CN117541736A - Ground disaster risk distribution map generation method and system for scanning geological three-dimensional model - Google Patents
Ground disaster risk distribution map generation method and system for scanning geological three-dimensional model Download PDFInfo
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Abstract
The invention discloses a method and a system for generating a ground disaster risk distribution map of a scanning geological three-dimensional model, which relate to the technical field of geological disaster analysis and have the technical scheme that: according to the method, on the basis of constructing the three-dimensional geological model with the attributes, information contained in the three-dimensional geological model is directly scanned, geological environment complexity indexes of corresponding virtual partitions are obtained through complexity index function calculation, geological disaster susceptibility indexes are obtained through combination of the geological environment complexity indexes and basic field environment conditions, automatic analysis of ground disaster risk degrees of different parts of the earth surface is achieved, and the ground disaster risk degrees of underground potential unstable bodies can be deduced.
Description
Technical Field
The invention relates to the technical field of geological disaster analysis, in particular to a method and a system for generating a ground disaster risk distribution map of a scanning geological three-dimensional model.
Background
Ground disaster risk analysis is a primary task of various engineering construction activities in a feasibility research stage, and is particularly important in hydropower development engineering in mountain gorge areas. The susceptibility to geological disasters is an important index for analyzing the occurrence risk probability of geological disasters at different positions in an engineering area, and the accuracy of the risk probability greatly influences the effectiveness and the economy of the ground disaster treatment work.
At present, two main methods for obtaining geological disaster susceptibility indexes exist in the prior art: first, a professional evaluates the degree of ground disaster risk in a scoring mode by examining factors such as topography, formation lithology, structure, hydrogeology, human activities and the like. Secondly, obtaining quantitative grading results of factors such as geology, topography, vegetation conditions, relatively stable human activities and the like based on a GIS model database, and predicting distribution conditions of the ground disaster susceptibility indexes, such as an evidence weight method, an analytic hierarchy process, a support vector machine method, a neural network method and the like by superposing information amounts of the factors through mathematical statistical models or machine learning calculation.
However, the first standard scoring method has low quantification and relies on the experience level of professionals in performing ground disaster risk analysis. The method is not tightly combined with geological three-dimensional technology application, each evaluation unit needs to be scored and calculated manually one by one, and the data batch processing capacity is weak. In addition, the current geological disaster analysis results mainly comprise the steps of compiling a ground disaster risk analysis report, drawing a two-dimensional chart and the like, and the current investigation digital transformation requirements are difficult to meet. Secondly, the method combined with GIS model analysis can generate geological disaster risk distribution prediction results relatively quickly for a large-scale area, but is limited by the characteristics of the GIS model (mainly mass data acquisition and storage, large research areas are large areas and small scale), and aiming at the scale of a smaller key engineering area, training samples are insufficient, so that the accuracy requirements on space analysis and prediction are difficult to meet. In addition, the analysis factors are mostly based on surface layer mapping data such as topography, river vegetation and the like, and the influence degree of the deep geological factors on disaster vulnerability indexes is not considered enough. Although the analysis method based on GIS data has thousands of years in basic mathematical theory, the analysis method has the capability of hardly considering the influence of deep geological conditions, and has a certain improvement space in the ground disaster risk analysis profession.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a method and a system for generating a ground disaster risk distribution map of a scanning geological three-dimensional model, which are used for calculating a geological environment complexity index of a corresponding virtual partition through a complexity index function, calculating a geological disaster susceptibility index by combining the geological environment complexity index and basic field environment conditions, realizing the automatic analysis of the ground disaster risk degree of different parts of the earth surface, and deducing the ground disaster risk degree of an underground potential unstable body.
