CN107957982A - Secondary Geological Hazards liability fast evaluation method and system after shake - Google Patents

Secondary Geological Hazards liability fast evaluation method and system after shake Download PDF

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CN107957982A
CN107957982A CN201711266808.4A CN201711266808A CN107957982A CN 107957982 A CN107957982 A CN 107957982A CN 201711266808 A CN201711266808 A CN 201711266808A CN 107957982 A CN107957982 A CN 107957982A
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function
fitting
value
evaluation index
geological
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CN107957982B (en
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陈玉
王钦军
魏永明
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Institute of Remote Sensing and Digital Earth of CAS
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Institute of Remote Sensing and Digital Earth of CAS
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism

Abstract

Secondary Geological Hazards liability fast evaluation method and system after being shaken the invention discloses one kind, including：Determine the evaluation index of susceptibility of geological hazards after shaking, each evaluation index is quantized, and discretization is carried out to continuous variable, obtain the sample point of sample areas, geological disaster proportion in the corresponding discrete partition of Calculation Estimation index, determine the corresponding fitting function of each evaluation index, the value of each evaluation index in each sample point is inputted into corresponding fitting function respectively, obtain sensitiveness result of calculation, determine the assessment models of Secondary Geological Hazards liability rapid evaluation after shaking, for any one point to be assessed, the corresponding sensitiveness result of calculation of each evaluation index of point to be assessed is substituted into assessment models, obtained value is closer to 0, represent that evaluation point is less susceptible to geological disaster after shaking, obtained value is closer to 1, represent evaluation point is easier shake after geological disaster.By the present invention, Secondary Geological Hazards assessment of easy generation accuracy after shake is improved.

Description

Secondary Geological Hazards liability fast evaluation method and system after shake
Technical field
The present invention relates to geological information processing technology field, and Secondary Geological Hazards are easily sent out after being shaken more particularly, to one kind Property fast evaluation method and system.
Background technology
Secondary Geological Hazards assessment of easy generation method can be divided into qualitative method, semi-quantitative method and quantitative square after existing shake Method three classes.Qualitative method is mainly based upon the experience accumulation of expert or field condition judges, provides geology calamity in monomer or region For evil assessment of easy generation as a result, such method fully relies on expertise, subjectivity is too strong, is subject to expert's academic level and to commenting The limitation of valency region understanding, assessment result objectivity is poor, and accuracy is not corresponding also high；Semi-quantitative method is recognized based on expert Determine the segmentation assignment of geological disaster factor of influence and the weight of each factor, the current most widely used analytic approach that has levels should Class method still has the shortcomings that randomness is strong, quantification is insufficient, and assessment result accuracy is than relatively low；Quantitative approach is formally Want stringenter, obtained in a manner of numerical computations as a result, existing geological disaster distribution situation is mainly utilized, based on mathematics system Meter or the intelligent model such as artificial neural network, support vector machines establish occurred geological disaster and the geological disaster image factor it Between relation function, such method lacks regional geohazardss Disaster mechanism sufficiently analysis profit based entirely on mathematical computations With assessment result accuracy is also than relatively low.
Therefore it provides Secondary Geological Hazards liability fast evaluation method and system after a kind of high shake of accuracy, are these Field urgent problem to be solved.
The content of the invention
In view of this, Secondary Geological Hazards liability fast evaluation method and system after being shaken the present invention provides one kind, solution Determine technical problem relatively low to Secondary Geological Hazards assessment of easy generation accuracy after shake in the prior art.
The present invention provides Secondary Geological Hazards liability fast evaluation method after a kind of shake, and this method includes：After determining shake N evaluation index of susceptibility of geological hazards, wherein, n evaluation indexes include description seismic signature, topography and geomorphology, Matter condition, hydrologic condition, the index of Information of Ancient Human Activity and surface vegetation；Each evaluation index is quantized, is obtained Discrete variable or continuous variable, wherein, the discrete variable includes some discrete partitions；By the continuous variable into Row discretization, obtains the corresponding some discrete partitions of the continuous variable；Obtain incomplete high score remote sensing image data after shaking The area of coverage is as sample areas；Multiple samples that geological disaster has occurred in the sample areas are obtained according to the image data This point；Non- geological disaster generation area in the sample areas randomly chooses multiple sample points that geological disaster does not occur, Wherein, the value of each sample point includes (Z, W), wherein, during Z=0, geological disaster do not occur for expression, and during Z=1, expression is Generation geological disaster, W=(w1, w2, w3…wn), wherein, w1, w2, w3…wnThe value of respectively one evaluation index；Using The following formula calculates geological disaster proportion in the corresponding discrete partition of the evaluation index：Pi=Ai/Asum, its In, PiFor geological disaster proportion in i-th of discrete partition of the evaluation index, AiFor in i-th of discrete partition The quantity of the sample point of geological disaster, A occurssumFor the quantity of the sample point of geological disaster has occurred in the sample areas；It is right In each evaluation index, using the value of evaluation index described in each sample point as input, with each sample point Described in evaluation index value residing for discrete partition in geological disaster proportion be output, carry out Function Fitting, obtain every The corresponding fitting function of a evaluation index；By the value w of each evaluation index in each sample point1, w2, w3…wn, Corresponding fitting function is inputted respectively, obtains the corresponding sensitiveness result of calculation of each evaluation index of the sample point, its In, w1, w2, w3…wnThe sensitiveness result of calculation being corresponding in turn to is x1, x2, x3…xn；Secondary Geological Hazards are easy after determining shake The mathematical model of hair property rapid evaluation：Wherein, p is secondary after a point to be assessed shakes The assessment result of geological disaster, x1, x2, x3…xnCalculated for the corresponding sensitiveness of each evaluation index of the point to be assessed As a result；By the x of all sample points1, x2, x3…xnThe mathematical model is substituted into respectively, it is true using logistic regression analysis method Determine logistic regression coefficient a, b1, b2, b3…bnValue；By logistic regression the coefficient a, b1, b2, b3…bnValue substitute into the number Model is learned, obtains assessment models；For any one of point to be assessed, by each evaluation index pair of the point to be assessed The sensitiveness result of calculation answered substitutes into the assessment models, and the value of obtained p represents that the evaluation point is less susceptible to closer to 0 Geological disaster after shaking, the value of obtained p is closer to 1, geological disaster after representing that the evaluation point is easier and shaking.
Further, describing the index of the seismic signature includes macroscopic epicenter and earthquake intensity, with describing the landform The index of looks includes elevation, the gradient and slope aspect, describes the index of the geological conditions and includes rock soil mass types and rift structure, retouches Stating the index of the hydrologic condition includes water system and rainfall, and describing the index of the Information of Ancient Human Activity includes road information, retouches The index for stating the surface vegetation is vegetation cover degree.
Further, each evaluation index is carried out numeralization includes：The macroscopic epicenter numerical value is turned into distance shake In Euclidean distance；The earthquake intensity numerical value is turned into earthquake intensity grade；The elevation numerical value is turned into height value；By the slope Number of degrees value is value of slope；The slope aspect numerical value is turned into slope aspect value；The rock soil mass types numerical value is turned into symbol, wherein, The different rock soil mass types numerical value turn to different symbols；The numeralization of the rift structure is included principal earthquake number of fracture Value be apart from principal earthquake be broken Euclidean distance and by the principal earthquake be broken outside fracture numeralization be apart from all fractures most Short distance；It is apart from water-based beeline by water system numeralization；The rainfall numerical value is turned into rainfall；By the road Road information value turns to the distance apart from road；And by the value of the vegetation cover number of degrees it is vegetation cover angle value.
