JP7761863B2 - Estimation device, estimation system, estimation method, and program - Google Patents

Description

The present disclosure relates to an estimation device, an estimation system, an estimation method, and a program.

To date, several technologies for predicting the occurrence of landslides have been considered in order to forecast damage caused by landslides. For example, "Kikikuru," provided by the Japan Meteorological Agency, predicts the likelihood of landslides based on the soil precipitation index, surface precipitation index, and watershed precipitation index, and publishes this information (Non-Patent Document 1). Furthermore, "Doshaburu," provided by Pacific Consultants, calculates a "Doshaburu Index" that indicates the risk of disaster based on rainfall (data from XRAIN (eXtended RAdar Information Network)), soil precipitation index, slope angle, etc., and sends an alert (Non-Patent Document 2). These services aim to protect human lives by encouraging appropriate evacuation.

As a technology that can be used to inspect infrastructure facilities, Nomura et al. have investigated a simple method for predicting the occurrence of disasters based on rainfall, land use, etc. (Non-Patent Document 3). Furthermore, known examples of infrastructure damage prediction include prediction of damage to water pipes due to seismic motion (Non-Patent Document 4) and prediction of damage to utility poles due to typhoons (Non-Patent Document 5).

"Japan Meteorological Agency | Warning Risk Distribution," [online], [searched June 6, 2022], Internet <URL: https://www.jma.go.jp/jma/kishou/know/bosai/riskmap.html> "Landslide Disaster Risk Information Service Doshaburu - Pacific Consultants Co., Ltd." [online] [Retrieved June 6, 2022], Internet <URL: https://www.pacific.co.jp/service/38.html> Mitsuharu Nomura and 1 other person, "Proposal of an evaluation method for the possibility of landslide disasters for the purpose of supporting patrols of power transmission facilities," Central Research Institute of Electric Power Industry Research Report N20002, October 2020. Yoshihisa Maruyama and 1 other collaborators, "Improvement of Macroscopic Water Distribution Pipe Damage Prediction Formulas Taking into Account Recent Earthquake Damage Data," Journal of the Japan Society of Civil Engineers, A1 (Structural and Earthquake Engineering), Vol. 65, No. 1, pp. 565-574, 2009 Naohiro Hayata and four others, "Improvement of the Wind Speed Calculation Method in the RAMPT Typhoon Damage Prediction System for Power Distribution Facilities (Part 1) - Parameter Estimation of Typhoon Models Using Numerical Weather Models," Central Research Institute of the Electric Power Industry Research Report N17008, May 2018.

As mentioned above, technologies for predicting the occurrence of landslides based on rainfall forecasts are known, as are technologies for predicting damage to infrastructure caused by earthquakes and typhoons. However, it is not possible to estimate the extent of damage to structures, including infrastructure, based on rainfall and other wetness information. This makes it difficult to appropriately prepare for damage to structures.

The purpose of this disclosure, made in consideration of these circumstances, is to provide an estimation device, estimation system, estimation method, and program that can estimate the extent of damage to a structure based on wetness condition information.

To solve the above problem, the estimation device disclosed herein comprises an average structure number memory unit that stores an average structure number, which is the average number of structures located in each of one or more expected damage areas included in a specified geographical range; a damage rate memory unit that stores a damage rate, which is the probability that the structures will be damaged in the event of a disaster; a structure number estimation unit that estimates an estimated number of structures, which is the number of structures located in the expected damage area where the disaster is expected to occur, based on the number of occurrence locations, which is the number of expected damage areas where the disaster is expected to occur, among the one or more expected damage areas, and the average number of structures; a damage estimation unit that estimates a damage number, which is the number of structures that will be damaged in the specified range, based on the estimated number of structures and the damage rate; and an output unit that outputs the damage number.

In addition, to solve the above-mentioned problems, the estimation system disclosed herein comprises an estimation device and a display device. In the estimation system, the estimation device comprises: an average structure number memory unit that stores an average structure number, which is the average number of structures located in each of one or more expected damage areas included in a predetermined geographical range; a damage rate memory unit that stores a damage rate, which is the probability that the structures will be damaged in the event of a disaster; a structure number estimation unit that estimates an estimated number of structures, which is the number of structures located in the expected damage area where the disaster is expected to occur, based on the number of occurrence locations, which is the number of expected damage areas where the disaster is expected to occur, among the one or more expected damage areas, and the average number of structures; a damage estimation unit that estimates a damage number, which is the number of structures that will be damaged in the predetermined range, based on the number of structures and the damage rate; and an output unit that outputs the damage number, and the display device displays the damage number.

In addition, to solve the above-mentioned problems, the estimation method disclosed herein is an estimation method executed by an estimation device having an average structure number memory unit that stores an average structure number, which is the average number of structures installed in each of one or more expected damage areas included in a predetermined geographical range, and a damage rate memory unit that stores a damage rate, which is the probability that the structures will be damaged in the event of a disaster, and includes the steps of: estimating the estimated number of structures, which is the number of structures installed in the expected damage area where the disaster is estimated to occur, based on the number of occurrence locations, which is the number of expected damage areas where the disaster is estimated to occur, and the average number of structures, among the one or more expected damage areas; estimating the damage number, which is the number of structures that will be damaged in the predetermined range, based on the estimated number of structures and the damage rate; and outputting the damage number.

