KR102315972B1 - Disaster site reconstruction and cause analysis method and system using drones - Google Patents

Abstract

Disclosed are a method and a system for disaster site reconstruction and cause analysis using a drone, which reconstruct a target site through 3D spatial information analysis on the basis of an accident site image acquired from a drone device flying over a disaster accident site, store a site situation as a recordable and manageable tangible data if necessary, and can analyze an accident cause on the basis of the recordable and manageable tangible data. The system of the present invention comprises: a drone device for acquiring disaster accident site information by flying over a disaster accident site to photograph the same, and transmitting the same to a control device; a control device for controlling the flight of the drone device and transmitting the disaster accident site information received from the drone device to an analysis device; and an analysis device for reconstructing a disaster site by analyzing the disaster accident site information received from the control device, and analyzing an accident cause on the basis of the reconstructed disaster site.

Description

Disaster site reconstruction and cause analysis method and system using drones

The present invention relates to a disaster site reconstruction and cause analysis method and system using a drone, and more particularly, to a target site through 3D spatial information analysis based on an accident scene image obtained from a drone device flying over a disaster accident site. It relates to a disaster site reconstruction and cause analysis method and system using drones, which, if necessary, store the on-site situation as a type of data that can be recorded and managed, and allow analysis of the cause of an accident based on these data. .

An effective field investigation in the field of natural disasters means an investigation that is superior to the existing methods in obtaining objective and scientific information. However, in practice, there are cases in which data that must be acquired cannot be acquired. For example, when measuring slope and height in a large slope disaster area, even an expert may feel confused about where to measure the height and where to measure the slope.

Even though the data must be acquired at the actual site, if it is impossible to obtain it due to the conditions of the site, an unmanned aerial vehicle (UAV, or drone) can be used.

By using drones, basic data for slope disaster risk assessment can be obtained, but it is necessary to use a lot of other information to make an accurate slope disaster risk assessment.

Therefore, there is a need for a technology that can reconstruct the disaster/accident site where actual damage occurred only with basic data.

Republic of Korea Patent Publication No. 10-2019-0037212 (published on April 5, 2019) describes a disaster site exploration system using a drone.

An object of the present invention for achieving the above-described technical requirements is to reconstruct the target site through 3D spatial information analysis based on the accident scene image acquired from the drone device flying at the disaster accident site, and to analyze the site situation as necessary It is to provide a method and system for disaster site reconstruction and cause analysis using drones, which are stored as tangible data that can be recorded and managed, and the cause of an accident can be analyzed based on these data.

Disaster site reconstruction and cause analysis system according to an embodiment of the present invention for achieving the above object, a drone device for acquiring disaster site information by shooting while flying at the disaster site and transmitting it to a control device; a control device for controlling the flight of the drone device and transmitting disaster accident site information received from the drone device to the analysis device; and an analysis device for reconstructing the disaster site by analyzing the disaster site information received from the control device, and analyzing the cause of the accident based on the reconstructed disaster site.

In addition, the drone device, while flying at the disaster site, by executing an outdoor survey including inclination angle investigation, slope height investigation, natural slope longitudinal cross-sectional shape investigation, slope valley investigation, upper external force and surrounding environment investigation, the disaster accident site information can be obtained.

In addition, the inclination angle investigation may measure the heights of the lowermost and uppermost vertices of the longitudinal section, and the moving distance from the starting point of the inclination to the uppermost point.

In addition, the inclination angle investigation is performed by setting the altitude of the drone device to 0 m on the ground where the inclination starts and vertically ascending to the top vertex to measure the flying altitude value, and the gimbal and camera mounted on the drone device are horizontal. In this state, the height value (H) of the top vertex is recorded when the focal length displayed on the image and the target match, and then the inclination angle can be calculated using a trigonometric function using the horizontally moved distance value (D) to the top vertex. have.

In addition, the inclination height investigation may measure the height value (H) of the drone device flying vertically up to the top vertex by setting the altitude of the drone device to 0 m on the ground where the inclination starts.

In addition, the longitudinal cross-sectional shape investigation of the natural slope is investigated using a visual or topographic map of the shape viewed from the side of the steep slope, and is divided into circular, straight, concave, and complex depending on the longitudinal shape, and descending according to the transverse shape, It is divided into parallel type, ascending type, and complex type, and it is possible to acquire transverse and longitudinal shapes from the side and various angles by approaching steep slopes, fall danger zones, and dense vegetation areas, which are difficult for investigators to access due to slope collapse.

In addition, in the investigation of the slope valley, the distance between the extension and width of the valley adjacent to the start point and the end point of the steep slope is investigated, but the distance to the target point and location is measured using equipment in principle, and the approach and movement of the surveyor are measured In cases where this is not possible, it can be investigated using a topographic map (a numerical topographic map).

In addition, the slope valley survey is based on the real-time image information received through the flight of the drone device to determine the location of the valley extension adjacent to the start and end points of the valley, calculate the flight path and altitude for each section, and then By fixing the direction of the camera at a right angle (90) to the ground, the length of the valley extension can be obtained by using the log value that flies along the path from the bottom to the top of the valley extension close to the horizontal plane.

In addition, in the investigation of the upper external force and the surrounding environment, the existence of houses, pylons, farmland, railways, and roads is checked on the upper part of the steep slope, and the flight zone and the progress route are set on the electronic map for the area that needs to be investigated, so that the drone device is Perform automatic flight, and while the drone device flies according to a predetermined route, the image of the upper external force from the drone device can be transmitted in real time to the control device so that the investigator can check the upper external force of the field in real time.

In addition, the analysis device may reconstruct the disaster site, including the orthoimage production, damage factor analysis, and evaluation table preparation process according to a method of deriving objective and quantitative investigation results by analyzing the disaster site information.

In addition, the analysis device, based on the disaster accident site information obtained from the drone device, evaluates the evaluation items that can quantitatively investigate and analyze the slope collapse site through 3D image processing, among all 17 types of inclination angle, slope height, and end. Quantitative analysis can be performed by classifying into 11 categories related to shape, transverse shape, ground deformation and cracks, slope valley, upper external force, collapse and loss history, surrounding environment, and distance between steep slopes and adjacent facilities.

In addition, the analysis of the inclination angle may measure the angle between the horizontal plane and the line connecting the lower vertex and the uppermost vertex by a method of measuring a cross section in which an inclination occurs in the three-dimensional point cloud and mesh data.

In addition, the analysis of the slope height can be measured as the height connected vertically from the road to the top of the steep slope based on the horizontal plane by extracting the cross section of the investigation target from the three-dimensional point cloud.

In addition, in the analysis of the longitudinal shape of the steep slope, contour lines are extracted at intervals of 5 m using the result of the numerical surface model through image registration processing, and then the orthographic image and the contour line are superimposed using the ESRI ArcGIS program. The longitudinal shape of the point can be analyzed.

In addition, as for the longitudinal shape of the steep slope, the shape of the contour analyzed through image processing is convex by comparing and examining the results of the 3D point cloud and the video in which the drone device shoots the investigation point in the sky above the investigation site from various angles, It can be analyzed as one of straight, concave, and complex.

In addition, the analysis of the transverse shape is performed in the same way as the analysis of the inclination angle with respect to the transverse shape of the natural slope, but by extracting the cross section of the investigation target site to analyze the transverse shape, and a drone image taken from multiple angles of the target point As a result of analysis using the shape information expressed on the 3D point cloud, the shape of the steep slope can be analyzed as one of descending type, parallel type, rising type, and complex type.

In addition, in the analysis of the slope valley, with respect to the extension and width of the slope valley, the results are analyzed for the valleys adjacent to the starting point and the ending point of the steep slope where the slope damage has occurred, but the starting point and the ending point of the slope valley on the three-dimensional point cloud The results are analyzed by measuring the length of the slope, and the extension length of the slope valley is a method of measuring the distance from the top to the bottom where the valley starts. , the result can be analyzed as a value that connects all the lengths between points.

In addition, in the analysis of the upper external force, factors affecting the upper external force of the steep slope include houses, pylons, farmland, railways, and mounds, and the analysis of the upper external force includes drone images and image processing processes taken in the field. The presence, location, and area of the upper external force can be analyzed by using the orthographic image and the three-dimensional point cloud generated through the process.

In addition, in the analysis of the collapse and loss history, the traces of collapse, rockfall, and surface layer loss are investigated in the steep slope and the damage scale is analyzed accordingly, but within a certain distance from the point where the slope loss damage occurred in the steep slope. It is possible to compare and analyze the images before and after the slope loss damage at the location where they are located.

In addition, the analysis of the distance between the steep slope and the adjacent facility may determine whether or not there is a facility in the damaged area when the steep slope collapses, and analyze the distance between the steep slope and the adjacent facility.

On the other hand, the disaster site reconstruction and cause analysis method according to an embodiment of the present invention for achieving the above object includes the steps of (a) a drone device photographing a disaster accident site to acquire disaster accident site information and transmitting it to a control device ; (b) transmitting, by the control device, the received disaster accident site information to an analysis device; (c) reconstructing the disaster site by analyzing the disaster site information by the analysis device; and (d) analyzing, by the analysis device, the cause of the accident based on the reconstructed disaster site.

In addition, in step (a), the drone device performs field surveys including inclination angle survey, inclination height survey, natural slope longitudinal cross-sectional shape survey, slope valley survey, upper external force and surrounding environment survey to obtain disaster accident site information can be obtained

In addition, the inclination angle investigation may measure the heights of the lowermost and uppermost vertices of the longitudinal section, and the moving distance from the starting point of the inclination to the uppermost point.

