CN114863643A - Early warning method for rainfall type landslide based on GIS area - Google Patents
Early warning method for rainfall type landslide based on GIS area Download PDFInfo
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Abstract
The invention discloses a rainfall type landslide early warning method based on a GIS region, which comprises the following steps of: 1) dynamically monitoring the regional rainfall type landslide based on a time sequence InSAR technology, and dividing the risk level of the regional rainfall type landslide; 2) analyzing the influence of the accumulated rainfall on the landslide damage mechanism at different time intervals by adopting an experiment and numerical simulation mode, establishing a regional rainfall early warning model, and determining a rainfall early warning index taking the rainfall as a threshold value; 3) a GIS technology is adopted to combine the risk level of the regional rainfall type landslide with rainfall early warning indexes, and a regional rainfall type landslide early warning and forecasting system is established, so that early warning of the regional rainfall type landslide is realized. According to the method, the GIS technology is adopted to combine the regional rainfall type landslide risk evaluation grade with the regional rainfall early warning model result, and a regional rainfall type landslide early warning and forecasting system is established, so that early warning of regional rainfall type landslides in space and time is realized, and the reliability and feasibility of early warning are further ensured.
Description
Technical Field
The invention belongs to the technical field of landslide monitoring and early warning, and particularly relates to a rainfall type landslide early warning method based on a GIS (geographic information system) area.
Background
China is a mountainous country, the area of mountainous regions accounts for 69% of the total area of the national soil, and common geological disasters in mountainous regions pose great threats to road construction and operation. Landslide refers to the phenomenon that rock and soil mass on a side slope loses stability under the influence of natural or human factors and integrally slides down along a through damaged surface, and the landslide is used as a common geological disaster and is wide in distribution and great in harm. Through experience and training of a series of landslide disaster events, early warning of landslide disasters and effective disaster analysis are the main ways of changing 'passive disaster avoidance and relief' into 'active disaster prevention and control' and reducing loss caused by disasters.
The existing rainfall type landslide early warning method can be divided into a statistical early warning method based on empirical rainfall threshold, a cause early warning method considering underlying surface factor weight and a mechanism early warning method based on a rainfall type landslide physical mechanical process. Among them, the statistical early warning method established based on the empirical "rainfall Intensity-rainfall Duration" (I-D) threshold is most widely applied. The I-D threshold value curve is formed by taking average rainfall intensity I (mm/h) as a vertical coordinate and taking rainfall duration D (h) experienced when a landslide event occurs as a horizontal coordinate through measured data statistics and drawing. The I-D threshold curve is usually the lower limit curve, when the average rainfall intensity I (mm/h) actually born by the slope body and the rainfall duration D (h) exceed the curve, the landslide early warning information is issued. The early warning method for the rainfall type landslide realizes early warning of the landslide by a single rainfall threshold, underlying surface factor weight or a mechanism of a physical mechanical process, and has the following problems: 1) the prediction method is mainly established on the analysis of the static influence factors of the existing landslide area, but the landslide is dynamically changed, the prediction result lacks the update of the landslide dynamic change result, and the prediction result has larger deviation with the actual condition; 2) the prediction model in time mainly takes a single landslide as an object, analyzes the change curve of the displacement (speed) of the landslide along with the time, and takes the inflection point of the displacement (speed) curve or a certain displacement value (speed value) as the landslide instability criterion; 3) the regional landslide time instability criterion is rarely researched at present, and a prediction model of the regional landslide in two dimensions of time and space is rarely researched: 4) the landslide early identification method is mainly characterized in that a statistical model simulation result is refined according to an InSAR monitoring result, analysis on landslide induction factors, geological conditions and landslide damage mechanism differences is neglected, and the influence of data precision on an evaluation result is large; 5) the research on the regional landslide quantitative analysis method is less, mainly because the occurrence and development of single landslide are influenced by the terrain conditions, the stratum lithology, the landform pattern and the like in the regional range. In conclusion, the traditional early warning method has large errors and poor reliability.
Disclosure of Invention
The invention aims to provide a rainfall type landslide early warning method based on a GIS area, and the early warning method is used for solving the problem that the traditional rainfall type landslide early warning method is poor in reliability.
