KR20190113289A - Automation system for disaster damage investigation - Google Patents

Abstract

The present invention relates to an automatic disaster damage investigating system using a high-resolution satellite image, which comprises: a database (120) including a GIS DB (105), an image DB (110), and a damage DB (115); an automatic damage investigating system main body (125) of a system interface; and an automatic damage investigating module (130) of a typhoon or heavy snow for each natural disaster.

Description

Disaster Damage Survey Automation System Using High Resolution Satellite Imagery {AUTOMATION SYSTEM FOR DISASTER DAMAGE INVESTIGATION}

The present invention relates to a satellite-based disaster damage automation system for investigation of natural disaster damage, more specifically, using the satellite image, GIS thematic map, recovery unit price to grasp the rough damage size before the investigation and establish a quick recovery plan It is about disaster disaster investigation automation system that investigates natural disaster damages and utilizes high-resolution satellite image to detect natural disasters so that it can be used as a basis for selecting basic data and field investigation priority area.

Disasters or disasters are mainly caused by abnormal natural phenomena or anthropogenic accidents, and are causing great social and economic damage. Disaster causes of abnormal natural phenomena include storms, heavy rain, heavy snow, floods, tsunamis, and earthquakes. Other causes of artificial disasters include fire, explosion, release of radioactive materials, car accidents, ship sinking, and aircraft distress. Etc.

The development of information and communication technology, the proliferation of mobile terminals, and the proliferation of Internet services are causing a surge in data produced in proportion to the exploding Internet population. There is a growing expectation to create a lot of value through the collection and analysis of various data, but it is not easy to selectively search for and use information related to disasters.

National Disaster Management System (NDMS) is a nationwide comprehensive information system that supports work in each stage of disaster management, including prevention, preparedness, response, and recovery. Disaster information sharing system that links and utilizes disaster information of related organizations such as control station, and 119 firefighting site response system that supports disaster sites are in operation.

In order to upgrade the functions and services of the national disaster management system to the next level, for example, the National Security Agency has expanded the disaster response system built around central administrative agencies and cities and provinces to major cities, counties, and districts. It is expanding the scope of the nationwide disaster management network that has been established.

In order to upgrade the national disaster management program, efficient disaster area damage investigation should be preceded. However, most current damage investigations require a lot of manpower and time, depending on manual labor, which not only lacks promptness and objectivity in the damage investigation process, Due to the lack of standardized on-site survey equipment and extensive damage areas, it is difficult to calculate the magnitude of damage and the amount of damage. Therefore, the investigator has to rely on the discretion of the investigator. Can be generated.

Since there is no standardized survey process and equipment for each local government that conducts on-site survey, it is difficult to derive the result items and prepare the basis for calculation. Because it is necessary to proceed to the process, not only a lot of manpower and time are wasted, but there is also a risk of error.

As a prior art, the Republic of Korea Patent No. 10-0748528 (in real-time automatic update system for disaster damage investigation using wireless communication and Web-GS) and its operation method collects the cause information, damage image, video, and voice information to the server. Establish a field equipment stage composed of various equipments for transmission, and transmit damage investigation information acquired through the field equipment stages to each server stage to automatically process in real time in the form of information suitable for a predetermined type, Not only posting on the bulletin board but also processing the standardized disaster log form to create web pages, and register damage points and their attributes on the Web-GIS through coordinates of the point of occurrence. It is possible to establish quick recovery measures by linking GIS to search and confirm various information. And to support the progress of the re-established policy, and help by posting a variety of information on the investigation of the disaster the general Internet by ensuring the transparency of emergency measures and disaster recovery policies to enhance citizen confidence.

Korean Patent Laid-Open Publication No. 10-2014-32205 discloses a disaster damage investigation system based on a mobile (eg, a smartphone) associated with a National Disaster Management System (NDMS) and a method thereof, including an investigator terminal, Provides damage investigation information of the disaster area collected through the investigator terminal, and receives and stores the damage investigation information provided from the mobile server and the mobile server for storing and managing the additional information included in the damage investigation information in the additional information DB Mobile-based disaster prevention investigation system including a relay DB and a disaster management server that periodically verifies the disaster register of the damage investigation information stored in the relay DB through a scheduler and stores and manages the verified damage investigation information in the main DB. To provide.

