CN111340668B - Typhoon disaster assessment system - Google Patents
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Abstract
The invention discloses a typhoon disaster evaluation system, which comprises a typhoon data management module, a disaster area data management module and an economic production value influence evaluation module; the economic output value influence evaluation module is used for accumulating rainfall and maximum wind speed of each grid point in a preset period according to the disaster area acquired by the typhoon data management module; calculating disaster-causing factor intensity indexes of all grid points, calculating economic vulnerability indexes of all grid points according to GDP data, land areas and population numbers, calculating disaster-causing environment sensitivity indexes of all grid points according to slope directions and elevation standard deviations of all grid points, and finally, according to the disaster-causing factor intensity indexes, the disaster-causing environment sensitivity indexes and the economic vulnerability indexes, displaying the total economic influence value of an administrative region to be evaluated, thereby realizing the evaluation of the economic influence of each administrative region in a disaster area when typhoons come, and intuitively displaying the economic influence degree of typhoons on each administrative region in the disaster area.
Description
Technical Field
The invention relates to the technical field of typhoon disaster risk assessment, in particular to a typhoon disaster assessment system.
Background
Typhoons are a natural disaster with extremely strong destructive power on the earth, and usually the wind, the flood and the tide burst together to destroy water conservancy facilities such as river and sea embankments and influence industrial and agricultural production such as traffic, communication, ships, aquaculture and the like, and cause great losses of buildings, people, lives, properties and the like. Liaokuda land coastline in the western coast area of Pacific ocean is more than 18800km in length, typhoons and storm surge attack are frequently suffered along the coastal area, especially the south coast of the Yangtze river, and typhoon disaster loss caused by the annual development of economy in the coastal area is also increasingly larger.
The typhoons come in a wide time and range, a plurality of administrative regions such as a plurality of towns and a plurality of cities exist in one disaster-stricken region, and how to determine the influence degree of typhoons on the economy of each administrative region in the disaster-stricken region according to the real-time rainfall, wind speed and geographic environment of each administrative region in the disaster-stricken region is a problem to be solved.
Disclosure of Invention
The embodiment of the invention provides a typhoon disaster assessment system which can assess the influence of typhoons on economic output values of administrative areas of disaster areas according to real-time rainfall at wind speed and display assessment results.
An embodiment of the present invention provides a typhoon disaster assessment system method, including:
typhoon data management module, disaster area data management module and economic output value influence evaluation module;
the typhoon data management module is used for acquiring the accumulated rainfall and the maximum wind speed of each grid point in a disaster area within a preset period;
the disaster area data management module is used for acquiring digital elevation data, administrative division data, GDP data of administrative areas of village and town levels, land areas of the administrative areas of village and town levels and population numbers of the administrative areas of village and town levels of the disaster area data management module;
the economic output value influence evaluation module is used for calculating the disaster factor intensity index of each grid point according to the accumulated rainfall and the maximum wind speed of each grid point;
calculating the ground average GDP and population density of the administrative areas of the villages and towns according to the GDP data, the land area and the population quantity; performing interpolation processing on the ground average GDP and population density, and interpolating to corresponding grid points to obtain the ground average GDP and population density of each grid point; calculating an economic vulnerability index of each grid point according to the ground average GDP and population density of each grid point;
Determining the slope direction and the elevation standard deviation of each grid point according to the digital elevation data, and then calculating the pregnancy disaster environment sensitivity index of each grid point according to the slope direction and the elevation standard deviation of each grid point;
calculating economic impact values of all grid points according to disaster causing factor intensity indexes, economic vulnerability indexes, disaster inducing environment sensitivity indexes and ground average GDP of all grid points;
and determining each evaluation grid point corresponding to the administrative region to be evaluated according to the administrative region data, determining the total economic influence value of the administrative region to be evaluated according to the economic influence value of each evaluation grid point, and displaying the total economic influence value of the administrative region to be evaluated on a display interface.
Furthermore, the disaster area data management module is further used for acquiring the industrial production value data of the administrative areas of the village and town levels and the industrial area of the administrative areas of the village and town levels.
Further, the system also comprises an industrial production value influence evaluation module;
the industrial production value influence evaluation module is used for calculating the ground average industrial production value of the administrative region of each village and town level according to each industrial production value data and each industrial land area, then carrying out interpolation processing on the ground average industrial production value and the population density, and interpolating the ground average industrial production value and the population density to corresponding grid points to obtain the ground average industrial production value and the population density of each grid point; calculating the industrial vulnerability index of each grid point according to the ground average industrial production value and population density of each grid point;
Calculating the industrial production value influence value of each grid point according to the disaster causing factor intensity index, the industrial vulnerability index, the pregnant disaster environment sensitivity index and the ground average industrial production value of each grid point;
and determining the total industrial production value influence value of the administrative region to be evaluated according to the industrial influence value of each evaluation grid point, and displaying the total industrial production value influence value of the administrative region to be evaluated on a display interface.
Further, the disaster area data management module is further used for obtaining the type of agricultural land, the area of each type of agricultural land, the agricultural yield value of each type of agricultural land, the planting density of each type of agricultural land and the grid point range of each type of agricultural land in the administrative area of each village and town level; determining the grid points of the agricultural land belonging to the agricultural land according to the grid point range of the various types of agricultural lands; calculating the land average agricultural yield value of each administrative region of the village and town level according to the agricultural yield values of each agricultural land and the land areas of the administrative regions of the village and town level, and then carrying out interpolation treatment on the land average agricultural yield value, interpolating the land average agricultural yield value to corresponding agricultural land grid points to obtain the land average agricultural yield value of each agricultural land grid point; and carrying out interpolation treatment on the planting densities of the various types of agricultural land, interpolating the planting densities to corresponding agricultural land grid points, and obtaining the planting density of each agricultural land grid point.