Further, the mathematical function used when carrying out Function Fitting to the macroscopic epicenter includes inverse function and linear letter Number, using the higher fitting result of the fitting precision for using inverse function and linear function obtain after Function Fitting as described grand See the corresponding fitting function in earthquake centre；When Function Fitting is carried out to the earthquake intensity mathematical function that uses include exponential function, Linear function and piecewise function, wherein, for the discrete partition of the earthquake intensity grade more than or equal to 10, index will be used The higher fitting result of fitting precision that function and linear function obtained after Function Fitting is corresponded to as the earthquake intensity Fitting function, otherwise using piecewise function, directly with geological disaster proportion in each discrete regions as a result；To institute Stating the mathematical function that elevation used during Function Fitting includes linear function, quadratic function and cubic function, when using linear When the fitting precision that function obtained after Function Fitting is greater than or equal to 0.6, after linear function being used to carry out Function Fitting Obtained fitting result is as the corresponding fitting function of the elevation, the plan obtained after Function Fitting is carried out using linear function When closing precision less than 0.6, the fitting precision that will carry out obtaining after Function Fitting using quadratic function is greater than or equal to 0.6 fitting As a result the corresponding fitting function of the elevation is used as, the fitting precision obtained after quadratic function carries out Function Fitting is less than 0.6 When, using the fitting result for using cubic function obtain after Function Fitting as the corresponding fitting function of the elevation；To institute Stating the mathematical function that the gradient used during Function Fitting includes quadratic function and cubic function, when using quadratic function progress letter , will be using the fitting obtained after quadratic function progress Function Fitting when the fitting precision obtained after number fitting is greater than or equal to 0.6 As a result the corresponding fitting function of the gradient is used as, the fitting precision obtained after Function Fitting is carried out using quadratic function is less than When 0.6, using the fitting result for using cubic function obtain after Function Fitting as the corresponding fitting function of the gradient；It is right The mathematical function that the slope aspect used during Function Fitting includes cubic function；Function Fitting is carried out to the rock soil mass types The mathematical function of Shi Caiyong includes piecewise function；Numeralization to the rift structure, which includes being broken principal earthquake, carries out Function Fitting The mathematical function of Shi Caiyong includes linear function and inverse function, is obtained after using inverse function and linear function progress Function Fitting The higher fitting result of fitting precision as the corresponding fitting function of the rift structure；Function Fitting is carried out to the water system The mathematical function of Shi Caiyong includes linear function and inverse function, is obtained after using inverse function and linear function progress Function Fitting The higher fitting result of fitting precision as the corresponding fitting function of the water system；Adopted when carrying out Function Fitting to the rainfall Mathematical function includes linear function and inverse function, the plan that using inverse function and linear function will obtain after Function Fitting The higher fitting result of precision is closed as the corresponding fitting function of the rainfall；Adopted when carrying out Function Fitting to the road information Mathematical function includes linear function and inverse function, the plan that using inverse function and linear function will obtain after Function Fitting The higher fitting result of precision is closed as the corresponding fitting function of the road information；And letter is carried out to earth's surface vegetation coverage The mathematical function used during number fitting includes linear function and inverse function, and inverse function and linear function will be used to carry out Function Fitting The higher fitting result of the fitting precision that obtains afterwards is as the corresponding fitting function of the vegetation cover degree.
Further, multiple samples that geological disaster has occurred in the sample areas are obtained according to the image data The step of point, includes：The region that geological disaster has occurred in the image data is subjected to net with 30 meters * 30 meters for base unit Format；During sampling, represent region of the area scale less than or equal to 30 meters * 30 meters as a sample point, often exceed 30 meters of * 30 meters of increases, one sample point.
Further, the number phase of sample point of the number of the sample point of geological disaster with geological disaster has occurred does not occur Together.
Further, the continuous variable is subjected to discretization, it is corresponding some discrete obtains the continuous variable Subregion includes：The continuous variable is divided into by 30 discrete partitions using geometry partitioning method.
The present invention provides Secondary Geological Hazards liability RES(rapid evaluation system) after a kind of shake, which includes：Evaluation index Determining module, for determining n evaluation index of susceptibility of geological hazards after shaking, wherein, the n evaluation indexes include description Seismic signature, topography and geomorphology, geological conditions, hydrologic condition, the index of Information of Ancient Human Activity and surface vegetation；Evaluation index numerical value Change module, for each evaluation index to be quantized, obtain discrete variable or continuous variable, wherein, it is described from Dissipating type variable includes some discrete partitions；Evaluation index discrete block, for the continuous variable to be carried out discretization, obtains The corresponding some discrete partitions of the continuous variable；Sample areas acquisition module, incomplete high score remote sensing after being shaken for acquisition The image data area of coverage is as sample areas；Sample point sampling module, for obtaining the sample area according to the image data Multiple sample points that geological disaster has occurred in domain, and the non-geological disaster generation area in the sample areas is selected at random Multiple sample points that geological disaster does not occur are selected, wherein, the value of each sample point includes (Z, W), wherein, during Z=0, table Show and geological disaster does not occur, during Z=1, geological disaster, W=(w have occurred for expression1, w2, w3…wn), wherein, w1, w2, w3…wnPoint Not Wei an evaluation index value；Geological disaster proportion computing module, for calculating institute's commentary using the following formula Geological disaster proportion is in the corresponding discrete partition of valency index：Pi=Ai/Asum, wherein, PiFor the evaluation index I-th of discrete partition in geological disaster proportion, AiFor the sample of geological disaster has occurred in i-th of discrete partition The quantity of point, AsumFor the quantity of the sample point of geological disaster has occurred in the sample areas；Function Fitting module, for pair In each evaluation index, using the value of evaluation index described in each sample point as input, with each sample point Described in evaluation index value residing for discrete partition in geological disaster proportion be output, carry out Function Fitting, obtain every The corresponding fitting function of a evaluation index；Sensitiveness result of calculation computing module, it is each in each sample point for inciting somebody to action The value w of the evaluation index1, w2, w3…wn, corresponding fitting function is inputted respectively, obtains each evaluation of the sample point The corresponding sensitiveness result of calculation of index, wherein, w1, w2, w3…wnThe sensitiveness result of calculation being corresponding in turn to is x1, x2, x3…xn；Mathematical model determining module, for determining the mathematical model of Secondary Geological Hazards liability rapid evaluation after shaking：Wherein, the assessment result of Secondary Geological Hazards, x after p shakes for a point to be assessed1, x2, x3…xnFor the corresponding sensitiveness result of calculation of each evaluation index of the point to be assessed；Logistic regression coefficient determines mould Block, the x for all sample points1, x2, x3…xnThe mathematical model is substituted into respectively, it is true using logistic regression analysis method Determine logistic regression coefficient a, b1, b2, b3…bnValue；Assessment models determining module, for by logistic regression the coefficient a, b1, b2, b3…bnValue substitute into the mathematical model, obtain assessment models；Assessment of Geological Hazard module after shaking, for by described in Each evaluation index corresponding sensitiveness result of calculation substitution assessment models of point to be assessed, the value of obtained p more connect Nearly 0, represent that the value for the p that the evaluation point is less susceptible to geological disaster after shaking, and obtains closer to 1, represents the evaluation point It is easier shake after geological disaster.
