JP4220140B2 - Sediment disaster prediction system and prediction method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a sediment disaster prediction system and a prediction method. The monitoring of landslides due to volcanic activity is recognized as the first report of disaster occurrence from the viewpoint of sudden event detection, and if accompanied by natural phenomena such as rainfall, it is necessary for secondary disaster prediction such as debris flow occurrence It is an essential management task. In recent years, with the occurrence of such natural disasters nationwide, it has become necessary to provide evacuation advice with a personality to the general population.
[0002]
[Prior art]
The sabo monitoring system in the Ministry of Land, Infrastructure, Transport and Tourism and local governments is an integrated system for monitoring the state of mountains and foothills where volcanoes and landslides occur frequently, and has the following functions.
(1) Remote monitoring of rainfall data (2) Remote monitoring of earthquake data (3) Status monitoring of various landslide disaster prevention facilities using cameras A road (a facility that forces a debris flow to flow into the estuary; a waterless river).
▲ 4 ▼ Debris flow detection wire sensor, etc. is attached to the sabo dam sediment outlet, and when the wire is cut by the landslide, it is recognized that debris flow occurs. ▲ 5 Various data management / data provision FIG. In the figure, 1 is a volcano, 2 and 3 are rain gauges installed in mountainous areas. When there is a volcano, the debris from the eruption flows through Route 4 in the figure. 5 is a monitoring camera for monitoring the state of the route 4, and 6 is a debris flow detection sensor for detecting the occurrence of debris flow. The debris flow detection sensor 6 detects the occurrence of debris flow by cutting a wire installed in the flow path.
[0003]
Reference numeral 7 denotes a sabo dam provided for the debris flow route 4. 8 is a surveillance camera for monitoring the state of the sabo dam 7, 9 is a vibration sensor provided in the vicinity of the sabo dam 7, and 10 is a water level meter for measuring the water level when water flows downstream of the sabo dam 7. Reference numeral 11 denotes a river that flows as a water stream when it rains. This river 11 is often a Minashi river when it does not rain.
[0004]
Reference numeral 12 denotes a road that crosses the river 11, reference numeral 13 denotes an information display board provided on the road 12, and reference numeral 14 denotes a bridge that spans the river 11. A sabo control center 15 collects information from various sensors as described above and generates various alarms.
[0005]
The outputs of the rain gauges 2 and 3, the debris flow detection sensor 6, the vibration sensor 9, and the water level gauge 10 are collected in the sabo management center 15 by an optical cable, a wired cable, or wirelessly. In addition, images taken by the monitoring cameras 5 and 8 are also collected in the sabo management center 15. The sabo management center 15 looks at the outputs of the rain gauges 2 and 3 and issues a warning that a debris flow may occur if it rains more than a predetermined amount. This warning is displayed on, for example, the information display board 13 installed on the road 12, and other general media are used to notify the general residents of the warning.
[0006]
When the output of the debris flow detection sensor 6 is detected and it is recognized that a debris flow has occurred, the sabo management center 15 notifies the general residents of the debris flow occurrence and recommends evacuation in some cases. This information is also displayed on the information display board 13 and notifies the closure when necessary.
[0007]
In addition, when the debris flow occurrence is photographed by the monitoring cameras 5 and 8, the sabo management center 15 notifies the general inhabitants of the debris flow occurrence and urges to evacuate in some cases, as in the method described above. In particular, when the debris flow gets over the sabo dam 7 by the surveillance camera 8, there is a possibility that a large amount of debris flow will flow downstream, so the sabo management center 15 issues an emergency evacuation order.
[0008]
[Problems to be solved by the invention]
Conventional landslide monitoring of volcanoes and the like is only regular monitoring, and cannot cope with sudden event detection that requires instantaneous suddenness. Specifically, in the past, monitoring of mountain bodies represented by monitoring of landslides such as volcanoes has been performed mainly by photographing with a still camera and judging the presence or absence of collapse by visual observation. For this reason, operations such as operation of the operator on the site occur, and the problem of lack of personnel overlaps with the situation of congestion of the monitoring operation.
[0009]
Also, the amount of collapse was difficult to grasp due to visual monitoring and lacked accuracy. Furthermore, due to information lacking in accuracy, real-time disaster occurrence information is not notified to the residents. For this reason, an accident has actually occurred.
[0010]
On the other hand, there is a movement to detect collapse by installing an optical fiber sensor and a large civil engineering structure near the site to break down such a situation, but it is also necessary to be exposed to the danger zone. Once the collapse occurred, it was necessary to return to the site for repair and maintenance.