Further, the system also comprises an agricultural output value influence evaluation module;
the agricultural yield impact evaluation module is used for determining a crop flooding index and a crop lodging index corresponding to each agricultural land grid according to the accumulated rainfall and the maximum wind speed of each agricultural land grid; calculating the agricultural vulnerability index of each agricultural land lattice point according to the crop flooding index, the crop lodging index and the planting density of each agricultural land lattice point;
calculating an agricultural disaster recovery environment sensitivity index of each agricultural land lattice point according to the agricultural land type of each agricultural land lattice point, the slope direction of each agricultural land lattice point and the elevation standard deviation of each agricultural land lattice point;
calculating the agricultural yield value influence value of each agricultural land lattice point according to the disaster causing factor intensity index, the agricultural vulnerability index, the agricultural disaster environment sensitivity index and the land average agricultural yield value of each agricultural land lattice point;
and according to the administrative division data, taking the agricultural land grid points corresponding to the administrative areas to be evaluated as agricultural evaluation grid points, then determining the total agricultural impact value of the administrative areas to be evaluated according to the economic impact value of each agricultural evaluation grid point, and displaying the total agricultural impact value of the administrative areas to be evaluated on a display interface.
Further, the disaster-stricken area data management module is further configured to obtain population age data and low house data of administrative areas of each village and town level; dividing administrative areas of village and town levels into low house land and non-low house land according to the low house data, and determining building types of grid points in administrative areas of the village and town levels; wherein the building types include low houses and non-low houses.
Further, the system also comprises a population influence evaluation module;
the population influence evaluation module is used for carrying out interpolation processing on population density data and population age data of administrative areas of each village and town level, interpolating the population density data and the population age data to corresponding grid points, and obtaining population density and population age of each grid point;
calculating the population vulnerability index of each grid point according to the population density and the population age of each grid point;
calculating the population disaster pregnancy environment sensitivity index of each grid point according to the building type of each grid point, the slope direction of each grid point and the elevation standard deviation of each grid point;
calculating population influence values of all grid points according to the disaster causing factor intensity index, the population vulnerability index, the population pregnant environment sensitivity index and the population density of all grid points;
And determining the population influence value total value of the administrative region to be evaluated according to the population influence value of each evaluation grid point, and displaying the population influence value total value of the administrative region to be evaluated on a display interface.
Further, the typhoon data management module is further used for acquiring the accumulated rainfall and the maximum wind speed of grid points in each preset period; wherein each preset period includes a past period and a future period.
Further, the economic output value influence evaluation module is further configured to calculate a disaster factor intensity index of each grid point in each preset period according to the accumulated rainfall and the maximum wind speed in each preset period; and then calculating the total economic influence value of the administrative region to be evaluated in each time period according to the disaster causing factor intensity index of each grid point in each preset time period, and displaying the total economic influence value of the administrative region to be evaluated in each time period.
Further, the industrial output value influence evaluation module is further configured to calculate, according to the disaster factor intensity index of each grid point in each preset period, an industrial influence total value of the administrative region to be evaluated in each period, and then display the industrial influence total value of the administrative region to be evaluated in each period.
The embodiment of the invention provides a typhoon disaster assessment system, which comprises a typhoon data management module, a disaster area data management module and an economic production value influence assessment module; the economic output value influence evaluation module is used for accumulating rainfall and maximum wind speed of each grid point in a preset period according to the disaster area acquired by the typhoon data management module; calculating disaster-causing factor intensity indexes of all grid points, calculating economic vulnerability indexes of all grid points according to GDP data, land areas and population numbers, calculating disaster-causing environment sensitivity indexes of all grid points according to slope directions and elevation standard deviations of all grid points, and finally, according to the disaster-causing factor intensity indexes, the disaster-causing environment sensitivity indexes and the economic vulnerability indexes, displaying the total economic influence value of an administrative region to be evaluated, thereby realizing the evaluation of the economic influence of each administrative region in a disaster area when typhoons come, and intuitively displaying the economic influence degree of typhoons on each administrative region in the disaster area.
Drawings
Fig. 1 is a system architecture diagram of a typhoon disaster assessment system according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an embodiment of the present invention provides a typhoon disaster assessment system, including a typhoon data management module, a disaster area data management module, and an economic output value influence assessment module;
the typhoon data management module is used for acquiring the accumulated rainfall and the maximum wind speed of each grid point in a disaster area within a preset period;
the disaster area data management module is used for acquiring digital elevation data, administrative division data, GDP data of administrative areas of village and town levels, land areas of the administrative areas of village and town levels and population numbers of the administrative areas of village and town levels of the disaster area data management module;
the economic output value influence evaluation module is used for calculating the disaster factor intensity index of each grid point according to the accumulated rainfall and the maximum wind speed of each grid point;
calculating the ground average GDP and population density of the administrative areas of the villages and towns according to the GDP data, the land area and the population quantity; performing interpolation processing on the ground average GDP and population density, and interpolating to corresponding grid points to obtain the ground average GDP and population density of each grid point; calculating an economic vulnerability index of each grid point according to the ground average GDP and population density of each grid point;
Determining the slope direction and the elevation standard deviation of each grid point according to the digital elevation data, and then calculating the pregnancy disaster environment sensitivity index of each grid point according to the slope direction and the elevation standard deviation of each grid point;
calculating economic impact values of all grid points according to disaster causing factor intensity indexes, economic vulnerability indexes, disaster inducing environment sensitivity indexes and ground average GDP of all grid points;
and determining each evaluation grid point corresponding to the administrative region to be evaluated according to the administrative region data, determining the total economic influence value of the administrative region to be evaluated according to the economic influence value of each evaluation grid point, and displaying the total economic influence value of the administrative region to be evaluated on a display interface.