Therefore, natural disasters such as typhoons, snowfall, and landslides are increasing worldwide due to extreme weather events.However, the characteristics of such natural disasters occur suddenly in a wide range of areas, and therefore, effective damage survey methods are required. have. In Korea, local governments dispatch civil servants to conduct damage surveys through field surveys to find out the scale of natural disasters.

As the area affected by such natural disaster is wide, there is a problem that it takes a lot of time when the damage investigation due to the lack of manpower of local governments. In addition, the longer the damage investigation time causes a variety of problems, such as causing secondary damage due to incomplete emergency recovery and causing inconvenience to local residents. Therefore, it is urgent to develop a system that supports the investigation of damages because it is difficult to supplement the personnel of local government officials.

The prior art is a method of calculating the damage range by fusing the satellite image and the map of the region, but the present inventors considering this can effectively recover by measuring the damage range of the affected area by the satellite measurement photo, and conveying the recovery priority. Developed an automated system.

The present invention has been invented in view of the above circumstances, and it is possible to quickly establish a recovery plan and to prioritize field investigation by selecting the damage area, the damage amount and the field investigation priority by using satellite image, the GIS theme map, and the unit price. The purpose is to provide an automatic disaster damage investigation system that can be used as evidence, and especially to automate natural disaster damage detection using high resolution satellite images.

In order to achieve the above object, the present invention, in the satellite-based disaster damage investigation automated system for natural disaster damage investigation in a networkable computer system server with the Internet network, the continuous map, numerical shape, land cover, administrative area map A database 120 including a GIS DB 105, an image DB 110 storing satellite images Kompsat-2 and Landsat-8, and a damage DB 115 storing a recovery unit price; An automatic damage investigation system 125 for a system interface including an image preprocessing program, a file management function, a damage information extraction function, and other functions; The satellite-based disaster damage investigation automation system main body 125, characterized in that it comprises a damage investigation automation module 130 of natural storms or heavy snow applied to each.

 Another specific feature of the present invention is a GIS DB (105) and satellite image (Kompsat-2, Landsat-8) for storing a continuous map, numerical shape, land cover, administrative area map in a computer system server capable of network with the Internet network A database 120 including an image DB 110 for storing the damage data and a damage amount DB 115 for storing the recovery unit price; An automatic damage investigation system 125 for a system interface including an image preprocessing program, a file management function, a damage information extraction function, and other functions; A disaster investigation automation module 130 for a typhoon or heavy snowfall by natural disaster to be applied to the satellite-based disaster damage investigation automation system main body 125; For example, the computer system server receives the before and after image of the high resolution satellite Kompsat-2 from the Aerospace Research Institute site and stores the image before and after the damage of the high resolution satellite Kompsat-2 as the image DB 110 of the database 120. ; Pre-processing satellite images before and after Kompsat-2 damage in the image DB 110 through an image preprocessing program in the main body 125 of the damage investigation automation system; After the pre-processing Kompsat-2 damage before and after satellite image correction by the pre-processing program linkage, and inputs to the damage investigation automation module 130 through the file management function of the damage investigation automation system main body 125; In order to apply the damage information extraction function to the input image, the range setting button in the damage investigation automation module 130 is selected to select a range to perform the change detection, and then the damage detection is performed by clicking the automatic detection execution button; Damage detection is applied to the R, G, B and NIR bands of Kompsat-2 satellite images before and after damage by applying CVA, an algorithm that can efficiently detect the magnitude and pattern of changes in spectroscopic characteristics in the image, and then apply the DNDVI algorithm. The area where vegetation increased in the post-damage image rather than the pre-damage image is considered as not the damaged region, and the final damage area is calculated.

According to the present invention, when the damage amount calculation button is clicked in the damage investigation automation module 130 to apply the damage information extraction function to the damage area, the continuous area map, the digital topographic map, and the forest map network in the damage area GIS DB 105 are clicked. Nesting and calculating nested GIS DB items; The GIS DB 105 and the damage amount DB 115 calculated as overlapping items may be linked to indicate damage amount calculation on the damage investigation automation module.

In addition, it may be configured to unify the coordinate system of the pre- and post-damage image coordinate system and the overall data, and to unify the satellite image and the general data therefrom.

