evaluation value; The each factor of evaluation calculating shared weight in high and cold river valley flows sand ground revegetation Potential Evaluation value is set up to the total sorted lists of level.
4. alpine sandy land revegetation potential evaluation method as claimed in claim 3, is characterized in that,
Described utilization Field Using Fuzzy Comprehensive Assessment, carries out dissimilar sand ground revegetation potential comprehensive evaluation and calculates, and specifically comprises the steps:
For default comment threshold value corresponding to different stage of each factor of evaluation;
The shared weight scope in multistage comment threshold value in sand ground revegetation Potential Evaluation value that flows in high and cold river valley according to each factor of evaluation, determines each factor of evaluation sand ground revegetation Potential Evaluation information that flows in high and cold river valley;
Determine subordinate function:
Determining after the corresponding comment rank that 15 factors of evaluation flow in sand ground revegetation Potential Evaluation information in high and cold river valley respectively, set up evaluation criterion system and the interval list in 5 grades thereof, and establish the subordinate function of 5 comment ranks of each factor of evaluation;
The interval intermediate value of choosing each factor of evaluation in described evaluation criterion system and the interval list in 5 grades thereof as index in standard value at different levels, utilize described subordinate function to calculate i the standard value Sij of index in j level, i=1,2,3 ..., 15; J=1,2 ..., 5;
Wherein, the subordinate function type of above-mentioned 15 factors of evaluation can be divided into 3 classes, that is: (1) annual precipitation C1, soil moisture C7, soil organism C9, total soil nitrogen C10, slope aspect C6, soil texture C11, fence fencing C14, suitable biological species select C13, floor treatment C15 to belong to ring mo(u)ld bottom half for the subordinate function of grade 1;
(2) height above sea level C4, gradient C5 belong to ring mo(u)ld top half for the subordinate function of grade 1;
(3) average temperature of the whole year C2, year sunshine time C3, soil pH value C8, sand dune ground temperature C12 belong to symmetric form for the subordinate function of grade 1;
Set up fuzzy evaluation matrix:
Obtain the degree of membership that each factor of evaluation belongs to different comment ranks, set up fuzzy evaluation matrix R;
Have i if participate in the index of revegetation Potential Evaluation, revegetation Potential Evaluation standard is made up of j rank, because revegetation potentiality situation and revegetation potential classification standard are all fuzzy, therefore it is proper to carry out partition level boundary by degree of membership;
If Rij represents the revegetation potential value of i kind index and can be evaluated as the possibility of j kind grade, so just form the fuzzy relationship matrix r between revegetation Potential evaluation index and grade; According to evaluation object measured value and the evaluation criterion value of sand ground revegetation of flowing, and subordinate function algorithm, determine the fuzzy relationship matrix r of alpine sandy land revegetation Potential evaluation index layer;
Wherein, m represents that evaluation index counts i=1,2 ..., 15; N represents that revegetation potentiality rank is j=1,2,3,4,5; The degree of membership of i to j, their relation is subordinate function;
Build model of fuzzy synthetic evaluation:
Set up model of fuzzy synthetic evaluation:
Wherein,
be fuzzy synthesis operational symbol, in fuzzy mathematics, be called fuzzy operator; Fuzzy operator has various ways, and wherein the most frequently used situation is " get and get greatly little operator " and " take advantage of with and operator ";
Weight sets W21, W22, W23, W24 and W1 that binding hierarchy analytic approach is definite, based on model of fuzzy synthetic evaluation, build alpine sandy land revegetation potentiality fuzzy overall evaluation rule layer model, and obtain the fuzzy relation matrix list that rule layer is evaluated;
The fuzzy relation matrix list of evaluating according to described rule layer, obtain the degree of membership value of the corresponding different brackets under rule layer mesoclimate conditional information B1, topographic condition information B2, these four different conditions constraints of soil regime information B3, recovery presence information B4, judge the capacity of water of revegetation potentiality under four different conditions according to described degree of membership value;
The fuzzy relation matrix of described rule layer evaluation is:
Weather conditions:
Topographic condition:
Soil regime:
Recover present situation:
Determine alpine sandy land revegetation potentiality fuzzy overall evaluation destination layer model, and obtain the fuzzy relation matrix list that destination layer is evaluated:
The fuzzy relation matrix list of evaluating according to described destination layer, obtain in destination layer the degree of membership value of 15 corresponding different brackets of factor of evaluation that four conditions specifically comprise, judge under four conditions the capacity of water of revegetation potentiality under concrete factor of evaluation according to degree of membership value corresponding to described factor of evaluation;
The fuzzy relation matrix of described destination layer evaluation is:
5. alpine sandy land revegetation potential evaluation method as claimed in claim 4, it is characterized in that,
The mobile sand ground revegetation Potential Evaluation information in described high and cold river valley comprises five comment ranks; Be followed successively by strong i.e. I level, more i.e. II level, generally i.e. III level, weak i.e. IV level, very weak i.e. V level.
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| CN104298889A (en) * | 2014-09-28 | 2015-01-21 | 中国矿业大学(北京) | Method of comprehensive assessment for heavy metal pollution of metal slag and soil |
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Inventor after: Li Haidong Inventor after: Lu Junqing Inventor after: Shen Weishou Inventor after: Tian Meirong Inventor after: Fang Ying Inventor after: Yan Shouguang Inventor before: Li Haidong Inventor before: Shen Weishou Inventor before: Tian Meirong Inventor before: Fang Ying |
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| COR | Change of bibliographic data |
Free format text: CORRECT: INVENTOR; FROM: LI HAIDONG SHEN WEISHOU TIAN MEIRONG FANG YING TO: LI HAIDONG LU JUNQING SHEN WEISHOU TIAN MEIRONG FANG YING YAN SHOUGUANG |
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| C14 | Grant of patent or utility model | ||
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| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20161214 |