The following further describes the respective modules:
the invention relates to a typhoon data management module, which is mainly used for acquiring weather live monitoring data forecast data of a disaster area where typhoons come temporarily, wherein the data in two aspects are mainly collected, one is accumulated rainfall and the other is maximum wind speed; the preset period may be a past period, for example, within the past 1 hour, or a future period, for example, within 3 hours, assuming that the latitude is within the range of 106.10 ° E to 120.36 ° E: 1.30-23.61 DEG N, as the range of the disaster area, the preset time period is 1 hour in the past, and then the typhoon data management module acquires the longitude of 106.10 DEG E-120.36 DEG E, latitude: 1.30 to 23.61 DEG N, the cumulative rainfall and maximum wind speed of each grid point in the past 1 hour, the grid point refers to a grid point on meteorological data corresponding to a disaster area (the resolution of a preferable grid is 0.01 DEG)
The disaster area data management module is mainly used for acquiring elevation data (raster data, 5m grid resolution) and administrative division data (vector data mainly comprising Shapefile format data of province, city, county and village and town levels) of a disaster area; in the present invention, the lowest administrative division level is the first level of villages and towns, and the statistical unit is the first level of villages and towns, and the GDP data (P k In ten thousand yuan), land area (S k Units of square kilometers and population number (N) k The unit: person), each administrative town (village) is identified hereinafter by the letter k, each administrative town corresponding to a fixed geographic coordinate (longitude, latitude).
The economic output value influence evaluation module is used for evaluating the economic output value influence of the disaster-affected area, and specifically comprises the following steps:
C 1 ＝αH 1 ·βS 1 ·δV 1 (1.3.1.1)
C 1 is an economic typhoon disaster risk index, H 1 、S 1 、V 1 Respectively representing disaster causing factor intensity index, pregnant disaster environment sensitivity index and economic vulnerability index in the risk evaluation model; the alpha, the beta and the delta are respectively weight coefficients of all the evaluation factors, the alpha + the beta + the delta=1, the size of the weight coefficients is based on the influence degree of all the factors on typhoon disasters,
firstly, calculating the intensity index of the disaster causing factor: 
H 1 For rainfall intensity index->
For wind speed intensity indexes, α1 and α2 are corresponding weights, in the preferred embodiment of the present invention, α1 and α2 are both 0.5, different rainfall intensity indexes (corresponding relations are shown in table 1) are corresponding to different rainfall amounts, and different wind speed intensity indexes (corresponding relations are shown in table 2) are corresponding to different maximum wind speeds; />
TABLE 1
TABLE 2
According to the accumulated rainfall and the maximum wind speed of each grid point and the corresponding relation of the table 1 and the table 2, the corresponding weights alpha 1 and alpha 2 can calculate the disaster factor intensity index of each grid point. It should be noted that the weights α1 and α2 may be adjusted according to actual situations.
The economic vulnerability of each lattice point is calculated nextThe index is calculated by the following formula according to the GDP data, land area and population number of each village and town level administrative region, and the land average GDP (p) k Ten thousand yuan/km 2 ) And population density (ρ) k Person/km 2 )；
The calculated ground average GDP data (p k ) And population density data (ρ) k ) Interpolation is carried out to the grid points (i, j) corresponding to the meteorological data to obtain the ground average GDP data (p) i,j ) And population density data (ρ) i,j )；
The economic vulnerability index is then calculated: 
The ground average GDP index as a lattice point,
And beta 1 and beta 2 are corresponding weights for population density indexes, and can be adjusted according to actual conditions.
In a preferred embodiment of the invention, β1, β2 are both 0.5; different population densities at the grid point correspond to different population density indexes (the corresponding relationship is shown in table 3), and different ground average GDPs correspond to different ground average GDP indexes (the corresponding relationship is shown in table 4):
TABLE 3 Table 3
TABLE 4 Table 4
According to tables 3 and 4, population density index and ground average GDP index of each grid point and the weight values of the beta 1 and beta 2 are determined, and economic vulnerability index V of each grid point is calculated 1 ；
Calculating a disaster-tolerant environmental sensitivity index, wherein the disaster-tolerant environmental sensitivity mainly considers the influence of the terrain on economy; extracting slope directions and elevation standard deviations of all lattice points through elevation data of the disaster affected area:
and carrying out microscopic landform extraction on the disaster affected area by utilizing GIS space analysis on the elevation standard deviation, and converting each extracted landform factor grid model into each grading model. Calculating 65 grid (including self height) elevation standard deviations in 8 x 8 fields around the grids by using an Arcmap space analysis module as quantitative indexes for representing the terrain change degree at the positions to obtain elevation influence indexes of all grid points 
The size is between 0 and 1; the different elevation standard deviations are preset with corresponding elevation impact indexes,
the slope direction utilizes ARCGIS-Surface Analysis-Aspect to extract slope direction information of disaster-affected area, and in the output slope direction data, the slope direction is divided into flat slope (-1 degree), east slope (45-135 degrees), south slope (135-225 degrees), west slope (225-315 degrees), north slope (315-360 degrees and 360-45 degrees), and the east slope is defined as windward slope, and the slope direction influence index thereof is defined
1, the slope influence index of other slopes +.>
Is 0;
calculating a pregnancy disaster environment sensitivity index according to the following formula:
is elevation influence index->
For the slope impact index, δ1 and δ2 are preferably both 0.5 as the weight coefficient;
determining elevation influence indexes and slope influence indexes of all grid points according to the elevation standard deviation and slope direction of all grid points, and calculating disaster-pregnant environment sensitivity indexes of all grid points by combining corresponding weight coefficients;
calculating an economic typhoon risk index C of each grid point according to the disaster causing factor intensity index, the economic vulnerability index and the pregnant disaster environment sensitivity index of each grid point 1 The weight coefficients alpha, beta and delta can be adjusted according to actual conditions.