In order to solve the technical problems, the invention adopts the technical scheme that:
the invention relates to a rainfall type landslide early warning method based on a GIS region, which comprises the following steps of:
1) dynamically monitoring the regional rainfall type landslide based on a time sequence InSAR technology, and dividing the risk level of the regional rainfall type landslide;
2) analyzing the influence of the rainfall accumulated at different time periods on a landslide damage mechanism by adopting an experiment and numerical simulation mode, establishing a regional rainfall early warning model, and determining a rainfall early warning index taking the rainfall as a threshold value;
3) a GIS technology is adopted to combine the risk level of the regional rainfall type landslide with rainfall early warning indexes, and a regional rainfall type landslide early warning and forecasting system is established, so that early warning of the regional rainfall type landslide is realized.
Preferably, the specific steps of step 1) include:
1.1) carrying out ground surface continuous deformation monitoring on the rainfall type landslide in the region by adopting a time sequence InSAR technology to obtain ground surface deformation displacement values on a long-time sequence, carrying out filtering analysis according to the space-time continuity characteristics of the rainfall type landslide in a remote sensing monitoring result, removing deformation values generated by non-rock and earth body movement in the ground surface deformation displacement values, and extracting rock and earth body movement displacement values in the region;
1.2) calculating the deformation rate value of the rainfall type landslide in the area based on the rock-soil body movement displacement value;
1.3) carrying out remote sensing interpretation on a known rainfall type landslide list and landslide influence factors in an area in a GIS (geographic information system), taking a remote sensing interpretation result as a landslide influence factor, researching influence proportion of each influence factor on rainfall type landslide in the area and possibility of landslide occurrence by adopting a binary logistic regression model, and establishing an area landslide risk evaluation model;
1.4) dividing the risk level of rainfall type landslide in the area according to the deformation rate value obtained in the step 1.2).
Preferably, the step 1.1) is to extract the surface deformation information of the research area by searching points with high scattering characteristics in the SAR image as permanent scattering points or coherent points.
Preferably, the step of calculating the deformation rate value of the rainfall type landslide in the area in the step 1.2) comprises:
1.2.1) obtaining the earth surface sight line direction deformation rate V of the region based on the rock-soil mass movement displacement value los Vertical velocity value V v And horizontal velocity value V h ；
1.2.2) rate of deformation V based on the Earth's surface line of sight los Vertical velocity value V v And horizontal velocity value V h Calculating the value of the deformation rate V slope The calculation formula is as follows:
in the formula, alpha represents the included angle between the sliding displacement speed direction along the slope surface and the horizontal direction of the ground.
Preferably, the step 1.3) of researching the influence proportion of each influence factor on the regional rainfall type landslide and the possibility of landslide by using a binary logistic regression model comprises the following specific steps:
1.3.1) taking the rainfall type landslide in the list as a sample, randomly dividing the sample into a training sample and a verification sample, setting the probability of occurrence of the landslide as P, the probability of non-occurrence as 1-P and the value range of P as (0, 1) during the training of the sample; in the binary logistic regression model, the value of the dependent variable of the occurrence region of the landslide hazard is 1, the value of the dependent variable of the non-occurrence region of the landslide hazard is 0, the value form of the P value is transformed by adopting a Logit transformation mode, so that the value range of the transformed P value is changed to be (-infinity, + ∞), and the change form is as follows:
Logit P＝ln(P/(1-P))＝β 0 +β 1 x 1 +β 2 x 2 +…+β i x i (2)
in the formula, P is the probability of landslide; beta is a 0 Is a constant term; beta is a i The regression coefficient of the logistic regression model is x i The estimated parameters of (2); x is the number of i Representing independent variables, namely all influence factors of the landslide, calculating the probability P of the landslide:
1.3.2) obtaining the regression coefficient beta of each influence factor through multiple iterations i ；
1.3.3) regression coefficient β of each influencing factor i In the formula (2), calculating to obtain a landslide occurrence probability P value of each sample unit, wherein the landslide occurrence probability predicted value in the training sample is greater than 0.5 to indicate a landslide occurrence area, and the value less than 0.5 to indicate a landslide non-occurrence area;
1.3.4) comparing the training sample result with the verification sample, calculating the prediction precision of the logistic regression model, if the comparison rate is more than 80%, indicating that the test is passed, and the prediction value is the probability value of landslide occurrence.