[0011]
The present invention has been made in view of such problems, and it is an object of the present invention to provide a landslide disaster prediction system and a prediction method that can reliably predict the occurrence of a landslide disaster and can reduce the burden of work contents. Yes.
[0012]
[Means for Solving the Problems]
(1) FIG. 1 is a principle block diagram of the present invention. In the figure, 20 is a television camera installed at a plurality of predetermined locations, 21 is a signal transmission cable connected to these television cameras 20, and 22 is a video signal of the television camera sent via the cable 21. An image processing means for receiving and performing predetermined image processing. A storage means 23 is connected to the image processing means 22 and stores various kinds of information, particularly digital map information of a target location.
[0013]
The image processing means 22 receives the video signal from the television camera 20, and detects the occurrence of collapse by capturing the change in luminance of the moved part relative to the part where the mountain body is not moving.
[0014]
If comprised in this way, the planar change amount and three-dimensional collapse amount of the shape of a mountain body can be measured .
[0015]
(2) The invention according to claim 2 comprises a television camera for monitoring mountain bodies, and image processing means for performing predetermined image processing based on a video signal from the television camera, wherein the image processing means Using the video signal from the TV camera, the amount of planar change before and after the change of the shape of the mountain body is measured, and the map information equipped with the GIS function is stored in the storage means and stored in the storage means. A three-dimensional collapse amount is measured by overlapping a video captured by the television camera with a digital map .
[0016]
If comprised in this way, the image | video image | photographed with the television camera may overlap with a digital map, and a three-dimensional collapse amount can be measured.
[0018]
The present invention is characterized in that information taken by the television camera 20 is stored in a storage means as an IP video.
Here, the IP (Information Protocol) video is a video packetized by a moving image compression technique compliant with the information protocol.
[0019]
With this configuration, it is possible to reduce the work load even in video situation monitoring when a sudden event occurs by accumulating video as IP video.
In the present invention, the image processing means 22 measures the planar change amount before and after the change of the shape of the mountain using the video of the television camera 20.
[0020]
If comprised in this way, the planar variation | change_quantity of the shape of a mountain body can be measured by the pattern matching of a brightness | luminance.
In the present invention, the image processing means 22 has map information equipped with a GIS function in the storage means 23 and overlaps the video captured by the television camera 20 with the digital map stored in the storage means 23. Thus, the three-dimensional collapse amount is measured.
[0021]
The storage means 23 stores latitude, longitude, and altitude data (digital map information). Therefore, the three-dimensional collapse amount can be measured by overlapping the video photographed by the television camera 20 on this digital map. If the amount of collapse can be measured, it is possible to determine the possibility of debris flow.
[0022]
Further, in the present invention, the image processing means 22 measures the amount of planar change before and after the change of the shape of the mountain using the video of the television camera 20, and uses the map information equipped with the GIS function. A three-dimensional collapse amount is measured by overlapping a video captured by a television camera on a digital map stored in the storage unit and stored in the storage unit.
[0023]
Here, GIS refers to the Giographic Information System.
If comprised in this way, the planar change amount and three-dimensional collapse amount of the shape of a mountain body can be measured.
[0024]
In the present invention, a plurality of laser light emitting elements are attached to the television camera 20, and simultaneously with the turning of the television camera, the laser is irradiated toward the cliff of the mountain body, and the reflected light is received by the image processing means 22 for processing. It is characterized by performing.
[0025]
If comprised in this way, it will become possible to grasp | ascertain the unevenness | corrugation of the surface part of a cliff clearly.
In the present invention, a near-infrared camera is used as the television camera 20.
[0026]
If constituted in this way, it becomes possible to shoot even at night.
In the present invention, the image processing means measures the amount of planar change before and after the change of the shape of the mountain using the video of the television camera.
[0027]
If comprised in this way, the planar variation | change_quantity of the shape of a mountain body can be measured by brightness pattern matching.
In the present invention, the image processing means has map information having a GIS function in the storage means, and overlaps a digital map stored in the storage means with a video photographed by a television camera, so It is characterized by measuring the amount of collapse.
[0028]
The storage means 23 stores brightness, lightness, and altitude data (digital map information). Therefore, the three-dimensional collapse amount can be measured by overlapping the video captured by the camera 20 on this digital map. If the amount of collapse can be measured, it is possible to determine the possibility of debris flow.
