KR20220084751A - System and method for comprehensive diagnosis of possible disasters in decayed urban regeneration areas - Google Patents

Abstract

A system for comprehensively diagnosing disasters in a declining area according to an embodiment of the present invention includes an input unit for inputting a disaster disaster DB related to a declining area selected as an urban regeneration complex provided from the outside; a disaster risk analysis unit that selects a disaster disaster type that has occurred in the past in the declining area, and analyzes the disaster risk of the declining area according to the selected disaster disaster type; and a comprehensive diagnosis evaluation index calculation unit that calculates and provides a comprehensive diagnosis evaluation index and grade of a disaster disaster in a grid unit within the spatial geography of a declining area based on the degree of decline, disaster risk, and resilience of the declining area.

Description

System and method for comprehensive diagnosis of possible disasters in decayed urban regeneration areas

The present invention relates to a system and method for comprehensively diagnosing disasters in a declining area.

Risk refers to numerically estimating the probability of damage to people's lives, property, and the environment under the assumption that the severity of the consequences of a hazard on people can be predicted and clearly identified.

Therefore, the degree of risk is the frequency of occurrence, location, spatial area (that is, the ratio of the area where disaster damage is expected to the total area of the area), the duration of the disaster, and the secondary It is greatly affected by Secondary Effects, Seasonality, Speed of onset, and Warning availability.

Meanwhile, regional safety evaluation is a key factor in establishing a disaster prevention plan.

a'Albe (1979) defined regional safety assessment as 'quantitatively and qualitatively assessing the intensity of local disaster risk'. In the academic definition, regional safety evaluation is understood as the same concept as regional risk analysis.

The U.S. Federal Emergency Management Agency (FEMA), for regional safety assessments, is 'a process for identifying the probability and outcome of a disaster to provide a basis for determining a series of disaster mitigation and response tasks at a given level of information (1992)'. It is defined as 'a process or method (1997) for estimating the disaster risk associated with a specific hazard in terms of the probability and frequency of the occurrence, intensity and severity, exposure, and outcome of a disaster'.

And for the safety evaluation of the area, the disaster risk that may occur in the local government where you live, the physical, social and economic damage caused by these disaster risks, the areas vulnerable to these disaster risks, and the future disaster damage He said that damage and costs that can be reduced through reduction projects should be included.

Looking at the technology development trends for regional safety evaluation at home and abroad, the National Disaster Management System (NDMS) has been established and operated in Korea. We are operating a disaster prediction system, and as disaster management policies have been shifted to focus on disaster prevention since the 1990s, regional safety assessment has been recognized as a key issue in disaster management, and research support is actively underway.

In particular, in the case of the United States, CRS evaluation has been used for flood insurance since 1990, and with the passage of the Disaster Mitigation Act (DMA) in 2000, a nationwide evaluation of natural disasters based on damage data from the past 50 years has been conducted. It is configured and operated as a program-oriented system linked to the start-up and integrated GIS system.

On the other hand, the need for development of a regional comprehensive safety management system is raised for the following reasons. A regional disaster risk and damage in consideration of the characteristics of each type of disaster and reduced work efficiency and double work possibility due to insufficient standardization of damage data by type of disaster. The necessity of establishing standardized data for city, county and gu for size calculation, the insufficiency of disaster data management and disaster history management system, causes insufficiency of base data for disaster characteristics analysis such as disaster risk and potential damage or damage size, The reasons for the necessity include policy development through analysis of disaster damage coping capacity and improvement of disaster damage reduction capacity, establishment of a foundation for strengthening responsible administration, and improvement of low information utilization due to the use of disaster information among related organizations and poor system connection. will be

Looking at the conditions for collecting disaster data for disaster assessment by region in Korea, in the event of a disaster, the damage data reported by each region is collected and the sum of the number of damage to facilities or land loss, the number of casualties, etc. is calculated for each type of disaster. I ended up writing a disaster annual report using programs such as Microsoft Excel by converting and summing the results.

In addition, the comprehensive data on a national scale was also added up on the basis of the annual report prepared for each region, and the damage caused by the disaster for a specific period was presented as a comprehensive amount of damage.

