CN115391896A - Slope instability prone area identification method and device based on double parameters of height difference and gradient - Google Patents
Slope instability prone area identification method and device based on double parameters of height difference and gradient Download PDFInfo
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Abstract
The invention provides a slope instability prone area identification method and a slope instability prone area identification device based on double parameters of height difference and gradient, wherein the method comprises the following steps of S100, determining slope strength parameters c1 and phi 1 on a slope scale; s200, measuring the undulation degree H and the slope angle beta of each subdivision area A of the slope; step S300, calculating the limit undulation degree Hc of the subdivision area A; step S400, comparing the difference value between the current undulation degree H and the limit undulation degree Hc to estimate the stable state of the area A. Determining the area with the current undulation degree larger than the limit undulation degree as an easy area for slope instability; and S500, repeating the steps S100-S400, searching all the slope fine areas of the research area, and estimating the instability susceptibility state of the research area. The invention solves the technical problems that the existing method is mainly suitable for single scale and can not meet the requirements of disaster prevention and reduction of regional scale at the present stage.
Description
Technical Field
The invention belongs to the technical field of geotechnical engineering and seismic engineering, and particularly relates to a slope instability prone area identification method and device based on elevation difference and slope double parameters.
Background
The identification of the easy-to-occur area of the instability of the high and steep slope is the basis for carrying out geological disaster easy-to-occur evaluation and scientific disaster prevention and reduction. The engineering geological conditions for controlling slope instability can be investigated in detail through field and field investigation, and include stratum lithology, rock mass strength, joint density, terrain conditions, tectonic activity and the like, so that the position and the range of potential slope instability can be determined reasonably. However, for slope instability identification under the regional scale, the traditional field investigation method has a limited investigation range and consumes more time and manpower resources. In addition, it is very difficult to perform this work in mountainous areas, especially in steep high mountain canyon areas. Therefore, in recent years, some researchers have interpreted and identified potential unstable areas or vulnerable areas of geological disasters by means of satellite optical remote sensing images and the like. But this type of method is limited by the availability of satellite data, the experientiality of the interpreter, and the size of the interpretation area, which limits the rationality and accuracy of the results. In addition, researchers develop a regional disaster susceptibility model based on ArcGIS, and evaluate and grade the susceptibility of geological disasters in the whole region by using influence factors such as lithology, terrain, elevation, fault, rainfall, earthquake and the like. However, the results achieved by the models and the methods are the sequencing and grading of the whole-range geological disaster proneness degree of the research area, and the identification and the definition of the actual instability hidden danger area are not based on the slope instability condition. With the increase of the construction strength of cross-regional long-line engineering in high and steep mountainous areas in China, the requirements of regional disaster prevention and reduction are more urgent than the prior art, and a method for identifying the instability prone area of the regional scale slope is urgently needed.
Disclosure of Invention
The invention provides a slope instability prone area identification method and device based on elevation difference and slope double parameters, and aims to at least solve the technical problems that the existing method is mainly suitable for single scale and cannot meet the requirements of disaster prevention and reduction of the area scale at the present stage.
In order to achieve the purpose, the invention provides a slope instability prone area identification method based on double parameters of height difference and slope, which comprises the following steps:
s100: determining the strength parameters of the rock mass of the bed rock slope on the slope scale;
s200: measuring the current undulation and the side slope angle of each subdivided region; wherein the size of the subdivided region is obtained by counting the size of the historical destabilizing region of the research region in step S100;
s300: calculating the limit fluctuation degree of the subdivided region based on a Culmann principle;
s400: comparing the difference value between the current fluctuation degree and the limit fluctuation degree to evaluate the stable state of the subdivided region, wherein the region with the current fluctuation degree larger than the limit fluctuation degree is determined as a slope instability prone region;
s500: and repeating the steps S100-S400, searching all the slope fine areas of the research area, and estimating the instability susceptibility state of the research area.
Preferably, step S100 includes:
identifying a historical instability area of a research area by combining a digital elevation model, and extracting the fluctuation degree and the slope angle of the historical instability area;
and fitting according to the extracted fluctuation degree and slope angle, and inverting to obtain a rock mass strength parameter value of a slope scale.