The technical aim of the invention is realized by the following technical scheme:
in a first aspect, a method for generating a ground disaster risk distribution map of a scanned geological three-dimensional model is provided, including the following steps:
calibrating geological units required by the calculation of the ground disaster vulnerability index in the three-dimensional geological model containing the attribute, and inputting basic field environment conditions required by the calculation of the ground disaster vulnerability index;
determining a parameter range corresponding to the complexity level of each geological environment condition factor;
dividing a projection plane of the ground surface in the three-dimensional geological model in the elevation direction into a plurality of virtual partitions which are independently analyzed;
scanning geological unit information input in the range of each virtual partition, and determining the complexity analysis result of each geological unit in the same virtual partition according to the corresponding parameter range;
analyzing the regional degree grade of the corresponding virtual partition according to the distribution condition of the complexity grade in the complexity analysis result;
selecting a corresponding complexity index function according to the regional level, and combining the complexity analysis result and the selected complexity index function to calculate and obtain the geological environment complexity index of the corresponding virtual partition;
and calculating to obtain a geological disaster susceptibility index by combining the geological environment complexity index and the basic field environment condition, and giving corresponding grid points as geological attributes so as to realize three-dimensional visualization processing of the ground disaster risk analysis result.
Further, the geological units include ground surfaces, overburden interfaces, penetrating structural surfaces, ground water levels, surface water influence range lines, undesirable geological phenomenon outcrop lines, goafs, and land range lines. The basic intensity of earthquake in the field, average annual rainfall for many years and average daily rainfall are input.
Further, the basic field environmental conditions include basic intensity of earthquakes, average annual rainfall over years, and average daily rainfall.
Further, the analysis process of the regional level specifically includes:
determining the complexity level of the virtual partition under each control factor;
and selecting the most unfavorable result in all the complexity levels as the regional level of the corresponding virtual partition.
Further, the regional level of controllability is divided into a primary controllability and a secondary controllability;
the main control factors comprise natural steep slope height, a relation between a penetrability structural surface and a slope, a proportion of occupied ground area of poor geological phenomenon and human activities for destroying geological environment;
the secondary controlling factors include terrain slope angle, soil layer thickness, formation or soil layer differential, rock structure type, fracture configuration, seismic intensity, surface water influence, groundwater influence, thickness-to-span ratio, and goaf footprint ratio.
Further, the expression of the complexity index function is specifically:
wherein D represents a geological environment complexity index; gamma ray 1 、γ 2 、γ 3 、γ 4 、γ 5 For calculating the coefficients, interpolation calculation is carried out from a database; a represents the repetition times of complexity level being complexity level in the virtual partition; b represents the number of repetitions of a medium level of complexity within the virtual partition.
Further, the number of repetitions of the complexity level being the complexity level in the virtual partition is the sum of the number of complexity levels corresponding to the primary control factor and the number of complexity levels corresponding to the secondary control factor.
Further, the number of repetitions of the complexity level being the intermediate level in the virtual partition is the sum of the intermediate level number corresponding to the primary control factor and the intermediate level number corresponding to the secondary control factor.
Further, the calculation formula of the geological disaster susceptibility index specifically comprises:
γ＝0.618D+0.382R
wherein, gamma represents a geological disaster susceptibility index; d represents a geological environment complexity index; r represents the precipitation index.