Therefore, detailed information related to the disaster, the impact assessment of the disaster reflecting regional characteristics, the relationship between the disaster and the damage, and the assessment of the disaster damage reduction capacity of a specific area could not be performed with the above comprehensive data.

In addition, in Korea, there is no comprehensive evaluation system and objective risk evaluation index for the evaluation of the safety management capacity of local governments, so it is difficult to promote disaster prevention projects and establish response plans in consideration of regional characteristics. The system that induces efforts to secure a safety foundation such as ratio, facility investment, and personnel allocation performance is also insufficient.

Moreover, since it was difficult to secure continuous objectivity in the disaster-related assessment of regional disasters with the disaster-related information obtained through the above work, the evaluation area is first determined and data are collected. When the administrative boundaries of the region change, it is almost impossible to utilize the accumulated data, and the causes of natural disasters, human disasters, and social disasters depend on countless factors. Due to the inadequacy of basic data acquisition, storage, standardization, and management system, it is difficult to determine the cause of the above occurrence, and disaster damage causes indirect damage to the local economy by not only causing direct damage to facilities and human life, but also damage to local productivity and stability of residence. There was no method to calculate such indirect damage.

Republic of Korea Patent Registration No. 10-0755890 (2007. 08. 30.) "Regional safety evaluation system and method using GS"

An object of the present invention is to provide a system and method for comprehensively diagnosing disasters in a declining area, which can solve the problems of the prior art.

The system according to an embodiment of the present invention for solving the above problems is an input unit for inputting a disaster disaster DB related to a declining area selected as an urban regeneration complex provided from the outside; a disaster risk analysis unit for selecting the disaster disaster type of the declining area and analyzing the disaster risk of the declining area according to the selected disaster disaster type; and a comprehensive diagnosis evaluation index calculation unit that calculates and provides a comprehensive diagnosis evaluation index and grade of a disaster disaster in a grid unit within the spatial geography of a declining area based on the degree of decline, disaster risk, and resilience of the declining area.

A method according to an embodiment of the present invention for solving the above problems comprises the steps of: inputting a disaster disaster DB related to a declining area selected as an urban regeneration complex provided from the outside; After selecting the disaster disaster type of the declining area, analyzing the disaster risk of the declining area according to the selected disaster disaster type; and calculating and providing a comprehensive diagnostic evaluation index and grade of a disaster disaster in a grid unit within the spatial geography of the declining area based on the degree of decline, disaster risk, and resilience of the declining area.

Using the system and method according to an embodiment of the present invention, by introducing a concept of resilience that can recover and respond from the risk or impact of a disaster in a declining urban regeneration area, a physically, environmentally, socially, and economically deteriorated area It is possible to comprehensively diagnose disasters on a grid basis, so if it is selected as an urban regeneration area in the future, it has the advantage that it can be provided as information for building a city that can respond to disasters when constructing an urban regeneration area.

1 is a block diagram of a system for comprehensively diagnosing disasters in a declining area according to an embodiment of the present invention.
FIG. 2 is a detailed configuration diagram of the disaster risk analysis unit shown in FIG. 1 .
3 is a flowchart illustrating a method for comprehensively diagnosing a disaster in a declining area according to an embodiment of the present invention.
4 is an exemplary diagram of a GUI displayed on spatial information in which a disaster disaster comprehensive diagnosis evaluation index is displayed in a declining area.
5 is a diagram illustrating an example computing environment in which one or more embodiments disclosed herein may be implemented.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement them. However, the present invention may be embodied in several different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween. . In addition, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated, and one or more other features However, it is to be understood that the existence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded in advance.

The terms "about", "substantially", etc. to the extent used throughout the specification are used in or close to the numerical value when manufacturing and material tolerances inherent in the stated meaning are presented, and are intended to enhance the understanding of the present invention. To help, precise or absolute figures are used to prevent unfair use by unconscionable infringers of the stated disclosure. As used throughout the specification of the present invention, the term "step of (to)" or "step of" does not mean "step for".

In this specification, a "part" includes a unit realized by hardware, a unit realized by software, and a unit realized using both. In addition, one unit may be implemented using two or more hardware, and two or more units may be implemented by one hardware.