Preferably, the method specifically comprises:
inputting 3D surface elevation data DEM of a research area, and respectively calculating surface gradient data slope and surface undulation SSR in a neighborhood area NA;
determining a gradient threshold value, performing logic calculation, defining the grid PSS as a potential gradient surface if the gradient is greater than the grid PSS of the threshold value, and otherwise, deleting the grid;
calculating strength parameters C and phi of the slope rock mass under the slope scale, and obtaining a limit fluctuation LSR in the neighborhood NA through grid operation by utilizing a Culmann model;
performing logical operation on the current surface undulation SSR and the limit undulation LSR of the research area, estimating the stable state of the current surface undulation SSR and judging the area as an early warning grid when the SSR is larger than the LSR;
and carrying out noise point filtration on the early warning grids to obtain the final identified instability prone region distribution range.
Preferably, the grade threshold is 35 ° to 45 °.
Preferably, all scripts are encoded in Python 3 and use the arcpy, os, numpy and operator libraries of the ESRI toolset for Python; using SurfaceVolume _3D tool embedded in 3D analysis package, neighborwood tool embedded in spatial analysis and Map Algebra tool;
wherein LSR is the maximum undulation, beta is the side slope angle, rho is the density of the slope material, g is the gravity acceleration, C is the cohesion force, and phi is the friction angle.
Preferably, the instability prone area identification uses a digital elevation model DEM as a main input and uses a folder for storing and outputting; DEM uses any grid format supported by ArcGIS 10.1; in addition, the use of the tool also needs six additional parameters, namely a neighborhood range, a threshold slope, a cohesive force C, a friction angle phi, a slope material density rho and a gravity acceleration g; wherein:
the neighborhood range is set as a rectangle by default; the threshold slope is defined as a lower limit slope at which the collapse occurs; performing fitting calculation on the cohesive force C and the friction angle phi according to the undulation degree and gradient data of the historical collapse; and the density rho and the gravity acceleration g of the slope material are set according to the characteristics of the research area.
Preferably, when all information is entered and the run button is clicked, the result is returned in a pop-up window containing additional information about the running of the script, and the output file for each step is saved in the designated folder.
The invention also provides a slope instability prone area identification device based on the elevation difference and slope double parameters, which comprises the following steps: the device comprises an intensity parameter determining unit, a measuring unit, a calculating unit, a comparing unit and a stability estimating unit;
the strength parameter determining unit is used for determining the strength parameter of the bedrock slope rock mass on the slope scale;
the measuring unit is used for measuring the current undulation degree and the side slope angle of each subdivision region; wherein the size of the subdivided region is obtained by counting the size of the historical destabilizing region of the research region in step S100;
the calculating unit is used for calculating the limit fluctuation degree of the subdivided region based on the Culmann principle;
the comparison unit is used for comparing the difference value between the current fluctuation degree and the limit fluctuation degree to evaluate the stable state of the subdivided region, and the region with the current fluctuation degree larger than the limit fluctuation degree is determined as the volatile region of slope instability;
and the stability estimation unit is used for repeating the steps S100-S400, searching the fine areas of all slopes of the research area and estimating the instability susceptibility state of the research area.