In addition, the inclination angle investigation is performed by setting the altitude of the drone device to 0 m on the ground where the inclination starts and vertically ascending to the top vertex to measure the flying altitude value, and the gimbal and camera mounted on the drone device are horizontal. In this state, the height value (H) of the top vertex is recorded when the focal length displayed on the image and the target match, and then the inclination angle can be calculated using a trigonometric function using the horizontally moved distance value (D) to the top vertex. have.

In addition, the inclination height investigation may measure the height value (H) of the drone device flying vertically up to the top vertex by setting the altitude of the drone device to 0 m on the ground where the inclination starts.

In addition, the longitudinal cross-sectional shape investigation of the natural slope is investigated using a visual or topographic map of the shape viewed from the side of the steep slope, and is divided into circular, straight, concave, and complex depending on the longitudinal shape, and descending according to the transverse shape, It is divided into parallel type, ascending type, and complex type, and it is possible to acquire transverse and longitudinal shapes from the side and various angles by approaching steep slopes, fall danger zones, and dense vegetation areas, which are difficult for investigators to access due to slope collapse.

In addition, in the investigation of the slope valley, the distance between the extension and width of the valley adjacent to the start point and the end point of the steep slope is investigated, but the distance to the target point and location is measured using equipment in principle, and the approach and movement of the surveyor are measured In cases where this is not possible, it can be investigated using a topographic map (a numerical topographic map).

In addition, the slope valley survey is based on the real-time image information received through the flight of the drone device to determine the location of the valley extension adjacent to the start and end points of the valley, calculate the flight path and altitude for each section, and then By fixing the direction of the camera at a right angle (90) to the ground, the length of the valley extension can be obtained by using the log value that flies along the path from the bottom to the top of the valley extension close to the horizontal plane.

In addition, in the investigation of the upper external force and the surrounding environment, the existence of houses, pylons, farmland, railways, and roads is checked on the upper part of the steep slope, and the flight zone and the progress route are set on the electronic map for the area that needs to be investigated, so that the drone device is Perform automatic flight, and while the drone device flies according to a predetermined route, the image of the upper external force from the drone device can be transmitted in real time to the control device so that the investigator can check the upper external force of the field in real time.

In addition, in step (c), the analysis device analyzes the disaster site information and analyzes the disaster site information and analyzes the disaster site, including the orthographic image production, damage factor analysis, and evaluation table preparation process according to a method of deriving objective and quantitative survey results. can be reconstructed.

In addition, in step (d), the analysis device, based on the image information obtained from the drone device, quantitatively investigates and analyzes the slope collapse site through 3D image processing. Quantitative analysis can be performed by classifying into 11 categories related to slope height, longitudinal shape, transverse shape, ground deformation and cracks, slope valley, upper external force, collapse and loss history, surrounding environment, and distance between steep slopes and adjacent facilities.

In addition, the analysis of the inclination angle may measure the angle between the horizontal plane and the line connecting the lower vertex and the uppermost vertex by a method of measuring a cross section in which an inclination occurs in the three-dimensional point cloud and mesh data.

In addition, the analysis of the slope height can be measured as the height connected vertically from the road to the top of the steep slope based on the horizontal plane by extracting the cross section of the investigation target from the three-dimensional point cloud.

In addition, in the analysis of the longitudinal shape of the steep slope, contour lines are extracted at intervals of 5 m using the result of the numerical surface model through image registration processing, and then the orthographic image and the contour line are superimposed using the ESRI ArcGIS program. The longitudinal shape of the point can be analyzed.

In addition, as for the longitudinal shape of the steep slope, the shape of the contour analyzed through image processing is convex by comparing and examining the results of the 3D point cloud and the video in which the drone device shoots the investigation point in the sky above the investigation site from various angles, It can be analyzed as one of straight, concave, and complex.

In addition, the analysis of the transverse shape is performed in the same way as the analysis of the inclination angle with respect to the transverse shape of the natural slope, but by extracting the cross section of the investigation target site to analyze the transverse shape, and a drone image taken from multiple angles of the target point As a result of analysis using the shape information expressed on the 3D point cloud, the shape of the steep slope can be analyzed as one of descending type, parallel type, rising type, and complex type.

In addition, in the analysis of the slope valley, the results are analyzed for the valleys adjacent to the start and end points of the steep slope where the slope damage has occurred with respect to the extension and width of the slope valley, but the start and end points of the slope valley on the 3D point cloud The results are analyzed by measuring the length of the slope, and the extension length of the slope valley is a method of measuring the distance from the top to the bottom where the valley starts. , the result can be analyzed as a value that connects all the lengths between points.

In addition, in the analysis of the upper external force, factors affecting the upper external force of the steep slope include houses, pylons, farmland, railways, and mounds, and the analysis of the upper external force includes drone images and image processing processes taken in the field. The presence, location, and area of the upper external force can be analyzed by using the orthographic image and the three-dimensional point cloud generated through the process.

In addition, in the analysis of the collapse and loss history, the traces of collapse, rockfall, and surface layer loss are investigated in the steep slope and the damage scale is analyzed accordingly, but within a certain distance from the point where the slope loss damage occurred in the steep slope. It is possible to compare and analyze the images before and after the slope loss damage at the location where they are located.

In addition, the analysis of the distance between the steep slope and the adjacent facility may determine whether or not there is a facility in the damaged area when the steep slope collapses, and analyze the distance between the steep slope and the adjacent facility.

According to the present invention, it is possible to reconstruct the disaster accident site through 3D spatial information analysis based on the accident scene image acquired from the drone device flying over the disaster accident site.

Therefore, the on-site situation can be stored as a type of data that can be recorded and managed as needed, and there is an effect of analyzing the cause of a disaster based on the on-site reconstruction data.

1 is a configuration diagram schematically showing the overall configuration of a disaster site reconstruction and cause analysis system according to an embodiment of the present invention.
Figure 2 is a view showing the items of the field investigation and the field investigation for the reconstruction of the disaster site according to an embodiment of the present invention.
3 is a diagram illustrating an example of measuring an inclination angle in a drone device according to an embodiment of the present invention.
4 is a view showing an example of measuring the inclination height in the drone device according to an embodiment of the present invention.
5 is a view showing an example of measuring a natural slope transverse shape in a drone device according to an embodiment of the present invention.
6 is a diagram illustrating an example of measuring a slope valley in a drone device according to an embodiment of the present invention.
7 is a view showing an example of irradiating the upper external force in the drone device according to an embodiment of the present invention.
8 is a diagram illustrating a process of generating 3D spatial information using PiX4D Mapper for field data acquired from a drone device according to an embodiment of the present invention.
9 is a diagram illustrating a quantitative analysis process using an image analysis program of an analysis apparatus according to an embodiment of the present invention.
10 is a view showing investigation items through three-dimensional reconstruction of a disaster site according to the analysis of the analysis device according to an embodiment of the present invention.
11 is a view showing a result of analyzing an inclination angle in the analysis apparatus according to an embodiment of the present invention.
12 is a view showing the result of analyzing the inclination height in the analysis device according to an embodiment of the present invention.
13 is a view showing a result of analyzing the longitudinal shape of a steep slope in the analysis apparatus according to an embodiment of the present invention.
14 is a view showing a result of analyzing a natural slope cross-sectional shape in the analysis apparatus according to an embodiment of the present invention.
15 is a view showing a result of analyzing a slope valley in the analysis device according to an embodiment of the present invention.
16 is a view showing the results of analyzing the upper external force in the analysis device according to an embodiment of the present invention.
17 is a view showing the results of analyzing the collapse and loss history in the analysis device according to an embodiment of the present invention.
18 is a view showing a result of analyzing a lost area near a steep slope in the analysis device according to an embodiment of the present invention.
19 is a view showing a result of analyzing a distance between a steep slope and an adjacent facility in the analysis apparatus according to an embodiment of the present invention.
20 is a diagram illustrating an operation flowchart for explaining a disaster site reconstruction and cause analysis method according to an embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings, the embodiments of the present invention will be described in detail so that those of ordinary skill in the art to which the present invention pertains can easily implement them. The present invention may be embodied in several different forms and is not limited to the embodiments described herein.

In order to clearly explain the present invention, parts irrelevant to the description are omitted, and the same reference numerals are given to the same or similar elements throughout the specification.

Throughout the specification, when a part is said to be "connected" to another part, it includes not only the case where it is "directly connected" but also the case where it is "electrically connected" with another element interposed therebetween. . In addition, when a part "includes" a certain component, this means that other components may be further included rather than excluding other components unless otherwise stated.

When a part is referred to as being “above” another part, it may be directly on top of the other part, or the other part may be involved in between. In contrast, when a part refers to being "directly above" another part, no other part is involved in between.

Terms such as first, second and third are used to describe, but are not limited to, various parts, components, regions, layers and/or sections. These terms are used only to distinguish one part, component, region, layer or section from another part, component, region, layer or section. Accordingly, a first part, component, region, layer or section described below may be referred to as a second part, component, region, layer or section without departing from the scope of the present invention.

The terminology used herein is for the purpose of referring to specific embodiments only, and is not intended to limit the invention. As used herein, the singular forms also include the plural forms unless the phrases clearly indicate the opposite. The meaning of "comprising," as used herein, specifies a particular characteristic, region, integer, step, operation, element and/or component, and includes the presence or absence of another characteristic, region, integer, step, operation, element and/or component. It does not exclude additions.