In addition, to solve the above problem, the program disclosed herein causes a computer to operate as the above-mentioned estimation device.

The estimation device, estimation system, estimation method, and program disclosed herein make it possible to estimate the extent of damage to a structure based on wetness condition information.

FIG. 1 is a schematic diagram illustrating an example of an estimation system according to a first embodiment of the present disclosure. FIG. 2 is a schematic diagram illustrating an example of the estimation device shown in FIG. 1 . 3 is a diagram showing an example of the number of occurrence locations stored in an occurrence location number storage unit shown in FIG. 2; FIG. 3 is a diagram for explaining the average number of structures stored in an average number of structures storage unit shown in FIG. 2 . FIG. 3 is a diagram showing an example of a damage rate stored in a damage rate storage unit shown in FIG. 2 . FIG. 3 is a flowchart showing an example of the operation of the estimation device shown in FIG. 2 . FIG. 10 is a schematic diagram illustrating an example of an estimation device according to a second embodiment of the present disclosure. FIG. 3 is a diagram illustrating an example of a hardware configuration of the estimation device illustrated in FIG. 2 .

<<First Embodiment>>
The overall configuration of the first embodiment will be described with reference to Fig. 1. Fig. 1 is a schematic diagram showing an example of an estimation system 100 according to the first embodiment.

As shown in FIG. 1, the estimation system 100 includes an estimation device 10 and a display device 20. The estimation device 10 and the display device 20 may communicate with each other via a communication network. The estimation device 10 and the display device 20 may also be configured as an integrated unit.

<Configuration of Estimation Device>
As shown in Fig. 2, the estimation device 10 includes a landslide disaster occurrence estimation unit (disaster occurrence estimation unit) 11, a temporary storage unit 12, and a structure damage estimation unit 13. In the following, an example of executing estimation for a "landslide disaster," which is an example of a disaster, will be described, but the invention is not limited to landslide disasters.

The landslide disaster occurrence estimation unit 11 has an input unit 111, an occurrence location number storage unit 112, and an occurrence location number extraction unit 113. The input unit 111 is composed of an input interface. The input interface may be composed of a mouse, keyboard, etc., or a communications interface. The communications interface may use standards such as Ethernet (registered trademark), FDDI (Fiber Distributed Data Interface), or Wi-Fi (registered trademark). The occurrence location number storage unit 112 is composed of memory. The memory may be composed of a HDD (Hard Disk Drive), SSD (Solid State Drive), EEPROM (Electrically Erasable Programmable Read-Only Memory), ROM (Read-Only Memory), RAM (Random Access Memory), etc. The occurrence location number extraction unit 113 is composed of a controller. The controller may be configured with dedicated hardware such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array), or may be configured with a processor, or may be configured with both.

The input unit 111 accepts input of information relating to a predetermined geographical range. In an example where the disaster is a landslide, the input unit 111 accepts input of wetness information expected in the predetermined geographical range. The wetness information is information indicating the wetness of the soil, which is a cause of a landslide. In the first embodiment, the wetness information is rainfall. The predetermined range may be a predetermined square range, for example, 1 km on each side. The predetermined range may also be an administrative district such as a city, ward, town, or village.

The occurrence location number storage unit 112 stores the number of locations where landslides have occurred within a predetermined range, corresponding to the amount of rainfall. The number of occurrence locations is the number of expected damage areas where landslides are predicted to occur, out of one or more expected damage areas included in the predetermined range. The expected damage areas are areas where landslides are predicted to occur, and may be, for example, landslide warning areas as shown in the following non-patent document 6. The structures are, for example, infrastructure facilities such as utility poles. The structures may also include, for example, houses.
Non-patent document 6: "National Land Numerical Information | Landslide Disaster Warning Area Data," [online], [searched June 6, 2022], Internet <URL: https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-A33-v1_4.html>

The occurrence location number storage unit 112 may store the number of locations where landslides have occurred for each type of landslide within a predetermined range, corresponding to the amount of rainfall. The types of landslides include cliff collapses, debris flows, and landslides, as shown in the following Non-Patent Document 7. For example, as shown in FIG. 3, the occurrence location number storage unit 112 may store the number of cliff collapses, debris flows, and landslides within a predetermined range, corresponding to the amount of rainfall.
Non-patent document 7: "Special Feature 2: Preparing for Landslides: Disaster Prevention Information Page - Cabinet Office," [online], [searched June 6, 2022], Internet <URL: https://www.bousai.go.jp/kohou/kouhoubousai/h27/79/special_02.html>

In the example shown in FIG. 3 , the occurrence location number storage unit 112 stores, for a predetermined range, the number of cliff collapse locations " _Na locations," the number of debris flow locations " _Nb locations," and the number of landslide locations "Nc locations" that correspond to rainfall of X mm/day or more but less than Y mm/day (Y>X). The occurrence location number storage unit 112 also stores the number of cliff collapse locations " _Nd locations," the number of debris flow locations " _Ne locations," and the number of landslide locations " _Nf locations" that correspond to rainfall of Y mm/day or more but less than Z mm/day (Z>Y). The occurrence location number storage unit 112 also stores the number of cliff collapse locations " _Ng locations," the number of debris flow locations " _Nh locations," and the number of landslide locations " _Ni locations" that correspond to rainfall of Z _mm /day or more.