Some of the operations or functions described as being performed by the terminal, apparatus, or device in the present specification may be performed instead of by a server connected to the terminal, apparatus, or device. Similarly, some of the operations or functions described as being performed by the server may also be performed in a terminal, apparatus, or device connected to the server.

In this specification, some of the operations or functions described as mapping or matching with the terminal means mapping or matching the terminal's unique number or personal identification information, which is the identification data of the terminal. can be interpreted as

Hereinafter, a system and method for comprehensively diagnosing a disaster in a declining area according to an embodiment of the present invention will be described in more detail based on the accompanying drawings.

First, the system 100 for comprehensively diagnosing disasters in a declining area according to an embodiment of the present invention is for comprehensively diagnosing and evaluating disaster disasters in a declining area based on the disaster disaster risk and resilience of the declining urban regeneration area. it is a system

The types of disasters referred to in this application include heavy rain, heavy snow, strong winds, heat waves, earthquakes, fires, collapses, and explosions.

In addition, the type of disaster includes risk calculation factors such as risk, vulnerability, exposure, and reduction capability, and each calculation factor includes a plurality of index factors.

Here, hazards are factors that are likely to occur in the future, natural or man-made physical phenomena that can adversely affect vulnerable and exposed factors, and exposure are factors in an area where hazardous phenomena can occur. , Vulnerability is a factor that tends to suffer adverse effects when exposed factors such as people and assets are affected by a risk phenomenon, and resilience is a factor that continuously improves safety even in the face of disasters and physical risks. Factors that have the ability to maintain and reduce risk.

Table 1 below is a table showing factors for risk, vulnerability, exposure, and mitigation ability to heavy rain.

[Table 1]

On the other hand, the risk calculation factors according to the type of disaster are fixed indices, which are equally applied to calculating the risk of disasters in declining areas designated nationwide.

Meanwhile, the risk calculation factor referred to herein may be a term used in the Intergovernmental Panel of Climate Change (IPCC) risk assessment system.

1 is a configuration diagram of a system for comprehensively diagnosing a disaster in a declining area according to an embodiment of the present invention, and FIG. 2 is a detailed configuration diagram of the disaster risk analysis unit shown in FIG. 1 .

1 and 2, the system 100 for comprehensively diagnosing disasters in a declining area according to an embodiment of the present invention includes an input unit 200, a disaster risk analysis unit 300, and a comprehensive diagnosis index calculation unit. (400).

The input unit 200 may be configured to input disaster disaster DB information related to a declining area provided from the outside.

The disaster and disaster DB information includes a plurality of index factors related to risk calculation factors of disasters occurring in the corresponding declining area, for example, Hazard, Vulnerability, Exposure, and Resilience. It may be coded information.

Here, the plurality of index factors may be index factors processed in units of 100 m grids.

For example, the spatial interpolation method is used to expand the observation point data to the entire target area by reconstructing the index factor consisting of observation points, spatial information, and statistics for each administrative district based on the standard grid system in units of 100 m provided by the National Geographic Information Service. Inverse distance weighted (IDW), which is one of interpolation, may be information processed in 100 m grid units by using spatial statistics (Zonal Statistics) GIS technique.

Next, the disaster and disaster risk analysis unit 300 selects the type of disaster that occurred in the declining area, and then the disaster risk of the declining area according to the selected disaster disaster type (Hazard; H), exposure ( Exposure; E), vulnerability (Vulnerability; V)) and the disaster risk (risk (H), exposure (E), vulnerability (V)) using resilience (reducing capacity, Resilience; R) It may be a configuration that analyzes the risk of a disaster.

More specifically, the disaster risk analysis unit 300 includes a disaster disaster type selection unit 310, an index standardization unit 320, a weighting unit for each index factor 330, a disaster rating unit 340, and each type of disaster. It includes a weight unit 350 and a disaster risk calculation unit 360 .

The disaster type selection unit 310 may be configured to select a disaster type (heavy rain, heavy snow, strong wind, heat wave, earthquake, fire, collapse, explosion) based on the past disaster disaster DB that occurred in the declining area. .

In addition, the disaster type selection unit 310 may be configured to extract a plurality of index factors corresponding to the risk calculation factors (risk, vulnerability, exposure) related to the selected disaster from the disaster DB.