Terms indicating a relative space such as “below” and “above” may be used to more easily describe the relationship of one part shown in the drawings to another part. These terms, along with their intended meanings in the drawings, are intended to include other meanings or operations of the device in use. For example, if the device in the figures is turned over, some parts described as being "below" other parts are described as being "above" other parts. Thus, the exemplary term “down” includes both the up and down directions. The device may be rotated 90 degrees or at other angles, and terms denoting relative space are interpreted accordingly.

Although not defined otherwise, all terms including technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention belongs. Commonly used terms defined in the dictionary are additionally interpreted as having a meaning consistent with the related technical literature and the presently disclosed content, and unless defined, they are not interpreted in an ideal or very formal meaning.

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 carry out the embodiments of the present invention. However, the present invention may be embodied in various different forms and is not limited to the embodiments described herein.

1 is a configuration diagram schematically showing the overall configuration of a disaster site reconstruction and cause analysis system according to an embodiment of the present invention.

Referring to FIG. 1 , a disaster site reconstruction and cause analysis system 100 according to an embodiment of the present invention may include a drone device 110 , a control device 120 , and an analysis device 130 .

The drone device 110 acquires disaster accident site information by photographing it while flying over the disaster site, and transmits it to the control device 120 .

The control device 120 controls the flight of the drone device 110 , and transmits disaster accident site information received from the drone device 110 to the analysis device 130 . In this case, the control device 120 may be implemented as equipment installed on the ground, for example, a portable terminal such as a smart phone or a PDA, a computer terminal, a notebook device, a server device, and the like.

The analysis device 130 reconstructs the disaster site by analyzing the disaster site information received from the control device 120 , and analyzes the cause of the accident based on the reconstructed disaster site. The analysis device 130 is also installed on the ground, and may be installed inside the control device 120 , or may be implemented as a computer terminal, a server device, etc. as a separate device.

Figure 2 is a view showing the items of the field investigation and the field investigation for the reconstruction of the disaster site according to an embodiment of the present invention.

Referring to FIG. 2 , the disaster site reconstruction and cause analysis system 100 according to the present invention executes the field investigation through the drone device 110 , and reconstructs and analyzes the field investigation result through the analysis device 130 . You can conduct a business survey.

The drone device 110 may perform an out-of-the-box survey to obtain disaster accident site information by directly performing a survey using a sensor while flying over a disaster site investigation area under the control of the control device 120 . For example, the drone device 110 may perform an out-of-office survey on 8 items out of a total of 17 items.

The drone device 110 for the field survey, as shown in FIG. 2, as the collapse risk (70%), the inclination angle (°), height (m), steep slope longitudinal shape, natural slope transverse shape, slope valley ( Valley extension/width (m)), upper external force, etc. can be investigated. In addition, the drone device 110 may investigate the surrounding environment as a social influence (30%) with respect to the field survey.

The analysis device 130 may perform an internal examination for 11 items out of a total of 17 items. Analysis device 130, as shown in FIG. 2 for the internal investigation, as the collapse risk (70%), the inclination angle (°), the height (m), the shape of the steep slope, the transverse shape of the natural slope, the ground deformation crack , slope valley (valley extension/width (m)), upper external force, collapse loss history, etc. can be investigated. In addition, the analysis device 130 may investigate the surrounding environment, the distance between the steep slope and the adjacent facilities, etc. as a social influence (30%) with respect to the field survey.

The drone device 110, while flying at the site of the disaster, as shown in Table 1 and FIGS. 3 to 7, inclination angle investigation, slope height investigation, natural slope cross-section shape investigation, slope valley investigation, upper external force and surrounding environment It is possible to acquire disaster accident site information by carrying out field investigations including investigations.

Item 1 Item 2 Item 3,4 Items 5 and 6 Items 7, 8 angle of inclination slope height slope
Vertical and transverse shape slope valley
(extension, width) upper external force,
circumstance

Hereinafter, examples in which the drone device performs field surveys for disaster site reconstruction according to an embodiment of the present invention will be described with reference to FIGS. 3 to 7 .

3 is a diagram illustrating an example of measuring an inclination angle in a drone device according to an embodiment of the present invention.

Referring to FIG. 3 , the drone device 110 according to the present invention may measure the heights of the lowermost and uppermost vertices of the longitudinal section, and the moving distance from the starting point of the inclination to the uppermost point with respect to the inclination angle investigation.

In the inclination angle investigation, the altitude of the drone device 110 is set to 0 m on the ground where the inclination starts, and the altitude value of flying is measured by ascending vertically to the top vertex. At this time, the height value (H) of the uppermost vertex is recorded in a state that the focal length displayed in the image and the target match in a state where the gimbal and the camera mounted on the drone device 110 are horizontal. Then, the angle of inclination can be calculated using a trigonometric function using the horizontally moved distance value (D) to the top vertex.

4 is a view showing an example of measuring the inclination height in the drone device according to an embodiment of the present invention.

In general, the existing method of measuring the slope height is to measure the height from the horizontal plane (ground) to the top of the steep slope using a laser distance measuring device at the site. Investigate the location of the target point by dividing it into 10 equal parts from (ground) to the top.

4 , the drone device 110 according to the present invention sets the altitude of the drone device 110 to 0 m on the ground where the inclination starts in the same way as in the method of measuring the inclination angle above with respect to the investigation of the inclination height, , it can be measured as the height value (H) flying vertically from point 1 to point 2, which is the topmost vertex.

5 is a view showing an example of measuring a natural slope transverse shape in a drone device according to an embodiment of the present invention.

In general, longitudinal and transverse shape investigation is a method of examining the shape viewed from the side of a steep slope using a visual or topographic map, and as shown in FIG. According to the transverse shape, it is divided into descending type, parallel type, rising type, and complex type.

In land-based surveys, it may be difficult to obtain on-site information on steep slopes, fall danger zones, and dense vegetation areas, where it is difficult for investigators to access due to slope collapse.

Referring to FIG. 5 , the drone device 110 according to the present invention can efficiently obtain information necessary for the cross-sectional shape survey from the side and various angles by approaching the position to be moved with respect to the natural slope cross-sectional shape investigation. have.

That is, the drone device 110 investigates the shape viewed from the side of the steep slope using a visual or topographic map, and is divided into circular, straight, concave, and complex types according to the longitudinal shape, and descending type, parallel type, It is classified into ascending type and complex type, and it is possible to obtain cross-sectional and longitudinal shapes from the side and various angles by approaching steep slopes, fall risk sections, and dense vegetation areas that are difficult for investigators to access due to slope collapse.

6 is a diagram illustrating an example of measuring a slope valley in a drone device according to an embodiment of the present invention.

Referring to FIG. 6 , the drone device 110 according to the present invention investigates the distance between the extension and width of the valley adjacent to the start point and the end point of the steep slope with respect to the investigation of the slope valley.

In principle, the distance between the target point and the location is measured using equipment.

However, in the case of land-based surveys, in the case of a method in which the surveyor moves or measures the field section directly or surveys and records the topographical map based on the information confirmed with the naked eye, the investigator's experience and subjective Results may be reflected.

On the other hand, as shown in FIG. 6, the slope valley survey method using the drone device 110 according to the embodiment of the present invention identifies the location and point of the valley extension through aerial photography from a long distance, and investigates by section, This is done by recording and confirming the route and location information of the drone device 110 on the map.

First, based on the real-time image information received through the flight of the drone device 110, the location of the valley extension adjacent to the start and end points of the valley is determined, and the flight path and altitude for each section are calculated. After that, the direction of the camera is fixed at a right angle to the ground (90°), and the length of the valley extension can be obtained by using the log value that flies along the path from the bottom to the top of the valley extension close to the horizontal plane.

7 is a view showing an example of irradiating the upper external force in the drone device according to an embodiment of the present invention.

Referring to FIG. 7 , the drone device 110 according to the present invention checks the presence or absence of houses, iron towers, agricultural land, railroads, and roads in the upper part of the steep slope with respect to the investigation of the upper external force and the surrounding environment.

In the existing survey method, a surveyor moves the upper part of the steep slope and the surrounding area to the site and visually checks it. Depending on the situation, the upper external force of a steep slope can be investigated by using a cadastral map, etc.

On the other hand, in the upper external force irradiation method using the drone device 110 according to the embodiment of the present invention, as shown in FIG. 7 , field confirmation is possible with a relatively easy and simple procedure using autonomous flight software.

Autonomous flight is a method of using an application that supports the operation of the drone device 110. By setting a flight zone and a route on the electronic map for an area requiring investigation, the drone device 110 can perform automatic flight. .

The drone device 110 transmits the upper external force image to the control device 120 in real time so that the investigator can check the upper external force of the field in real time. While the drone device 110 is flying according to a predetermined route, the investigator can check the image transmitted from the drone device 110 in real time to grasp the upper external force of the field in real time. In addition, since the information captured by the drone device 110 is stored in the analysis device 130 or the smart device, it is possible to reconfirm the on-site information as necessary even after the survey site flight is finished.

8 is a diagram illustrating a process of generating 3D spatial information using PiX4D Mapper for field data acquired from a drone device according to an embodiment of the present invention.

Referring to FIG. 8 , the analysis device 130 according to the present invention includes ortho image production, damage factor analysis, and evaluation table preparation process according to a method of deriving objective and quantitative survey results by analyzing disaster accident site information. The disaster scene can be reconstructed.

That is, the analysis device 130, based on the disaster accident site information obtained from the drone device 110, quantitatively investigates and analyzes the slope collapse site through 3D image processing, out of 17 items in the following table. As shown in Fig. 2, it is classified into 11 categories related to slope angle, slope height, longitudinal shape, transverse shape, ground deformation and cracks, slope valley, upper external force, collapse and loss history, surrounding environment, and distance between steep slopes and adjacent facilities. Quantitative analysis can be performed.