The occurrence location number extraction unit 113 extracts the number of locations where landslides have occurred corresponding to the wetness information (rainfall) indicating the wetness state of the soil within a specified range, which is stored in the occurrence location number memory unit 112. The occurrence location number extraction unit 113 may also extract the number of locations where landslides have occurred for each type of landslide disaster.

In the example shown in FIG. 3 , when the rainfall in a predetermined range input by the input unit 111 is equal to or greater than X mm/day and less than Y mm/day, the occurrence location number extraction unit 113 extracts the number of cliff collapse locations " _Na locations," the number of debris flow locations " _Nb locations," and the number of landslide locations " _Nc locations," which are stored in association with the rainfall.

The temporary storage unit 12 is composed of a memory. The temporary storage unit 12 stores the number of landslide occurrence locations extracted by the occurrence location number extraction unit 113. As described above, in a configuration in which the occurrence location number extraction unit 113 extracts the number of occurrence locations for each landslide occurrence type, the temporary storage unit 12 may store the number of occurrence locations for each landslide occurrence type.

The structure damage estimation unit 13 has an average structure number memory unit 131, a damage rate memory unit 132, a structure number estimation unit 133, a damage estimation unit 134, and an output unit 135. The average structure number memory unit 131 and the damage rate memory unit 132 are configured by memory. The structure number estimation unit 133 and the damage estimation unit 134 are configured by a controller. The output unit 135 is configured by an output interface. The output interface may include a communication interface.

The average structure number memory unit 131 stores the average structure number, which is the average value of the number of structures located in each of one or more expected damage areas within a specified geographical range.

For example, the average structure number storage unit 131 may store an average number of structures for each disaster type, which is the average number of structures provided in each of one or more estimated damage areas defined for each disaster type. In an example where the disaster is a landslide, the average structure number storage unit 131 may store an average number of structures for each landslide type, which is the average number of structures provided in each of one or more estimated damage areas defined for each landslide type. Figure 4 shows an example in which the numbers of structures (indicated by circles in Figure 4) provided in three estimated damage areas A, B, and C for debris flow included in a predetermined range are _ma , _mb , and _mc, respectively. In this example, the average structure number storage unit 131 stores the average number of structures m ave in a debris flow landslide, m _ave = ( _ma + _mb + _mc )/3. Similarly, the average number of structures storage unit 131 stores the average number of structures in landslide disasters caused by cliff collapses and the average number of structures in landslide disasters caused by landslides.

The average structure number storage unit 131 may also store the average number of structures for each structure type. The average structure number storage unit 131 may also store the average number of structures for each landslide disaster type and structure type. The structure type is information indicating the type of structure, and may, for example, be information indicating whether the structure is a house or an infrastructure facility.

The damage rate memory unit 132 stores a damage rate, which is the probability that a structure will be damaged if a disaster occurs. In an example where the disaster is a landslide, the damage rate memory unit 132 stores a damage rate, which is the probability that a structure will be damaged if a landslide occurs. Note that the damage rates stored in the damage rate memory unit 132 are calculated based on damage from disasters that have occurred in the past.

The damage rate storage unit 132 may store a damage rate for each disaster type. In an example where the disaster is a landslide, the damage rate storage unit 132 may store a damage rate for each landslide type, as shown in Fig. 5. In the example shown in Fig. 5, the damage rate storage unit 132 stores a structure damage rate _Pa corresponding to the landslide type "cliff collapse," a structure damage rate _Pb corresponding to the landslide type "debris flow," and a structure damage rate _Pc corresponding to the landslide type "landslide."

Furthermore, as described above, in a configuration in which the average structure number storage unit 131 stores the average number of structures for each structure type, the damage rate storage unit 132 may store the damage rate for each structure type.Furthermore, in a configuration in which the average structure number storage unit 131 stores the average number of structures for each landslide disaster type and structure type, the damage rate storage unit 132 may store the damage rate for each landslide disaster type and structure type.

The structure number estimation unit 133 estimates the estimated number of structures, which is the number of structures installed in an estimated damage area where a disaster is estimated to occur, based on the number of occurrence locations, which is the number of estimated damage areas where a disaster is estimated to occur, among one or more estimated damage areas, and the average number of structures. In an example where the disaster is a landslide, the structure number estimation unit 133 estimates the estimated number of structures, which is the number of structures installed in an estimated damage area where a landslide is estimated to occur, based on the number of occurrence locations, which is the number of estimated damage areas where a landslide is estimated to occur, among one or more estimated damage areas, and the average number of structures. For example, the structure number estimation unit 133 estimates the estimated number of structures based on the number of occurrence locations extracted by the occurrence location number extraction unit 113 and stored in the temporary memory unit 12, and the average number of structures stored in the average structure number memory unit 131. Specifically, the structure number estimation unit 133 estimates the product of the number of occurrence locations and the average number of structures as the estimated number of structures in a predetermined range.