Next, the index standardization unit 320 may be configured to process and calculate a plurality of index factors having individual unit values measured by different scales into an index standardization score (Z-Score) through a Z-Score algorithm.

Here, Z-Score means a random variable (X-axis of the probability density function) with a mean of 0 and a standard deviation of 1.

)을 빼고 표분편차(

)로 나누어 산출한다.For example, the Z-Score defines the average of the standard normal distribution of a plurality of index factors for each risk factor as '0', processes the 'standard deviation to '1', and then the average of the entire group of individual data (indicator factors). (

) minus the standard deviation (

) is divided by

[Equation 1]

That is, Z is a number that evaluates how many times the standard deviation is away from the mean value.

Next, the weight unit 330 for each index factor may be configured to assign different index factor weights among a plurality of index factors.

The index factor weight is a weight given among a plurality of index factors corresponding to vulnerability (V) among risk calculation factors for the disaster type when the disaster type is heavy rain.

A plurality of index factors for vulnerability to heavy rain are: ① impermeability rate, ② number of safety-vulnerable classes, ③ number of semi-underground households, ④ river density, and ⑤ lifeline area. If ①, ②, ③ exist, A weight, ①, If ④ exists, it may be a configuration that provides a B weight.

As described above, a unique weight is given between the index factors of the risk calculation factors for the type of disaster.

Next, the disaster grading unit 340 may be configured to grade a rating for each of a plurality of weighted index factors into a preset band section. Here, the band section is classified into steps 1 to 5.

Next, the weight unit 350 for each type of disaster may be configured to provide a weight according to the type of disaster. For example, as weights for the risk of disasters, heavy rain 0.5, heavy snow 1.2, strong wind 0.3, heatwave 0.75, earthquake 3, fire 1.1, collapse 2, and explosion 3 may be assigned.

Next, the disaster risk calculation unit 360 applies the Z-Scored risk (H), exposure (E), and vulnerability (V) of the declining area to Equation 1 below to determine the risk by disaster type of the declining area It may be a configuration to be calculated.

[Equation 2]

R = ((H V) + E)

Here, R : Risk, H : Risk, E : Exposure, V : Vulnerability

Next, the comprehensive diagnostic evaluation index calculation unit 400 calculates and provides a preset evaluation index in grid units based on the degree of decline (population, industrial economy), the disaster risk and resilience of the declining area. have. Here, the degree of decline may be a value processed by Z-Score.

The comprehensive diagnostic index calculation unit 400 calculates the comprehensive diagnostic evaluation index using Equation 3 below.

[Equation 3]

Comprehensive diagnosis evaluation index = ((H V) + E)-C

Here, R: Risk, H: Risk, E: Exposure, V: Vulnerability, C: Reduction ability

3 is a flowchart illustrating a method for comprehensively diagnosing a disaster in a declining area according to an embodiment of the present invention.

As shown in FIG. 3 , the method ( S700 ) for comprehensively diagnosing a disaster in a declining area according to an embodiment of the present invention is a declining area selected as an urban regeneration complex provided from the outside in the input unit 200 first. Input the disaster disaster DB related to (S710).

The disaster and disaster DB information includes a plurality of index factors related to risk calculation factors of disasters occurring in the corresponding declining area, for example, Hazard, Vulnerability, Exposure, and Resilience. It may be coded information.

Here, the plurality of index factors may be index factors processed in units of 100 m grids.

For example, the spatial interpolation method is used to expand the observation point data to the entire target area by reconstructing the index factor consisting of observation points, spatial information, and statistics for each administrative district based on the standard grid system in units of 100 m provided by the National Geographic Information Service. Inverse distance weighted (IDW), which is one of interpolation, may be information processed in 100 m grid units by using spatial statistics (Zonal Statistics) GIS technique.

After that, the disaster risk analysis unit 300 selects a disaster disaster type that occurred in the past in the declining area, and then the disaster risk of the declining area according to the selected disaster disaster type and the disaster risk based on the resilience to the disaster risk When the risk of disaster is analyzed (S720), the comprehensive diagnosis evaluation index calculation unit 400 calculates a comprehensive diagnostic evaluation index for disaster disasters based on the degree of decline, disaster risk, and resilience of the declining area, and the space of the declining area It is provided in a grid unit within a geographic area (S730).