In a second aspect, there is provided a ground-disaster risk distribution map generation system for scanning a geological three-dimensional model, the system being applied to the ground-disaster risk distribution map generation method for scanning a geological three-dimensional model according to any one of the first aspects, comprising:
the model processing module is used for calibrating geological units required by the calculation of the ground disaster vulnerability index in the three-dimensional geological model containing the attribute and inputting basic field environment conditions required by the calculation of the ground disaster vulnerability index;
the parameter determining module is used for determining a parameter range corresponding to the complexity level of each geological environment condition factor;
the region dividing module is used for dividing a projection surface of the ground surface in the three-dimensional geological model in the elevation direction into a plurality of virtual partitions which are independently analyzed;
the complex analysis module is used for scanning the geological unit information input in the range of each virtual partition and determining the complexity analysis result of each geological unit in the same virtual partition according to the corresponding parameter range;
the regional analysis module is used for analyzing regional degree grades of the corresponding virtual partitions according to the distribution condition of the complexity grade in the complexity analysis result;
the index calculation module is used for selecting a corresponding complexity index function according to the regional level, and calculating to obtain the geological environment complexity index of the corresponding virtual partition by combining the complexity analysis result and the selected complexity index function;
the risk analysis module is used for combining the geological environment complexity index and the basic field environment condition to calculate and obtain a geological disaster susceptibility index, and is used as geological attributes to be endowed with corresponding grid points so as to realize three-dimensional visualization processing of the ground disaster risk analysis result.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the method for generating the ground disaster risk distribution map of the scanned geological three-dimensional model, on the basis of constructing the three-dimensional geological model with the attributes, information contained in the three-dimensional geological model is directly scanned, geological environment complexity indexes of corresponding virtual partitions are obtained through complexity index function calculation, and the geological disaster susceptibility indexes are obtained through calculation by combining the geological environment complexity indexes and basic field environment conditions, so that ground disaster risk degree automatic analysis of different parts of the ground surface is realized, and the ground disaster risk degree of underground potential unstable bodies can be deduced;
2. the method combines the ground disaster risk analysis method with the three-dimensional geological modeling technology, comprehensively surveys various geological condition judgment factors of the earth surface and the underground to analyze the ground disaster risk degree, has stronger pertinence of inputting samples on engineering scale compared with a factor scoring method based on a GIS platform, and has the capability of considering the influence of deep geological information on an evaluation result;
3. according to the invention, the three-dimensional digital graphic technology and the geological experience knowledge are combined, virtual partition refinement is carried out on the evaluation area, and the problem of insufficient quantification degree of the traditional standard method is solved; compared with the traditional manual calculation scoring method, the automatic calculation analysis is realized by utilizing a computer, the evaluation efficiency and accuracy can be improved, the result output is mainly based on three-dimensional digital images, the use friendliness is stronger, and the method can be popularized to different topography and topography conditions.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention. In the drawings:
FIG. 1 is a flow chart in embodiment 1 of the present invention;
FIG. 2 is a three-dimensional geological model data map of the field region in example 1 of the present invention;
FIG. 3 is a map of complex parameter definitions of the geologic environment in accordance with embodiment 1 of the invention;
FIG. 4 is a schematic diagram of the result of virtual partitioning in embodiment 1 of the present invention;
FIG. 5 is a graph showing the analysis result of the slope angle of the topography of the field area in example 1 of the present invention;
FIG. 6 is a graph showing the analysis result of the field region steep slope height in example 1 of the invention;
FIG. 7 is a graph showing the analysis result of the soil layer thickness of the field area in example 1 of the present invention;
FIG. 8 is a graph showing the analysis result of the field region geotechnical layer difference in example 1 of the present invention;
FIG. 9 is a schematic diagram showing the analysis result of the field fracture structure in example 1 of the present invention;
FIG. 10 is a graph showing the analysis results of intersection angles of field penetration structures in example 1 of the present invention;
FIG. 11 is a graph showing the analysis results of the disaster liability degree of the field area in example 1 of the present invention;
fig. 12 is a system block diagram in embodiment 2 of the present invention.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
Example 1: a method for generating a ground disaster risk distribution map of a scanning geological three-dimensional model is shown in fig. 1, and comprises the following steps:
s1: calibrating geological units required by the calculation of the ground disaster vulnerability index in the three-dimensional geological model containing the attribute, and inputting basic field environment conditions required by the calculation of the ground disaster vulnerability index;
s2: determining a parameter range corresponding to the complexity level of each geological environment condition factor;
s3: dividing a projection plane of the ground surface in the three-dimensional geological model in the elevation direction into a plurality of virtual partitions which are independently analyzed;
s4: scanning geological unit information input in the range of each virtual partition, and determining the complexity analysis result of each geological unit in the same virtual partition according to the corresponding parameter range;
s5: analyzing the regional degree grade of the corresponding virtual partition according to the distribution condition of the complexity grade in the complexity analysis result;
s6: selecting a corresponding complexity index function according to the regional level, and combining the complexity analysis result and the selected complexity index function to calculate and obtain the geological environment complexity index of the corresponding virtual partition;
s7: and calculating to obtain a geological disaster susceptibility index by combining the geological environment complexity index and the basic field environment condition, and giving corresponding grid points as geological attributes so as to realize three-dimensional visualization processing of the ground disaster risk analysis result.