Preferably, the deformation values generated by the non-geotechnical body movement removed in the step 1.1) include human activities and vegetation growth.
Preferably, after the regional rainfall type landslide risk level is divided in the step 1.4), verification is performed through a field investigation mode, if the verification is not correct, the step 1.3 is returned, and if the verification is successful, the next step is performed.
Preferably, the specific steps of step 2) are:
2.1) establishing different homogeneous slope models by adopting an indoor experimental model method, setting the slope which is most easy to generate landslide as the slope of the slope model, burying a displacement measurement positioning deformation value in the slope model, burying a pore water pressure sensor to measure the change of the pore water pressure of a slope body in the rainfall infiltration process, adopting a rainfall measuring and spraying device, presetting sponge and permeable stones below the slope body, carrying out experiments on the slope model by controlling the rainfall intensity and the rainfall time and the rainfall interval time until the slope model has a run-through sliding surface, and recording the total rainfall R and the displacement value s;
2.2) setting a total rainfall early warning threshold R under different rainfall intensities according to the total rainfall R m ；
2.3) taking a soil body soil sample in a destabilization state, measuring the change of an internal friction angle phi and cohesive force c in stability under different rainfall intensity conditions by adopting a direct shear experiment, drawing a curve fitting function, setting the fitting curve as a destabilization damage envelope F (c, phi), and setting the fitting curve as the destabilization damage envelope F m Setting the unstable sliding area beyond the range;
2.4) measuring the displacement change value of the soil body through the displacement meter, setting the displacement value s under different rainfall intensities as a displacement early warning threshold value s m ；
2.5) based on the total rainfall R of two kinds of soil and the change of different rainfall intensities, the internal friction angle of the soil body
And the cohesive force c, the change of different rainfall intensities and the displacement change value of the soil body, and the total rainfall R and the base internal friction angle are set
A fitting dotted line F of the cohesive force c and a displacement value s;
2.6) grading C based on the regional rainfall type landslide risk, taking rainfall as a landslide triggering mechanism, and establishing a threshold value which changes according to a curve relation according to statistical indexes: and F (C, R, F, s), and further determining a rainfall early warning index taking the rainfall as a threshold value.
Preferably, the rainfall early warning indexes in the step 2.6) are divided into 4 early warning levels, and the judgment criteria are as follows:
(1) early warning 1:
(2) early warning 2:
(3) early warning 3:
(4) early warning 4:
P＝{p∈R∩p∈F∩p∈s∩p∈C (4|5) 。
compared with the prior art, the technical scheme of the invention has the following beneficial effects:
the early warning method for rainfall type landslide based on GIS area analyzes the response of different soil conditions to rainfall, corrects landslide according to factors such as different soil types and different gradients in an area range by adopting a remote sensing interpretation mode to reflect the response of landslide to critical rainfall, establishes a landslide rainfall early warning quantitative analysis method, establishes an area rainfall type landslide early warning system, finally achieves the purpose of early warning of rainfall type landslide in time and space, and ensures the reliability and feasibility of early warning.
Drawings
FIG. 1 is a flow chart of a rainfall type landslide early warning method based on a GIS area according to the present invention;
FIG. 2 is a graph showing deformation rate values V slope Velocity V of change in direction of the earth's surface line of sight los The geometric relationship diagram of (1).