Item 1 Item 2 Item 3 Item 4 Item 5 angle of inclination slope height longitudinal shape cross-section ground
strain crack Items 6 and 7 Item 8 Item 9 Item 10 Item 11 slope
Valley (extension/width) upper external force Collapse loss history circumstance Distance between steep slope and adjacent facilities

The analysis device 130 uses an image analysis program, PIX4D Mapper, as shown in FIG. 8, as shown in (a) data acquisition, (b) image analysis screen, (c) extraction of key points through the process of data extraction, image such as point cloud generation, etc. After the processing process, it is possible to reconstruct disaster site information by finally generating three-dimensional topographic information (DSM, DEM) and orthographic images.

9 is a diagram illustrating a quantitative analysis process using an image analysis program of an analysis apparatus according to an embodiment of the present invention.

Referring to FIG. 9 , the analysis device 130 according to an embodiment of the present invention uses the image analysis program to process the data obtained from the drone device 120 through an image processing process, and then through 3D topographic information and orthoimage data. Quantitative analysis is performed on the necessary items.

Quantitative analysis based on image information can quantitatively analyze collapse risk items such as length, volume, and cross-sectional confirmation of shape required for investigation by using mapping data through two-dimensional orthogonal images and three-dimensional modeling. Quantitative analysis minimizes possible errors through comparative verification of the results of investigation using the drone device 110 in the field, and records and analyzes the field situation as 3D spatial information, so it is also possible to manage the target site in the mid- to long-term. It can be used as a useful resource.

As shown in FIG. 9 , quantitative analysis using an image analysis program in the analysis apparatus 130 according to an embodiment of the present invention includes data input and preparation process, Sparse Point Clouds process, Densified Point Clouds process, and DSM, DTM, Orthomosaic includes the process.

In the data input and preparation process, basic data input and image processing are executed, such as inputting a photographed picture and selecting a coordinate system.

The Sparse Point Clouds process performs feature point extraction and matching of photos.

Densified Point Clouds process generates point cloud data and prepares numerical image basic data.

The DSM, DTM, orthomosaic process creates and constructs 3D spatial information.

In the image analysis process, the data acquired from the drone device 110 is subjected to an image processing process using an image analysis program to analyze items necessary for investigation through 3D topographic information and orthographic image data.

The picture taken by the drone device 110 is an exchange image file format (EXIF), and basic information such as camera information, shooting date, exposure time, shooting method, focal length, aperture value, GPS information, etc. is stored as metadata, and the coordinate system is based on data of longitude and latitude coordinates of WGS-84, a world geodetic system.

Image processing for image analysis uses an image analysis program for drone footage containing meta information in a general way to extract and match feature points of photos to create sparse point clouds, and to create sparse point clouds based on photo feature points and location information A 3D point cloud is created by applying the from Motion (SfM) algorithm.

In the generated data, each point cloud data including position information of X, Y, and Z values and RGB information is expressed. Finally, the results of orthographic images, numerical surface models, and numerical elevation models are generated through processing of the three-dimensional point cloud data.

As shown in FIGS. 10 to 10, the analysis apparatus 130 according to an embodiment of the present invention produces an orthogonal image according to a method of deriving objective and quantitative survey results through three-dimensional spatial information construction and field reconstruction; It is possible to carry out an internal investigation including the process of analyzing the damage factor and preparing an evaluation table.

That is, the analysis device 130 quantitatively investigates and analyzes the slope collapse site through 3D image processing based on the image information obtained from the drone device 110 for the indoor survey, the inclination angle, Quantitative analysis can be performed by classifying into 11 categories related to slope height, longitudinal shape, transverse shape, ground deformation and cracks, slope valley, upper external force, collapse and loss history, surrounding environment, and distance between steep slopes and adjacent facilities.

In addition, the analysis apparatus 130 according to an embodiment of the present invention may analyze the image information obtained from the drone apparatus 110 through the process as described above, and reconstruct the survey site by using a three-dimensional point cloud.

The drone footage went through an image processing process using the image analysis program PIX4D Mapper, and as shown in FIG. can be analyzed. 10 is a view showing investigation items through three-dimensional reconstruction of a disaster site according to the analysis of the analysis device according to an embodiment of the present invention. Two items that were not analyzed (ground cracks, surrounding environment) were excluded as not related to the investigation site. The analysis method analyzes the necessary information by reconstructing the damaged site on the 3D point cloud and extracting the length, slope, and volume according to the type of investigation.

The angle of inclination is to measure the angle between the horizontal plane and the line connecting the lowermost and uppermost vertices in the longitudinal section. The slope height is the measurement of the vertical height from the horizontal plane (ground) to the top of the steep slope. The shape of the steep slope is to confirm the shape of the section cut in the slope direction. The cross-sectional shape of the natural slope is to confirm the shape of the steep slope viewed from the side of the steep slope. The slope valley measures the extension and width of the valley adjacent to the start and end points of the steep slope. The upper external force is to check houses, iron towers, farmland, railways, tombs, etc. on the upper part of the steep slope. The history of collapse and loss in the vicinity is to check the traces of past occurrences such as collapse within steep slopes, rockfalls, and surface layer loss. The distance between the steep slope and the adjacent facilities is to check whether there are any facilities in the affected area when the steep slope collapses, and if there are facilities, to figure out the degree of damage expected according to the distance from the steep slope.

11 is a view showing a result of analyzing an inclination angle in the analysis apparatus according to an embodiment of the present invention.

Referring to FIG. 11 , in the analysis of the inclination angle, an angle between a line connecting a lower vertex and an uppermost vertex and a horizontal plane may be measured by measuring a cross-section in which an inclination occurs in a three-dimensional point cloud and mesh data. 11 , as a result of analysis of the analysis device 130 , it was confirmed that the inclination angle of the target slope was 40 .

12 is a view showing the result of analyzing the inclination height in the analysis device according to an embodiment of the present invention.

Referring to FIG. 12 , the analysis of the slope height is to extract the cross section of the object to be investigated on the three-dimensional point cloud and measure the height connected vertically from the road to the top of the steep slope based on the horizontal plane.

In FIG. 12 , as a result of analysis of the analysis device 130 , the height of the target slope was confirmed to be 71.9 m.

13 is a view showing a result of analyzing the longitudinal shape of a steep slope in the analysis apparatus according to an embodiment of the present invention.

Referring to FIG. 13, the longitudinal shape of the steep slope is obtained by extracting contour lines at intervals of 5 m using the result of the numerical surface model through image registration processing, and then using the ESRI ArcGIS program to superimpose the orthogonal image and the contour line. to analyze the longitudinal shape of

For the longitudinal shape of the steep slope, the result of the 3D point cloud is compared and reviewed with the video obtained by the drone device 110 of the investigation point being photographed from various angles above the investigation site.

In FIG. 13 , the analysis result of the longitudinal shape of the steep slope of the analysis device 130 was confirmed to be concave. In order to verify the analysis results, we compared and reviewed the results of the 3D point cloud and the video of the survey point from the sky at the time of the field survey.

The shape of the contour analyzed through image processing was analyzed as one of convex, straight, concave, and complex, and compared to the method using the existing numerical topographic map, the current field situation such as the undulation and shape of the terrain can be reflected as it is. Using up-to-date field data, it was possible to efficiently check the longitudinal shape of the steep slope.

14 is a view showing a result of analyzing a natural slope cross-sectional shape in the analysis apparatus according to an embodiment of the present invention.

Referring to FIG. 14 , the analysis of the transverse shape is performed in the same way as the inclination angle analysis and the slope height analysis for the transverse shape of the natural slope, but the cross section of the site to be investigated is extracted and the transverse shape is analyzed.

For example, as a result of analysis using a drone image of a target point taken from various angles and shape information expressed on a 3D point cloud, the shape of a steep slope can be analyzed as one of descending type, parallel type, rising type, and complex type. .

In FIG. 14 , as a result of cross-sectional analysis of the analysis device 130 , the shape of the steeply inclined paper was confirmed to be a parallel type with a constant inclination. To objectively confirm and verify the shape, the analysis results were compared and reviewed using the drone image of the target point taken from various angles and the shape information expressed on the 3D point cloud. As a result of the analysis, the shape of the steep slope was analyzed as one of descending type, parallel type, ascending type, and complex type.

15 is a view showing a result of analyzing a slope valley in the analysis device according to an embodiment of the present invention.

Referring to FIG. 15 , the analysis of the slope valley is to analyze the results of the valleys adjacent to the starting point and the ending point of the steep slope where the slope damage occurred with respect to the extension and width of the slope valley.

In FIG. 15 , the analysis device 130 analyzed the result by measuring the length between the starting point and the ending point of the slope valley on the three-dimensional point cloud.

The extension length of the slope valley is a method of measuring the distance from the top to the bottom where the valley starts. The target point is specified on the 3D point cloud along the path where the valley is formed, and the result is extracted as a value that connects all the lengths between the points. did. The length of the slope valley width was analyzed to be 9.82 m, the same as the projected 2D value and the topographic 3D value.

16 is a view showing the results of analyzing the upper external force in the analysis device according to an embodiment of the present invention.

In the analysis of the upper external force, factors affecting the upper external force of a steep slope include houses, iron towers, farmland, railroads, and mounds. detrimental to stability.