Further, describing the index of the seismic signature includes macroscopic epicenter and earthquake intensity, with describing the landform The index of looks includes elevation, the gradient and slope aspect, describes the index of the geological conditions and includes rock soil mass types and rift structure, retouches Stating the index of the hydrologic condition includes water system and rainfall, and describing the index of the Information of Ancient Human Activity includes road information, retouches The index for stating the surface vegetation is vegetation cover degree.
Further, the step of evaluation index numeralization module is when each evaluation index is quantized, execution is wrapped Include：The macroscopic epicenter numerical value is turned to the Euclidean distance apart from earthquake centre；The earthquake intensity numerical value is turned into earthquake intensity grade；Will The elevation numerical value turns to height value；It is value of slope by gradient numeralization；The slope aspect numerical value is turned into slope aspect value；By institute State rock soil mass types numerical value and turn to symbol, wherein, the different rock soil mass types numerical value turns to different symbols；Will be described disconnected Splitting the numeralization of construction includes principal earthquake fracture numeralization being outside being broken Euclidean distance apart from principal earthquake and being broken the principal earthquake Fracture numeralization be apart from all fractures beeline；It is apart from water-based beeline by water system numeralization；Will The rainfall numerical value turns to rainfall；The road information numerical value is turned to the distance apart from road；And surface vegetation is covered Cover degree numerical value turns to vegetation cover angle value.
Compared with prior art, Secondary Geological Hazards liability fast evaluation method and system after shake of the invention, are realized Following beneficial effect：The Space Elements information of the extensive Secondary Geological Hazards of great earthquake-induced is fully excavated, to secondary The single evaluation index of raw disaster, namely single-factor influent factor carry out curve fitting, and avoid being absorbed in traditional Evaluation of Geologic Hazards Present in " monotonicity trap ", weight coefficient finally is determined to multiple single-factor fitting result logic-based homing methods, and Obtain in area secondary disaster evaluation of probability of occurrence after shake as a result, it is possible to it is quick and accurately evaluate shake after Secondary Geological Hazards it is whether easy Hair.
By referring to the drawings to the present invention exemplary embodiment detailed description, further feature of the invention and its Advantage will be made apparent from.
Brief description of the drawings
It is combined in the description and the attached drawing of a part for constitution instruction shows the embodiment of the present invention, and even It is used to explain the principle of the present invention together with its explanation.
Fig. 1 be the embodiment of the present invention 1 described in shake after Secondary Geological Hazards liability fast evaluation method flow chart；
Fig. 2 be the embodiment of the present invention 2 described in shake after Secondary Geological Hazards liability fast evaluation method flow chart；
Fig. 3 be the embodiment of the present invention 3 described in shake after Secondary Geological Hazards liability RES(rapid evaluation system) block diagram.
Embodiment
Carry out the various exemplary embodiments of detailed description of the present invention now with reference to attached drawing.It should be noted that：Unless in addition have Body illustrates that the unlimited system of component and the positioned opposite of step, numerical expression and the numerical value otherwise illustrated in these embodiments is originally The scope of invention.
The description only actually at least one exemplary embodiment is illustrative to be never used as to the present invention below And its application or any restrictions that use.
It may be not discussed in detail for technology, method and apparatus known to person of ordinary skill in the relevant, but suitable In the case of, the technology, method and apparatus should be considered as part for specification.
In shown here and discussion all examples, any occurrence should be construed as merely exemplary, without It is as limitation.Therefore, other examples of exemplary embodiment can have different values.
It should be noted that：Similar label and letter represents similar terms in following attached drawing, therefore, once a certain Xiang Yi It is defined, then it need not be further discussed in subsequent attached drawing in a attached drawing.
Embodiment 1
The embodiment of the present invention 1 describes Secondary Geological Hazards liability fast evaluation method after a kind of shake, and Fig. 1 is the present invention The flow chart of Secondary Geological Hazards liability fast evaluation method after shake described in embodiment 1, as shown in Figure 1, the appraisal procedure Including steps S101 to step S113.
Step S101：Determine n evaluation index of susceptibility of geological hazards after shaking.
Wherein, n is the integer more than or equal to 3, and in this embodiment, it is special that definite evaluation index includes description earthquake Sign, topography and geomorphology, geological conditions, hydrologic condition, the index of Information of Ancient Human Activity and surface vegetation, can be with for same feature Described using one or more evaluation indexes, for example, special using macroscopic epicenter and two evaluation index evaluation earthquakes of earthquake intensity Sign.
Step S102：Each evaluation index is quantized, obtains discrete variable or continuous variable.
In this step, the process of numeralization refers to each evaluation index being converted to numerical value, wherein, a part of evaluation index Discrete variable is directly obtained after numeralization, which includes some discrete partitions, another part evaluation index numerical value That obtained after change is continuous variable.
Step S103：Continuous variable is subjected to discretization, obtains the corresponding some discrete partitions of continuous variable.
In this step, the continuous variable obtained to step S102 carries out sliding-model control, and continuous variable is also turned Discreteness variable is changed to, so as to obtain the corresponding some discrete partitions of continuous variable, it is preferable that be by continuous variable is discrete 25 to 35 discrete partitions, on the one hand, continuity can more accurately be covered by the number of appropriate number of discrete partition and become The numerical value of amount, on the other hand, avoids data processing amount excessive by the number of appropriate number of discrete partition.
Step S104：The incomplete high score remote sensing image data area of coverage is as sample areas after obtaining shake.
Can be by the region for actually occurring earthquake, the incomplete high score remote sensing image data area of coverage is as sample area after shake Domain, sample point is extracted in the sample areas.
Step S105：Multiple sample points that geological disaster has occurred in sample areas are obtained according to image data.
Step S106：Multiple geological disaster does not occur for the non-geological disaster generation area random selection in sample areas Sample point.
Wherein, the sample point of geological disaster has either occurred, the sample point of geological disaster, each sample still do not occur The value of point includes (Z, W), wherein, during Z=0, geological disaster do not occur for expression, during Z=1, represents that geological disaster has occurred, W =(w1, w2, w3…wn), wherein, w1, w2, w3…wnThe value of respectively one evaluation index.
Step S107：Geological disaster proportion in the corresponding discrete partition of Calculation Estimation index.
For each evaluation index, after above-mentioned steps S102 numeralizations and step S103 discretizations, correspond to respectively multiple Discrete partition, to each discrete partition of each evaluation index, calculates geological disaster in discrete partition using the following formula and sends out Raw ratio：
Pi=Ai/Asum
Wherein, PiFor geological disaster proportion in i-th of discrete partition of an evaluation index, AiFor i-th discrete point The quantity of the sample point of geological disaster, A have occurred in areasumFor the quantity of the sample point of geological disaster has occurred in sample areas.
By the step, for the value w of each evaluation index of each sample point1, w2, w3…wn, can be commented according to each Valency refers to the discrete partition residing for target value, determines a geological disaster proportion.