For example, the structure number estimation unit 133 may estimate the estimated number of structures for each disaster type based on the number of locations where each disaster type occurs and the average number of structures for each disaster type. In an example where the disaster is a landslide, the structure number estimation unit 133 may estimate the estimated number of structures for each landslide type based on the number of locations where each landslide type occurs and the average number of structures for each landslide type. Specifically, the structure number estimation unit 133 may estimate the estimated number of structures based on the number of locations where each landslide type occurs stored in the temporary memory unit 12 and the average number of structures for each landslide type stored in the average structure number memory unit 131. More specifically, the structure number estimation unit 133 calculates the estimated number of structures as the product of the number of locations where each landslide type occurs and the average number of structures for the corresponding landslide type.

Furthermore, as described above, in a configuration in which the average structure number storage unit 131 stores the average number of structures for each structure type, the structure number estimation unit 133 may estimate the estimated number of structures for each structure type based on the number of occurrence locations and the average number of structures for each structure type.Furthermore, in a configuration in which the average structure number storage unit 131 stores the average number of structures for each landslide disaster type and structure type, the structure number estimation unit 133 may estimate the estimated number of structures for each landslide disaster type and structure type based on the number of occurrence locations for each landslide disaster type and the average number of structures for each landslide disaster type and structure type.

The damage estimation unit 134 estimates the number of damages, which is the number of structures that will be damaged, based on the estimated number of structures and the damage rate if a disaster occurs. In an example where the disaster is a landslide, the damage estimation unit 134 estimates the number of damages, which is the number of structures that will be damaged, based on the estimated number of structures and the damage rate if a landslide occurs. Specifically, the damage estimation unit 134 estimates the number of damages to be the product of the estimated number of structures and the damage rate.

As an example, the damage estimation unit 134 may estimate the number of damages for each disaster type based on the estimated number of structures for each disaster type and the damage rate for each disaster type. In an example where the disaster is a landslide, the damage estimation unit 134 may estimate the number of damages for each landslide type based on the estimated number of structures for each landslide type and the damage rate for each landslide type. Specifically, the damage estimation unit 134 estimates the number of damages for each landslide type as the product of the estimated number of structures for each landslide type and the damage rate for the corresponding landslide type.

Furthermore, as described above, in a configuration in which the average structure number memory unit 131 stores the average number of structures for each structure type and the damage rate memory unit 132 stores the damage rate for each structure type, the damage estimation unit 134 may estimate the number of damages for each structure type based on the estimated number of structures for each structure type and the damage rate for each structure type. Specifically, the damage estimation unit 134 estimates the number of damages for each structure type as the product of the number of structures for each structure type and the damage rate for the corresponding structure type.

Furthermore, as described above, in a configuration in which the average structure number memory unit 131 stores the average number of structures for each landslide disaster type and structure type, and the damage rate memory unit 132 stores the damage rate for each landslide disaster type and structure type, the damage estimation unit 134 may estimate the number of damages for each landslide disaster type and structure type based on the estimated number of structures for each landslide disaster type and structure type and the damage rate for each landslide disaster type and structure type. Specifically, the damage estimation unit 134 estimates the number of damages for each landslide disaster type and structure type as the product of the number of structures for each landslide disaster type and structure type and the damage rate for the corresponding landslide disaster type and structure type.

The output unit 135 outputs the number of damages. The output unit 135 may output the number of damages for each disaster type. In an example where the disaster is a landslide, the output unit 135 may output the number of damages for each landslide type. The output unit 135 may output the number of damages for each structure type. The output unit 135 may output the number of damages for each landslide type and each structure type. The output unit 135 may output the number of damages to the display device 20, or to another device via a communication network.

<Configuration of the display device>
The display device 20 is configured by a computer having a memory, a controller, and a display. The computer configuring the display device 20 may further include a communication interface. The display is configured by an organic EL (Electro Luminescence) panel, a liquid crystal panel, or the like.

The display device 20 displays the number of damages output by the output unit 135 of the estimation device 10. The display device 20 may display the number of damages for each disaster type. In an example where the disaster is a landslide, the display device 20 may display the number of damages for each landslide type. The display device 20 may output the number of damages for each structure type. The display device 20 may output the number of damages for each landslide type and structure type.

The display device 20 may also store a map including the range within which the number of damages is estimated by the estimation device 10. In such a configuration, the display device 20 may display the map and display the number of damages at a position on the map that corresponds to a predetermined range.

<Operation of the estimation device>
Here, the operation of the estimation device 10 according to the first embodiment will be described with reference to FIG. 6 . FIG. 6 is a flowchart showing an example of the operation of the estimation device 10 according to the first embodiment. The operation of the estimation device 10 described with reference to FIG. 6 corresponds to an example of an estimation method of the estimation device 10 according to the first embodiment. In this example, an example will be described in which the disaster is a landslide. However, the disaster is not limited to a landslide. Furthermore, the estimation device 10 according to this example includes the average structure number storage unit 131, the damage rate storage unit 132, and the occurrence location number storage unit 112 described above.