And then calculating economic impact values of all grid points according to the economic platform risk indexes and the ground average GDP of all grid points by the following formula: q i,j ＝C i,j *p i,j ，q i,j The economic impact value of the grid point with the longitude i and the latitude j is C o,j For the economic typhoon risk index corresponding to the grid point, p i,j A ground average GDP for the grid;
and finally, calculating the total economic impact value of the administrative region to be evaluated through the following formula:
s i,j land area for the administrative area to be assessed; [ m1, m2 ]]The administrative area to be evaluated is in the range of grid points in the longitudinal direction. [ k1, k2 ]]The range of grid points in the latitude direction is the administrative area to be evaluated. And finally, displaying the total economic impact value on a display interface.
In a preferred embodiment, the typhoon data management module is further configured to obtain an accumulated rainfall and a maximum wind speed of grid points in each preset period; wherein each preset period includes a past period and a future period. The economic output value influence evaluation module is further used for calculating disaster factor intensity indexes of the grid points in each preset period according to the accumulated rainfall and the maximum wind speed in each preset period; and then calculating the total economic influence value of the administrative region to be evaluated in each time period according to the disaster causing factor intensity index of each grid point in each preset time period, and displaying the total economic influence value of the administrative region to be evaluated in each time period. In this embodiment, the total economic impact value of a plurality of different time periods is mainly evaluated, for example, the typhoon data management module collects the cumulative rainfall and the maximum wind speed of each grid point in the past 1 hour, the cumulative rainfall and the maximum wind speed in the weather forecast of 3 hours, 6 hours, 12 hours and 24 hours, and then the total economic impact value of the administrative region to be evaluated in each time period is evaluated by the economic impact value impact evaluation module (the specific evaluation method is the same as the above, and is not repeated, and the cumulative rainfall and the maximum wind speed of each time period are different, so that the disaster factor intensity indexes of each time period are different, and the total economic impact value obtained by final calculation is different).
After the total economic impact value under each time period is obtained, the total economic impact value is displayed on a display interface, the total economic impact value can be displayed in a linkage coordinate axis mode, each time period can be taken as an abscissa, the total economic impact value corresponding to each time period is taken as an ordinate, a statistical graph is generated, and then the statistical graph is displayed on the display interface.
In a preferred embodiment, the disaster area data management module is further configured to obtain industrial production value data of administrative areas of village and town levels, and industrial land areas of administrative areas of village and town levels.
Typhoon disaster assessment system, still includes: an industrial production value influence evaluation module;
the industrial production value influence evaluation module is used for calculating the ground average industrial production value of the administrative region of each village and town level according to each industrial production value data and each industrial land area, then carrying out interpolation processing on the ground average industrial production value and the population density, and interpolating the ground average industrial production value and the population density to corresponding grid points to obtain the ground average industrial production value and the population density of each grid point; calculating the industrial vulnerability index of each grid point according to the ground average industrial production value and population density of each grid point;
calculating the industrial production value influence value of each grid point according to the disaster causing factor intensity index, the industrial vulnerability index, the pregnant disaster environment sensitivity index and the ground average industrial production value of each grid point;
And determining the total industrial production value influence value of the administrative region to be evaluated according to the industrial influence value of each evaluation grid point, and displaying the total industrial production value influence value of the administrative region to be evaluated on a display interface.
The disaster area data management module and the industrial production value influence evaluation module are further described below:
in this embodiment, the disaster area data management module obtains the industrial production value data and the industrial land area of each town level administrative area in the disaster area by taking the town level administrative area as the smallest statistical unit; identification and extraction of industrial land in disaster affected area the land type shown in table 5 can be extracted as the industrial land described herein according to land classification file corresponding to disaster affected area and land utilization status classification GB/T21010-2017, and then the size of industrial land of each industrial land can be calculated according to geographical coordinates of each industrial land (S) Ik The unit is square kilometers), and the industrial production value data of administrative areas of each village and town level are obtained (can be obtained from the statistical data of administrative units and authorities of each town level);
TABLE 5
For the industrial production value influence evaluation module, the industrial production value disaster risk index calculation module is mainly used for calculating the industrial production value disaster risk indexes of all grid points, and then evaluating the total industrial production value influence value of the administrative region to be evaluated:
The industrial production disaster risk index calculation formula of each lattice point is as follows: c (C) 2 ＝αH 2 ·βS 2 ·δV 2 ；
C 2 Is the disaster risk index of industrial production value, H 2 、S 2 、V 2 Respectively representing the intensity index of the disaster causing factors and the sensitivity index of the pregnant disaster environment; industrial vulnerability index; the alpha, the beta and the delta are weight coefficients of all the evaluation factors, wherein alpha+beta+delta=1, and the weight coefficients are set according to the influence degree of all the factors on typhoon disasters;
it should be noted that in this embodiment, in the industrial production value influence evaluation module, the disaster factor intensity index H of each grid point 2 Environmental sensitivity index S of pregnancy disaster 2 And the disaster factor intensity index H of the economic output value influence evaluation module 1 Environmental sensitivity index S of pregnancy disaster 1 The same is not needed to be repeatedly calculated, only the data calculated by the economic value influence evaluation module is required to be called, and the industrial vulnerability index V is calculated by the industrial value influence evaluation module 2 The explanation is made:
based on industrial value data (I k In ten thousand yuan), industrial floor area (S) Ik Square kilometers, and calculating the average land industrial yield value of the administrative areas of each village and town level;
the population density calculated by the assessment module is then affected in conjunction with the economic value. Interpolation processing is carried out on the ground average industrial production value and the population density, and the ground average industrial production value I 'of each grid point is obtained by interpolation on the corresponding grid point' i,j ) Population density (ρ) i,j )。
Different average industrial production values at the grid point correspond to different average industrial production value indexes
(as shown in Table 6);
TABLE 6
According to the table above and the following formula, calculating the industrial vulnerability index of each lattice point:
Then according to the disaster causing factor intensity index, the industrial vulnerability index and the disaster inducing environment sensitivity index of each lattice point, the method passes through the formula C 2 ＝αH 2 ·βS 2 ·δV 2 The method comprises the steps of carrying out a first treatment on the surface of the Calculating the disaster risk index of the industrial production value of each grid point; the alpha, beta and delta can be adjusted according to actual conditions. The value of the alpha, beta and delta is not necessarily the same as the value of the alpha, beta and delta in the economic value influence evaluation module.