Here, the step of analyzing the risk (S720) selects and selects the disaster disaster type (heavy rain, heavy snow, strong wind, heat wave, earthquake, fire, collapse, explosion) based on the past disaster disaster DB that occurred in the declining area and extracting a plurality of index factors corresponding to the risk calculation factors (risk, vulnerability, and exposure) related to the disaster and disaster from the disaster DB.

In addition, the method includes processing and calculating the plurality of index factors having individual unit values measured by the different scales into an index standardized score (Z-Score) through a Z-Score algorithm.

In addition, the method includes the step of assigning different index factor weights among the plurality of index factors.

In addition, it includes the step of grading each of the plurality of weighted index factors into a preset band section, and providing a weight according to the type of disaster.

In addition, It includes the step of calculating the risk for each disaster type in the declining area by applying the Z-Scored risk (H), exposure (E), vulnerability (V), and mitigation capacity (C) of the declining area to Equation 2 below. .

[Equation 2]

R = ((H V) + E)

Here, R : Risk, H : Risk, E : Exposure, V : Vulnerability

The step of analyzing the risk (S720) is performed through the disaster risk analysis unit 300 shown in FIG. 1, and the disaster risk analysis unit 300 includes a disaster type selection unit 310, an indicator standardization unit ( 320), each of the above-described steps is performed using the weighting unit 330 and the disaster rating unit 340 for each index factor, the weight unit 350 for each type of disaster and the disaster risk calculation unit 360 .

The disaster type selection unit 310 may be configured to select a disaster type (heavy rain, heavy snow, strong wind, heat wave, earthquake, fire, collapse, explosion) based on the past disaster disaster DB that occurred in the declining area. .

In addition, the disaster type selection unit 310 may be configured to extract a plurality of index factors corresponding to the risk calculation factors (risk, vulnerability, exposure) related to the selected disaster from the disaster DB.

Next, the index standardization unit 320 may be configured to process and calculate a plurality of index factors having individual unit values measured by different scales into an index standardization score (Z-Score) through a Z-Score algorithm.

Here, Z-Score means a random variable (X-axis of the probability density function) with a mean of 0 and a standard deviation of 1.

)을 빼고 표분편차(

)로 나누어 산출한다.For example, the Z-Score defines the average of the standard normal distribution of a plurality of index factors for each risk factor as '0', processes the 'standard deviation to '1', and then the average of the entire group of individual data (indicator factors). (

) minus the standard deviation (

) is divided by

[Equation 1]

That is, Z is a number that evaluates how many times the standard deviation is away from the mean value.

Next, the weight unit 330 for each index factor may be configured to assign different index factor weights among a plurality of index factors.

The index factor weight is a weight given among a plurality of index factors corresponding to vulnerability (V) among risk calculation factors for the disaster type when the disaster type is heavy rain.

A plurality of index factors for vulnerability to heavy rain are: ① impermeability rate, ② number of safety-vulnerable classes, ③ number of semi-underground households, ④ river density, and ⑤ lifeline area. If ①, ②, ③ exist, A weight, ①, If ④ exists, it may be a configuration that provides a B weight.

As described above, a unique weight is given between the index factors of the risk calculation factors for the type of disaster.

Next, the disaster grading unit 340 may be configured to grade a rating for each of a plurality of weighted index factors into a preset band section. Here, the band section is classified into steps 1 to 5.

Next, the weight unit 350 for each type of disaster may be configured to provide a weight according to the type of disaster. For example, as weights for the risk of disasters, heavy rain 0.5, heavy snow 1.2, strong wind 0.3, heatwave 0.75, earthquake 3, fire 1.1, collapse 2, and explosion 3 may be assigned.

Next, the disaster risk calculation unit 360 applies the Z-Scored risk (H), exposure (E), vulnerability (V) and reduction capacity (C) to the following Equation 1 of the declining area to decline It may be a configuration that calculates the risk for each disaster type in the region.