In step S1, the geological units include, but are not limited to, ground surfaces, overburden interfaces, penetrating structural surfaces, groundwater level surfaces, surface water influence range lines, undesirable geological phenomenon outcrop lines, goafs, and land range lines. The basic intensity of earthquake in the field, average annual rainfall for many years and average daily rainfall are input. While basic field environmental conditions include, but are not limited to, seismic basic intensity, years of average annual rainfall, and daily average rainfall.
FIG. 2 shows three-dimensional geologic model data for a field, including a penetrating fracture and overburden within an analysis range.
In step S2, as shown in fig. 3, parameters of different factors in determining the level of complexity from "complex" to "simple" are different, so that an adaptive determination is required for different factors.
In step S3, the virtual partition may be square or rectangular, and the minimum partition area in the topographic map is 0.01m 2 The actual investigation region is related to the topography scale. For the embodiment, the scale of the topography is 1/500, and the corresponding actual area is 2500m 2 . Thus, for rectangular partitions, the U and V values (respectively the length and width of the rectangle) correspond to 50m, and the virtual partition results are shown in fig. 4.
In step S4, geological unit information input in the range of each virtual partition is scanned, and geological environment complexity calculation results of all evaluation partitions are obtained by adopting a corresponding calculation method, wherein the geological environment complexity calculation results comprise 14 calculation contents of natural steep slope height, through structural surface and slope relation, poor geological phenomenon occupation area proportion, human activities damaging geological environment, topography slope angle, soil layer thickness, rock stratum or soil layer difference, rock mass structure type, fracture structure, seismic intensity, surface water influence, groundwater influence, thickness-span ratio and goaf occupation area ratio. In the embodiment, the influence of bad geological phenomena, human activities damaging geological environments, rock mass structure types, surface water, underground water, thickness-to-span ratio and goaf in the geological environment complexity investigation is small, so that the other 7 indexes are mainly considered.
Specifically, when calculating the slope angle of the terrain, calculating the inclination angle and the area of each triangle in the virtual ground surface partition, wherein the slope angle of the terrain of the ith triangle is obtained by calculating the inclination angle of the triangle and the adjacent triangle according to the area weighting, and the weighting calculation adopts the following formula:
wherein A is j And beta j The area (m 2) and the inclination angle (°) of the j-th adjacent triangle (including itself), respectively. The result of the topographic slope angle calculation is shown in fig. 5.
Specifically, when the steep slope height calculation and type division are performed, the slope height definition is performed by referring to the slope inclination angle of the terrain except the elevation index. For the soil slope, inquiring triangles with a topography slope angle larger than 35 degrees in the area, defining the difference between the minimum and maximum elevation coordinates of triangle corner points with adjacent (continuous connection) conditions as the slope height, assigning the height value to all the connected triangles, and assigning zero to the triangle slope height value when the topography slope angle is smaller than 35 degrees; the rock slope height calculation method is consistent with the soil slope, and is different in that the slope height criterion, namely the terrain slope angle, is used as a threshold value by 60 degrees. The slope type is identified by adopting the relation between the slope type and the boundary surface of the covering layer, the soil slope is positioned below the ground surface in the range of the covering layer, and the rest ranges belong to the rock slope. The calculation result of the rock slope steep slope height is shown in fig. 6.
Specifically, when the soil layer thickness is calculated, the boundary of the covering layer is vertically projected to the ground surface, namely, the boundary and the top and bottom of the covering layer are used for limiting and determining the subareas and triangles in the subareas, the calculated thickness of the covering layer is used as the soil layer thickness to be assigned to the triangles, and when no covering layer exists, the thickness is recorded as zero or blank. The soil layer thickness calculation results are shown in fig. 7.