As shown in FIG. 16 , the analysis of the upper external force was performed using the drone image taken at the site, the orthographic image generated through the image processing process, and the 3D point cloud to analyze the presence, location, and area of the upper external force.

In FIG. 16 , as a result of the analysis of the upper external force of the analysis device 130 , seedlings and fields could be identified in and around the steep slope as shown in Table 3 below.

division upper external force
Factor (number) 2D area (m ² ) 3D area (m ² ) loss of slope
Adjacent distance (m) Zone A Grave (4) 261.60 278.74 178.17 Zone B Grave (3) 533.87 550.01 139 Zone C Field (1) 922.89 1013.07 43.54

A total of 7 graves were identified in 2 (A, B) areas, and the total area of the area where the tombs are located was analyzed to be 795.47 m2. In addition, the linear distance from the point where the slope loss occurred to the nearest grave (B) was confirmed to be 139 m.

Fields were identified in a total of one area (C), and the area of the fields was analyzed to be 922.69 m2. The closest distance between the point where the slope loss occurred and the field was confirmed to be 43.54 m.

17 is a view showing the results of analyzing the collapse and loss history in the analysis device according to an embodiment of the present invention.

Referring to FIG. 17 , in the analysis of the collapse/loss history, traces of collapse, rockfall, surface layer loss, etc. in the steep slope were investigated, and the damage scale was analyzed accordingly. The collapse/loss history survey of the neighboring area was analyzed for point B.

In other words, it is to compare and analyze the images before and after the slope loss at a point located within a certain distance from the point where the slope loss occurred in the steep slope. In FIG. 17 , as a result of the analysis of the analysis device 130 , point B was located at a relatively short distance from point A where the slope loss damage occurred in the steep slope. At point B, there was a sudden change in the weather at the time of the site survey, which made it impossible to conduct on-site investigations such as drone flight and visual inspection. However, in the process of re-illuminating the site on the 3D point cloud based on the image data of photos acquired by drone operation and automatic flight for about 20 minutes before rainfall occurred, as shown in FIG. 17, traces of collapse and loss of point B was able to confirm

As shown in FIG. 18 , the traces of collapse and loss were located at a horizontal distance of about 221.82 m from point A where the slope collapse occurred, and it was confirmed that the section where the collapse occurred was 150 m in total. 18 is a view showing a result of analyzing a lost area near a steep slope in the analysis device according to an embodiment of the present invention. The soil lost in FIG. 18 was lost from the upper part of the steep slope to the lower part over the one-lane road located in the middle, and the area was analyzed to be 1,938.23 m2.

19 is a view showing a result of analyzing a distance between a steep slope and an adjacent facility in the analysis apparatus according to an embodiment of the present invention.

Referring to FIG. 19 , the analysis of the distance between the steep slope and the adjacent facilities is to check the presence or absence of facilities in the damaged area when the steep slope collapses, and to analyze the distance between the steep slope and the adjacent facilities.

In FIG. 19 , as a result of distance analysis of the analysis device 130 , the height of the steep slope where the damage occurred due to the loss of slope was confirmed to be 71.6 m as analyzed from the steep slope height. The location of the pension buried due to the loss of the slope was located at the lowest point of the steep slope, and it was confirmed that it was within 1/2 the height of the steep slope.

20 is a diagram illustrating an operation flowchart for explaining a disaster site reconstruction and cause analysis method according to an embodiment of the present invention.

Referring to FIG. 20 , in the disaster site reconstruction and cause analysis system 100 according to the present invention, the drone device 110 captures a disaster accident site, acquires disaster accident site information, and transmits it to the control device 120 ( S2010).

At this time, the drone device 110, while flying at the site of the disaster, conducts field surveys including inclination angle investigation, slope height investigation, natural slope longitudinal cross-sectional shape investigation, slope valley investigation, upper external force and surrounding environment investigation by executing a disaster accident site information can be obtained.

Here, the inclination angle investigation may measure the heights of the lowermost and uppermost vertices of the longitudinal section, and the moving distance from the starting point of the inclination to the uppermost point. In addition, in the inclination angle investigation, the altitude of the drone device 110 is set to 0 m on the ground where the inclination starts, and the altitude value is measured by ascending vertically to the top vertex, and the gimbal and camera mounted on the drone device 110 are In the horizontal state, the height value (H) of the top vertex is recorded when the focal length displayed in the image and the target match, and then the inclination angle is calculated using a trigonometric function using the horizontally moved distance value (D) to the top vertex. can be calculated

In addition, the inclination height investigation may measure the height value (H) of flying the drone device 110 by setting the altitude of the drone device 110 to 0 m on the ground where the inclination starts and ascending vertically to the top vertex.

In addition, in the investigation of the cross-sectional shape of the natural slope, the shape viewed from the side of the steep slope is investigated using a visual observation or a topographic map, and it is divided into circular, straight, concave, and complex according to the longitudinal shape, and descending type and parallel according to the transverse shape. It is classified into type, ascending type, and complex type, and it is possible to obtain cross-sectional and longitudinal shapes from the side and various angles by approaching steep slopes, fall risk sections, and dense vegetation areas that are difficult for investigators to access due to slope collapse.

In addition, in the slope valley investigation, the distance between the extension and width of the valley adjacent to the starting point and the ending point of the steep slope should be investigated, but the distance to the target point and location should be measured using equipment in principle. In cases where this is not possible, it can be investigated using a topographic map (a numerical topographic map).

In addition, the slope valley survey is based on the real-time image information received through the flight of the drone device 110 to determine the location of the valley extension adjacent to the start and end points of the valley, calculate the flight path and altitude for each section, After that, the direction of the camera is fixed at a right angle (90) to the ground, and the length of the valley extension can be obtained by using the log value that flies along the path from the bottom to the top of the valley extension close to the horizontal plane.

In addition, the investigation of the upper external force and the surrounding environment confirms the existence of houses, pylons, farmland, railroads, and roads in the upper part of the steep slope, and sets the flight zone and route on the electronic map for the area requiring investigation, so that the drone device (110) performs automatic flight, and while the drone device 110 flies according to a predetermined route, the image of the upper external force from the drone device 110 is used in real time with the control device 120 so that the investigator can check the upper external force of the field in real time. can send

Then, the control device 120 transmits the disaster accident site information received from the drone device 110 to the analysis device 130 (S2020).

Then, the analysis device 120 reconstructs the disaster site by analyzing the disaster site information (S2030).

Here, the analysis device 120 may reconstruct the disaster site, including the ortho image production, damage factor analysis, and evaluation table preparation process according to a method of deriving objective and quantitative survey results by analyzing disaster accident site information.

Next, the analysis device 120 analyzes the cause of the accident based on the reconstructed disaster site (S2040).

Here, the analysis device 120, based on the image information acquired from the drone device 110, quantitatively investigates and analyzes the slope collapse site through 3D image processing, among all 17 types of evaluation items, slope angle, slope height. , longitudinal shape, transverse shape, ground deformation and cracks, slope valley, upper external force, collapse and loss history, surrounding environment, and the distance between steep slopes and adjacent facilities can be classified into 11 categories to perform quantitative analysis.

The analysis of the inclination angle can measure the angle between the horizontal plane and the line connecting the lower vertex and the uppermost vertex by measuring the inclination section in the three-dimensional point cloud and mesh data.

Analysis of the slope height can be measured as the height connected vertically from the road to the top of the steep slope based on the horizontal plane by extracting the cross section of the object to be investigated on the 3D point cloud.

For the analysis of the longitudinal shape of steep slopes, contour lines are extracted at intervals of 5 m using the result of the numerical surface model through image registration processing, and then the longitudinal shape of the survey point is superimposed by using the ESRI ArcGIS program. can be analyzed.

As for the longitudinal shape of the steep slope, the shape of the contour analyzed through image processing is convex, straight, It can be analyzed as one of a yaw type, and a complex type.

The analysis of the transverse shape is performed in the same way as the analysis of the inclination angle for the transverse shape of the natural slope, but extracts the cross section of the investigation target and analyzes the transverse shape, and the drone image and 3D point cloud taken from various angles of the target point As a result of the analysis using the shape information expressed in the top, the shape of the steep slope can be analyzed as one of descending type, parallel type, rising type, and complex type.

For the analysis of the slope valley, the results are analyzed for the valleys adjacent to the starting point and ending point of the steep slope where the slope damage occurred with respect to the extension and width of the slope valley, and the length between the starting point and the ending point of the slope valley is measured on the 3D point cloud. Analyze the results in this way, and the extension length of the slope valley is measured by measuring the distance from the top to the bottom of the valley. The results can be analyzed with all connected values.

In the analysis of the upper external force, factors that affect the upper external force on a steep slope include houses, pylons, farmland, railways, and tombs. Using a three-dimensional point cloud, it is possible to analyze the presence, location, and area of the upper external force.

The analysis of collapse and loss history examines the traces of collapse, rockfall, and surface layer loss within a steep slope and analyzes the size of the damage. It can be analyzed by comparing the images before and after the slope loss.

Analysis of the distance between the steep slope and adjacent facilities can confirm the presence or absence of facilities in the affected area when the steep slope collapses, and analyze the distance between the steep slope and adjacent facilities.

Meanwhile, the disaster site reconstruction and cause analysis method according to an embodiment of the present invention may be recorded in a computer-readable recording medium.

That is, the present invention comprises the steps of: (a) capturing, by a drone device, a disaster accident site, acquiring disaster accident site information, and transmitting it to a control device; (b) transmitting, by the control device, the received disaster accident site information to an analysis device; (c) reconstructing the disaster site by analyzing the disaster site information by the analysis device; And (d) the analysis device can record the disaster site reconstruction and cause analysis method comprising the step of analyzing the cause of the accident based on the reconstructed disaster site on a computer-readable recording medium.