Detailed Description
The present invention is described in detail below, and technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to the attached drawing 1, the invention relates to a rainfall type landslide early warning method based on a GIS area, which is characterized in that: which comprises the following steps:
1) the method comprises the following steps of dynamically monitoring regional rainfall type landslides based on a time sequence InSAR technology, and dividing the risk level of the regional rainfall type landslides, wherein the method specifically comprises the following steps:
1.1) carrying out earth surface continuous deformation monitoring on the rainfall type landslide in the region by adopting a time sequence InSAR technology, namely searching a point with high scattering property in an SAR image as a permanent scattering point or a coherent point so as to extract earth surface deformation displacement values of the research region on a long-time sequence, carrying out filter analysis according to the space-time continuity characteristic of the rainfall type landslide in a remote sensing monitoring result, and removing deformation values (including human activities, vegetation growth and the like) generated by non-rock and earth body movement in the earth surface deformation displacement values. In time distribution, landslide generally occurs after rainfall occurs, continuous deformation is generated, particularly in rainy seasons, the time continuity of displacement can be shown, the increase of displacement values can be shown before and after the rainy seasons, and discontinuous displacement areas before and after the rainy seasons can be removed; in space, landslide generally has a certain scale, so that sporadic displacement regions in monitoring results can be filtered out, and rock and soil mass movement displacement values in the regions are finally extracted;
1.2) calculating the deformation rate value of the regional rainfall type landslide based on the rock-soil mass movement displacement value, namely:
1.2.1) obtaining the earth surface sight line direction deformation rate V of the region based on the rock-soil mass movement displacement value los Vertical velocity value V v And horizontal velocity value V h ；
1.2.2)Referring to FIG. 2, the deformation rate V is based on the ground surface view los Vertical velocity value V v And horizontal velocity value V h Calculating the value of the deformation rate V slope The calculation formula is as follows:
in the formula, alpha represents an included angle between the sliding displacement speed direction along the slope surface and the horizontal direction of the ground;
1.3) carrying out remote sensing interpretation on a known rainfall type landslide list and landslide influence factors in an area, taking a remote sensing interpretation result as a landslide influence factor, researching influence proportion of each influence factor on the rainfall type landslide of the area and possibility of occurrence of landslide by adopting a binary logistic regression model, and establishing an area landslide risk evaluation model, wherein the method comprises the following specific steps:
1.3.1) taking the rainfall type landslide in the list as a sample, randomly dividing the sample into a training sample and a verification sample, setting the probability of occurrence of the landslide as P, the probability of non-occurrence as 1-P and the value range of P as (0, 1) during the training of the sample; in the binary logistic regression model, the value of the dependent variable of the occurrence region of the landslide hazard is 1, the value of the dependent variable of the non-occurrence region of the landslide hazard is 0, the value form of the P value is transformed by adopting a Logit transformation mode, so that the value range of the transformed P value is changed to be (-infinity, + ∞), and the change form is as follows:
Logit P＝ln(P/(1-P))＝β 0 +β 1 x 1 +β 2 x 2 +…+β i x i (2)
in the formula, P is the probability of landslide; beta is a 0 Is a constant term; beta is a i The regression coefficient of the logistic regression model is x i The estimated parameters of (2); x is the number of i Representing independent variables, namely all influence factors of the landslide, calculating the probability P of the landslide:
1.3.2) obtaining the regression coefficient beta of each influence factor through multiple iterations i ；
1.3.3) regression coefficient β of each influencing factor i In the formula (2), calculating to obtain a landslide occurrence probability P value of each sample unit, wherein the landslide occurrence probability predicted value in the training sample is greater than 0.5 to indicate a landslide occurrence area, and the value less than 0.5 to indicate a landslide non-occurrence area;
1.3.4) comparing the training sample result with the verification sample, calculating the prediction precision of the logistic regression model, if the comparison rate is more than 80%, indicating that the test is passed, and the prediction value is the probability value of landslide occurrence;
1.4) deformation rate value V obtained according to step 1.2) slope Dividing the danger level of rainfall type landslide in the region,
namely, the risk grade of the regional rainfall type landslide is preliminarily divided according to the deformation rate variance, and the regional landslide occurrence probability obtained in the step 1.3) is divided into 5 grades: class 1: p <0.3 is a very insensitive region; class 2: 0.3-0.4 is an insensitive area; class 3: 0.4-0.5 is an uncertain zone; class 4: 0.5-0.6 is a sensitive area; class 5: p >0.6 is a very sensitive region. In order to eliminate the depolarisation bias caused by the change of the landslide with time in the regional landslide risk evaluation model result obtained in the step 1.3), the regional rainfall type landslide risk levels are reclassified according to the method shown in table 1, and then the regional rainfall type landslide risk level C is divided.