Compared with the prior art, the invention has the following advantages and technical effects:
according to the method and the device for identifying the slope instability susceptibility area based on the elevation difference and the slope gradient, the strength of the slope rock mass is considered as a basic control factor of the slope stability, and according to a two-dimensional slope stability model of Culmann, the fluctuation degree and the slope gradient are a pair of important indexes for identifying the slope instability susceptibility area. The invention integrates the research foundation of foreigners, and provides a method and a device for identifying a slope instability prone area based on dual parameters of undulation and gradient based on a Culmann model in consideration of the limitation of field investigation and the increasing large-area identification requirement, so as to solve the problems that the existing method provided in the background technology is mainly suitable for single scale and cannot meet the requirements of regional scale disaster prevention and reduction at the present stage.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation of the invention. In the drawings:
FIG. 1 is a flow chart of a slope instability prone area identification method based on a height difference parameter and a gradient parameter;
FIG. 2 is a specific working flow chart of the identification method of the slope instability prone area based on the elevation difference and the slope gradient double parameters;
FIG. 3 is a block diagram of the slope instability prone area identification device based on the dual parameters of the height difference and the gradient.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
Example 1
According to an embodiment of the present invention, a slope instability prone area identification method based on dual parameters of a height difference and a slope is provided, referring to fig. 1, including the following steps:
s100: determining the strength parameters c1 and phi 1 of the rock mass of the bedrock slope on the slope scale;
s200: measuring the current undulation degree H and the side slope angle beta of each subdivision area A; the size of the subdivision area A is obtained through the size statistics of the historical destabilization area of the research area in the step S100, and the undulation degree H is the topographic height difference in unit area;
s300: calculating the limit fluctuation Hc of the subdivision region A based on a Culmann principle; the waviness of the side slope is controlled by the strength of the rock mass of the slope, and the side slope angle beta and the limit waviness Hc have the following relationship:
s400: the difference between the current waviness H and the limit waviness Hc is compared to evaluate the steady state of the region a. Determining the area with the current undulation degree larger than the limit undulation degree as an easy area for slope instability;
s500: and repeating the steps S100-S400, searching all the slope fine areas of the research area, and estimating the instability susceptibility state of the research area.
Wherein, step S100 includes:
and (4) identifying the historical instability area of the research area by combining a digital elevation model, and fitting according to the identification result to obtain the rock mass strength parameter value.
The method specifically comprises the following steps:
inputting 3D surface elevation data DEM of a research area, and respectively calculating surface gradient data slope and surface undulation SSR in a neighborhood area NA;
determining a gradient threshold value, performing logic calculation, defining the grid PSS as a potential gradient surface if the gradient is greater than the grid PSS of the threshold value, and otherwise, deleting the grid;
calculating strength parameters C and phi of the slope rock mass under the slope scale, and obtaining a limit fluctuation LSR in the neighborhood NA through grid operation by utilizing a Culmann model;
performing logical operation on the current surface undulation SSR and the limit undulation LSR of the research area, estimating the stable state of the research area, and judging the area as an early warning grid when the SSR is larger than the LSR;
and carrying out noise point filtration on the early warning grids to obtain the final identified instability prone area distribution range.
Wherein the gradient threshold value is 35-45 degrees.
Wherein all scripts are encoded in Python 3 and use the arcpy, os, numpy and operator libraries for the ESRI toolset for Python; the method uses a SurfaceVolume _3D tool embedded in a 3D analysis package, a Neighborwood tool embedded in a spatial analysis and a Map Algebra tool;
wherein LSR is the maximum undulation, beta is the side slope angle, rho is the density of the slope material, g is the gravity acceleration, C is the cohesion force, and phi is the friction angle.
The instability prone area identification uses a digital elevation model DEM as a main input, and uses a folder for storing and outputting; DEM uses any grid format supported by ArcGIS 10.1; in addition, the use of the tool also needs six additional parameters, namely a neighborhood range, a threshold gradient, cohesive force C, a friction angle phi, a slope material density rho and a gravity acceleration g; wherein:
firstly, setting a neighborhood range as a rectangle by default; the threshold gradient is defined as a lower limit gradient at which slope instability occurs; calculating rock mass strength parameters according to terrain and gradient data of a historical instability area; and finally, setting the density and the gravity acceleration of the slope material according to the characteristics of the research area.
Wherein, once all information is input, the result is returned in a pop-up window after clicking the run button, the window also contains additional information about the running of the script, and the output file of each step is stored in the designated folder.
The method for identifying a slope instability prone area based on double parameters of altitude difference and gradient will be described in detail with specific embodiments as follows:
the strength of the slope rock mass is considered as a basic control factor of the slope stability, and according to a two-dimensional slope stability model of Culmann, the fluctuation degree and the slope are a pair of important indexes for identifying a slope instability prone area. The invention integrates the research foundation of predecessors, and provides a method and a device for identifying the slope instability hair-prone area based on dual parameters of the undulation degree and the gradient based on a Culmann model in consideration of the limitation of field investigation and the increasing large-area identification requirement, and further provides an implementation mode for automatically identifying the hair-prone area by taking ArcGIS as a frame.