Meanwhile, the analysis apparatus 130 according to an embodiment of the present invention may include a display unit that displays the disaster site reconstruction result and cause analysis result on the screen.

In this case, in the display unit, a gate metal layer including a gate electrode and a signal wiring is formed on a substrate. Here, the substrate may be made of a flexible plastic material having a flexible characteristic so that display performance can be maintained even when the display unit is bent like paper.

In addition, the gate metal layer may be formed of any one of a first metal material having a low resistance characteristic, for example, aluminum (Al), aluminum alloy (AlNd), copper (Cu), copper alloy, molybdenum (Mo), and molybdenum (MoTi). It may be formed as a single-layer structure or a double-layer or triple-layer structure by being made of two or more first metal materials. This gate metal layer forms the lower electrode of the capacitor C1, and is formed on the same layer as the gate electrode 1131 of the driving thin film transistor DRT, but has a separate configuration that is not electrically connected.

In addition, a gate insulating layer and an etch stop layer made of an insulating material, for example, silicon oxide (SiO2) or silicon nitride (SiNx), which are inorganic insulating materials, are formed on the entire surface of the display area of the substrate including the gate metal layer.

A semiconductor layer made of any one selected from amorphous silicon, polysilicon, and semiconductor oxide is formed between the upper portion of the gate insulating layer and the etch stop layer, corresponding to each of the thin film transistors SWT, SST, and DRT. A portion of the semiconductor layer is exposed through a contact hole formed on the etch stop layer, and the source and drain electrodes of the driving thin film transistor (DRT) and the data signal (Vdata) are formed on the insulating layer including the contact hole and the etch stop layer. The first source and drain metal layers, which are separate components that are not electrically connected to the application wiring and the power supply voltage (ELVDD) application wiring, are formed.

Here, the first source and drain metal layers are, for example, aluminum (Al), aluminum alloy (AlNd), copper (Cu), copper alloy, molybdenum (Mo), moly titanium (MoTi), chromium (Cr), and titanium (Ti). ) of any one or a combination of two or more substances.

In particular, in the driving thin film transistor (DRT), a source electrode and a drain electrode made of a metallic material are formed spaced apart from each other and in contact with the semiconductor layer exposed through the contact hole, respectively. Accordingly, the gate electrode, the gate insulating layer, the semiconductor layer, and the source and drain electrodes form one driving thin film transistor (DRT). In addition, in addition to the driving thin film transistor (DRT), the switching thin film transistor (SWT) and the sensing thin film transistor (SST) are also formed in the same stacked structure.

Here, the gate electrode and the drain electrode of the switching thin film transistor (SWT) are connected to the scan line and the data line, respectively, and the source electrode of the switching thin film transistor (SWT) is electrically connected to the gate electrode of the driving thin film transistor (DRT). and source electrodes of the sensing thin film transistor SST and the driving thin film transistor DRT are connected to each other.

In addition, the first source and drain metal layers form the upper electrode of the capacitor C1.

Meanwhile, although both the first source and drain metal layers may have a single-layer structure, a double-layer or triple-layer structure may be formed by a combination of two metal materials.

A passivation layer is formed on the first source and drain metal layers to cover the driving thin film transistor (DRT) and to expose a portion of the first source and drain metal layers. In particular, a partial region of the passivation layer is etched to expose the source electrode of the lower driving thin film transistor (DRT), and is brought into contact with the upper second source and drain metal layers.

A second source and drain metal layer is formed on the passivation layer. The second source and drain metal layers may be formed of the same material as the first source and drain metal layers. In particular, the second source and drain metal layers are patterned on the upper portion of the driving thin film transistor (DRT) and the same voltage as that of the gate electrode is applied to form a dual gate structure. and an auxiliary gate electrode that forms The second source and drain metal layers and the auxiliary gate electrode are formed on the same layer but are not electrically connected to each other.

The second source and drain metal layers extend to regions where the first source and drain metal layers are exposed and come into contact with the anode metal layer, so that a signal supplied therefrom is applied to the anode metal layer.

In addition, an interlayer insulating film is formed on the second source and drain metal layers. A first contact hole exposing the lower second source and drain metal layers is formed in a partial region of the interlayer insulating layer, and the anode metal layer is separated for each pixel on the upper portion of the interlayer insulating layer including the first contact hole. is formed.

Here, the region exposed by the first contact hole overlaps the capacitor C1 formed by the gate metal layer and the first source and drain metal layers downward, and is defined as a first region in which the second source and drain metal layers and the anode metal layer are in contact. do.

In the first region, the first source and drain metal layers and the second source and drain metal layers are insulated from each other by a passivation film.

Although not shown, the anode metal layer constitutes the anode electrode of the organic light emitting diode. On the anode metal layer, an organic light emitting layer and a cathode electrode are formed in an organic light emitting pattern emitting red, green and blue, respectively. Accordingly, the anode metal layer, the cathode electrode, and the organic light emitting layer interposed between the two electrodes form an organic light emitting diode.

Here, the organic light emitting layer may be composed of a single layer made of an organic light emitting material, or a hole injection layer, a hole transporting layer, a light emitting material layer, to increase luminous efficiency. It may consist of multiple layers of an electron transporting layer and an electron injection layer.

In particular, the anode metal layer extends in one direction and extends not to the first contact hole, but to the second contact hole of the interlayer insulating film where the second source and drain metal layers that do not overlap with the passivation film are exposed, so that the second source and drain metal layers are double characterized in that it is in contact with

That is, in the interlayer insulating film included in one pixel, not only the first contact hole formed in the region overlapping the passivation film, but also the passivation film is etched to contact the source electrode and the second source and drain metal layers of the driving thin film transistor (DRT). A second contact hole is further formed corresponding to the region, and the anode metal layer extends to the second contact hole so that the second source and drain metal layers and the anode metal layer come into contact with each other in redundancy.

Here, the region exposed by the second contact hole is defined as a second region in which the gate metal layer, the source electrode of the driving thin film transistor (DRT), the second source and drain metal layers, and the anode metal layer are sequentially formed and in direct contact with each other. .

According to this structure, even if an open failure of the second source and drain metal layers occurs due to the step difference of the passivation film in the etching process of the second source and drain metal layers, the electrical connection between the anode metal layer and the second source and drain metal layers is there will be no change The signal supplied to the anode metal layer is the power supply voltage ELVDD applied through the driving thin film transistor DRT.

At least one passivation film, an organic film, and a protective film are further provided on the anode metal layer to prevent moisture from penetrating into the organic light emitting layer, thereby forming one organic light emitting display device.

On the other hand, the analysis device 130 according to the present invention is a computer device equipped with a high-performance GPU, which can be provided in an investigation vehicle to explore the disaster site and be formed as a field-operated artificial intelligence system that can be operated at the disaster site, Alternatively, it can be processed by a separate automatic analysis server installed on the ground to form an internally operated artificial intelligence system that automatically analyzes with high performance.

For example, the analysis device 130 is a learning data set construction unit for building a plurality of learning data sets based on disaster site reconstruction information, and is formed by learning a plurality of learning data sets built in the learning data set construction unit. It may be configured to include an artificial intelligence model unit.

The learning data set construction unit may include an information recording unit, an information synchronization unit, an image extraction unit, an image correction unit, a learning information generating unit, and a database unit.

The information recorder records and stores meta information of the drone's video, and the information synchronizer synchronizes individual frames of the video with the drone's flight log information through a synchronization algorithm.

Here, the synchronization algorithm finds a first specific time point in which the amount of pixel change between frames is greater than or equal to a certain range in individual frames of the video, finds a second specific point in time in which the change in attitude of the drone is greater than or equal to a certain range in flight log information of the drone, and In the flight log information, find a third specific point in time when the amount of change in the gimbal's attitude is over a certain range, and use the first, second, and third specific points, i.e., synchronization points, to record individual frames of the drone's video and flight log information of the drone. can be synchronized.

The image extractor extracts a specific keyframe (still image) from among individual frames of the drone's moving picture based on preset keyframe extraction reference information. The reason for extracting a specific keyframe is that the number of frames in the video is too large and there is little change in the contents of the video in each frame. Based on the information, specific keyframes in which the image change amount is large, and the drone/camera posture changes rapidly at regular intervals are extracted.

In this case, the preset keyframe extraction reference information includes information for each period, pixel change information of an image, and attitude change information of drones and cameras, and may be set and changed by a user.

The image compensator may correct the meta information of the image by recording (geo-tagging) log information (position/attitude angle information) of the drone corresponding to the image information of the keyframe extracted by the image extraction unit as meta information of the image.

The learning information generating unit generates learning data by labeling the disaster type and the disaster damage area according to preset disaster hierarchical information on the extracted image information of the keyframe. In the labeled area, each pixel coordinate can be stored in a Json file format for learning. That is, the learning information generating unit uses a plurality of image information for each disaster type as input data, and uses the disaster type information according to the hierarchy and the area information labeled for the disaster-damaged area as output data to learn multiple learning data according to the disaster hierarchy information. it will create

The disaster hierarchical information is classified and included into upper, middle, and lower hierarchical information for each disaster type, and may be preset by a system builder, expert, or manager.

High-level information includes natural disaster and social disaster information, and medium-level information includes more than 20 types of natural disasters including typhoons, heavy rain, cold waves, heavy snow, heat waves, drought, earthquakes, yellow sand, tsunamis, floods, inundation, landslides, and volcanoes. Disaster information, fire, collapse, explosion, forest fire, traffic accident, electric accident, water accident, infectious disease, and more than 20 types of social disaster information including fine dust can be included.