Step S108：For each evaluation index, using the value of evaluation index in each sample point as input, with each sample Geological disaster proportion is output in discrete partition in point residing for the value of evaluation index, carries out Function Fitting, obtains each The corresponding fitting function of evaluation index.
For each evaluation index, the value of an evaluation index is corresponding with each sample point, if Q sample Point, then each evaluation index there is Q value, using the value of each evaluation index as inputting, namely independent variable will pass through above-mentioned step Geological disaster proportion is output in discrete partition residing for the value for each evaluation index that rapid S107 is determined, namely because becoming Amount, carries out Function Fitting, can obtain the corresponding fitting function of each evaluation index.
Step S109：By the value w of each evaluation index in each sample point1, w2, w3…wn, corresponding fitting letter is inputted respectively Number, obtains the corresponding sensitiveness result of calculation of each evaluation index of sample point.
For example, w1, w2, w3…wnThe first evaluation index, the second evaluation index, the 3rd evaluation index value n-th are followed successively by respectively The value of evaluation index, then by w1Substitute into the independent variable of the corresponding fitting function of the first evaluation index, obtain sensitiveness and calculate knot Fruit x1, by w2Substitute into the independent variable of the corresponding fitting function of the second evaluation index, obtain sensitiveness result of calculation x2, with such Push away, w1, w2, w3…wnThe sensitiveness result of calculation being corresponding in turn to is x1, x2, x3…xn。
Step S110：Determine the mathematical model of Secondary Geological Hazards liability rapid evaluation after shaking.
Using number sequence moduleAs Secondary Geological Hazards liability rapid evaluation after shake Model, wherein, the assessment result of Secondary Geological Hazards, x after p shakes for a point to be assessed1, x2, x3…xnFor point to be assessed The corresponding sensitiveness result of calculation of each evaluation index.
Step S111：By the x of all sample points1, x2, x3…xnMathematical model is substituted into respectively, using logistic regression analysis side Method determines logistic regression coefficient a, b1, b2, b3…bnValue.
In this step, each sample point of geological disaster will occur and each sample point of geological disaster does not occur Each sensitiveness result of calculation substitute into above-mentioned mathematical model, the value of each parameter in mathematical model is calculated.
Step S112：By logistic regression coefficient a, b1, b2, b3…bnValue substitute into mathematical model, obtain assessment models.
The value for the parameters being calculated is substituted into mathematical model in this step, assessment models are obtained, for The region of earthquake occurs, the value of each evaluation index in the region can be gathered, and the value of evaluation index is substituted into corresponding plan Function is closed, the corresponding sensitiveness result of calculation of each evaluation index is obtained, then using following step S112, obtains assessment result.
Step S113：For any one point to be assessed, the corresponding sensitiveness of each evaluation index of point to be assessed is calculated As a result assessment models are substituted into, the value of obtained p represents that evaluation point is less susceptible to geological disaster after shaking, obtain closer to 0 The value of p is closer to 1, geological disaster after representing that evaluation point is easier and shaking.
Using the embodiment, the Space Elements information of the extensive Secondary Geological Hazards of great earthquake-induced is fully excavated, Definite evaluation index includes description seismic signature, topography and geomorphology, geological conditions, hydrologic condition, Information of Ancient Human Activity and earth's surface The index of vegetation, carries out curve fitting the single evaluation index of secondary disaster, namely single-factor influent factor, avoids being absorbed in biography Unite present in Evaluation of Geologic Hazards " monotonicity trap ", it is finally true to multiple single-factor fitting result logic-based homing methods Determine weight coefficient, and obtain shaken in area after secondary disaster evaluation of probability of occurrence as a result, it is possible to quick and accurately evaluate secondary after shake Whether geological disaster is easily sent out.
Embodiment 2
The embodiment of the present invention 2 describes Secondary Geological Hazards liability fast evaluation method after a kind of preferably earthquake, the reality Example 2 is applied on the basis of above-described embodiment 1, further describes the invention thought of the present invention, related part can be referred to mutually.Figure 2 for Secondary Geological Hazards liability fast evaluation method after the shake described in the embodiment of the present invention 2 flow chart, as shown in Fig. 2, should Appraisal procedure includes the steps.
Step is 1.：Susceptibility of geological hazards evaluation index after being shaken in region is obtained, it is (such as grand to specifically include evaluation seismic signature See earthquake centre, earthquake intensity etc.), topography and geomorphology (such as elevation, the gradient, slope aspect), geological conditions (such as rock soil mass types, fracture structure Make), hydrologic condition (such as water system, rainfall), Information of Ancient Human Activity (such as road), the index of vegetation cover degree etc..
Step is 2.：Evaluation index quantify, also will each evaluation index quantize, numeralization specific method it is as follows：
Macroscopic epicenter：Apart from earthquake centre Euclidean distance (tiff forms, unit：Rice)
Earthquake intensity：Earthquake intensity grade (shp forms, unit：Degree)
Elevation：Height value (tiff forms, unit：Rice)
The gradient：Value of slope (tiff forms, unit：Degree)
Slope aspect：Slope aspect value (tiff forms, unit：Degree)
Rock soil mass types：Symbol marks (shp forms, unit：Nothing)
Principal earthquake is broken：Euclidean distance (tiff forms, unit are broken apart from principal earthquake：Rice)
Other fractures：Apart from all fracture beeline (tiff forms, units：Rice)
Water system：Apart from water system beeline (tiff forms, unit：Rice)
Rainfall：Rainfall (tiff forms, unit：Mm/y or mm/24h)
Road：Apart from road distance (tiff forms, unit：Rice)
Vegetative coverage：Vegetative coverage NDVI (tiff forms, unit：Dimensionless)
Step is 3.：According to the attribute of evaluation index, discretization is carried out to the evaluation index of continuous type：
To discrete variable (such as：Lithology, earthquake intensity subregion) retain its discrete partition, to continuous variable (such as gradient, Slope aspect, distance construct distance etc.) turn to 25-35 subregion according to the progress of its numerical value is discrete.
Step is 4.：Calculate each discrete partition geological disaster proportion：
Geological disaster proportion is defined as：
Pi=Ai/Asum
Pi:Geological disaster proportion in discrete partition i；Ai：Geology disaster samples number has occurred in discrete partition i；Asum： Geology disaster samples number occurs in statistical regions A altogether.
Step is 5.：Disaster resampling has occurred after shake.
The incomplete high score remote sensing image data area of coverage obtained after shake is defined as A areas, interprets earthquake-induced in A areas Geological disaster is distributed.Geological disaster is converted to 30*30 meters of Poit data, and (* 30 meters of area scale≤30 meter are with a sample point Represent, often more than 30 meters * 30 meters according to one sample points of sampling rule increase).
Step is 6.：Disaster point sampling does not occur after shake.
Non- geological disaster generation area random selection sample point, quantity keep one with disaster samples point has occurred in A areas Cause, sample point, which is tried one's best, covers the different subregions of all evaluation indexes.
Step is 7.：Single-factor based on Geographical Laws, namely single evaluation index carry out curve fitting.