The invention aims to provide a slope instability prone area identification method based on elevation difference and slope double parameters, and aims to solve the problems that the existing method provided in the background technology is mainly suitable for single scale and cannot meet the requirements of regional scale disaster prevention and reduction at the present stage.
In order to achieve the above purpose, the present invention provides the following technical solution, including the steps of:
(1) And determining the rock mass strength parameters c1 and phi 1 of the bed rock side slope on the slope scale. Firstly, based on the prior art of the prior literature, the rock mass strength parameters in the area are inquired for reference application; and secondly, identifying the historical instability area of the research area by combining a digital elevation model, fitting according to the identification result, identifying the historical instability area of the research area by combining the digital elevation model, extracting the fluctuation degree and the slope angle of the historical instability part, and fitting according to the extracted data, thereby obtaining the rock mass strength parameter value of the slope scale through inversion.
(2) Measuring the current undulation degree H and the side slope angle beta of each subdivision area A; the size of the subdivision area A is obtained through the size statistics of the historical destabilizing area of the research area in the step S100;
(3) Calculating the limit fluctuation Hc of the subdivision region A based on a Culmann principle; the waviness of the side slope is controlled by the strength of the rock mass of the slope, and the side slope angle beta and the limit waviness Hc have the following relationship:
(4) The difference between the current degree of undulation H and the limit degree of undulation Hc is compared to evaluate the steady state of the area a. Determining the area with the current undulation degree larger than the limit undulation degree as an easy area for slope instability;
(5) And repeating the steps S100-S400, searching all the slope fine areas of the research area, and estimating the instability susceptibility state of the research area.
The specific technical scheme of the invention is as follows:
the strength of the slope rock mass is considered as a basic control factor of the slope stability. According to the Culmann two-dimensional slope stability model, when the slope fluctuation degree in a specified neighborhood exceeds a threshold value, a slope instability prone area is in the neighborhood. Aiming at the problem, the invention provides an automatic slope instability identification tool (FSI) based on an ArcGIS framework and a Culman two-dimensional slope stability model, realizes the rapid identification of the slope instability of a large-scale research area, and applies the technology to the research area. All scripts are encoded in Python 3 and use arcpy (ESRI toolset for Python), os, numpy, and operator libraries. The SurfaceVolume _3D tool embedded in the 3D analysis package, the Neighborwood tool embedded in the spatial analysis, and the Map Algebra tool are mainly used.
Wherein LSR is the maximum undulation, beta is the side slope angle, rho is the density of the slope material, g is the gravity acceleration, C is the cohesion force, and phi is the friction angle.
Tool box input parameters and script execution: the source identification tool requires a Digital Elevation Model (DEM) of the surface of the study area as a primary input and a folder to store the output. The DEM may use any grid format supported by ArcGIS 10.1, among others. In addition, the use of the tool requires six additional parameters, namely the neighborhood range, the threshold slope, the cohesion C, the friction angle phi, the slope material density ρ, and the gravitational acceleration g. The first is the neighborhood range, which is set by default to be rectangular, 50 meters in length and width, but can be modified according to the characteristics of the study area (depending on the size of the slope instability scale of the study area and the vertical resolution of the DEM). The threshold slope is defined as the lower limit slope below which the collapse occurs, and the present invention recognizes that the slope instability occurs, and the default value is 40 °. The rock mass strength parameter is calculated according to the relief terrain and gradient data of historical slope instability, the default values are 240Kpa and 23 degrees respectively, and the user can freely modify the values again. And finally, setting the density and the gravity acceleration of the slope material according to the characteristics of the research area. Once all information is entered, clicking the run button returns the result in a pop-up window that also contains additional information about the running of the script. The output files for each step will be saved in the designated folder.
The specific working flow of the invention is shown in fig. 2:
(1) Inputting 3D surface elevation Data (DEM) of a research area, and respectively calculating surface gradient data (slope) and surface undulation (SSR) in a Neighborhood Area (NA).
(2) Determining a gradient threshold (conservative calculation, 40 degrees is selected in the invention), performing logic calculation, and defining a potential gradient surface if the gradient is larger than the grid (PSS) of the threshold, otherwise, deleting the grid.
(3) And (3) calculating the strength parameters (C, phi) of the rock mass of the slope under the slope scale, and obtaining the limit fluctuation (LSR) in the neighborhood NA through grid operation by utilizing a Culmann model.