In step S11, the input unit 111 accepts input of the amount of rainfall expected in a specified geographical area.

In step S12, the occurrence location number extraction unit 113 extracts the number of landslide occurrence locations stored in correspondence with the amount of rainfall within a predetermined range. For example, the occurrence location number extraction unit 113 may extract the number of occurrence locations for each type of landslide disaster.

In step S13, the temporary storage unit 12 stores the number of landslide disaster occurrence locations extracted by the occurrence location number extraction unit 113. For example, the temporary storage unit 12 may store the number of landslide disaster occurrence locations for each type of landslide disaster.

In step S14, the structure number estimation unit 133 estimates the estimated number of structures, which is the number of structures located in the estimated damage area where a landslide is estimated to occur, based on the number of occurrence locations, which is the number of estimated damage areas where a landslide is estimated to occur, among one or more estimated damage areas, and the average number of structures. For example, the structure number estimation unit 133 estimates the estimated number of structures based on the number of occurrence locations extracted in step S12 and stored in step S13, and the average number of structures stored in the average structure number memory unit 131.

In this case, the structure number estimation unit 133 may estimate the estimated number of structures for each landslide disaster type based on the number of locations where each landslide disaster type occurred and the average number of structures for each landslide disaster type. The structure number estimation unit 133 may also estimate the estimated number of structures for each structure type based on the number of locations where each landslide disaster occurred and the average number of structures for each structure type. The structure number estimation unit 133 may also estimate the estimated number of structures for each landslide disaster type and structure type based on the number of locations where each landslide disaster type occurred and the average number of structures for each landslide disaster type and structure type.

In step S15, the damage estimation unit 134 estimates the number of damages, which is the number of structures affected within a predetermined range, based on the estimated number of structures and the damage rate. For example, the damage estimation unit 134 may estimate the number of damages for each landslide disaster type based on the number of structures for each landslide disaster type and the damage rate for each landslide disaster type. The damage estimation unit 134 may also estimate the number of damages for each structure type based on the number of structures for each structure type and the damage rate for each structure type. The damage estimation unit 134 may also estimate the number of damages for each landslide disaster type and structure type based on the number of structures for each landslide disaster type and the damage rate for each landslide disaster type and structure type.

In step S16, the output unit 135 outputs the number of damages. For example, the output unit 135 may output to the display device 20 the number of damages for each landslide disaster type, the number of damages for each structure type, or the number of damages for each landslide disaster type and each structure type.

The estimation device 10 may not execute steps S11 and S12. In this case, the estimation device 10 may execute the processing from step S13 onwards based on the number of occurrence locations estimated by any method. In this case, the estimation device 10 may not be provided with the number of occurrence locations storage unit 112.

As described above, the estimation device 10 according to the first embodiment includes an average structure number memory unit 131 that stores the average number of structures, which is the average number of structures installed in each of one or more estimated damage zones within a predetermined geographical range; a damage rate memory unit 132 that stores the damage rate, which is the probability that structures will be damaged in the event of a disaster; a structure number estimation unit 133 that estimates the estimated number of structures, which is the number of structures installed in the estimated damage zones where a disaster is expected to occur, based on the number of occurrence locations, which is the number of estimated damage zones where a disaster is expected to occur, and the average number of structures, among one or more estimated damage zones; a damage estimation unit 134 that estimates the damage number, which is the number of structures that will be damaged within the predetermined range, based on the estimated number of structures and the damage rate; and an output unit 135 that outputs the damage number. This allows the estimation device 10 according to the first embodiment to estimate the extent of damage within a predetermined range. This enables efficient disaster prevention measures.

In addition, in the estimation device 10 according to the first embodiment, the average structure number memory unit 131 stores the average number of structures for each disaster type, which is the average number of structures in each of one or more predicted damage areas defined for each disaster type. The damage rate memory unit 132 stores the damage rate for each disaster type. The structure number estimation unit 133 estimates the estimated number of structures for each disaster type based on the number of occurrence locations for each disaster type and the average number of structures for each disaster type. The damage estimation unit 134 estimates the number of damages for each disaster type based on the estimated number of structures for each disaster type and the damage rate for each disaster type. Generally, damage to structures caused by disasters varies depending on the disaster type. Therefore, by estimating the number of damages for each disaster type, the estimation device 10 can estimate the degree of damage within a specified area in detail with high accuracy. This enables more efficient disaster countermeasures.

In addition, in the estimation device 10 according to the first embodiment, the structure number estimation unit 133 estimates the number of damages for each structure type. Furthermore, the structure number estimation unit 133 estimates the number of damages for each disaster type and structure type. Generally, damage to structures caused by disasters can vary depending on the structure type. Therefore, by estimating the number of damages for each structure type, the estimation device 10 can estimate the degree of damage within a specified range in detail with high accuracy. Therefore, it becomes possible to implement disaster countermeasures more efficiently.