[Equation 1]

R = ((H V) + E)

Here, R : Risk, H : Risk, E : Exposure, V : Vulnerability

Next, the comprehensive diagnostic evaluation index calculation unit 400 performing the step S730 calculates a preset evaluation index in a grid unit based on the degree of decline (population, industrial economy), the disaster risk and resilience of the declining area It may be a configuration provided by Here, the degree of decline may be a value processed by Z-Score.

The comprehensive diagnosis evaluation index calculation unit 400 calculates the comprehensive diagnosis evaluation index using Equation 3 below.

[Equation 3]

Comprehensive diagnosis evaluation index = ((H V) + E)-C

Here, R: Risk, H: Risk, E: Exposure, V: Vulnerability, C: Reduction ability

Therefore, by using the system and method for comprehensively diagnosing a disaster in a declining area according to an embodiment of the present invention, a concept of resilience that can recover and respond to the risk or impact of a disaster in a declining urban regeneration area is introduced. Thus, disasters and disasters can be comprehensively diagnosed on a grid basis in areas that are physically, environmentally, socially, and economically degraded. There is an advantage that it can be provided as information for

5 is a diagram illustrating an example computing environment in which one or more embodiments disclosed herein may be implemented, and is an illustration of a system 1000 including a computing device 1100 configured to implement one or more embodiments described above. shows For example, computing device 1100 may be a personal computer, server computer, handheld or laptop device, mobile device (mobile phone, PDA, media player, etc.), multiprocessor system, consumer electronics, minicomputer, mainframe computer, distributed computing environments including any of the aforementioned systems or devices, and the like.

The computing device 1100 may include at least one processing unit 1110 and a memory 1120 . Here, the processing unit 1110 may include, for example, a central processing unit (CPU), a graphic processing unit (GPU), a microprocessor, an application specific integrated circuit (ASIC), a Field Programmable Gate Arrays (FPGA), and the like. and may have a plurality of cores. The memory 1120 may be a volatile memory (eg, RAM, etc.), a non-volatile memory (eg, ROM, flash memory, etc.), or a combination thereof. Additionally, computing device 1100 may include additional storage 1130 . Storage 1130 includes, but is not limited to, magnetic storage, optical storage, and the like. The storage 1130 may store computer readable instructions for implementing one or more embodiments disclosed herein, and other computer readable instructions for implementing an operating system, an application program, and the like. Computer readable instructions stored in storage 1130 may be loaded into memory 1120 for execution by processing unit 1110 . Computing device 1100 may also include input device(s) 1140 and output device(s) 1150 .

Here, the input device(s) 1140 may include, for example, a keyboard, mouse, pen, voice input device, touch input device, infrared camera, video input device, or any other input device, or the like. Further, the output device(s) 1150 may include, for example, one or more displays, speakers, printers, or any other output device, or the like. Also, the computing device 1100 may use an input device or an output device included in another computing device as the input device(s) 1140 or the output device(s) 1150 .

Computing device 1100 may also include communication connection(s) 1160 that enable computing device 1100 to communicate with another device (eg, computing device 1300 ).

Here, communication connection(s) 1160 may be a modem, network interface card (NIC), integrated network interface, radio frequency transmitter/receiver, infrared port, USB connection, or other for connecting computing device 1100 to another computing device. It may include interfaces. Further, the communication connection(s) 1160 may include a wired connection or a wireless connection. Each component of the above-described computing device 1100 may be connected by various interconnections such as a bus (eg, peripheral component interconnection (PCI), USB, firmware (IEEE 1394), optical bus structure, etc.) and may be interconnected by a network 1200 . As used herein, terms such as "component," "system," and the like, generally refer to a computer-related entity that is hardware, a combination of hardware and software, software, or software in execution.

For example, a component can be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. For example, both an application running on a controller and a controller may be a component. One or more components may reside within a process and/or thread of execution, and a component may be localized on one computer or distributed between two or more computers.

In the above, various embodiments of the present invention have been illustrated and described, but the present invention is not limited to the specific embodiments described above, and it is common in the technical field to which the present invention pertains without departing from the gist of the present invention as claimed in the claims. Various modifications are possible by those having the knowledge of, of course, and these modifications should not be individually understood from the technical spirit or perspective of the present invention.