TABLE 1 landslide sensitivity dynamic evaluation hybrid model calculation method
The depolarisation deviation means that the area is actually a landslide position, but the landslide sensitivity evaluation result shows that the non-sensitive area can not be used for limiting the area, and if buildings or other facilities are built on the area, the construction safety, the building stability and the life are directly seriously threatened, so that the immeasurable loss is caused. Therefore, such errors are unacceptable and are to be avoided as much as possible.
After dividing the risk level of the rainfall type landslide in the region, verifying in a field investigation mode, if the verification is incorrect, returning to the step 1.3), and if the verification is successful, performing the next step;
the steps are used for researching the early dynamic identification of the rainfall type landslide in the spatially effective area.
2) Rainfall is an important trigger mechanism of landslide, and can directly cause the change of the water content of a soil body, so that the size of an internal friction angle is influenced. For a single landslide, the landslide area soil body is always in a sliding state before the residual shear strength (namely, an internal friction angle) of the landslide area soil body is not reached. The deformation amount before and after the rainy season is obviously different in a large-range area. On the basis of the evaluation level of the risk of the rainfall type landslide in the region, according to the obvious change of the displacement value of the rainfall type landslide before and after rainfall, by analyzing the influence of the accumulated rainfall at different time periods on the landslide damage mechanism, a rainfall early warning model is established, and the multi-threshold early warning index is determined. Because the actual landslide mass characteristics are difficult to monitor, the embodiment adopts an experimental mode to analyze the influence of rainfall accumulated in different periods on the landslide damage mechanism, establishes a regional rainfall early warning model, determines rainfall early warning indexes taking the rainfall as threshold values, namely researches the evolution law of different rainfall intensities on the rock-soil internal force change (factors such as internal friction angle, cohesive force and the like) and the evolution law of different rainfall intensities on the landslide external performance characteristics (factors such as displacement, speed and the like) by designing indoor different homogeneous slope rainfall simulation experiments respectively, simulates the whole process of the slope from the initial stage to the destabilization stage, establishes a relation model of the rainfall and each parameter, and researches the early warning indexes with multiple threshold values, and the method comprises the following specific steps:
2.1) establishing different homogeneous slopes by adopting an indoor experimental model method, dividing the slope into sandy soil and clay for carrying out experiments, and showing concrete soil sample test parameters in a table 2. Set up 1m 3 The side slope model, statistically showing, is most likely to be generated when the side slope is 38 °, so the side slope is set to 38 °. A displacement meter is embedded in the side slope to measure the positioning displacement deformation value, and a pore water pressure sensor is embedded to measure the change of the pore water pressure of the slope body in the rainfall infiltration process. MiningA rainfall measuring and spraying device is used, sponge and permeable stones are preset below a slope body, rainfall intensity I is respectively set to be 40mm/h, 80mm/h, 120mm/h and 160mm/h, 1h of rainfall is carried out each time, the interval is 1h, and the total rainfall R and the displacement value s are recorded until a sliding surface is penetrated on the sliding surface.
TABLE 2 basic parameters of the test soil samples
2.2) setting the total rainfall early warning threshold R under different rainfall intensities m Then R is>R m It is unstable.
2.3) taking soil samples of soil bodies in a destabilization state, and measuring the internal friction angle of the two soil bodies in the destabilization state by adopting a direct shear experiment
And the cohesive force c are changed under different rainfall intensity I conditions, a curve fitting function is drawn,
the fitting curve is set as a destabilization destruction envelope F m Namely, a stable region is defined within the envelope range, and a destabilizing sliding region is defined beyond the range.
2.4) measuring the displacement change value of the soil body through a displacement meter; setting the displacement value s under different rainfall intensities as a displacement early warning threshold value s m Then s>s m It is unstable.
2.5) based on the total rainfall R of two kinds of soil and the change of different rainfall intensities, the internal friction angle of the soil body
And the variation of the cohesive force c and different rainfall intensities and the variation value of the displacement of the soil body. Setting is based on total rainfall R, base internal friction angle
And a fitting dotted line F of the cohesion force c and a displacement value s. Each parameterThe thresholds are summarized in table 3.