As described above, according to the present invention, it is possible to increase the efficiency of damage investigation work by using new types of natural disaster damage information such as satellite field, GIS thematic map, and the unit cost of restoration to select the field priority.

The present invention, by providing a quantitative damage investigation support system to provide a disaster management work reduction and disaster management capacity reinforcement, it can provide a convenience to the public by supporting a quick damage investigation.

According to the present invention, it is possible to calculate the damage area for the disaster area and to calculate the rough damage amount according to the damage area, and to perform the rough damage information calculation such as providing other damage information such as the field investigation priority.

1 is an overall configuration diagram illustrating a satellite-based disaster damage automation system for investigation of natural disaster damage according to an embodiment of the present invention,
2 is an exemplary view showing an image of a damage area and a damage amount by performing a typhoon damage detection using a high resolution satellite image according to an embodiment of the present invention;
3 is a detailed flowchart illustrating a damage area and a damage amount screen of a high-resolution typhoon shown in FIG. 2;
4 is a diagram showing the size and direction of the CVA (Change Vector Analysis) and the change sector (3 bands),
5 is a diagram illustrating reflection characteristics of an object according to a wavelength band.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is an overall configuration diagram illustrating a satellite-based disaster damage investigation automated system for natural disaster damage investigation according to an embodiment of the present invention, the present invention is a satellite-based disaster damage investigation automation system for natural disaster damage investigation, It provides natural disaster damage area, amount of damage and field investigation priority by using satellite image, GIS theme map, and recovery unit price. It is an automated disaster investigation system for disaster investigation.

The present invention comprises a database 120, a damage investigation automation system main body 125 and a damage investigation automation module 130 as a computer system server capable of network with the Internet network, in the database 120, continuous map, numerical diagram , GIS database (DB) 105 for storing land cover, administrative area map, image DB 110 for storing satellite images (Kompsat-2, Landsat-8), and damage DB for storing recovery unit price 115 It includes.

The damage investigation automation system main body 125 of the system interface includes an image preprocessing program, a file management function unit, a damage information extracting unit, and other functions, and the natural disaster-specific (typhoon / snowfall) damage to be applied to the damage investigation automation system body. It is configured to include a survey automation module 130.

The damage investigation automation system main body 125 supports orthodontic correction of satellite images and generation of a DSM (DiskStation Manager) by performing an association with a commercial preprocessing system through an image preprocessing program. The damage investigation automation system main body 125 supports file search or input / output management and metadata management of a satellite image, system result file storage and loading through a file management function.

The damage investigation automation system main body 125 supports manual detection and automatic detection, damage calculation, and conversion of system results to KML (Keyhole Markup Language) file through typhoon damage detection using high resolution satellite image through damage information extraction function. Can be.

The KML can be used for modeling and expressing terrain information in Google Earth, Google Map, etc., and was developed by Google. The present invention is used to search and utilize the results of the automatic damage calculation system in Google Earth. .

Therefore, the reason for using KML file as the result conversion is the result of this system in Google Earth, which is used by many people, and anyone can easily search the damage area, intellectual and cover information.

In the present invention, through the damage information extraction function unit of the damage investigation automation system 125 through the typhoon damage detection using low- and medium-resolution satellite image to provide detailed information about the automatic detection, field investigation priority selection, intellectual information and land cover information It can support the conversion of system output into KML files.

In addition, through the damage information extraction function of the damage investigation automation system 125, snowfall damage detection using low and low resolution satellite images provides automatic detection, detailing priorities for field investigation, intellectual information and land cover information, It can support conversion of system output to KML file.

The damage investigation automation system main body 125 is divided into map operation and measurement tools in other functions, while in the damage investigation automation module 130, as well as typhoons / snowfalls as natural disasters, landslides, forest fires, and earthquakes / tsunamis / droughts. And the like.

As described above, using the new type of damage scale information generated by superimposing satellite image and GIS thematic map through the disaster damage investigation automation system of the present invention, when roughly estimating damage size and prioritizing field investigation prior to the damage investigation, It can be used as evidence.

Reference is made to FIG. 2 and FIG. 3 based on the system configuration shown in FIG. 1 and the preferred embodiment of the present invention will be described in detail. The scope of the present invention is not limited to the preferred embodiment, and is easy to those skilled in the art. If the invention can be modified to the same, the technical spirit is the same all puts it belongs to the scope of the present invention.