Specifically, in fitting, for different evaluation indexes, following fit procedure is respectively adopted：
The mathematical function used when carrying out Function Fitting to macroscopic epicenter includes inverse function and linear function, will use inverse letter The higher fitting result of obtained fitting precision is as the corresponding fitting of macroscopic epicenter after number and linear function progress Function Fittings Function；
The mathematical function used when carrying out Function Fitting to earthquake intensity includes exponential function, linear function and segmentation letter Number, wherein, for discrete partition of the earthquake intensity grade more than or equal to 10, exponential function and linear function will be used to intend into line function The higher fitting result of the fitting precision that is obtained after conjunction is as the corresponding fitting function of earthquake intensity, otherwise using piecewise function, Directly with geological disaster proportion in each discrete regions as a result；
The mathematical function used when carrying out Function Fitting to elevation includes linear function, quadratic function and cubic function, when When the fitting precision for using linear function obtain after Function Fitting is greater than or equal to 0.6, linear function will be used to carry out letter The fitting result obtained after number fitting is obtained as the corresponding fitting function of elevation after Function Fitting is carried out using linear function Fitting precision when being less than 0.6, obtained fitting precision after Function Fitting will be carried out using quadratic function more than or equal to 0.6 For fitting result as the corresponding fitting function of elevation, the fitting precision obtained after quadratic function carries out Function Fitting is less than 0.6 When, using the fitting result for using cubic function obtain after Function Fitting as the corresponding fitting function of elevation；
The mathematical function used when carrying out Function Fitting to the gradient includes quadratic function and cubic function, when using secondary letter When counting the fitting precision for carrying out being obtained after Function Fitting more than or equal to 0.6, quadratic function will be used to be obtained after carrying out Function Fitting The fitting result arrived is as the corresponding fitting function of the gradient, the fitting precision obtained after Function Fitting is carried out using quadratic function During less than 0.6, using the fitting result for using cubic function obtain after Function Fitting as the corresponding fitting function of the gradient；
The mathematical function used when carrying out Function Fitting to slope aspect includes cubic function；
The mathematical function used when carrying out Function Fitting to rock soil mass types includes piecewise function；
The mathematical function that numeralization to rift structure uses when including and being broken to principal earthquake and carry out Function Fitting includes linear Function and inverse function, by using the higher fitting result of the fitting precision obtained after inverse function and linear function progress Function Fitting As the corresponding fitting function of rift structure；
The mathematical function that uses includes linear function and inverse function when carrying out Function Fitting to water system, will use inverse function with Linear function carries out the higher fitting result of obtained fitting precision after Function Fitting as the corresponding fitting function of water system；
The mathematical function that uses includes linear function and inverse function when carrying out Function Fitting to rainfall, will use inverse function with Linear function carries out the higher fitting result of obtained fitting precision after Function Fitting as the corresponding fitting function of rainfall；
The mathematical function used when carrying out Function Fitting to road information includes linear function and inverse function, will use inverse letter The higher fitting result of obtained fitting precision is as the corresponding fitting of road information after number and linear function progress Function Fittings Function；And
The mathematical function used when carrying out Function Fitting to earth's surface vegetation coverage includes linear function and inverse function, will adopt The fitting result higher by the use of the fitting precision obtained after inverse function and linear function progress Function Fitting is used as vegetation cover Spend corresponding fitting function.
Step is 8.：Multiple-factor logistic regression
Using single-factor sensitiveness result of calculation as independent variable, disaster samples point (Y=1) occurs and disaster sample does not occur This point (Y=0) is used as dependent variable, carries out multiple-factor logistic regression.
Logistic regression analysis is the regression analysis to qualitative variable, its logical function form is：
According to the definition of discrete random variable desired value, with P represent independent variable as x when y=l probability, can obtain：
Since changes of the function f (p) to x is insensitive, slow and non-near f (p)=0 or f (p)=1 Linear degree is higher, therefore introduces the Logistic conversion of f (p), i.e.,
Logit (p)=logit (p/ (1-p))=(a+b1x1+b2x2+…+bnxn) (4)
At this time, the probability of P can be calculated：
Formula 5 is logistic regression as a result, wherein a, b1、b2…bnFor logistic regression coefficient.It can be calculated and ground using formula 5 Studying carefully susceptibility of geological hazards in area, (codomain scope 0-1, is worth close to 0 expression geological disaster and is not susceptible to, geology is represented closer to 1 The easier generation of disaster).
In this embodiment, Secondary Geological Hazards are easy after earthquake centre, earthquake intensity, principal earthquake fracture etc. being introduced shake as evaluation index In the index system of hair property assessment, earthquake-induced factor is highlighted so that assessment result is more accurate, the relevance with earthquake-induced It is stronger.
It is above the embodiment of Secondary Geological Hazards liability fast evaluation method after shake provided by the invention, the present invention is also The embodiment of Secondary Geological Hazards liability RES(rapid evaluation system) after shaking is provided, it is necessary to illustrate, provided by the invention Secondary Geological Hazards liability fast evaluation method can be applied to secondary geology after shake provided by the invention after a kind of shake of meaning Disaster liability RES(rapid evaluation system).
Embodiment 3
The embodiment of the present invention 3 describes Secondary Geological Hazards liability RES(rapid evaluation system) after a kind of shake, and Fig. 3 is the present invention The block diagram of Secondary Geological Hazards liability RES(rapid evaluation system) after shake described in embodiment 3, as shown in figure 3, the assessment system bag Evaluation index determining module 301, evaluation index numeralization module 302, evaluation index discrete block 303, sample areas is included to obtain Module 304, sample point sampling module 305, geological disaster proportion computing module 306, Function Fitting module 307, sensitiveness Result of calculation computing module 308, mathematical model determining module 309, logistic regression coefficient determination module 310, assessment models determine Module 311 and Assessment of Geological Hazard module 312 after shaking.
Wherein, evaluation index determining module 301 is used for n evaluation index of susceptibility of geological hazards after determining to shake, wherein, N evaluation index includes description seismic signature, topography and geomorphology, geological conditions, hydrologic condition, Information of Ancient Human Activity and surface vegetation Index；
Evaluation index numeralization module 302 is used to quantize each evaluation index, obtains discrete variable or continuous Property variable, wherein, discrete variable includes some discrete partitions；
Evaluation index discrete block 303 is used to continuous variable carrying out discretization, if it is corresponding to obtain continuous variable Dry discrete partition；
The incomplete high score remote sensing image data area of coverage is as sample area after sample areas acquisition module 304 is used for acquisition shake Domain；
Sample point sampling module 305 is used to multiple geological disaster occur according to what image data obtained in sample areas Sample point, and the non-geological disaster generation area in sample areas randomly chooses multiple sample points that geological disaster does not occur, Wherein, the value of each sample point includes (Z, W), wherein, during Z=0, geological disaster do not occur for expression, and during Z=1, expression has occurred Geological disaster, W=(w1, w2, w3…wn), wherein, w1, w2, w3…wnThe value of respectively one evaluation index；
Geological disaster proportion computing module 306 is used to use the corresponding discrete partition of the following formula Calculation Estimation index Interior geological disaster proportion is：Pi=Ai/Asum, wherein, PiOccur for geological disaster in i-th of discrete partition of evaluation index Ratio, AiFor the quantity of the sample point of geological disaster, A have occurred in i-th of discrete partitionsumFor spot in sample areas The quantity of the sample point of matter disaster；
Function Fitting module 307 is used for for each evaluation index, using the value of evaluation index in each sample point as input, Using geological disaster proportion in the discrete partition residing for the value of evaluation index in each sample point as output, intend into line function Close, obtain the corresponding fitting function of each evaluation index；
Sensitiveness result of calculation computing module 308 is used for the value w of each evaluation index in each sample point1, w2, w3…wn, Corresponding fitting function is inputted respectively, obtains the corresponding sensitiveness result of calculation of each evaluation index of sample point, wherein, w1, w2, w3…wnThe sensitiveness result of calculation being corresponding in turn to is x1, x2, x3…xn；
Mathematical model determining module 309 is used for the mathematical model of Secondary Geological Hazards liability rapid evaluation after determining to shake：
Wherein, p is the assessment result of Secondary Geological Hazards after a point shakes, x1, x2, x3…xnFor the corresponding sensitiveness result of calculation of each evaluation index of point；
Logistic regression coefficient determination module 310 is used for the x of all sample points1, x2, x3…xnMathematical model is substituted into respectively, Logistic regression coefficient a, b are determined using logistic regression analysis method1, b2, b3…bnValue；
Assessment models determining module 311 is used for logistic regression coefficient a, b1, b2, b3…bnValue substitute into mathematical model, obtain To assessment models；
Assessment of Geological Hazard module 312 is used to calculate the corresponding sensitiveness of each evaluation index of point to be assessed after shaking As a result assessment models are substituted into, the value of obtained p represents that evaluation point is less susceptible to geological disaster after shaking, obtain closer to 0 The value of p is closer to 1, geological disaster after representing that evaluation point is easier and shaking.