[0029]
In the present invention, the image processing means measures the amount of planar change before and after the change of the shape of the mountain using the video of the television camera, and stores map information equipped with a GIS function. The three-dimensional collapse amount is measured by overlapping a video captured by a television camera with a digital map stored in the storage means.
[0030]
If comprised in this way, the planar change amount and three-dimensional collapse amount of the shape of a mountain body can be measured.
[0031]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 2 is a block diagram showing an embodiment of the present invention. The same components as those in FIG. 1 are denoted by the same reference numerals. In the figure, reference numeral 20 denotes a plurality of CCTV cameras installed with respect to the mountain body 24. These cameras 20 are installed with respect to the mountain body 24, for example, near a cliff or in the vicinity of a sabo dam.
[0032]
Reference numeral 31 denotes an IP conversion apparatus that converts the NTSC signal output from the CCTV camera 30 into an IP signal, and reference numeral 32 denotes a conversion apparatus that receives the output from the IP conversion apparatus 31 and converts an electrical signal into an optical signal. Reference numeral 33 denotes an optical cable connected to the conversion device 32.
[0033]
Reference numeral 34 denotes a layer 3 switch (SW) that is connected to these optical cables 33, converts optical signals into electrical signals, and is connected to various devices. Reference numeral 35 denotes a management server connected to the layer 3 switch 34, and the storage means 23 shown in FIG. 1 is connected to the management server 35. A decoder 36 is connected to the layer 3 switch 34 and connects an IP signal to an NTSC signal. As the decoder 36, for example, an IP-decoder is used.
[0034]
An image processing apparatus 22a is connected to the decoder 36 and performs predetermined image processing on the video signal. The image processing device 22 a and the management server 25 constitute the image processing means 22 shown in FIG. 1, and a storage means 23 is connected to the image processing means 22. A client terminal 37 is connected to the layer 3 switch 34, and a VOD server 38 is connected to the image processing apparatus 22a and stores the image processing results. The other end of the VOD server 38 is connected to the layer 3 switch 34. The layer 3 switch 34, the management server 35, the storage means 23, the IP-decoder 36, the client terminal 37, the image processing device 22, and the VOD server 38 are provided in the sabo management center 15. The operation of the system configured as described above will be described as follows.
[0035]
On the site side, the mountain body 24 is constantly monitored by the CCTV camera 20. The IP conversion device 31 is a device that can convert video into IP and stream distribution, and receives a video signal from the CCTV camera 20. The output of the IP conversion device 31 enters the outdoor type conversion device 32, and a video signal is transmitted to the sabo management center 15 side device via the optical fiber 33.
[0036]
On the sabo management center 15 side, the video signal is received by the layer 3 switch 34, and the IP-converted video is decoded by the IP-decoder 36 into an NTSC signal. The image processing device 22a has a built-in image processing algorithm for detecting occurrence of collapse, and performs predetermined image processing on the video signal sent from the CCTV camera 20. As this image processing, for example, there is a process of detecting the occurrence of collapse by detecting a change in luminance of a moving part with respect to a part where the mountain body 24 is not moving.
[0037]
The analyzed data is sent to the management server 35. At the client terminal 37, the stream video is popped up and notified to the operator. Further, by sending a signal that a collapse has occurred from the image processing device 22 to the VOD server 38, it is possible to record a necessary part.
[0038]
As described above, according to this embodiment, it is possible to reliably detect the occurrence of collapse by using the CCTV camera 20 as the collapse information detection means.
FIG. 3 is a block diagram showing another embodiment of the present invention. 1 and 2 are denoted by the same reference numerals. In the figure, 20 is a plurality of CCTV cameras provided for observing a mountain body, for example, and 31 is an IP conversion device for converting an NTSC signal output from the CCTV camera 20 into an IP signal. The CCTV camera 20 and the IP device 31 are installed on the site. An optical cable 33 is connected to the output side of the IP device 31, and is connected to the sabo control center 15 by the optical cable 33.
[0039]
On the other hand, on the sabo management center 15 side, 35 is a management server, 23 is a storage means connected to the management server 35, and 22a is an image processing apparatus connected to the management server 35 and performing predetermined image processing. An IP-decoder 36 is connected to the optical cable 33 and converts an IP signal into an NTSC signal. The output of the IP-decoder 36 is connected to the image processing device 22a. A VOD server 38 stores image information.