(4) And performing logical operation on the current surface fluctuation (SSR) and the limit fluctuation (LSR) of the research area to estimate the stable state of the research area. When SSR > LSR, the region is determined to be an early warning grid.
(5) And carrying out noise point filtration on the early warning grids to obtain a slope instability prone area which is finally identified, and obtaining the distribution range of the slope instability of the research area which is finally identified.
Example 2
According to another embodiment of the present invention, there is provided a slope instability prone area identification device based on dual parameters of a height difference and a gradient, referring to fig. 3, including:
the strength parameter determining unit 201 is used for determining the strength parameters c1 and phi 1 of the slope rock mass on the scale of the slope;
a measuring unit 202 for measuring the current undulation H and the slope angle β of each subdivided area a; the size of the subdivision area A is obtained through the size statistics of the historical destabilizing area of the research area in the step S100;
a calculating unit 203, configured to calculate a limit waviness Hc of the subdivided region a based on a Culmann principle; the waviness of the side slope is controlled by the strength of the rock mass of the slope, and the side slope angle beta and the limit waviness Hc have the following relationship:
a comparison unit 204 for comparing the difference between the current waviness H and the limit waviness Hc to evaluate the steady state of the region a. Determining the area with the current undulation degree larger than the limit undulation degree as an easy area for slope instability;
and the stability estimation unit 205 is configured to repeat steps S100 to S400, search for fine regions of all slopes of the research region, and estimate a vulnerability state of instability of the research region.
The following describes in detail the slope instability prone area identification device based on the dual parameters of altitude difference and gradient according to a specific embodiment of the present invention:
the strength of the slope rock mass is considered as a basic control factor of the slope stability, and according to a two-dimensional slope stability model of Culmann, the fluctuation degree and the slope are a pair of important indexes for identifying a slope instability prone area. The invention integrates the research foundation of predecessors, and provides a slope instability volatile area identification device based on dual parameters of undulation degree and gradient based on a Culmann model in consideration of the limitation of field investigation and the increasing large-area identification requirement, and further provides an implementation mode for automatically identifying the volatile area by taking ArcGIS as a frame.
The invention aims to provide a slope instability prone area identification device based on height difference and slope double parameters, and solves the problems that the existing method provided in the background technology is mainly suitable for single scale and cannot meet the requirements of disaster prevention and reduction of regional scale at the present stage.
In order to achieve the above purpose, the present invention provides the following technical solution, including the steps of:
(1) And determining the strength parameters (c 1, phi 1) of the rock mass of the bedrock slope on the slope scale. The method mainly comprises two methods, one is that based on the prior art of the prior literature, the rock mass strength parameter in the area is inquired for reference application; and secondly, identifying the historical instability area of the research area by combining a digital elevation model, fitting according to the identification result, identifying the historical instability area of the research area by combining the digital elevation model, extracting the fluctuation degree and the slope angle of the historical instability part, and fitting according to the extracted data, thereby obtaining the rock mass strength parameter value of the slope scale through inversion.
(2) Measuring the current undulation H and the side slope angle beta of each subdivision area A; the size of the subdivision area A is obtained through the size statistics of the historical destabilizing area of the research area in the step (1);
(3) Calculating the limit fluctuation Hc of the subdivided region A based on a Culmann principle; the waviness of the side slope is controlled by the strength of the rock mass of the slope, and the side slope angle beta and the limit waviness Hc (maximum height difference) have the following relations:
(4) The difference between the current waviness H and the limit waviness Hc is compared to evaluate the steady state of the region a. Determining the area with the current undulation degree larger than the limit undulation degree as an easy area for slope instability;
(5) And (5) repeating the steps (1) to (4), searching the fine areas of all slopes of the research area, and estimating the instability susceptibility state of the research area. Eventually, all potential destabilizing regions are identified.