Preferably, describing the index of seismic signature includes macroscopic epicenter and earthquake intensity, describes the index bag of topography and geomorphology Elevation, the gradient and slope aspect are included, describing the index of geological conditions includes rock soil mass types and rift structure, describes the finger of hydrologic condition Mark includes water system and rainfall, and describing the index of Information of Ancient Human Activity includes road information, and the index for describing surface vegetation is earth's surface Vegetation coverage.
Preferably, the step of evaluation index numeralization module is when each evaluation index is quantized, execution includes：Will be grand Sight earthquake centre numerical value turns to the Euclidean distance apart from earthquake centre；Earthquake intensity numerical value is turned into earthquake intensity grade；Elevation numerical value is turned into height Journey value；It is value of slope by gradient numeralization；Slope aspect numerical value is turned into slope aspect value；Rock soil mass types numerical value is turned into symbol, wherein, Different rock soil mass types numerical value turn to different symbols；By the numeralization of rift structure include by principal earthquake fracture numeralization be away from The beeline of fracture numeralization all fractures for a distance from outside being broken Euclidean distance from principal earthquake and being broken principal earthquake；By water system Numerical value is turned to apart from water-based beeline；Rainfall numerical value is turned into rainfall；Road information numerical value is turned to apart from road Distance；And by the value of the vegetation cover number of degrees it is vegetation cover angle value.
Preferably, when Function Fitting module 307 carries out Function Fitting, following steps are performed：To macroscopic epicenter into line function The mathematical function used during fitting includes inverse function and linear function, after using inverse function and linear function progress Function Fitting The higher fitting result of obtained fitting precision is as the corresponding fitting function of macroscopic epicenter；Function Fitting is carried out to earthquake intensity The mathematical function of Shi Caiyong includes exponential function, linear function and piecewise function, wherein, it is greater than or equal to 10 for earthquake intensity grade Discrete partition, the higher fitting result of the fitting precision that is obtained after Function Fitting will be carried out using exponential function and linear function As the corresponding fitting function of earthquake intensity, otherwise using piecewise function, directly with geological disaster proportion in each discrete regions As a result；The mathematical function used when carrying out Function Fitting to elevation includes linear function, quadratic function and cubic function, when When the fitting precision for using linear function obtain after Function Fitting is greater than or equal to 0.6, linear function will be used to carry out letter The fitting result obtained after number fitting is obtained as the corresponding fitting function of elevation after Function Fitting is carried out using linear function Fitting precision when being less than 0.6, obtained fitting precision after Function Fitting will be carried out using quadratic function more than or equal to 0.6 For fitting result as the corresponding fitting function of elevation, the fitting precision obtained after quadratic function carries out Function Fitting is less than 0.6 When, using the fitting result for using cubic function obtain after Function Fitting as the corresponding fitting function of elevation；To the gradient into The mathematical function that line function uses when being fitted includes quadratic function and cubic function, after Function Fitting is carried out using quadratic function When obtained fitting precision is greater than or equal to 0.6, using using quadratic function carry out after Function Fitting obtained fitting result as The corresponding fitting function of the gradient, when the fitting precision for using quadratic function obtain after Function Fitting is less than 0.6, will use The fitting result that cubic function obtained after Function Fitting is as the corresponding fitting function of the gradient；Function Fitting is carried out to slope aspect The mathematical function of Shi Caiyong includes cubic function；The mathematical function used when carrying out Function Fitting to rock soil mass types includes segmentation Function；The mathematical function that numeralization to rift structure uses when including and being broken to principal earthquake and carry out Function Fitting includes linear function And inverse function, will be carried out using inverse function and linear function the higher fitting result of the fitting precision that is obtained after Function Fitting as The corresponding fitting function of rift structure；The mathematical function used when carrying out Function Fitting to water system includes linear function and inverse letter Number, using the higher fitting result of the fitting precision for using inverse function and linear function obtain after Function Fitting as water system pair The fitting function answered；The mathematical function used when carrying out Function Fitting to rainfall includes linear function and inverse function, will use inverse The higher fitting result of fitting precision that function and linear function obtained after Function Fitting is as the corresponding fitting letter of rainfall Number；The mathematical function that uses includes linear function and inverse function when carrying out Function Fitting to road information, will use inverse function with Linear function carries out the higher fitting result of obtained fitting precision after Function Fitting as the corresponding fitting function of road information； And the mathematical function used when carrying out Function Fitting to earth's surface vegetation coverage includes linear function and inverse function, will use inverse The higher fitting result of fitting precision that function and linear function obtained after Function Fitting is as vegetation cover degree pair The fitting function answered.
Preferably, sample point sampling module 305 performs following steps when the sample point of geological disaster has occurred for acquisition： The region that geological disaster has occurred in image data is subjected to gridding with 30 meters * 30 meters for base unit；During sampling, by area Region of the scale less than or equal to 30 meters * 30 meters is represented as a sample point, often increases a sample more than 30 meters * 30 meters Point.
Preferably, the number phase of sample point of the number of the sample point of geological disaster with geological disaster has occurred does not occur Together.
Preferably, when continuous variable is carried out discretization by evaluation index discrete block 303, following steps are performed：Using Continuous variable is divided into 30 discrete partitions by geometry partitioning method.
By above-described embodiment, Secondary Geological Hazards liability fast evaluation method and system after shake of the invention, Following beneficial effect is reached：
Fully excavate the Space Elements information of the extensive Secondary Geological Hazards of great earthquake-induced, definite evaluation index Include the index of description seismic signature, topography and geomorphology, geological conditions, hydrologic condition, Information of Ancient Human Activity and surface vegetation, to secondary The single evaluation index of raw disaster, namely single-factor influent factor carry out curve fitting, and avoid being absorbed in traditional Evaluation of Geologic Hazards Present in " monotonicity trap ", weight coefficient finally is determined to multiple single-factor fitting result logic-based homing methods, and Obtain in area secondary disaster evaluation of probability of occurrence after shake as a result, it is possible to it is quick and accurately evaluate shake after Secondary Geological Hazards it is whether easy Hair.