TABLE 3 summary of various parameter thresholds
2.6) grading C based on the regional rainfall type landslide risk, taking rainfall as a landslide triggering mechanism, and establishing a threshold value which changes according to a curve relation according to statistical indexes: p ═ F (C, R, F, s).
Wherein: c, grading the risk of the regional landslide; r is the total rainfall value; f is an instability damage envelope; s is the displacement value.
2.7) establishing four early warning levels of 1, 2, 3 and 4, wherein the judgment criteria are as follows:
(1) early warning 1:
(2) early warning 2:
(3) early warning 3:
(4) early warning 4:
P＝{p∈R∩p∈F∩p∈s∩p∈C (4|5)
3) a GIS technology is adopted to combine the risk level of the regional rainfall type landslide with rainfall early warning indexes, and a regional rainfall type landslide early warning and forecasting system is established, so that early warning of the regional rainfall type landslide is realized.
The present invention has been described in detail with reference to the embodiments, but the description is only for the preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (9)
1. A rainfall type landslide early warning method based on a GIS area is characterized by comprising the following steps: which comprises the following steps:
1) dynamically monitoring the regional rainfall type landslide based on a time sequence InSAR technology, and dividing the risk level of the regional rainfall type landslide;
2) analyzing the influence of rainfall accumulated in different periods on a landslide damage mechanism by adopting an experimental mode, establishing a regional rainfall early warning model, and determining a rainfall early warning index with the rainfall as a threshold value;
3) a GIS technology is adopted to combine the risk level of the regional rainfall type landslide with rainfall early warning indexes, and a regional rainfall type landslide early warning and forecasting system is established, so that early warning of the regional rainfall type landslide is realized.
2. The early warning method for rainfall type landslide based on GIS area according to claim 1, wherein: the specific steps of the step 1) comprise:
1.1) carrying out ground surface continuous deformation monitoring on rainfall type landslides in an area by adopting a time sequence InSAR technology to obtain ground surface deformation displacement values on a long time sequence, carrying out filter analysis according to the space-time continuity characteristics of the rainfall type landslides in remote sensing monitoring results, removing deformation values generated by non-rock-soil body movement in the ground surface deformation displacement values, and extracting rock-soil body movement displacement values in the area;
1.2) calculating the deformation rate value of the rainfall type landslide in the area based on the rock-soil body movement displacement value;
1.3) carrying out remote sensing interpretation on a known rainfall type landslide list and landslide influence factors in an area in a GIS (geographic information system), taking a remote sensing interpretation result as a landslide influence factor, researching influence proportion of each influence factor on rainfall type landslide in the area and possibility of landslide occurrence by adopting a binary logistic regression model, and establishing an area landslide risk evaluation model;
1.4) dividing the risk level of rainfall type landslide in the area according to the deformation rate value obtained in the step 1.2).
3. The early warning method for rainfall type landslide based on GIS area as claimed in claim 2, wherein: in the step 1.1), the points with high scattering characteristics are searched in the SAR image to serve as permanent scattering points or coherent points, so that the surface deformation information of the research area is extracted.
4. The early warning method for rainfall type landslide based on GIS area as claimed in claim 2, wherein: the step of calculating the deformation rate value of the rainfall type landslide in the area in the step 1.2) comprises the following steps:
1.2.1) obtaining the earth surface sight line direction deformation rate V of the region based on the rock-soil mass movement displacement value los Vertical velocity value V v And horizontal velocity value V h ；
1.2.2) rate of deformation V based on the Earth's surface line of sight los Vertical velocity value V v And horizontal velocity value V h Calculating the value of the deformation rate V slope The calculation formula is as follows:
in the formula, alpha represents the included angle between the sliding displacement speed direction along the slope surface and the horizontal direction of the ground.