The specific technical scheme of the invention is as follows:
the strength of the slope rock mass is considered as a basic control factor of the slope stability. According to the Culmann two-dimensional slope stability model, when the slope fluctuation degree in a specified neighborhood exceeds a threshold value, a slope instability prone area is in the neighborhood. Aiming at the problem, the invention provides an automatic slope instability identification tool (FSI) based on an ArcGIS frame and a Culman two-dimensional slope stability model, realizes the rapid identification of the slope instability of a large-scale research area, and applies the technology to the research area. All scripts are encoded in Python 3 and use arcpy (ESRI toolset for Python), os, numpy, and operator libraries. The SurfaceVolume _3D tool embedded in the 3D analysis package, the Neighborwood tool embedded in the spatial analysis, and the Map Algebra tool are mainly used.
Wherein LSR is the maximum undulation, beta is the side slope angle, rho is the density of the slope material, g is the gravity acceleration, C is the cohesion force, and phi is the friction angle.
Tool box input parameters and script execution: the source recognition tool requires a Digital Elevation Model (DEM) of the surface of the area of investigation as a primary input and a folder to store the output. The DEM may use any grid format supported by ArcGIS 10.1, among others. In addition, the use of the tool requires six additional parameters, namely the neighborhood range, the threshold slope, the cohesion C, the friction angle phi, the slope material density ρ, and the gravitational acceleration g. The first is the neighborhood range, which is set by default to be rectangular, 50 meters in length and width, but can be modified according to the characteristics of the study area (depending on the size of the slope instability scale of the study area and the vertical resolution of the DEM). The threshold slope is defined as the lower limit slope below which the collapse occurs, and the present invention recognizes that the slope instability occurs, and the default value is 40 °. The rock mass strength parameter is calculated according to the relief terrain and gradient data of historical slope instability, the default values are 240Kpa and 23 degrees respectively, and the user can freely modify the values again. And finally, setting the density and the gravity acceleration of the slope material according to the characteristics of the research area. Once all information is entered, clicking the run button returns the result in a pop-up window that also contains additional information about the running of the script. The output files for each step will be saved in the designated folder.
The specific working process of the invention is as follows:
(1) Inputting 3D surface elevation Data (DEM) of a research area, and respectively calculating surface gradient data (slope) and surface undulation (SSR) in a Neighborhood Area (NA).
(2) Determining a gradient threshold (conservative calculation, 40 degrees is selected in the invention), performing logic calculation, and defining a potential gradient surface if the gradient is larger than the grid (PSS) of the threshold, otherwise, deleting the grid.
(3) And (3) calculating the strength parameters (C, phi) of the slope rock mass under the slope scale, and obtaining the limit fluctuation (LSR) in the neighborhood NA by using a Culmann model through grid operation.
(4) And performing logical operation on the current surface fluctuation (SSR) and the limit fluctuation (LSR) of the research area to estimate the stable state of the research area. When SSR > LSR, the region is determined to be an early warning grid.
(5) And carrying out noise point filtration on the early warning grids to obtain a slope instability prone area which is finally identified, and obtaining the distribution range of the slope instability of the research area which is finally identified.
According to the slope instability prone area identification method and device based on the height difference and the gradient, the strength of the slope rock mass is regarded as a basic control factor of the slope stability, and according to a Culmann two-dimensional slope stability model, the waviness and the gradient are a pair of important indexes for identifying the slope instability prone area. The invention integrates the research foundation of foreigners, and provides a method and a device for identifying a slope instability prone area based on dual parameters of undulation and gradient based on a Culmann model in consideration of the limitation of field investigation and the increasing large-area identification requirement, so as to solve the problems that the existing method provided in the background technology is mainly suitable for single scale and cannot meet the requirements of regional scale disaster prevention and reduction at the present stage.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are also within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. The slope instability prone area identification method based on the elevation difference and the slope gradient double parameters is characterized by comprising the following steps:
s100: determining the rock mass strength parameters of the bed rock slope on the slope scale;
s200: measuring the current undulation and the side slope angle of each subdivided region; the size of the subdivided region is obtained by counting the size of the historical destabilizing region of the research region in the step S100;
s300: calculating the limit fluctuation degree of the subdivided region based on a Culmann principle;
s400: comparing the difference value between the current fluctuation degree and the limit fluctuation degree to evaluate the stable state of the subdivided region, wherein the region with the current fluctuation degree larger than the limit fluctuation degree is determined as a slope instability prone region;
s500: and repeating the steps S100-S400, searching all the slope fine areas of the research area, and estimating the instability susceptibility state of the research area.