Therefore, the present invention can provide a disaster damage reduction and disaster management capacity reinforcement by establishing a rapid damage investigation, it can provide the convenience of the public by providing disaster-related information in connection with public services.

The database 120 of a networkable computer system server with an Internet network (not shown) constructs and manages various types of information about a disaster area in each independent database DB.

The GIS DB 105 stores GIS thematic maps such as continuous maps, digital topographic maps, land cover maps, and administrative district maps. In other words, it is used to calculate the area of disaster damage, to prioritize site investigation, and to provide detailed information.

For example, the image DB 110 stores images of Kompsat-2, Kompsat-3, and Landsat-8, and is collected and constructed when images of the disaster-affected areas are taken. That is, damage area is calculated by applying change detection algorithm through satellite image.

Here, the change detection algorithm may use change vector analysis (CVA), difference normalized difference vegetation index (DNDVI), normalized difference snow index (NDSI), and the like.

The damage amount DB 115 of the database 120 stores the restoration unit price information contained in the restoration plan establishment instructions, that is, it is used to calculate the damage amount during the typhoon damage detection using high resolution satellite image through the restoration unit unit information. .

2 is a result of performing damage area calculation and damage amount calculation during typhoon damage detection using high resolution satellite image, before damage list, after damage list, total damage of automatic detection, detail change, and before and after damage map of Icheon-si, Gyeonggi-do And the like are displayed.

FIG. 3 is a detailed flowchart illustrating the damage area and the amount of damage screen of the high resolution typhoon shown in FIG. 2, and FIG. 4 is a diagram illustrating the size and direction of the CVA (Change Vector Analysis) and the change sector (3 bands). 5 is a diagram illustrating reflection characteristics of an object according to a wavelength band.

Referring to the flow of high-resolution typhoon damage detection based on Figures 1 to 5, for example, the computer system server of the present invention to receive before and after the damage of the high-resolution satellite Kompsat-2 from the Aerospace Research Institute site through the Internet network not shown As can be seen, it stores the before and after damage of the high resolution satellite Kompsat-2 to the image DB 110 of the database 120.

The satellite image before and after the Kompsat-2 damage in the image DB 110 may be preprocessed through the image preprocessing program in the main body 125 of the damage investigation automation system. At this time, the unified before and after image coordinate system and the coordinate system of the general data can be unified, and the satellite image and the general data can be unified therefrom.

Thus, after the pre-processing Kompsat-2 damage before and after satellite image correction by preprocessing program linkage, the damage investigation automation system through the file management function of the main body 125 is input to the damage investigation automation module 130.

Therefore, in order to apply the damage information extraction function to the input image, the range setting button in the damage investigation automation module 130 is selected to select a range to perform the change detection, and then the damage detection is performed by clicking the automatic detection execution button. can do.

Therefore, damage detection is applied to the R, G, B, NIR bands of Kompsat-2 satellite image before and after damage, and the DNDVI algorithm is applied to CVA, an algorithm that can efficiently detect the magnitude and pattern of changes in spectroscopic characteristics in the image. As a result, the area where vegetation increased in the post-damage image is considered to be not the damaged region, and the final damage area is calculated.

To describe the change detection algorithm, CVA (Change Vector Analysis) is one of the representative unsupervised change detection techniques that estimates the size and direction of the change area by using the size and direction between the pixel vectors of two different time frames. .

For example, changes in land cause spectroscopic characteristics to change, and CVA is a method of analyzing vectors that describe magnitude and direction of the changed spectroscopic characteristics. The following values are ignored for areas that have not changed, and above thresholds can be detected as changed.

와

는 각각 k밴드의 Date2와 Date1의 화소의 밝기값(식)Change size of each pixel

Wow

Are the brightness values of the pixels of Date2 and Date1 of k band, respectively.

이다.

to be.

The direction of change can be represented by a sector, which explains whether the change is positive or negative.

으로 표현할 수 있으며, 만약 3개의 밴드가 사용되었다면 섹터는 8 개로 분류가 가능하다. 섹터의 가능한 형태(Type)는

으로 표현 할 수 있으며, 만약 3개의 밴드가 사용되었다면 섹터는 8개로 분류가 가능하다(도 4 참조).Possible types of sectors are

If three bands are used, eight sectors can be classified. Possible types of sectors are

If three bands are used, sectors can be classified into eight (see FIG. 4).