It should be understood by those skilled in the art that, the embodiment of the present invention can be provided as method, apparatus or computer program Product.Therefore, the present invention can use the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware Apply the form of example.Moreover, the present invention can use the computer for wherein including computer usable program code in one or more The computer program production that usable storage medium is implemented on (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) The form of product.
Although some specific embodiments of the present invention are described in detail by example, the skill of this area Art personnel it should be understood that example above merely to illustrating, the scope being not intended to be limiting of the invention.The skill of this area Art personnel are it should be understood that without departing from the scope and spirit of the present invention can modify above example.This hair Bright scope is defined by the following claims.

Claims (10)

1. Secondary Geological Hazards liability fast evaluation method after one kind shake, it is characterised in that
Determine n evaluation index of susceptibility of geological hazards after shake, wherein, n evaluation indexes include describing seismic signature, Topography and geomorphology, geological conditions, hydrologic condition, the index of Information of Ancient Human Activity and surface vegetation；
Each evaluation index is quantized, obtains discrete variable or continuous variable, wherein, the discrete variable Including some discrete partitions；
The continuous variable is subjected to discretization, obtains the corresponding some discrete partitions of the continuous variable；
The incomplete high score remote sensing image data area of coverage is as sample areas after obtaining shake；
Multiple sample points that geological disaster has occurred in the sample areas are obtained according to the image data；
Non- geological disaster generation area in the sample areas randomly chooses multiple sample points that geological disaster does not occur, its In, the value of each sample point includes (Z, W), wherein, during Z=0, geological disaster do not occur for expression, during Z=1, represents to have sent out Raw geological disaster, W=(w1, w2, w3…wn), wherein, w1, w2, w3…wnThe value of respectively one evaluation index；
Use the following formula calculate in the corresponding discrete partition of the evaluation index geological disaster proportion for：Pi=Ai/ Asum, wherein, PiFor geological disaster proportion in i-th of discrete partition of the evaluation index, AiFor described i-th discrete point The quantity of the sample point of geological disaster, A have occurred in areasumFor the sample point of geological disaster has occurred in the sample areas Quantity；
For each evaluation index, using the value of evaluation index described in each sample point as input, with each described Geological disaster proportion is output in discrete partition residing for the value of evaluation index described in sample point, carries out Function Fitting, Obtain the corresponding fitting function of each evaluation index；
By the value w of each evaluation index in each sample point1, w2, w3…wn, corresponding fitting function is inputted respectively, is obtained To the corresponding sensitiveness result of calculation of each evaluation index of the sample point, wherein, w1, w2, w3…wnIt is corresponding in turn to Sensitiveness result of calculation be x1, x2, x3…xn；
Determine the mathematical model of Secondary Geological Hazards liability rapid evaluation after shaking：
Wherein, p is the assessment result of Secondary Geological Hazards after a point to be assessed shakes, x1, x2, x3…xnFor the corresponding sensitiveness result of calculation of each evaluation index of the point to be assessed；
By the x of all sample points1, x2, x3…xnThe mathematical model is substituted into respectively, is determined using logistic regression analysis method Logistic regression coefficient a, b1, b2, b3…bnValue；
By logistic regression the coefficient a, b1, b2, b3…bnValue substitute into the mathematical model, obtain assessment models；
For any one of point to be assessed, the corresponding sensitiveness of each evaluation index of the point to be assessed is calculated into knot Fruit substitutes into the assessment models, and the value of obtained p represents that the evaluation point is less susceptible to geological disaster after shaking closer to 0, The value of obtained p is closer to 1, geological disaster after representing that the evaluation point is easier and shaking.
2. Secondary Geological Hazards liability fast evaluation method after shake according to claim 1, it is characterised in that
Describing the index of the seismic signature includes macroscopic epicenter and earthquake intensity, describes the index of the topography and geomorphology and includes height Journey, the gradient and slope aspect, describing the index of the geological conditions includes rock soil mass types and rift structure, describes the hydrologic condition Index include water system and rainfall, describing the index of the Information of Ancient Human Activity includes road information, describes the surface vegetation Index be vegetation cover degree.
3. Secondary Geological Hazards liability fast evaluation method after shake according to claim 2, it is characterised in that Jiang Gesuo Stating evaluation index and carrying out numeralization includes：
The macroscopic epicenter numerical value is turned to the Euclidean distance apart from earthquake centre；
The earthquake intensity numerical value is turned into earthquake intensity grade；
The elevation numerical value is turned into height value；
It is value of slope by gradient numeralization；
The slope aspect numerical value is turned into slope aspect value；
The rock soil mass types numerical value is turned into symbol, wherein, the different rock soil mass types numerical value turns to different symbols；
By the numeralization of the rift structure including being to be broken Euclidean distance and by described in apart from principal earthquake by principal earthquake fracture numeralization Fracture numeralization outside principal earthquake fracture is the beeline apart from all fractures；
It is apart from water-based beeline by water system numeralization；
The rainfall numerical value is turned into rainfall；
The road information numerical value is turned to the distance apart from road；And
It is vegetation cover angle value by the value of the vegetation cover number of degrees.
4. Secondary Geological Hazards liability fast evaluation method after shake according to claim 3, it is characterised in that
The mathematical function used when carrying out Function Fitting to the macroscopic epicenter includes inverse function and linear function, will use inverse letter The number fitting result higher with the fitting precision obtained after linear function progress Function Fitting is corresponding as the macroscopic epicenter Fitting function；
The mathematical function used when carrying out Function Fitting to the earthquake intensity includes exponential function, linear function and segmentation letter Number, wherein, be greater than or equal to for the earthquake intensity grade 10 the discrete partition, will use exponential function and linear function into After line function fitting otherwise the higher fitting result of obtained fitting precision makes as the corresponding fitting function of the earthquake intensity With piecewise function, directly with geological disaster proportion in each discrete regions as a result；
The mathematical function used when carrying out Function Fitting to the elevation includes linear function, quadratic function and cubic function, when When the fitting precision for using linear function obtain after Function Fitting is greater than or equal to 0.6, linear function will be used to carry out letter The fitting result obtained after number fitting is as the corresponding fitting function of the elevation, after Function Fitting is carried out using linear function When obtained fitting precision is less than 0.6, the fitting precision for using quadratic function obtain after Function Fitting is greater than or equal to 0.6 fitting result is as the corresponding fitting function of the elevation, the fitting essence obtained after quadratic function carries out Function Fitting When degree is less than 0.6, using the fitting result for using cubic function obtain after Function Fitting as the corresponding fitting of the elevation Function；
The mathematical function used when carrying out Function Fitting to the gradient includes quadratic function and cubic function, when using secondary letter When counting the fitting precision for carrying out being obtained after Function Fitting more than or equal to 0.6, quadratic function will be used to be obtained after carrying out Function Fitting The fitting result arrived is as the corresponding fitting function of the gradient, the fitting obtained after Function Fitting is carried out using quadratic function When precision is less than 0.6, using the fitting result for using cubic function obtain after Function Fitting as the corresponding plan of the gradient Close function；
The mathematical function used when carrying out Function Fitting to the slope aspect includes cubic function；
The mathematical function used when carrying out Function Fitting to the rock soil mass types includes piecewise function；
The mathematical function that numeralization to the rift structure uses when including and being broken to principal earthquake and carry out Function Fitting includes linear Function and inverse function, by using the higher fitting result of the fitting precision obtained after inverse function and linear function progress Function Fitting As the corresponding fitting function of the rift structure；
The mathematical function that uses includes linear function and inverse function when carrying out Function Fitting to the water system, will use inverse function with Linear function carries out the higher fitting result of obtained fitting precision after Function Fitting as the corresponding fitting function of the water system；
The mathematical function that uses includes linear function and inverse function when carrying out Function Fitting to the rainfall, will use inverse function with Linear function carries out the higher fitting result of obtained fitting precision after Function Fitting as the corresponding fitting function of the rainfall；
The mathematical function used when carrying out Function Fitting to the road information includes linear function and inverse function, will use inverse letter The number fitting result higher with the fitting precision obtained after linear function progress Function Fitting is corresponding as the road information Fitting function；And
The mathematical function used when carrying out Function Fitting to earth's surface vegetation coverage includes linear function and inverse function, will use inverse The higher fitting result of fitting precision that function and linear function obtained after Function Fitting is as the vegetation cover Spend corresponding fitting function.