2. The slope instability prone area identification method based on the dual parameters of the height difference and the gradient as claimed in claim 1, wherein step S100 comprises:
identifying a historical instability area of a research area by combining a digital elevation model, and extracting the fluctuation degree and the slope angle of the historical instability area;
and fitting according to the extracted fluctuation degree and slope angle, and inverting to obtain a rock mass strength parameter value of a slope scale.
3. The slope instability prone area identification method based on the elevation difference and gradient parameters as claimed in claim 2, wherein the method specifically comprises:
inputting 3D surface elevation data DEM of a research area, and respectively calculating surface gradient data slope and surface undulation SSR in a neighborhood area NA;
determining a gradient threshold value, performing logic calculation, defining the grid PSS as a potential gradient surface if the gradient is greater than the grid PSS of the threshold value, and otherwise, deleting the grid;
calculating the strength parameters C and phi of the slope rock mass under the slope scale, and obtaining the limit fluctuation LSR in the neighborhood NA through grid operation by utilizing a Culmann model;
performing logical operation on the current surface undulation SSR and the limit undulation LSR of the research area, estimating the stable state of the current surface undulation SSR and judging the area as an early warning grid when the SSR is larger than the LSR;
and carrying out noise point filtration on the early warning grids to obtain the final identified instability prone area distribution range.
4. The slope instability prone area identification method based on the dual parameters of altitude difference and gradient according to claim 3, wherein the gradient threshold value is 35-45 °.
5. The slope instability prone area identification method based on the double parameters of the altitude difference and the gradient according to claim 3, characterized in that all scripts are coded in Python 3, and the arcpy, os, numpy and operation symbol libraries of the ESRI tool set for Python are used; using SurfaceVolume _3D tool embedded in 3D analysis package, neighborwood tool embedded in spatial analysis and Map Algebra tool;
wherein LSR is the maximum undulation, beta is the side slope angle, rho is the density of the slope material, g is the gravity acceleration, C is the cohesion force, and phi is the friction angle.
6. The slope instability prone zone identification method based on the height difference and the gradient double parameters is characterized in that instability prone zone identification uses a digital elevation model DEM as a main input and uses a folder to store an output; DEM uses any grid format supported by ArcGIS 10.1; in addition, the use of the tool also needs six additional parameters, namely a neighborhood range, a threshold gradient, cohesive force C, a friction angle phi, a slope material density rho and a gravity acceleration g; wherein:
the neighborhood range is set as a rectangle by default; the threshold slope is defined as the lower limit slope of collapse; performing fitting calculation on the cohesive force C and the friction angle phi according to the undulation degree and gradient data of the historical collapse; and the density rho and the gravity acceleration g of the slope material are set according to the characteristics of the research area.
7. The method for identifying the instability prone area of a slope based on two parameters of height difference and gradient according to claim 6, wherein when all information is inputted and the run button is clicked, the result is returned in a pop-up window, the window further contains additional information about the running of the script, and the output file of each step is saved in the designated folder.
8. Slope unstability is liable to send out district recognition device based on discrepancy in elevation and slope double parameter, its characterized in that includes: the device comprises an intensity parameter determining unit, a measuring unit, a calculating unit, a comparing unit and a stability estimating unit;
the strength parameter determining unit is used for determining the strength parameter of the bedrock slope rock mass on the slope scale;
the measuring unit is used for measuring the current undulation degree and the side slope angle of each subdivision region; wherein the size of the subdivided region is obtained by counting the size of the historical destabilizing region of the research region in step S100;
the calculating unit is used for calculating the limit fluctuation degree of the subdivided region based on the Culmann principle;
the comparison unit is used for comparing the difference value between the current fluctuation degree and the limit fluctuation degree to evaluate the stable state of the subdivided region, and the region with the current fluctuation degree larger than the limit fluctuation degree is determined as a slope instability prone region;
and the stability estimation unit is used for repeating the steps S100-S400, searching the fine areas of all slopes of the research area and estimating the instability susceptibility state of the research area.
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| CN110941689A (en) * | 2019-11-18 | 2020-03-31 | 云南瀚哲科技有限公司 | Landform type dividing method based on ArcGIS |
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