The estimation device 10 according to the first embodiment further includes an occurrence location number memory unit 112 that stores the number of locations where landslides have occurred within a specified range, corresponding to the amount of rainfall, and an occurrence location number extraction unit 113 that extracts the number of locations where landslides have occurred, corresponding to the wetness information within the specified range. The structure number estimation unit 133 estimates the estimated number of structures based on the extracted number of occurrence locations and the average number of structures. This makes it possible to appropriately estimate the number of locations where disasters have occurred within a specified range, depending on the amount of rainfall. Accordingly, the extent of damage within a specified range can be estimated in detail with high accuracy. This makes it possible to implement disaster countermeasures more efficiently.

<<Second Embodiment>>
In the second embodiment, the estimation system 100 includes an estimation device 10-1 (see FIG. 7) instead of the estimation device 10 shown in FIG. 1. In the second embodiment, the same functional units as those in the first embodiment are denoted by the same reference numerals, and descriptions thereof will be omitted.

<Configuration of Estimation Device>
As shown in FIG. 7, the estimation device 10-1 includes a landslide disaster occurrence estimation unit (disaster occurrence estimation unit) 11-1, a temporary storage unit 12, and a structural damage estimation unit 13.

The landslide disaster occurrence estimation unit 11-1 has an input unit 111-1, an occurrence location number memory unit 112-1, and an occurrence location number extraction unit 113-1.

The input unit 111-1 accepts input of moisture condition information expected within a predetermined range. In the second embodiment, the moisture condition information is the soil moisture content.

The occurrence location number memory unit 112-1 stores the number of locations where landslides have occurred within a specified range, corresponding to the amount of soil moisture. The occurrence location number memory unit 112-1 may also store the number of locations where landslides have occurred within a specified range, corresponding to the amount of soil moisture for each type of landslide.

The occurrence location number extraction unit 113-1 extracts the number of landslide occurrence locations stored in the occurrence location number memory unit 112-1 in accordance with the soil moisture content within a specified range input by the input unit 111-1. The occurrence location number extraction unit 113-1 may also extract the number of landslide occurrence locations for each landslide disaster type.

<Operation of the estimation device>
Here, the operation of the estimation device 10-1 according to the second embodiment will be described. In the second embodiment, the estimation device 10-1 operates in the same manner as in the first embodiment, except that soil moisture content is used instead of rainfall in steps S11 and S12 of the first embodiment.

As explained above, the estimation device 10-1 according to the second embodiment can appropriately estimate the number of disaster occurrence locations within a specified area based on the soil moisture content. This allows for a highly accurate and detailed estimation of the extent of damage within a specified area. Therefore, it becomes possible to implement disaster countermeasures efficiently.

<Modification>
In the first and second embodiments described above, the occurrence location number storage unit 112, 112-1 may store the number of landslide occurrence locations corresponding to the wetness information (rainfall in the first embodiment, soil moisture content in the second embodiment) for each of a plurality of ranges. Furthermore, the occurrence location number storage unit 112, 112-1 may store the number of landslide occurrence locations corresponding to the wetness information for each type of landslide disaster for each of a plurality of ranges.

In this configuration, the input units 111, 111-1 may accept input of range identification information for identifying a range along with the wetness state information. In this case, the "predetermined range" in the first embodiment is the range identified by the range identification information accepted by the input units 111, 111-1. The occurrence location number extraction unit 113, 113-1 then extracts the number of landslide occurrence locations stored in the occurrence location number memory unit 112, 112-1 corresponding to the wetness state information in the range (predetermined range) identified by the range identification information input by the input units 111, 111-1. Furthermore, the output unit 135 outputs the number of damages estimated by the damage estimation unit 134 together with the range identification information.

Furthermore, in such a configuration, the display device 20 may display the number of damages for each of the multiple ranges at positions on the map that correspond to the multiple ranges. In this case, the display device 20 may display the number of damages corresponding to the positions on the map that correspond to the ranges indicated by the multiple range identification information output by the output unit 135. Alternatively, the display device 20 may simply display the number of damages together with the range identification information without displaying a map.

<Program>
The above-described estimation devices 10 and 10-1 can be realized by a computer 301. A program for causing the above-described estimation devices 10 and 10-1 to function may be provided. The program may be stored in a storage medium or provided via a network. FIG. 8 is a block diagram showing a schematic configuration of a computer 301 that functions as each of the estimation devices 10 and 10-1. Here, the computer 301 may be a general-purpose computer, a dedicated computer, a workstation, a PC (Personal Computer), an electronic notepad, or the like. The program instructions may be program code, code segments, or the like for executing necessary tasks.

As shown in FIG. 8, computer 301 includes processor 310, ROM (Read Only Memory) 320, RAM (Random Access Memory) 330, storage 340, input unit 350, output unit 360, and communication interface (I/F) 370. Each component is communicatively connected to one another via bus 380. Processor 310 is specifically a CPU (Central Processing Unit), MPU (Micro Processing Unit), GPU (Graphics Processing Unit), DSP (Digital Signal Processor), SoC (System on a Chip), etc., and may be composed of multiple processors of the same or different types.