5. Secondary Geological Hazards liability fast evaluation method after shake according to claim 1, it is characterised in that according to institute State that image data obtains in the sample areas it is multiple geological disaster has occurred sample point the step of include：
The region that geological disaster has occurred in the image data is subjected to gridding with 30 meters * 30 meters for base unit；
During sampling, represented region of the area scale less than or equal to 30 meters * 30 meters as a sample point, often more than 30 Rice one sample point of * 30 meters of increases.
6. Secondary Geological Hazards liability fast evaluation method after shake according to claim 5, it is characterised in that do not occur The number of sample point of the number of the sample point of geological disaster with geological disaster has occurred is identical.
7. Secondary Geological Hazards liability fast evaluation method after shake according to claim 1, it is characterised in that by described in Continuous variable carries out discretization, and obtaining the corresponding some discrete partitions of the continuous variable includes：
The continuous variable is divided into by 30 discrete partitions using geometry partitioning method.
8. Secondary Geological Hazards liability RES(rapid evaluation system) after one kind shake, it is characterised in that
Evaluation index determining module, for determining n evaluation index of susceptibility of geological hazards after shaking, wherein, the n evaluations Index includes the index of description seismic signature, topography and geomorphology, geological conditions, hydrologic condition, Information of Ancient Human Activity and surface vegetation；
Evaluation index numeralization module, for each evaluation index to be quantized, obtains discrete variable or continuity Variable, wherein, the discrete variable includes some discrete partitions；
Evaluation index discrete block, for the continuous variable to be carried out discretization, it is corresponding to obtain the continuous variable Some discrete partitions；
Sample areas acquisition module, for the incomplete high score remote sensing image data area of coverage after obtaining shake as sample areas；
Sample point sampling module, multiple has occurred geological disaster for obtain in the sample areas according to the image data Sample point, and non-geological disaster generation area in the sample areas randomly chooses multiple samples that geological disaster does not occur This point, wherein, the value of each sample point includes (Z, W), wherein, during Z=0, represent that geological disaster does not occur, during Z=1, Geological disaster, W=(w have occurred for expression1, w2, w3…wn), wherein, w1, w2, w3…wnRespectively evaluation index Value；
Geological disaster proportion computing module, it is described discrete point corresponding for calculating the evaluation index using the following formula Geological disaster proportion is in area：Pi=Ai/Asum, wherein, PiFor geology calamity in i-th of discrete partition of the evaluation index Evil proportion, AiFor the quantity of the sample point of geological disaster, A have occurred in i-th of discrete partitionsumFor the sample The quantity of the sample point of geological disaster has occurred in region；
Function Fitting module, for for each evaluation index, with the value of evaluation index described in each sample point To input, using geological disaster proportion in the discrete partition residing for the value of evaluation index described in each sample point to be defeated Go out, carry out Function Fitting, obtain the corresponding fitting function of each evaluation index；
Sensitiveness result of calculation computing module, for by the value w of each evaluation index in each sample point1, w2, w3… wn, corresponding fitting function is inputted respectively, obtains the corresponding sensitiveness result of calculation of each evaluation index of the sample point, Wherein, w1, w2, w3…wnThe sensitiveness result of calculation being corresponding in turn to is x1, x2, x3…xn；
Mathematical model determining module, for determining the mathematical model of Secondary Geological Hazards liability rapid evaluation after shaking：
Wherein, p is the assessment result of Secondary Geological Hazards after a point to be assessed shakes, x1, x2, x3…xnFor the corresponding sensitiveness result of calculation of each evaluation index of the point to be assessed；
Logistic regression coefficient determination module, the x for all sample points1, x2, x3…xnThe mathematical model is substituted into respectively, Logistic regression coefficient a, b are determined using logistic regression analysis method1, b2, b3…bnValue；
Assessment models determining module, for by logistic regression the coefficient a, b1, b2, b3…bnValue substitute into the mathematical model, Obtain assessment models；
Assessment of Geological Hazard module after shaking, based on the corresponding sensitiveness of each evaluation index by the point to be assessed Calculate result and substitute into the assessment models, the value of obtained p represents that the evaluation point is less susceptible to geology after shaking closer to 0 Disaster, the value of obtained p is closer to 1, geological disaster after representing that the evaluation point is easier and shaking.
9. Secondary Geological Hazards liability RES(rapid evaluation system) after shake according to claim 8, it is characterised in that
Describing the index of the seismic signature includes macroscopic epicenter and earthquake intensity, describes the index of the topography and geomorphology and includes height Journey, the gradient and slope aspect, describing the index of the geological conditions includes rock soil mass types and rift structure, describes the hydrologic condition Index include water system and rainfall, describing the index of the Information of Ancient Human Activity includes road information, describes the surface vegetation Index be vegetation cover degree.
10. Secondary Geological Hazards liability RES(rapid evaluation system) after shake according to claim 9, it is characterised in that evaluation When index value module is quantized each evaluation index, the step of execution, includes：
The macroscopic epicenter numerical value is turned to the Euclidean distance apart from earthquake centre；
The earthquake intensity numerical value is turned into earthquake intensity grade；
The elevation numerical value is turned into height value；
It is value of slope by gradient numeralization；
The slope aspect numerical value is turned into slope aspect value；
The rock soil mass types numerical value is turned into symbol, wherein, the different rock soil mass types numerical value turns to different symbols；
By the numeralization of the rift structure including being to be broken Euclidean distance and by described in apart from principal earthquake by principal earthquake fracture numeralization Fracture numeralization outside principal earthquake fracture is the beeline apart from all fractures；
It is apart from water-based beeline by water system numeralization；
The rainfall numerical value is turned into rainfall；
The road information numerical value is turned to the distance apart from road；And
It is vegetation cover angle value by the value of the vegetation cover number of degrees.
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