Then according to the industrial production disaster risk index and the land average industrial production (I' i,j Ten thousand yuan), the industrial production value influence value of each lattice point is calculated by the following formula:
industrial yield impact value for grid point with longitude i latitude j +.>
For the industrial production value disaster risk index corresponding to the lattice point, I' i,j The average industrial production value of the grid point;
and finally, calculating the total influence value of the industrial production value of the administrative region to be evaluated according to the following formula:
In a preferred embodiment, the industrial output value influence evaluation module is further configured to calculate, according to the disaster factor intensity index of each grid point in each preset period, an industrial influence total value of the administrative area to be evaluated in each period, and then display the industrial influence total value of the administrative area to be evaluated in each period. In this embodiment, the total industrial yield impact value of the administrative area to be evaluated in each period is mainly evaluated by the industrial yield impact evaluation module, for example, the typhoon data management module collects the cumulative rainfall and the maximum wind speed of each grid point in the past 1 hour, the cumulative rainfall and the maximum wind speed in the weather forecast of 3 hours, 6 hours, 12 hours and 24 hours, and the total industrial yield impact value of the administrative area to be evaluated in each period is evaluated by the industrial yield impact evaluation module (the specific evaluation method is the same as above, and is not repeated, so that the cumulative rainfall and the maximum wind speed of each period are different, the disaster causing factor intensity index of each period is different, and the final calculated industrial yield impact total value is different).
After the total industrial production value influence value under each period is obtained, the total industrial production value influence value is displayed on a display interface, the total industrial production value influence value can be displayed in a linkage coordinate axis mode, each period can be used as an abscissa, the total industrial production value influence value corresponding to each period is used as an ordinate, a statistical graph is generated, and then the statistical graph is displayed on the display interface.
In a preferred embodiment, the disaster area data management module is further used for acquiring the agricultural land type, the agricultural land area of each type, the agricultural yield value of each type of agricultural land, the planting density of each type of agricultural land and the grid point range of each type of agricultural land of each village and town level administrative area; determining the grid points of the agricultural land belonging to the agricultural land according to the grid point range of the various types of agricultural lands; calculating the land average agricultural yield value of each administrative region of the village and town level according to the agricultural yield values of each agricultural land and the land areas of the administrative regions of the village and town level, and then carrying out interpolation treatment on the land average agricultural yield value, interpolating the land average agricultural yield value to corresponding agricultural land grid points to obtain the land average agricultural yield value of each agricultural land grid point; and carrying out interpolation treatment on the planting densities of the various types of agricultural land, interpolating the planting densities to corresponding agricultural land grid points, and obtaining the planting density of each agricultural land grid point.
The typhoon disaster evaluation system further comprises an agricultural production value influence evaluation module;
the agricultural yield impact evaluation module is used for determining a crop flooding index and a crop lodging index corresponding to each agricultural land grid according to the accumulated rainfall and the maximum wind speed of each agricultural land grid; calculating the agricultural vulnerability index of each agricultural land lattice point according to the crop flooding index, the crop lodging index and the planting density of each agricultural land lattice point;
calculating an agricultural disaster recovery environment sensitivity index of each agricultural land lattice point according to the agricultural land type of each agricultural land lattice point, the slope direction of each agricultural land lattice point and the elevation standard deviation of each agricultural land lattice point;
calculating the agricultural yield value influence value of each agricultural land lattice point according to the disaster causing factor intensity index, the agricultural vulnerability index, the agricultural disaster environment sensitivity index and the land average agricultural yield value of each agricultural land lattice point;
and according to the administrative division data, taking the agricultural land grid points corresponding to the administrative areas to be evaluated as agricultural evaluation grid points, then determining the total agricultural impact value of the administrative areas to be evaluated according to the economic impact value of each agricultural evaluation grid point, and displaying the total agricultural impact value of the administrative areas to be evaluated on a display interface.
In the embodiment, the influence of typhoons on agriculture is mainly evaluated temporarily in typhoons, in the embodiment, a disaster area data management module extracts the types and geographic coordinates of each agricultural land in the disaster area according to utilization classification files of the disaster area and according to land utilization current situation classification GB/T21010-2017, and then calculates various agricultural land areas; the classification of the agricultural land types is specifically shown in table 7:
TABLE 7
Then obtaining the agricultural yield value of each type of agricultural land, and calculating the land average agricultural yield value of each village-town level administrative area on the land area of each village-town level administrative area; according to the areas of various types of agricultural lands and the crop planting quantity of various types of agricultural lands, the planting density of various types of agricultural lands can be calculated; and then determining the grid point range of each type of agricultural land according to the geographic coordinates of each type of agricultural land, and further determining the grid points belonging to the agricultural land in the disaster area, namely the agricultural land grid points. And then carrying out interpolation treatment on the land average agricultural yield value and the planting density, and interpolating the land average agricultural yield value and the planting density to corresponding agricultural land grid points to obtain the planting density of each agricultural land grid point.