Processor 310 controls each component and performs various arithmetic operations. That is, processor 310 reads a program from ROM 320 or storage 340 and executes the program using RAM 330 as a working area. Processor 310 controls each component and performs various arithmetic operations in accordance with the program stored in ROM 320 or storage 340. In the above-described embodiment, the program related to the present disclosure is stored in ROM 320 or storage 340.

The program may be stored on a storage medium readable by computer 301. Using such a storage medium, the program can be installed on computer 301. Here, the storage medium on which the program is stored may be a non-transitory storage medium. Non-transitory storage media are not particularly limited, but may be, for example, a CD-ROM, a DVD-ROM, or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via a network.

ROM 320 stores various programs and data. RAM 330 temporarily stores programs or data as a working area. Storage 340 is composed of an HDD (Hard Disk Drive) or SSD (Solid State Drive) and stores various programs and data, including the operating system.

The input unit 350 is an interface for accepting information input, and the output unit 360 is an interface for outputting information.

The communication interface (I/F) 370 is an interface for communicating with external devices.

The following additional notes are provided regarding the above-described embodiments.
[Additional note 1]
a memory, a controller, and an output interface;
The memory includes:
storing an average number of structures, which is the average number of structures provided in each of one or more estimated damage zones included in a predetermined geographical range;
storing a damage rate, which is the probability that the structure will be damaged in the event of a disaster;
The controller
Based on the number of occurrence locations, which is the number of expected damage areas where the occurrence of the disaster is predicted, and the average number of structures, an estimated number of structures, which is the number of structures provided in the expected damage areas where the occurrence of the disaster is predicted, is estimated;
estimating the number of damages, which is the number of structures that will be damaged within the predetermined range, based on the estimated number of structures and the damage rate;
The output interface outputs the number of damages.
[Additional note 2]
The memory includes:
The average number of structures for each disaster type is stored, which is the average number of structures installed in each of one or more estimated damage areas defined for each disaster type;
The damage rate for each disaster type is stored in the controller.
estimating the estimated number of structures for each disaster type based on the number of occurrence locations for each disaster type and the average number of structures for each disaster type;
The estimation device according to appended claim 1, wherein the number of damages for each disaster type is estimated based on the estimated number of structures for each disaster type and the damage rate for each disaster type.
[Additional note 3]
The disaster is a landslide,
The memory stores the number of locations where the landslide disaster has occurred, corresponding to the wetness state information indicating the wetness state of the soil within the predetermined range,
The controller
extracting the number of locations where the landslide disaster has occurred, which is stored in correspondence with the wetness state information within the predetermined range;
The estimation device according to claim 1, wherein the estimated number of structures is estimated based on the extracted number of occurrence locations and the average number of structures.
[Additional note 4]
The memory includes:
The average number of structures for each disaster type is stored as an average value of the number of structures in each of one or more estimated damage areas defined for each landslide disaster type.
storing the number of locations where the landslide disaster has occurred corresponding to the wetness state information for each type of landslide disaster;
The controller
Extracting the number of occurrence locations for each type of landslide disaster;
The estimation device described in appendix 3 estimates the estimated number of structures for each landslide disaster type based on the number of occurrence locations for each landslide disaster type and the average number of structures for each landslide disaster type.
[Additional note 5]
An estimation system including an estimation device and a display device,
the estimating device includes a memory, a controller, and an output interface;
The memory includes:
storing an average number of structures, which is the average number of structures provided in each of one or more estimated damage zones included in a predetermined geographical range;
storing a damage rate, which is the probability that the structure will be damaged in the event of a disaster;
The controller
Based on the number of occurrence locations, which is the number of expected damage areas where the occurrence of the disaster is predicted, and the average number of structures, an estimated number of structures, which is the number of structures provided in the expected damage areas where the occurrence of the disaster is predicted, is estimated;
estimating the number of damages, which is the number of structures that will be damaged within the predetermined range, based on the estimated number of structures and the damage rate;
The output interface outputs the number of damages;
The display device displays the number of damages.
Estimation system.
[Additional note 6]
An estimation method is carried out by an estimation device having a memory that stores an average number of structures, which is the average number of structures provided in each of one or more estimated damage areas included in a predetermined geographical range, and stores a damage rate, which is the probability that the structures will be damaged in the event of a disaster,
Based on the number of occurrence locations, which is the number of expected damage areas where the occurrence of the disaster is predicted, and the average number of structures, an estimated number of structures, which is the number of structures provided in the expected damage areas where the occurrence of the disaster is predicted, is estimated;
Estimating the number of damages, which is the number of structures that will be damaged within the predetermined range, based on the estimated number of structures and the damage rate;
An estimation method that outputs the number of damages.
[Additional note 7]
A non-transitory storage medium storing a program executable by a computer, the non-transitory storage medium storing a program that causes the computer to operate as an information processing device described in any one of appendix items 1 to 4.

All publications, patent applications, and technologies described in this specification are incorporated by reference into this specification to the same extent as if each individual publication, patent application, and technology was specifically and individually indicated to be incorporated by reference.