The sub-hierarchical information may include specific disaster information including soil spill, facility destruction, road destruction, landslide spill, building fire, explosion, and vehicle damage according to natural disaster and social disaster information.

The database unit generates a learning data set by converting a plurality of learning data generated through the learning information generating unit into a database (DB).

As described above, the learning data set construction unit creates a learning image of an appropriate size from the drone video in the disaster accident area, classifies the object according to the type of disaster, and then labels it by hierarchy according to the hierarchy to generate the learning data and convert it into a database By doing so, it is possible to build a training data set.

The artificial intelligence model unit consists of an information learning unit and a modeling unit, and it is a method for automatically determining disaster types and disaster damage information by self-processing disaster image information input by learning a lot through the learning data set built in the learning data set construction unit. Build an artificial intelligence model.

The information learning unit generates a plurality of determination information through automatic learning of various disaster event information multiple times on the basis of the plurality of learning data sets generated through the learning data set construction unit. The modeling unit forms an accident analysis algorithm using a plurality of judgment information generated through the information learning unit. That is, the AI model unit analyzes the disaster accident area from the drone video and forms an optimal AI algorithm for extracting damage information. In more detail, in consideration of the real-time of the system, when an HD image is given as an input, it is possible to form a neural network structure capable of inferring domain-based semantic segmentation of the presence or absence of disaster within a short time.

In addition, the artificial intelligence model unit can be composed of a neural network module to utilize not only local features of the image but also global features in consideration of the characteristics of the disaster area investigation, It may also have a function of a loss function for correcting the imbalance.

The image processing unit visualizes the disaster type and past damage area information determined through the disaster information analysis unit as orthoimage map information.

At this time, the image processing unit determines the absolute position of each pixel by using the position/attitude angle (X, Y, Z, Roll, Pitch, Yaw) information of the drone among the meta information of the video and generates an orthophoto. , it is possible to visualize the generated orthographic image by superimposing it on the background map (OpenstreetMap) driven in the web browser. Here, the user may roughly obtain the area of the disaster-affected area by drawing an area with the mouse on the orthographic image visualized on the map.

In addition, the image processing unit may perform 3D modeling to obtain 3D image information such as 3D point cloud data, 3D topographic information, and orthogonal image map information.

The damage information analysis unit provides damage scale information by analyzing the length of damage, the area, and the amount of runoff of the landmark through a preset analysis program based on the orthoimage information obtained through the image processing unit.

The information input unit receives various types of input information from the user, and the information display unit displays and provides various input/output information and image information to the user.

As described above, the disaster site reconstruction and cause analysis system using a drone according to the present invention builds a learning data set through the process of precisely synchronizing individual frames of a drone video and automatic flight log information of the drone. It can provide an artificial intelligence model for disaster analysis with high accuracy.

As described above, according to the present invention, the target site is reconstructed through 3D spatial information analysis based on the accident scene image acquired from the drone device flying at the disaster accident site, and the site situation can be recorded and managed as necessary. It is possible to provide a disaster site reconstruction and cause analysis method and system using drones that can be stored as data of

Those skilled in the art to which the present invention pertains should understand that the present invention can be embodied in other specific forms without changing the technical spirit or essential characteristics thereof, so the embodiments described above are illustrative in all respects and not restrictive. only do The scope of the present invention is indicated by the following claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention. .

100: disaster site reconstruction and cause analysis system
110: drone device
120: control device
130: analysis device

Claims (40)