100: system
200: input unit
300: Disaster Risk Analysis Department
310: Disaster Type Selection Department
320: indicator standardization unit
330: weight part for each index factor
340: Disaster Rating Division
350: weight part by type of disaster
360: Disaster Risk Calculation Unit
400: Comprehensive diagnosis evaluation index calculation unit

Claims (12)

an input unit for inputting a disaster disaster DB related to a declining area selected as an urban regeneration complex provided from the outside;
a disaster risk analysis unit for selecting the disaster disaster type of the declining area and then analyzing the disaster risk of the declining area according to the selected disaster disaster type; and
Disaster in a declining area comprising a comprehensive diagnostic evaluation index calculation unit that calculates and provides a comprehensive diagnostic evaluation index and grade of disaster disaster in a grid unit within the spatial geography of the declining area based on the degree of decline, disaster risk, and resilience of the declining area A system that comprehensively diagnoses disasters.
According to claim 1,
The disaster risk analysis department
Based on the database of past disasters occurring in the declining areas, the types of disasters (heavy rain, heavy snow, strong winds, heat waves, earthquakes, fires, collapses, explosions) are selected, and risk calculation factors (risk, vulnerability) related to the selected disaster are selected. , exposure), a system for comprehensively diagnosing disasters in declining areas extracted from the disaster disaster DB.
3. The method of claim 2,
The disaster risk analysis department
A system for comprehensively diagnosing disasters in a declining area that is calculated by processing the plurality of index factors having individual unit values measured by the different scales into an index standardized score (Z-Score) through a Z-Score algorithm.
4. The method of claim 3,
The disaster risk analysis department
A system for comprehensively diagnosing disasters in a declining area that assigns different weights to multiple index factors.
5. The method of claim 4,
The disaster risk analysis department
A system for comprehensively diagnosing disasters in declining areas that grades each of a plurality of weighted index factors into a preset band section and provides weights according to the types of disasters.
6. The method of claim 5,
The disaster risk analysis department
A system for comprehensively diagnosing disasters in a declining area that calculates the risk for each disaster type in the declining area by applying the Z-Scored risk (H), exposure (E), and vulnerability (V) of the declining area to Equation 2 below .
[Equation 2]
R = ((H V) + E)
Here, R: Risk, H: Risk, E: Exposure, V: Vulnerability
inputting a disaster disaster DB related to a declining area selected as an urban regeneration complex provided from the outside;
After selecting the disaster disaster type of the declining area, analyzing the disaster risk of the declining area according to the selected disaster disaster type; and
Comprehensive diagnosis of disasters in a declining area, including the step of calculating and providing a comprehensive diagnosis evaluation index and grade of a disaster disaster in a grid unit within the spatial geography of the declining area based on the degree of decline, disaster risk, and resilience of the declining area How to.
8. The method of claim 7,
The step of analyzing the risk is
Based on the database of past disasters occurring in the declining areas, the types of disasters (heavy rain, heavy snow, strong winds, heat waves, earthquakes, fires, collapses, explosions) are selected, and risk calculation factors (risk, vulnerability) related to the selected disaster are selected. , exposure) a method of comprehensively diagnosing disasters in a declining area, comprising extracting a plurality of index factors corresponding to the disaster disaster DB.
9. The method of claim 8,
The step of analyzing the risk is
Comprehensive diagnosis of disaster disasters in declining areas, including the step of processing and calculating the plurality of index factors having individual unit values measured by the different scales into an index standardized score (Z-Score) through a Z-Score algorithm Way.
10. The method of claim 9,
The step of analyzing the risk is
A method of comprehensively diagnosing disasters in a declining area, including the step of assigning different weights of index factors among a plurality of index factors.
11. The method of claim 10,
The step of analyzing the risk is
A method of comprehensively diagnosing disasters in a declining area, comprising grading a grade for each of a plurality of weighted index factors into a preset band section, and providing a weight according to the type of disaster.
12. The method of claim 11,
The step of analyzing the risk is
Disaster disasters in a declining area, including the step of calculating the risk by disaster type in the declining area by applying the Z-Scored risk (H), exposure (E), and vulnerability (V) of the declining area to Equation 2 below How to make a comprehensive diagnosis.
[Equation 2]
R = ((H V) + E)
Here, R: Risk, H: Risk, E: Exposure, V: Vulnerability

Images