Specifically, when the rock stratum or soil layer difference is calculated, the index calculation is carried out when the penetrability interface in the virtual partition range is not empty, all the virtual partitions in the evaluation domain are traversed, definition is carried out according to the stratum characteristics, the geological environment complexity degree is simple when the region only contains one stratum, the covering layer is medium when the region contains the covering layer and one stratum, the covering layer is complex when the region contains the covering layer and two or more strata, and the region defaults to medium. The results of the geotechnical layer difference calculation are shown in fig. 8.
Specifically, when the fracture structure index is calculated, all virtual partitions in the evaluation domain are traversed, definition is carried out according to the intersection relation between the structural surface with thickness and the region, the intersection relation between the region and the structural surface with thickness is simple, the intersection relation between the structural surface with thickness and the region is medium, the intersection relation between more than 2 structural surfaces with thickness and the region is complex, and the intersection relation between more than 2 structural surfaces with thickness and the region is simple by default. The fracture structure calculation results are shown in fig. 9.
Specifically, when the relation between the penetrating structure surface and the slope is calculated, the penetrating interface is not effective in the space, all areas are traversed, firstly, index calculation is carried out, wherein the index calculation comprises the average inclination of the slope surface of the area, the average inclination and the inclination angle of each penetrating structure surface intersected with the ground surface in the area, the average intersection angle (taking a value smaller than 180 degrees) of each penetrating structure surface inclination and the slope surface of the area, the complexity defaulting is simple, and if the inclination angle is larger than 15 degrees in all interfaces below the area (not intersected), the inclination angle of the interface intersected with the area is larger than 8 degrees and smaller than 15 degrees, and the inclination intersection angle is smaller than 30 degrees, the value is moderate; when the average inclination angle of a certain intersected through structural surface in the area is larger than 15 degrees and the inclined intersection angle is smaller than 30 degrees, the geological complexity of the reaction of the through structural surface and the slope relation index is complicated. The result of the calculation of the relationship between the penetrating structure surface and the slope is shown in fig. 10.
Specifically, the seismic intensity influence result is directly obtained from the field seismic basic intensity input index.
In step S5, the control factors of the area complexity are classified into two types: the main control factors comprise natural steep slope height, a relation between a penetrability structural surface and a slope, a proportion of occupied ground area of poor geological phenomenon and human activities for destroying geological environment, and the total number is 4; secondary controlling factors of regional complexity include terrain slope angle, soil layer thickness, formation or soil layer differences, rock mass structure type, fracture configuration, seismic intensity, surface water influence, groundwater influence, thickness-to-span ratio, goaf occupation area ratio, for a total of 10 items.
The number of main control factors in the calculation region reaching the "complex" or "medium" standard, such as N1 index components meeting the "complex" standard and N2 index components meeting the "medium" standard, should be 0.ltoreq.N 1 (or N2). Ltoreq.4. When the main index is used for judging the complexity level of the region, the complexity level of the region takes the least adverse results of the component indexes, and if any component meets the complexity standard, the complexity level of the region is defined as complexity.
Judging the number of secondary control factors in the region to reach the 'complex' or 'medium' standard, if 5 (or more) of the 10 component indexes can simultaneously meet the complexity standard, judging the obtained geological environment complexity of the region by utilizing the secondary indexes to be the level, and assuming that the component numbers meeting the 'complex' and 'medium' standard are N1 'and N2', respectively, obviously 0< = N1 '(or N2') < = 10.
Finally, comprehensively judging the regional complexity level according to the analysis result, taking the most unfavorable complexity level, and counting the total index number reaching a certain standard, namely the complex standard repetition number A=N1+N1 ', and the medium level repetition number B=N2+N2'.
In step S5, the expression of the complexity index function is specifically:
wherein D represents a geological environment complexity index; gamma ray 1 、γ 2 、γ 3 、γ 4 、γ 5 For calculating the coefficients, interpolation calculation is carried out from a database; a represents the repetition times of complexity level being complexity level in the virtual partition; b represents the number of repetitions of a medium level of complexity within the virtual partition.
In step S7, the calculation formula of the geological disaster susceptibility index specifically includes:
γ＝0.618D+0.382R
wherein, gamma represents a geological disaster susceptibility index; d represents a geological environment complexity index; r represents the precipitation index. The result of calculating the index of susceptibility to a disaster is shown in fig. 11.