a drone device that acquires disaster accident site information by shooting while flying over the disaster site and transmits it to a control device;
a control device for controlling the flight of the drone device and transmitting disaster accident site information received from the drone device to the analysis device; and
an analysis device for reconstructing a disaster site by analyzing the disaster site information received from the control device, and analyzing the cause of an accident based on the reconstructed disaster site;
including,
The drone device, while flying at the disaster accident site, by executing an out-of-the-box survey including inclination angle investigation, slope height investigation, natural slope cross-sectional shape investigation, slope valley investigation, upper external force and surrounding environment investigation, the disaster accident site information acquire,
The inclination angle investigation measures the height of the lowermost and uppermost vertices of the longitudinal section, and the moving distance from the point where the inclination starts to the uppermost point,
In the inclination angle investigation, the altitude of the drone device is set to 0 m on the ground where the inclination starts, and the altitude value is measured by ascending vertically to the top vertex, and the gimbal and the camera mounted on the drone device are horizontal. Record the height value (H) of the top vertex when the focal length displayed in the image and the target match, and then calculate the inclination angle using a trigonometric function using the horizontally moved distance value (D) to the top vertex,
The incline height investigation is performed by setting the altitude of the drone device to 0 m on the ground where the inclination starts and flying vertically up to the top vertex to measure the height value (H),
The cross-sectional shape of the natural slope is investigated using a visual or topographic map of the shape viewed from the side of the steep slope, and is divided into circular, straight, concave, and complex types according to the longitudinal shape, and descending type and parallel type according to the transverse shape. , ascending type, and complex type. Approaching steep slopes, fall risk sections, and dense vegetation areas where it is difficult for investigators to access due to slope collapse, acquire transverse and longitudinal shapes from the side and various angles,
In the slope valley survey, the distance between the extension and width of the valley adjacent to the starting point and the end point of the steep slope is investigated, but the distance to the target point and location is measured using equipment in principle, and it is impossible to measure the approach and movement of the surveyor In some cases, it is investigated using a topographic map,
The slope valley survey is based on the real-time image information received through the flight of the drone device to determine the location of the valley extension adjacent to the start and end points of the valley, calculate the flight path and altitude for each section, and then By fixing the direction at a right angle (90) to the ground, the length of the valley extension is obtained by using the log value that flies along the path from the bottom to the top of the valley extension close to the horizontal plane,
In the investigation of the upper external force and the surrounding environment, the existence of houses, pylons, farmland, railroads, and roads is checked on the upper part of the steep slope, and the flight zone and route are set on the electronic map for the area that needs investigation, so that the drone device automatically flies and transmits the image of the upper external force from the drone device to the control device in real time so that the investigator can check the upper external force of the field in real time while the drone device flies according to a predetermined route,
The analysis device is
a learning data set construction unit for constructing a plurality of learning data sets based on disaster site reconstruction information; and
Including an artificial intelligence model unit formed by learning a number of through the learning data set built in the learning data set construction unit,
The learning data set construction unit includes an information recording unit, an information synchronization unit, an image extraction unit, an image correction unit, a learning information generation unit and a database unit,
The information recording unit records and stores meta information of the drone's video,
The information synchronization unit finds a first specific point in time in the individual frame of the video in which the amount of pixel change between each frame is greater than or equal to a certain range, finds a second specific point in time in which the change in attitude of the drone is greater than or equal to a certain range in flight log information of the drone, and the flight of the drone In the log information, find a third specific point in time when the amount of change in the gimbal's posture is over a certain range, and synchronize individual frames of the drone's video with the drone's flight log information using the first, second, and third specific points of view Synchronizes the frame and the flight log information of the drone,
The image extraction unit extracts a specific keyframe from among individual frames of the drone's video based on preset keyframe extraction reference information,
The image correction unit corrects the meta information of the image by recording log information of the drone corresponding to the image information of the key frame extracted by the image extraction unit as meta information of the image,
The learning information generating unit generates learning data by labeling the disaster type and the disaster damage area according to preset disaster hierarchical information in the extracted image information of the keyframe,
The database unit is a disaster site reconstruction and cause analysis system for generating a learning data set by converting a plurality of learning data generated through the learning information generating unit into a database.
delete delete delete delete delete delete delete delete The method of claim 1,
The analysis device analyzes the disaster site information and reconstructs the disaster site, including the orthoimage production, damage factor analysis, and evaluation table preparation process according to a method of deriving objective and quantitative investigation results, disaster site reconstruction and cause analysis system.
11. The method of claim 10,
The analysis device selects the evaluation items that can quantitatively investigate and analyze the slope collapse site through three-dimensional image processing based on the disaster accident site information acquired from the drone device. Disaster site reconstruction and cause analysis system that performs quantitative analysis by classifying ground deformation and cracks, slope valleys, upper external forces, collapse and loss history, surrounding environment, and the distance between steep slopes and adjacent facilities.
12. The method of claim 11,
The analysis of the angle of inclination is a method of measuring a cross section in which an inclination occurs in a three-dimensional point cloud and mesh data, and a disaster site reconstruction and cause analysis system for measuring the angle between the horizontal plane and the line connecting the lower vertex and the uppermost vertex.
12. The method of claim 11,
The analysis of the slope height is a disaster site reconstruction and cause analysis system that extracts the cross section of the investigation target from the three-dimensional point cloud and measures the height connected vertically from the road to the top of the steep slope based on the horizontal plane.
12. The method of claim 11,
For the analysis of the longitudinal shape of the steep slope, contour lines are extracted at intervals of 5 m using the result of the numerical surface model through image registration processing, and then the orthographic image and the contour line are superimposed using the ESRI ArcGIS program. A disaster site reconstruction and cause analysis system that analyzes the longitudinal shape.
15. The method of claim 14,
As for the longitudinal shape of the steep slope, the shape of the contour analyzed through image processing is convex, straight, A disaster site reconstruction and cause analysis system that is analyzed as one of the yaw and complex types.
12. The method of claim 11,
The analysis of the transverse shape is performed in the same way as the analysis of the inclination angle with respect to the transverse shape of the natural slope, but extracts the cross section of the investigation target to analyze the transverse shape, and the drone image and 3D image of the target point taken from various angles A disaster site reconstruction and cause analysis system that analyzes the shape of a steep slope into one of descending, parallel, ascending, and complex as a result of analysis using shape information expressed on the point cloud.
12. The method of claim 11,
In the analysis of the slope valley, the results are analyzed for the valleys adjacent to the start and end points of the steep slope where the slope damage has occurred with respect to the extension and width of the slope valley, but the length between the starting point and the ending point of the slope valley on the three-dimensional point cloud Analyze the results by measuring
The extension length of the slope valley is a method of measuring the distance from the top to the bottom where the valley starts, and the target point is specified on the 3D point cloud along the path where the valley is formed, and the result is a value obtained by connecting all the lengths between the points. Analyze, disaster site reconstruction and cause analysis system.
12. The method of claim 11,
In the analysis of the upper external force, factors affecting the upper external force of the steep slope include houses, pylons, farmland, railways, and mounds,
The analysis of the upper external force is a disaster site reconstruction and cause analysis system that analyzes the presence, location, and area of the upper external force by using the drone image taken at the site, the orthographic image generated through the image processing process, and the 3D point cloud .
12. The method of claim 11,
The analysis of the collapse and loss history examines the traces of collapse, rockfall, and surface loss within the steep slope and analyzes the damage scale accordingly, but is located within a certain distance from the point where the slope loss damage occurred within the steep slope. A disaster site reconstruction and cause analysis system that compares and analyzes images before and after slope loss at a point.
12. The method of claim 11,
The analysis of the distance between the steep slope and the adjacent facility is a disaster site reconstruction and cause analysis system that checks the presence or absence of a facility in the damaged area when the steep slope collapses, and analyzes the distance between the steep slope and an adjacent facility.
(a) the drone device captures the disaster site, acquires disaster accident site information and transmits it to the control device;
(b) transmitting, by the control device, the received disaster accident site information to an analysis device;
(c) reconstructing the disaster site by analyzing the disaster site information by the analysis device; and
(d) analyzing, by the analysis device, the cause of the accident based on the reconstructed disaster site;
including,
In step (a), the drone device performs field surveys including inclination angle survey, inclination height survey, natural slope cross-sectional shape survey, slope valley survey, upper external force and surrounding environment survey to obtain disaster accident site information, and ,
The inclination angle investigation measures the height of the lowermost and uppermost vertices of the longitudinal section, and the moving distance from the point where the inclination starts to the uppermost point,
In the inclination angle investigation, the altitude of the drone device is set to 0 m on the ground where the inclination starts, and the altitude value is measured by ascending vertically to the top vertex, and the gimbal and the camera mounted on the drone device are horizontal. Record the height value (H) of the top vertex when the focal length displayed in the image and the target match, and then calculate the inclination angle using a trigonometric function using the horizontally moved distance value (D) to the top vertex,
The incline height investigation is performed by setting the altitude of the drone device to 0 m on the ground where the inclination starts and flying vertically up to the top vertex to measure the height value (H),
The cross-sectional shape of the natural slope is investigated using a visual or topographic map of the shape viewed from the side of the steep slope, and is divided into circular, straight, concave, and complex types according to the longitudinal shape, and descending type and parallel type according to the transverse shape. , ascending type, and complex type. Approaching steep slopes, fall risk sections, and dense vegetation areas where it is difficult for investigators to access due to slope collapse, acquire transverse and longitudinal shapes from the side and various angles,
In the slope valley survey, the distance between the extension and width of the valley adjacent to the starting point and the end point of the steep slope is investigated, but the distance to the target point and location is measured using equipment in principle, and it is impossible to measure the approach and movement of the surveyor In some cases, it is investigated using a topographic map,
The slope valley survey is based on the real-time image information received through the flight of the drone device to determine the location of the valley extension adjacent to the start and end points of the valley, calculate the flight path and altitude for each section, and then By fixing the direction at a right angle (90) to the ground, the length of the valley extension is obtained by using the log value that flies along the path from the bottom to the top of the valley extension close to the horizontal plane,
In the investigation of the upper external force and the surrounding environment, the existence of houses, pylons, farmland, railroads, and roads is checked on the upper part of the steep slope, and the flight zone and route are set on the electronic map for the area that needs investigation, so that the drone device automatically flies and transmits the image of the upper external force from the drone device to the control device in real time so that the investigator can check the upper external force of the field in real time while the drone device flies according to a predetermined route,
The analysis device is
a learning data set construction unit for constructing a plurality of learning data sets based on disaster site reconstruction information; and
Including an artificial intelligence model unit formed by learning a plurality of through the learning data set built in the learning data set construction unit,
The learning data set construction unit includes an information recording unit, an information synchronization unit, an image extraction unit, an image correction unit, a learning information generation unit and a database unit,
The information recording unit records and stores the meta information of the drone's video,
The information synchronization unit finds a first specific point in time in the individual frame of the video in which the amount of change in pixels between each frame is greater than or equal to a certain range, finds a second specific point in time in which the change in attitude of the drone is greater than or equal to a certain range in flight log information of the drone, and the flight of the drone From the log information, find a third specific point in time when the amount of change in the gimbal's posture is within a certain range, and synchronize individual frames of the drone's video with the drone's flight log information using the first, second, and third specific points of view. Synchronize the frame and the flight log information of the drone,
The image extraction unit extracts a specific keyframe from among individual frames of the drone's video, based on preset keyframe extraction reference information,
The image correction unit corrects the meta information of the image by recording log information of the drone corresponding to the image information of the keyframe extracted by the image extraction unit as meta information of the image,
The disaster site reconstruction and cause analysis method for generating learning data by labeling the disaster type and the disaster damage area according to preset disaster hierarchy information to the extracted keyframe image information.
delete delete delete delete delete delete delete delete 22. The method of claim 21,
In the step (c), the analysis device analyzes the disaster accident site information and reconstructs the disaster site, including the ortho image production, damage factor analysis, and evaluation table preparation process according to a method of deriving objective and quantitative investigation results. , disaster site reconstruction and cause analysis methods.
22. The method of claim 21,
In the step (d), the analysis device is, based on the image information obtained from the drone device, the slope angle, the slope height, the longitudinal shape, A disaster site reconstruction and cause analysis method that performs quantitative analysis by classifying cross-sectional shape, ground deformation and cracks, slope valleys, upper external forces, collapse and loss history, surrounding environment, and distance between steep slopes and adjacent facilities.
32. The method of claim 31,
The analysis of the angle of inclination is a method of measuring a cross section in which an inclination occurs in a three-dimensional point cloud and mesh data, and the angle between the line connecting the lower vertex and the uppermost vertex and the horizontal plane is measured, a disaster site reconstruction and cause analysis method.
32. The method of claim 31,
The analysis of the slope height is a disaster site reconstruction and cause analysis method that extracts the cross section of the investigation target from the three-dimensional point cloud and measures the height connected vertically from the road to the top of the steep slope based on the horizontal plane.
32. The method of claim 31,
For the analysis of the longitudinal shape of the steep slope, contour lines are extracted at intervals of 5 m using the result of the numerical surface model through image registration processing, and then the orthographic image and the contour line are superimposed using the ESRI ArcGIS program. Analyzing the longitudinal shape, disaster site reconstruction and cause analysis method.
35. The method of claim 34,
As for the longitudinal shape of the steep slope, the shape of the contour analyzed through image processing is convex, straight, A disaster site reconstruction and cause analysis method, which is analyzed as one of the yaw type and the complex type.
32. The method of claim 31,
The analysis of the transverse shape is performed in the same way as the analysis of the inclination angle with respect to the transverse shape of the natural slope, but extracts the cross section of the investigation target to analyze the transverse shape, and the drone image and 3D image of the target point taken from various angles As a result of analysis using the shape information expressed on the point cloud, the shape of the steep slope is analyzed as one of descending type, parallel type, rising type, and complex type. Disaster accident site information acquisition and analysis method
32. The method of claim 31,
In the analysis of the slope valley, the results are analyzed for the valleys adjacent to the start and end points of the steep slope where the slope damage has occurred with respect to the extension and width of the slope valley, but the length between the starting point and the ending point of the slope valley on the three-dimensional point cloud Analyze the results by measuring
The extension length of the slope valley is a method of measuring the distance from the top to the bottom where the valley starts, and the target point is specified on the 3D point cloud along the path where the valley is formed, and the result is a value obtained by connecting all the lengths between the points. Analyzing, disaster site reconstruction and cause analysis method.
32. The method of claim 31,
In the analysis of the upper external force, factors affecting the upper external force of the steep slope include houses, pylons, farmland, railways, and mounds,
The analysis of the upper external force is a disaster site reconstruction and cause analysis method that analyzes the presence, location, and area of the upper external force using a drone image taken at the site, an ortho image generated through an image processing process, and a three-dimensional point cloud .
32. The method of claim 31,
The analysis of the collapse and loss history examines the traces of collapse, rockfall, and surface loss within the steep slope and analyzes the damage scale accordingly, but is located within a certain distance from the point where the slope loss damage occurred within the steep slope. A disaster site reconstruction and cause analysis method that compares and analyzes images before and after slope loss at a point.
32. The method of claim 31,
The analysis of the distance between the steep slope and the adjacent facility is a disaster site reconstruction and cause analysis method of confirming the presence or absence of a facility in the damaged area when the steep slope collapses, and analyzing the distance between the steep slope and adjacent facilities.

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