[0040]
Reference numeral 40 denotes a LAN composed of an optical cable 33, to which a VOD server 38, a management server 35, an IP-decoder 36, and a client terminal 37 are connected. Reference numeral 41 denotes a firewall connected to the LAN 40. A firewall is a device that denies access by ordinary people who do not have a password. The output of the firewall 41 is connected to the LAN 42. 43 is a public server connected to the LAN 42. An operator who has not been rejected by the firewall 41 can access the public server 43 to view necessary information. The operation of the apparatus configured as described above will be described with reference to the flowchart of FIG.
[0041]
FIG. 4 is a flowchart showing the operation of the system of the present invention. First, the CCTV camera 20 photographs the cliff before the collapse (S1). The captured video is converted from an NTSC signal to an IP signal by the IP device 31 and then transmitted through the optical cable 33. The IP-decoder 36 converts the IP signal into an NTSC signal and then gives it to the image processing device 22a. The image processing device 22a stores this video information.
[0042]
Next, the image processing device 22a compares the next captured cliff video information with the previously stored cliff video information (S2). The comparison is performed by taking luminance pattern matching. Here, the image processing device 22a checks whether or not the images before and after the photographing match (S3). If they match, it indicates that no change has occurred on the cliff face, so the process returns to step S1 to continue shooting the cliff face.
[0043]
Here, when a pattern mismatch occurs in the preceding and succeeding images, the image processing device 22a detects the collapse of the cliff surface (S4). This collapse of the cliff is notified to the management server 35 as an alarm (S5). The management server 35 that has received the notification notifies the alarm output device (not shown) of the alarm and also notifies the client terminal 37 as necessary.
[0044]
Next, the image processing device 22a detects the moving part with respect to the non-moving part and measures the planar amount of collapse (S6). Since the image before collapse and the image after fall (back shadow portion) are stored in the image processing device 22a, the planar amount of collapse can be measured by comparing them. This collapsed area is notified from the image processing apparatus 22a to the management server 35 (S7). Alternatively, it is notified to the client terminal 37.
[0045]
If comprised in this way, the planar variation | change_quantity of the shape of a mountain body can be measured by the pattern matching of a brightness | luminance.
Next, the image processing device 22a detects the difference between the images before and after the collapse (S8). This difference is sent to the management server 35. The management server 35 accesses the storage means 23 and reads the digital map information. The digital map information stores longitude, latitude, and altitude data. Therefore, the management server 35 calculates the three-dimensional amount of cliff collapse by overlapping the difference in the video captured by the CCTV camera 20 with this digital map (S9). In this way, the three-dimensional collapse amount can be measured by overlapping the video captured by the CCTV camera 20 on the digital map. If the amount of collapse can be measured, it is possible to determine the possibility of debris flow. This collapse amount is notified from the management server 35 to an external display device, for example, the client terminal 37 (S10).
[0046]
In such a series of processing, the IP information captured by the CCTV camera 20 is stored in the VOD server 38. In this way, by accumulating the video as an IP video, it is possible to reduce the work load even in video status monitoring when a sudden event occurs.
[0047]
In a normal state, since there is no change in the cliff face, the CCTV camera 20 is always photographing the cliff face. It is assumed here that the cliff has collapsed. The CCTV camera 20 takes a picture of the cliff after the collapse.
[0048]
Here, a plurality of laser light emitting elements are attached to the CCTV camera 20, the laser is irradiated toward the cliff portion of the mountain body simultaneously with the turning of the CCTV camera 20, and the reflected light is received and processed by the image processing means. it can. According to this, it is possible to clearly grasp the unevenness of the surface portion of the cliff.
[0049]
Further, if a near-infrared camera is used as the CCTV camera 20, photographing can be performed at night.
Further, according to the present invention, a set of television cameras for monitoring mountain bodies and a plurality of image processing means for performing predetermined image processing on the basis of video signals from the television cameras are provided in the predicted disaster occurrence area. The sent information can be received by the sabo management center and the landslide disaster prediction can be collectively managed by the sabo management center. In this way, the disaster occurrence state can be collectively managed on the sabo management center side.
[0050]
(Additional remark 1) It comprises a television camera for mountain body monitoring and an image processing means for performing predetermined image processing based on a video signal from the television camera, and the image processing means receives the video signal from the television camera. An earth and sand disaster prediction system that detects the occurrence of a collapse by detecting the change in brightness of the moving part relative to the part where the mountain body is not moving.
[0051]
(Additional remark 2) The earth and sand disaster prediction system of Additional remark 1 characterized by memorize | storing the information image | photographed with the said television camera in a memory | storage means as an IP image | video.
(Supplementary note 3) The earth and sand disaster prediction system according to supplementary note 1, wherein the image processing unit measures a planar change amount before and after the change of the shape of the mountain using the video of the television camera.