Example 2: a ground disaster risk distribution map generation system for scanning a geological three-dimensional model, which is applied to the ground disaster risk distribution map generation method for scanning a geological three-dimensional model according to any one of the first aspect, as shown in fig. 12, and comprises a model processing module, a parameter determining module, a region dividing module, a complex analysis module, a region analysis module, an index calculation module and a risk analysis module.
The model processing module is used for calibrating geological units required by the calculation of the ground disaster vulnerability index in the three-dimensional geological model containing the attribute and inputting basic field environment conditions required by the calculation of the ground disaster vulnerability index; the parameter determining module is used for determining a parameter range corresponding to the complexity level of each geological environment condition factor; the region dividing module is used for dividing a projection surface of the ground surface in the three-dimensional geological model in the elevation direction into a plurality of virtual partitions which are independently analyzed; the complex analysis module is used for scanning the geological unit information input in the range of each virtual partition and determining the complexity analysis result of each geological unit in the same virtual partition according to the corresponding parameter range; the regional analysis module is used for analyzing regional degree grades of the corresponding virtual partitions according to the distribution condition of the complexity grade in the complexity analysis result; the index calculation module is used for selecting a corresponding complexity index function according to the regional level, and calculating to obtain the geological environment complexity index of the corresponding virtual partition by combining the complexity analysis result and the selected complexity index function; the risk analysis module is used for combining the geological environment complexity index and the basic field environment condition to calculate and obtain a geological disaster susceptibility index, and is used as geological attributes to be endowed with corresponding grid points so as to realize three-dimensional visualization processing of the ground disaster risk analysis result.
Working principle: according to the method, on the basis of constructing the three-dimensional geological model with the attributes, information contained in the three-dimensional geological model is directly scanned, geological environment complexity indexes of corresponding virtual partitions are obtained through complexity index function calculation, geological disaster susceptibility indexes are obtained through combination of the geological environment complexity indexes and basic field environment conditions, automatic analysis of ground disaster risk degrees of different parts of the earth surface is achieved, and the ground disaster risk degrees of underground potential unstable bodies can be deduced; in addition, the method integrates the ground disaster risk analysis method and the three-dimensional geological modeling technology, comprehensively surveys various geological condition judgment factors of the earth surface and the underground to analyze the ground disaster risk degree, has stronger pertinence of inputting samples on engineering scale compared with a factor scoring method based on a GIS platform, and has the capability of considering the influence of deep geological information on an evaluation result.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. A method for generating a ground disaster risk distribution map of a scanning geological three-dimensional model is characterized by comprising the following steps:
calibrating geological units required by the calculation of the ground disaster vulnerability index in the three-dimensional geological model containing the attribute, and inputting basic field environment conditions required by the calculation of the ground disaster vulnerability index;
determining a parameter range corresponding to the complexity level of each geological environment condition factor;
dividing a projection plane of the ground surface in the three-dimensional geological model in the elevation direction into a plurality of virtual partitions which are independently analyzed;
scanning geological unit information input in the range of each virtual partition, and determining the complexity analysis result of each geological unit in the same virtual partition according to the corresponding parameter range;
analyzing the regional degree grade of the corresponding virtual partition according to the distribution condition of the complexity grade in the complexity analysis result;
selecting a corresponding complexity index function according to the regional level, and combining the complexity analysis result and the selected complexity index function to calculate and obtain the geological environment complexity index of the corresponding virtual partition;
and calculating to obtain a geological disaster susceptibility index by combining the geological environment complexity index and the basic field environment condition, and giving corresponding grid points as geological attributes so as to realize three-dimensional visualization processing of the ground disaster risk analysis result.
2. The method for generating a ground disaster risk profile for scanning a geological three-dimensional model according to claim 1, wherein said geological units comprise ground surfaces, overburden interfaces, penetrating structural surfaces, groundwater level surfaces, surface water influence range lines, bad geological phenomenon outcrop lines, goaf and land use range lines. The basic intensity of earthquake in the field, average annual rainfall for many years and average daily rainfall are input.