Unlike conventional change detection, CVA change detection can detect the propensity of change along with the magnitude of change, and can often process and analyze multiple multispectral input data, and often occurs in multi-date classification. Spatial and spectroscopic errors can be avoided.

The change analysis and labeling can be easily performed through the combination of the vector calculation and the change image for the multi-dimensional change. Therefore, CVA is an algorithm that can grasp changes to the same point of satellite image before and after damage.

For example, the Normalized Difference Vegetation Index (NDVI), which represents the quality of forest greenery, is a quantitative representation of the distribution of forests. Values indicate snow, rock, water rubs and the like.

Non- vegetation areas are expressed with values of zero or less, and the more vegetation distribution, the closer to one. The normal vegetation index can be calculated using the properties of the vegetation reflectance in the visible region is low in the visible region and high in the near infrared region, where NIR is the reflectance in the near infrared region, RED represents the reflectance in the red region of the visible region.

Differenced NDVI (DNDVI) can be used to estimate vegetation damage due to disaster through the difference in NDVI measured at different times.

Therefore, DNDVI applies the DNDVI which can identify the time series difference of NDVI which can quantitatively determine the degree of vegetation on the satellite image before and after the damage.

The Normalized Difference Snow Index (NDSI), developed by Hall et al., Can be used to analyze snowfall conditions in the northeastern United States and to assess mapping accuracy.

m)에서는 반사율이 높고, 단파장적외선인 SWIR(1-3

m) 영역에서는 반사율이 낮은 눈의 분광특성을 이용하여 표현 가능(식)NDSI is called the snow index and is generally used for snow cover detection through low and medium resolution satellite images. NDSI is in the visible region (0.4-0.7

m) has high reflectivity and short wavelength infrared SWIR (1-3)

m) can be expressed by using spectral characteristics of the eye with low reflectance (expression)

NDSI values are aimed at detecting snow and ice zones and are used to distinguish snow from vegetation, land and most clouds. Since NDSI cannot distinguish between snow and snow covered ice regions, snow and snow covered ice regions are identified by snow.

In the case of snow and clouds, the spectroscopic characteristics show very similar reflectance in the visible and near-infrared region, but in the short-infrared region, most clouds show very high reflectivity, whereas snow has very low reflectivity.

Snow, vegetation, land and the like also have different reflection characteristics (see FIG. 5). Thus, the snow can be distinguished from other objects by utilizing different reflection characteristics such as snow, clouds, vegetation, and land. Therefore, NDSI is an algorithm that can clearly distinguish snow from other objects such as vegetation, land and clouds.

In the disaster damage investigation automation system of the present invention, if the damage calculation button is clicked in the damage investigation automation module 130 to apply the damage information extraction function to the damage area, the continuous area map and the digital topographic map in the GIS DB 105 are applied to the damage area. In addition, nested network diagrams can be nested and nested GIS DB items can be calculated.

Therefore, the damage amount may be calculated as shown in FIG. 2 on the damage investigation automation module by linking the GIS DB 105 and the damage amount DB 115 calculated as overlapping items.

As described above, the high resolution typhoon algorithm is applied to the CVA algorithm in the satellite image before and after the damage. For example, in the case of the threshold value, 100 can be shown to be the most suitable as a result of the pilot application in four regions. The final damage area can be calculated by applying DNDVI to the damage area calculated by applying the threshold value of 100 to the CVA algorithm and excluding areas where vegetation increased in the post-damage image compared to the pre-damage image.

According to the present invention, a new type of damage scale information generated by superimposing satellite images and GIS thematic maps can be used as a basis for estimating damage size before the damage investigation and selecting priorities for field investigation.

Therefore, if the disaster prevention investigation automation system of the present invention is used, it contributes to secondary damage analysis and IT-based disaster prevention work innovation through computerized damage scale data, and establish effective disaster prevention DB by linking the electronic disaster register of computerized damage information. I can prepare a framework.

Disaster damage investigation automation system of the present invention provides a disaster damage investigation and disaster management capacity reinforcement by establishing a rapid damage investigation, and provides disaster-related information in connection with public services to improve the convenience of the people. It will be able to roughly calculate the damage size of the disaster area and scientific damage amount according to the political damage size, and perform quantitative calculation of other damage locations, owners and land use.