[0052]
(Additional remark 4) The said image processing means has the map information carrying a GIS function in a memory | storage means, and overlaps the image image | photographed with the television camera on the digital map memorize | stored in this memory | storage means, By three-dimensionally The sediment disaster prediction system according to supplementary note 1, characterized by measuring a collapse amount.
[0053]
(Additional remark 5) The said image processing means measures the amount of planar changes before and after the change of the shape of the mountain using the video of the said TV camera, and has map information equipped with a GIS function in the storage means. The earth and sand disaster prediction system according to appendix 1, wherein a three-dimensional collapse amount is measured by overlapping a video photographed by a television camera on a digital map stored in the storage means.
[0054]
(Appendix 6) A plurality of laser light emitting elements are attached to the television camera, the laser is irradiated toward the cliff portion of the mountain body simultaneously with the turning of the television camera, and the reflected light is received and processed by the image processing means. The sediment disaster prediction system described in Appendix 1.
[0055]
(Supplementary note 7) The earth and sand disaster prediction system according to supplementary note 1, wherein a near-infrared camera is used as the television camera.
(Supplementary note 8) A plurality of sets of television cameras for monitoring mountain bodies and a plurality of image processing means for performing predetermined image processing based on video signals from the television cameras are provided in the predicted disaster occurrence area, and sent from these multiple systems. A landslide disaster prediction system that receives information at the sabo management center and collectively manages landslide prediction at the sabo management center.
[0056]
(Supplementary note 9) A television camera for monitoring mountain bodies and image processing means for performing predetermined image processing based on the video signal from the television camera, wherein the image processing means receives the video signal from the television camera. An earth and sand disaster prediction method characterized by detecting a collapse by detecting a change in luminance of a moving part relative to a part where the mountain body is not moving.
[0057]
(Supplementary note 10) The sediment disaster prediction method according to supplementary note 9, wherein the image processing means measures a planar change amount before and after the change of the shape of the mountain using the video of the television camera.
[0058]
(Additional remark 11) The said image processing means has map information carrying a GIS function in a memory | storage means, and overlaps the image | video image | photographed with the television camera on the digital map memorize | stored in this memory | storage means, By three-dimensionally The sediment disaster prediction method according to appendix 9, wherein the collapse amount is measured.
[0059]
(Supplementary note 12) The image processing means measures the amount of planar change before and after the change of the shape of the mountain using the video of the TV camera, and has map information equipped with a GIS function in the storage means. The sediment disaster prediction method according to appendix 9, wherein a three-dimensional collapse amount is measured by overlapping a video photographed by a television camera with a digital map stored in the storage means.
[0060]
【The invention's effect】
As described above, according to the present invention, the following effects can be obtained.
(1) According to the first aspect of the present invention, it is possible to measure a planar change amount and a three-dimensional collapse amount of a mountain shape .
[0061]
(2) According to the second aspect of the present invention, it is possible to measure a three-dimensional collapse amount by overlapping a video captured by a television camera on a digital map.
[0062]
Thus, according to the present invention, it is possible to provide a landslide disaster prediction system and a prediction method capable of reliably predicting the occurrence of a landslide disaster and reducing the workload of work contents.
[Brief description of the drawings]
FIG. 1 is a principle block diagram of the present invention.
FIG. 2 is a block diagram showing an embodiment of the present invention.
FIG. 3 is a block diagram showing another embodiment of the present invention.
FIG. 4 is a flowchart showing the operation of the system of the present invention.
FIG. 5 is a conceptual diagram of a sabo monitoring system.
[Explanation of symbols]
20 TV camera 21 cable 22 image processing means 23 storage means

Claims (2)

A TV camera for mountain body monitoring,
Image processing means for performing predetermined image processing based on a video signal from the television camera,
The image processing means measures the amount of planar change before and after the change of the shape of the mountain using the video signal from the TV camera, and has map information equipped with a GIS function in the storage means, A sediment disaster prediction system characterized in that a three-dimensional collapse amount is measured by overlapping a video photographed by the television camera with a digital map stored in the storage means. A TV camera for mountain body monitoring,
Image processing means for performing predetermined image processing based on a video signal from the television camera,
The image processing means measures the amount of planar change before and after the change of the shape of the mountain using the video signal from the TV camera, and has map information equipped with a GIS function in the storage means, A sediment disaster prediction method characterized in that a three-dimensional collapse amount is measured by overlapping a video photographed by the television camera on a digital map stored in the storage means .

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