The above-described embodiments have been described as representative examples, but it will be apparent to those skilled in the art that many modifications and substitutions are possible within the spirit and scope of the present disclosure. Therefore, the present invention should not be construed as being limited by the above-described embodiments, and various modifications and alterations are possible without departing from the scope of the claims.

100 Estimation system 10, 10-1 Estimation device 11, 11-1 Landslide disaster occurrence estimation unit 12 Temporary storage unit 13 Structure damage estimation unit 20 Display device 111, 111-1 Input unit 112, 112-1 Occurrence location number storage unit 113, 113-1 Occurrence location number extraction unit 131 Average structure number storage unit 132 Damage rate storage unit 133 Structure number estimation unit 134 Damage estimation unit 135 Output unit 301 Computer 310 Processor 320 ROM
330 RAM
340 Storage 350 Input unit 360 Output unit 370 Communication I/F
380 Bus

Claims (7)

an average structure number storage unit that stores an average structure number, which is an average value of the number of structures provided in each of one or more estimated damage areas included in a predetermined geographical range;
a damage rate storage unit that stores a damage rate within the predetermined range , which is the probability that the structure will be damaged in the event of a disaster;
a structure number estimation unit that estimates an estimated number of structures, which is the number of structures located in the estimated damage areas in which the disaster is estimated to occur within the specified range, based on the number of occurrence locations, which is the number of estimated damage areas in which the disaster is estimated to occur, among the one or more estimated damage areas included in the specified range , and the average number of structures;
a damage estimation unit that estimates the number of damaged structures, which is the number of structures that will be damaged within the predetermined range, based on the estimated number of structures and the damage rate;
An estimation device comprising: an output unit that outputs the number of damages. the average structure number storage unit stores an average number of structures for each disaster type, which is an average value within the predetermined range of the number of structures provided in each of one or more estimated damage areas defined for each disaster type;
the damage rate storage unit stores the damage rate within the predetermined range for each disaster type ,
the structure number estimation unit estimates the estimated number of structures for each disaster type in the predetermined range based on the number of occurrence locations for each disaster type in the predetermined range and the average number of structures for each disaster type;
The estimation device according to claim 1 , wherein the damage estimation unit estimates the number of damages for each disaster type based on the estimated number of structures for each disaster type and the damage rate for each disaster type. The disaster is a landslide,
an occurrence location number storage unit that stores the number of locations where the landslide disaster has occurred, corresponding to the wetness state information that indicates the wetness state of the soil within the predetermined range;
an occurrence location number extraction unit that extracts the number of occurrence locations of the landslide disaster corresponding to the wet state information in the predetermined range,
The estimation device according to claim 1 , wherein the structure number estimation unit estimates the estimated number of structures based on the extracted number of occurrence locations and the average number of structures. The average structure number storage unit stores the average structure number for each landslide disaster type, which is the average number of structures provided in each of one or more estimated damage areas defined for each landslide disaster type;
The occurrence location number storage unit stores the occurrence location number for each of the landslide disaster types,
the occurrence location number extraction unit extracts the number of occurrence locations for each of the landslide disaster types;
The estimation device according to claim 3, wherein the structure number estimation unit estimates the estimated number of structures for each landslide disaster type based on the number of occurrence locations for each landslide disaster type and the average number of structures for each landslide disaster type. An estimation system including an estimation device and a display device,
The estimation device includes:
an average structure number storage unit that stores an average structure number, which is an average value of the number of structures provided in each of one or more estimated damage areas included in a predetermined geographical range;
a damage rate storage unit that stores a damage rate within the predetermined range , which is the probability that the structure will be damaged in the event of a disaster;
a structure number estimation unit that estimates an estimated number of structures, which is the number of structures located in the estimated damage areas in which the disaster is estimated to occur within the specified range, based on the number of occurrence locations, which is the number of estimated damage areas in which the disaster is estimated to occur, among the one or more estimated damage areas included in the specified range , and the average number of structures;
a damage estimation unit that estimates the number of damaged structures, which is the number of structures that will be damaged within the predetermined range, based on the estimated number of structures and the damage rate;
an output unit that outputs the number of damages,
The display device displays the number of damages.
Estimation system. An estimation method performed by an estimation device including: an average structure number storage unit that stores an average number of structures, which is an average value within a predetermined geographical range of the number of structures provided in each of one or more assumed damage areas included in the predetermined range ; and a damage rate storage unit that stores a damage rate within the predetermined range , which is a probability that the structures will be damaged in the event of a disaster,
a step of estimating an estimated number of structures, which is the number of structures located in the estimated damage area in which the disaster is estimated to occur within the specified range, based on the number of occurrence locations, which is the number of estimated damage areas in which the disaster is estimated to occur, among the one or more estimated damage areas included in the specified range , and the average number of structures;
a step of estimating the number of damages, which is the number of structures that will be damaged within the predetermined range, based on the estimated number of structures and the damage rate;
and outputting the number of damages. A program for causing a computer to function as the estimation device described in any one of claims 1 to 4.