Next, an agricultural output impact evaluation module will be described: in accordance with the above, the agricultural yield impact evaluation module calculates an agricultural yield disaster risk index of each agricultural land lattice point through the disaster causing factor intensity index, the agricultural vulnerability index and the agricultural pregnancy environment sensitivity index of each agricultural land lattice point, and then evaluates the agricultural yield disaster risk index;
the calculation formula of the agricultural yield disaster risk index of each agricultural land is as follows:
C 3 ＝αH 3 ·βS 3 ·δV 3 ；C 3 is a disaster risk index for agricultural yield value, H 3 、S 3 、V 3 Respectively representing the intensity index of the disaster causing factors and the sensitivity index of the agricultural disaster-pregnant environment; agricultural vulnerability index; the alpha, beta and beta 1 are weight coefficients of all the evaluation factors, alpha+beta 0+delta=1, the weight coefficients are set according to the influence degree of all the factors on typhoon disasters (specific numerical values of alpha, beta and delta are not necessarily consistent with the numerical values of alpha, beta and delta defined in an economic and industrial production value influence evaluation module;
it should be noted that in this embodiment, in the agricultural output value influence evaluation module, the disaster factor intensity index H of each grid point 3 And the disaster factor intensity index H of the economic output value influence evaluation module 1 The same as the following influence evaluation module on the agricultural yield value, how to calculate the agricultural pregnancy and disaster environment sensitivity index S 3 Agricultural vulnerability index V 3 The explanation is made:
environmental sensitivity index for agricultural pregnancy and disaster
And +.A.in the economic value influence evaluation Module>
The correspondence is not described again, in addition to->
An agricultural type index indicating the type of agricultural land to which the grid belongs, different agricultural land types corresponding to different agricultural type indexes (as shown in table 8); β1, β2 and β3 are weight coefficients which can be adjusted according to practical situations, and β1+β2+β3=1
TABLE 8
The agricultural type index corresponding to each agricultural land lattice point is obtained according to table 8, so that the agricultural disaster recovery environment sensitivity index of each agricultural land lattice point is calculated.
Followed by an agricultural vulnerability index
Is the flooding index of crops at each grid point, < >>
Is crop lodging index, I.Y.)>
Is a planting density index; δ1, δ2, and δ3 are weight coefficients that can be adjusted according to practical situations, δ1+δ2+δ3=1
The crop flooding index is related to the accumulated rainfall of each grid point, and the specific see table 9:
TABLE 9
The crop lodging index is related to the maximum wind speed at each grid point, see in particular Table 10
Table 10
Different planting densities are correspondingly provided with different planting density indexes, and the planting density index is larger as the planting density is larger, so that the planting density is not exemplified at the time; calculating an agricultural vulnerability index V according to each corresponding relation 3
In a preferred embodiment, the disaster area data management module is further configured to obtain a crop growth cycle of each agricultural land; the agricultural vulnerability index calculation formula can be
Other parameters are defined identically, and->
Is the crop growth cycle index of each grid point; the growth cycle of different crops corresponds to different growth cycle indexes, and in the example of rice, the corresponding relationship is shown in table 11: />
TABLE 11
Calculating disaster factor intensity index, agricultural vulnerability index and agricultural disaster environment sensitivity index of each agricultural land lattice point, and then calculating agricultural yield disaster risk index of each agricultural land lattice point;
according to the agricultural yield disaster risk index and the land average agricultural yield (A' i,j Ten thousand yuan), the agricultural output value influence value of each agricultural land lattice point is obtained:
agricultural yield value influence value for grid point with longitude i latitude j +.>
For the agricultural production value disaster risk index corresponding to the grid point, A' i,j The land average agricultural production value of the grid point;
and finally, calculating the total influence value of the industrial production value of the administrative region to be evaluated according to the following formula:
In a preferred embodiment, the disaster area data management module is further configured to obtain population age data and low house data of each town level administrative area; dividing administrative areas of village and town levels into low house land and non-low house land according to the low house data, and determining building types of grid points in administrative areas of the village and town levels; wherein the building types include low houses and non-low houses.
The typhoon disaster assessment system also comprises a population influence assessment module;
the population influence evaluation module is used for carrying out interpolation processing on population density data and population age data of administrative areas of each village and town level, interpolating the population density data and the population age data to corresponding grid points, and obtaining population density and population age of each grid point;
calculating the population vulnerability index of each grid point according to the population density and the population age of each grid point;
calculating the population disaster pregnancy environment sensitivity index of each grid point according to the building type of each grid point, the slope direction of each grid point and the elevation standard deviation of each grid point;
calculating population influence values of all grid points according to the disaster causing factor intensity index, the population vulnerability index, the population pregnant environment sensitivity index and the population density of all grid points;
and determining the population influence value total value of the administrative region to be evaluated according to the population influence value of each evaluation grid point, and displaying the population influence value total value of the administrative region to be evaluated on a display interface.