5. The early warning method for rainfall type landslide based on GIS area as claimed in claim 2, wherein: the step 1.3) of researching the influence proportion of each influence factor on the regional rainfall type landslide and the possibility of landslide occurrence by adopting a binary logistic regression model comprises the following specific steps:
1.3.1) taking the rainfall type landslide in the list as a sample, randomly dividing the sample into a training sample and a verification sample, setting the probability of occurrence of the landslide as P, the probability of non-occurrence as 1-P and the value range of P as (0, 1) during the training of the sample; in the binary logistic regression model, the value of the dependent variable of the occurrence region of the landslide hazard is 1, the value of the dependent variable of the non-occurrence region of the landslide hazard is 0, the value form of the P value is transformed by adopting a Logit transformation mode, so that the value range of the transformed P value is changed to be (-infinity, + ∞), and the change form is as follows:
Logit P＝ln(P/(1-P))＝β 0 +β 1 x 1 +β 2 x 2 +…+β i x i (2)
in the formula, P is the probability of landslide; beta is a 0 Is a constant term; beta is a i The regression coefficient of the logistic regression model is x i The estimated parameters of (2); x is the number of i Representing independent variables, namely all influence factors of the landslide, calculating the probability P of the landslide:
1.3.2) obtaining the regression coefficient beta of each influence factor through multiple iterations i ；
1.3.3) regression coefficient β of each influencing factor i In the formula (2), calculating to obtain a landslide occurrence probability P value of each sample unit, wherein the landslide occurrence probability predicted value in the training sample is greater than 0.5 to indicate a landslide occurrence area, and the value less than 0.5 to indicate a landslide non-occurrence area;
1.3.4) comparing the training sample result with the verification sample, calculating the prediction precision of the logistic regression model, if the comparison rate is more than 80%, indicating that the test is passed, and the prediction value is the probability value of landslide occurrence.
6. The early warning method for rainfall type landslide based on GIS area as claimed in claim 2, wherein: the deformation values generated by the movement of the non-rock-soil body removed in the step 1.1) comprise human activities and vegetation growth.
7. The early warning method for rainfall type landslide based on GIS area as claimed in claim 2, wherein: after the rainfall type landslide risk level in the region is divided in the step 1.4), verification is carried out in a field investigation mode, if the verification is incorrect, the step 1.3 is returned, and if the verification is successful, the next step is carried out.
8. The early warning method for rainfall type landslide based on GIS area according to claim 1, wherein: the specific steps of the step 2) are as follows:
2.1) establishing different homogeneous slope models by adopting an indoor experimental model method, setting the slope which is most easy to generate landslide as the slope of the slope model, burying a displacement measurement positioning deformation value in the slope model, burying a pore water pressure sensor to measure the change of the pore water pressure of a slope body in the rainfall infiltration process, adopting a rainfall measuring and spraying device, presetting sponge and permeable stones below the slope body, carrying out experiments on the slope model by controlling the rainfall intensity and the rainfall time and the rainfall interval time until the slope model has a run-through sliding surface, and recording the total rainfall R and the displacement value s;
2.2) setting total rainfall early warning threshold R under different rainfall intensities according to the total rainfall R m ；
2.3) taking a soil body soil sample in a destabilization state, measuring the change of an internal friction angle phi and cohesive force c in stability under different rainfall intensity conditions by adopting a direct shear experiment, drawing a curve fitting function, setting the fitting curve as a destabilization damage envelope F (c, phi), and setting the fitting curve as the destabilization damage envelope F m Setting the unstable sliding area beyond the range;
2.4) measuring the displacement change value of the soil body through the displacement meter, setting the displacement value s under different rainfall intensities as a displacement early warning threshold value s m ；
2.5) based on the total rainfall R of two types of soil and the change of different rainfall intensities, the internal friction angle of the soil body
And the cohesive force c, the change of different rainfall intensities and the displacement change value of the soil body, and the total rainfall R and the base internal friction angle are set
A fitting dotted line F of the cohesive force c and a displacement value s;
2.6) grading C based on the regional rainfall type landslide risk, taking rainfall as a landslide triggering mechanism, and establishing a threshold value which changes according to a curve relation according to statistical indexes: and F (C, R, F, s), and determining a rainfall early warning index with the rainfall as a threshold value.
9. The early warning method for rainfall type landslide based on GIS area according to claim 8, wherein: the rainfall early warning indexes in the step 2.6) are divided into 4 early warning levels, and the judgment criteria are as follows:
(1) early warning 1:
(2) early warning 2:
(3) early warning 3:
(4) early warning 4:
P＝{p∈R∩p∈F∩p∈s∩p∈C (4|5) 。
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