 The disaster damage investigation automation system of the present invention contributes to decision support such as an emergency response system, a disaster recovery plan, and the establishment of future preventive measures. More accurate and efficient damage investigations will be possible for a wide range of affected areas, and contribute to the improvement of national disaster prevention capabilities, such as support for field investigations and the establishment of early recovery plans.

Disaster damage investigation automation system of the present invention has been described in the above embodiments, but can be carried out in various ways without departing from the spirit of the present invention, the contents of which are included in the rights of the present invention It will be natural.

105: GIS DB
110: Image DB
115: damage DB
120: database
125: damage investigation automation system
130: damage investigation automation module

Claims (3)

GIS DB 105 for storing continuous maps, numerical maps, land cover maps, administrative maps, and image DBs 110 for storing satellite images (Kompsat-2, Landsat-8) in network-enabled computer system servers with the Internet network. And a database 120 including a damage DB 115 storing a repair unit cost. An automatic damage investigation system 125 for a system interface including an image preprocessing program, a file management function, a damage information extraction function, and other functions; It is configured to include a disaster investigation automation module 130 of the typhoon or heavy snow for each natural disaster to be applied to the satellite-based disaster damage investigation automation system main body 125;
The disaster damage investigation automation system main body 125 is intended to support orthodontic correction and satellite station manager (DSM) generation for satellite images by performing linkage with a commercial preprocessing system through an image preprocessing program.
For example, the computer system server receives the before and after image of the high resolution satellite Kompsat-2 from the Aerospace Research Institute site and stores the image before and after the damage of the high resolution satellite Kompsat-2 as the image DB 110 of the database 120. ;
Performing preprocessing of the satellite image before and after the Kompsat-2 damage in the image DB 110 through an image preprocessing program in the main body 125 of the damage investigation automation system;
After the preprocessing, Kompsat-2 damages satellite images before and after the image correction by preprocessing program linkage, and converts them into KML (Keyhole Markup Language) files of the system result through the damage information extraction function of the main body of the damage investigation automation system 125. Inputting the damage investigation automation module 130 through the file management function of the damage investigation automation system main body 125;
In order to apply the damage information extraction function to the input image, the range setting button in the damage investigation automation module 130 is selected to select a range to perform the change detection, and then the damage detection is performed by clicking the automatic detection execution button;
Damage detection calculates the damage area by applying the change detection algorithm through satellite image. The change detection algorithm estimates the size and direction of the change area by using the size and direction between pixel vectors of two different time periods. The unsupervised change detection method, CVA (Change Vector Analysis), DNDVI (Differenced Normalized Difference Vegetation Index), and NDSI (Normalized Differenced Snow Index) must be used together.
First of all, if the land changes, the spectroscopic characteristics will change, so we use CVA, which is a method of analyzing vectors that explain the magnitude and direction of the changed spectroscopic characteristics.
To quantitatively analyze the distribution of forests, we use DNDVI, a normal vegetation index that represents the quality of forests.
In order to detect snow and freezing areas, NDSI is used together to distinguish clearly from other objects such as vegetation area, land and clouds.
CVA, an algorithm for detecting the magnitude and pattern of changes in spectroscopic characteristics, is applied to the R, G, B, and NIR bands of Kompsat-2 satellite images before and after damage, and then applied to the DNDVI algorithm to prevent damage. Automated disaster investigation investigation system using high-resolution satellite imagery, which calculates the final damage area, considering that the area where vegetation has increased afterwards is not the damage area. The method of claim 1,
When the damage amount calculation button is clicked in the damage investigation automation module 130 to apply the damage information extraction function to the damage area, the continuous area of the GIS DB 105 is overlaid on the damage area, and the network map is overlaid. Calculating the GIS DB items;
Disaster investigation investigation automation system using a high-resolution satellite image, characterized in that it further comprises the damage calculation calculation on the damage investigation automation module by linking the GIS DB (105) and the damage amount DB (115) calculated as an overlap item. The method according to claim 1 or 2,
Automated disaster investigation investigation system using high resolution satellite imagery, which is unified before and after image coordinate system and coordinate system of general data, and from this, satellite image and general data are unified.

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