In this embodiment, typhoons are more likely to damage temporary low houses, so that people in the main low houses are more likely to be affected;
The low house data comprise geographic coordinates of the low house, and the specific extraction modes are as follows:
the invention adopts high-resolution remote sensing images to extract, and extracts target objects (short houses in remote sensing influence are extracted) by selecting administrative region remote sensing images with resolution of 0.5 m in disaster areas and village and town levels in Google Earth, wherein the images share 2473 scenes, and the data size is 2.61TB. In addition, because the number of the identification targets is large, the labor cost and the time cost which are input by adopting a manual visual interpretation method are high, the study adopts a deep learning method to realize batch automatic extraction of the short houses, a model adopts a segmentation network model (Mask RCNN) in deep learning, the ArcGIS software is adopted to manually interpret sample images of the short houses, the sample positions of a greenhouse or an iron house are simplified, the SHP files of the identification targets are selected and then converted into grid files, and each view image is cut according to the position of the greenhouse, so that at least one identification target is ensured in the cut images; and finally generating training images, and selecting most of the training images as training samples and the small training images as verification samples to perform batch extraction. And (3) extracting the extraction targets in batches by adopting Mask RCNN (RCNN), and finally obtaining unified extraction junction results of simple work sheds and iron house in administrative areas of each village and town level, wherein the extraction format is SHP format and comprises information such as independent codes, positions, shapes and the like.
After the disaster area data management module acquires the low house data, dividing administrative areas of village and town levels into low house land and non-low house land, thereby determining the building type of each grid point in administrative areas of the village and town levels;
the population influence evaluation module is mainly used for evaluating the influence of typhoons on the population;
consistent with the above, the population impact assessment module calculates the population disaster risk index of each grid point through the disaster causing factor intensity index, the population vulnerability index and the population pregnant disaster environment sensitivity index of each grid point, and then assesses;
the calculation formula of the population disaster risk index of each grid point is as follows:
C 4 ＝αH 4 ·βS 4 ·δV 4 ；C 4 is the risk index of population disasters, H 3 、S 3 、V 3 Respectively representing the intensity index of the disaster causing factors and the sensitivity index of the pregnant environment of the population; population vulnerability index; the α, β, and δ are weight coefficients of the respective evaluation factors, and α+β+δ=1, and the magnitude of the weight coefficients is set according to the magnitude of the influence of the respective factors on typhoon disasters (specific numerical values of α, β, and δ herein are not necessarily the same as the present ones)The values of alpha, beta and delta defined in other modules are consistent;
it should be noted that in the present embodiment, in the population influence evaluation module, the disaster factor intensity index H of each grid point 4 And the disaster factor intensity index H of the economic output value influence evaluation module 1 The same;
the following evaluation module for population influence how to calculate the environmental sensitivity index S of the pregnancy disaster of population 4 Population vulnerability index V 4 The explanation is made:
environmental sensitivity index for pregnant disaster of population
And +.A.in the economic value influence evaluation Module>
The correspondence is not described again, in addition to->
Representing the building type index to which the grid point belongs, wherein different building types correspond to different building type indexes (shown in table 12); β1, β2, and β03 are weight coefficients that can be adjusted according to the actual situation, and β11+β2+β3=1 (specific values of β1, β2, and β3 herein do not necessarily coincide with values of β1, β2, and β3 defined by other modules of the present invention);
TABLE 11
And obtaining building type indexes corresponding to all the grid points according to the table 11, so as to calculate the environmental sensitivity index of the people pregnant with the disaster for each grid point.
Followed by the population vulnerability index
Is population density index (consistent with economic value influence evaluation module) of each grid point, < ->
The population age indexes δ1 and δ2 are weight coefficients and can be adjusted according to practical situations, and δ1+δ2=1 (specific numerical values of δ1 and δ2 herein are not necessarily consistent with numerical values of β1, β2 and β3 defined in other modules of the present invention); calculating the percentage of the high-risk population according to the population age and data of each grid point, and correlating the percentage of the high-risk population of each grid point with the population age index of each grid point (the corresponding relation is shown in table 12); the greater the influence of typhoon risk on the elderly and children, the higher the risk of the typhoon, so only the crowd of the elderly (older than 60 years) and children (younger than 10 years) are considered as the high risk crowd, the percentage (%) of the high risk crowd on the unit grid is calculated, and the corresponding population age index is obtained according to table 12.
Table 12
Calculating a population disaster risk index according to the disaster causing factor intensity index, the population vulnerability index and the population pregnant disaster environment sensitivity index of each grid point;
then based on the population disaster risk index and population density data (A') i,j Ten thousand yuan), the population influence value of each grid point is obtained:
population value influence value for grid point with longitude i latitude j +.>
Corresponds to the lattice pointIs the risk index of population disasters, ρ i,j Population density for the grid;
and finally, calculating the population influence total value of the administrative region to be evaluated according to the following formula:
in a preferred embodiment, the method further comprises interpolating population impact values for grid points of the administrative area to be assessed onto different streets of the administrative area to be assessed, thereby generating a population thermodynamic diagram representation by the intelligent drawing engine.
By implementing the embodiment of the invention, the disaster situation of each administrative area in the disaster area can be temporarily evaluated in a multi-dimension manner in typhoons, and the evaluation result is presented. The influence condition of typhoons on each administrative region of the disaster area in each dimension is intuitively displayed, so that the disaster relief work can be conveniently developed.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.