3. The method for generating a ground disaster risk profile for scanning geological three-dimensional model according to claim 1, wherein said basic field environmental conditions include basic intensity of earthquake, annual average annual rainfall and daily average rainfall.
4. The method for generating a ground disaster risk distribution map for scanning a geological three-dimensional model according to claim 1, wherein the analysis process of the regional degree level is specifically as follows:
determining the complexity level of the virtual partition under each control factor;
and selecting the most unfavorable result in all the complexity levels as the regional level of the corresponding virtual partition.
5. The method for generating a ground disaster risk distribution map for scanning a geological three-dimensional model according to claim 4, wherein said regional level of controllability factors are divided into primary and secondary ones;
the main control factors comprise natural steep slope height, a relation between a penetrability structural surface and a slope, a proportion of occupied ground area of poor geological phenomenon and human activities for destroying geological environment;
the secondary controlling factors include terrain slope angle, soil layer thickness, formation or soil layer differential, rock structure type, fracture configuration, seismic intensity, surface water influence, groundwater influence, thickness-to-span ratio, and goaf footprint ratio.
6. The method for generating a ground disaster risk distribution map for scanning a geological three-dimensional model according to claim 1, wherein the expression of the complexity index function is specifically:
wherein D represents a geological environment complexity index; gamma ray 1 、γ 2 、γ 3 、γ 4 、γ 5 For calculating the coefficients, interpolation calculation is carried out from a database; a represents the repetition times of complexity level being complexity level in the virtual partition; b represents the number of repetitions of a medium level of complexity within the virtual partition.
7. The method for generating a ground disaster risk distribution map for scanning a geological three-dimensional model according to claim 6, wherein the complexity level in the virtual partition is the sum of the number of complexity levels corresponding to the primary control factor and the number of complexity levels corresponding to the secondary control factor.
8. The method for generating a ground disaster risk distribution map for scanning a geological three-dimensional model according to claim 6, wherein the number of repetitions of the complexity level being the intermediate level in the virtual partition is the sum of the intermediate level number corresponding to the primary control factor and the intermediate level number corresponding to the secondary control factor.
9. The method for generating a ground disaster risk distribution map for scanning a geological three-dimensional model according to claim 1, wherein the calculation formula of the geological disaster susceptibility index is specifically as follows:
γ＝0.618D+0.382R
wherein, gamma represents a geological disaster susceptibility index; d represents a geological environment complexity index; r represents the precipitation index.
10. A ground disaster risk distribution map generation system for scanning a geological three-dimensional model, characterized in that the system is applied to a ground disaster risk distribution map generation method for scanning a geological three-dimensional model according to any one of claims 1 to 9, comprising:
the model processing module is used for calibrating geological units required by the calculation of the ground disaster vulnerability index in the three-dimensional geological model containing the attribute and inputting basic field environment conditions required by the calculation of the ground disaster vulnerability index;
the parameter determining module is used for determining a parameter range corresponding to the complexity level of each geological environment condition factor;
the region dividing module is used for dividing a projection surface of the ground surface in the three-dimensional geological model in the elevation direction into a plurality of virtual partitions which are independently analyzed;
the complex analysis module is used for scanning the geological unit information input in the range of each virtual partition and determining the complexity analysis result of each geological unit in the same virtual partition according to the corresponding parameter range;
the regional analysis module is used for analyzing regional degree grades of the corresponding virtual partitions according to the distribution condition of the complexity grade in the complexity analysis result;
the index calculation module is used for selecting a corresponding complexity index function according to the regional level, and calculating to obtain the geological environment complexity index of the corresponding virtual partition by combining the complexity analysis result and the selected complexity index function;
the risk analysis module is used for combining the geological environment complexity index and the basic field environment condition to calculate and obtain a geological disaster susceptibility index, and is used as geological attributes to be endowed with corresponding grid points so as to realize three-dimensional visualization processing of the ground disaster risk analysis result.
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