Claims (6)
1. A typhoon disaster assessment system, comprising: typhoon data management module, disaster area data management module, economic output value influence evaluation module and industrial output value influence evaluation module;
the typhoon data management module is used for acquiring the accumulated rainfall and the maximum wind speed of each grid point in a disaster area within a preset period; the method is also used for acquiring the accumulated rainfall and the maximum wind speed of grid points in each preset period; wherein each preset period includes a past period and a future period;
the disaster area data management module is used for acquiring digital elevation data, administrative division data, GDP data of administrative areas of village and town levels, land areas of the administrative areas of village and town levels and population numbers of the administrative areas of village and town levels of the disaster area data management module; the method is also used for acquiring the industrial production value data of the administrative areas of the villages and towns and the industrial land areas of the administrative areas of the villages and towns;
The economic output value influence evaluation module is used for calculating the disaster factor intensity index of each grid point according to the accumulated rainfall and the maximum wind speed of each grid point; the disaster factor intensity index of each grid point is calculated according to the accumulated rainfall and the maximum wind speed in each preset period; then calculating the total economic influence value of the administrative region to be evaluated in each time period according to the disaster causing factor intensity index of each grid point in each preset time period, and displaying the total economic influence value of the administrative region to be evaluated in each time period;
calculating the ground average GDP and population density of the administrative areas of the villages and towns according to the GDP data, the land area and the population quantity; performing interpolation processing on the ground average GDP and population density, and interpolating to corresponding grid points to obtain the ground average GDP and population density of each grid point; calculating an economic vulnerability index of each grid point according to the ground average GDP and population density of each grid point;
determining the slope direction and the elevation standard deviation of each grid point according to the digital elevation data, and then calculating the pregnancy disaster environment sensitivity index of each grid point according to the slope direction and the elevation standard deviation of each grid point;
Calculating economic impact values of all grid points according to disaster causing factor intensity indexes, economic vulnerability indexes, disaster inducing environment sensitivity indexes and ground average GDP of all grid points;
determining each evaluation grid point corresponding to the administrative region to be evaluated according to the administrative region data, determining the total economic influence value of the administrative region to be evaluated according to the economic influence value of each evaluation grid point, and displaying the total economic influence value of the administrative region to be evaluated on a display interface;
the industrial production value influence evaluation module is used for calculating the ground average industrial production value of the administrative region of each village and town level according to each industrial production value data and each industrial land area, then carrying out interpolation processing on the ground average industrial production value and the population density, and interpolating the ground average industrial production value and the population density to corresponding grid points to obtain the ground average industrial production value and the population density of each grid point; calculating the industrial vulnerability index of each grid point according to the ground average industrial production value and population density of each grid point;
calculating the industrial production value influence value of each grid point according to the disaster causing factor intensity index, the industrial vulnerability index, the pregnant disaster environment sensitivity index and the ground average industrial production value of each grid point;
And determining the total industrial production value influence value of the administrative region to be evaluated according to the industrial influence value of each evaluation grid point, and displaying the total industrial production value influence value of the administrative region to be evaluated on a display interface.
2. The typhoon disaster assessment system according to claim 1, wherein said disaster area data management module is further configured to obtain an agricultural land type, an agricultural land area of each type, an agricultural yield value of each type, a planting density of each type and a grid point range of each type of agricultural land for each town level administrative area; determining the grid points of the agricultural land belonging to the agricultural land according to the grid point range of the various types of agricultural lands; calculating the land average agricultural yield value of each administrative region of the village and town level according to the agricultural yield values of each agricultural land and the land areas of the administrative regions of the village and town level, and then carrying out interpolation treatment on the land average agricultural yield value, interpolating the land average agricultural yield value to corresponding agricultural land grid points to obtain the land average agricultural yield value of each agricultural land grid point; and carrying out interpolation treatment on the planting densities of the various types of agricultural land, interpolating the planting densities to corresponding agricultural land grid points, and obtaining the planting density of each agricultural land grid point.
3. The typhoon disaster assessment system according to claim 2, further comprising an agricultural production value impact assessment module;
the agricultural yield impact evaluation module is used for determining a crop flooding index and a crop lodging index corresponding to each agricultural land grid according to the accumulated rainfall and the maximum wind speed of each agricultural land grid; calculating the agricultural vulnerability index of each agricultural land lattice point according to the crop flooding index, the crop lodging index and the planting density of each agricultural land lattice point;
calculating an agricultural disaster recovery environment sensitivity index of each agricultural land lattice point according to the agricultural land type of each agricultural land lattice point, the slope direction of each agricultural land lattice point and the elevation standard deviation of each agricultural land lattice point;
calculating the agricultural yield value influence value of each agricultural land lattice point according to the disaster causing factor intensity index, the agricultural vulnerability index, the agricultural disaster environment sensitivity index and the land average agricultural yield value of each agricultural land lattice point;
and according to the administrative division data, taking the agricultural land grid points corresponding to the administrative areas to be evaluated as agricultural evaluation grid points, then determining the total agricultural impact value of the administrative areas to be evaluated according to the economic impact value of each agricultural evaluation grid point, and displaying the total agricultural impact value of the administrative areas to be evaluated on a display interface.
4. The typhoon disaster assessment system according to claim 1, wherein said disaster affected area data management module is further configured to obtain population age data and low house data of administrative areas of each town level; dividing administrative areas of village and town levels into low house land and non-low house land according to the low house data, and determining building types of grid points in administrative areas of the village and town levels; wherein the building types include low houses and non-low houses.
5. The typhoon disaster assessment system according to claim 4, further comprising a population impact assessment module;
the population influence evaluation module is used for carrying out interpolation processing on population density data and population age data of administrative areas of each village and town level, interpolating the population density data and the population age data to corresponding grid points, and obtaining population density and population age of each grid point;
calculating the population vulnerability index of each grid point according to the population density and the population age of each grid point;
calculating the population disaster pregnancy environment sensitivity index of each grid point according to the building type of each grid point, the slope direction of each grid point and the elevation standard deviation of each grid point;
Calculating population influence values of all grid points according to the disaster causing factor intensity index, the population vulnerability index, the population pregnant environment sensitivity index and the population density of all grid points;
and determining the population influence value total value of the administrative region to be evaluated according to the population influence value of each evaluation grid point, and displaying the population influence value total value of the administrative region to be evaluated on a display interface.
6. The typhoon disaster assessment system according to claim 1, wherein the industrial production value influence assessment module is further configured to calculate an industrial influence total value of the administrative area to be assessed in each period according to the disaster causing factor intensity index of each grid point in each preset period, and then display the industrial influence total value of the administrative area to be assessed in each period.
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