A method for identifying a high-risk avalanche gully

Abstract

The application discloses a kind of high-risk avalanche groove identification method, it is related to avalanche identification technical field, comprising:1, the area of each groove is calculated to snow area;2, the average slope of each groove snow area and the area of each groove snow area are calculated, and the area ratio of each groove snow area and snow area is obtained;3, when the area ratio is greater than or equal to the set ratio, and the average slope is greater than or equal to the set slope, determine that the corresponding groove is high-risk avalanche groove.The method combines the slope of snow area and the area ratio of snow area and snow area to identify avalanche groove, not only directly considers the geomorphic main control factor of groove type avalanche, but also can identify the risk size of groove type avalanche in the to-be-identified basin through high-precision remote sensing data, determines the target area for the installation of subsequent avalanche monitoring instrument, solves the technical problems that the existing identification method is not comprehensive, the identification difficulty is big, the cost is higher and it is not convenient for subsequent installation monitoring instrument.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of avalanche identification, in particular to a high-risk avalanche gully identification method, which is especially suitable for effective identification of high-risk avalanche gullies in high-cold and high-altitude mountainous areas. BACKGROUND

[0002] An avalanche is a snow disaster phenomenon that occurs when the snow layer slides along the bottom or intermediate discontinuous layer under external disturbance factors. In recent years, under the background of climate change and human engineering activities, snow avalanche disasters in high mountainous areas have occurred frequently and are showing an increasing trend. Among them, compared with slope-type avalanches, gully-type avalanches are the most widely developed, and are larger in scale and more devastating, so early identification of such disasters has become one of the urgent problems of disaster prevention and mitigation for important roads and major projects being planned.

[0003] Gully-type avalanches often lead to major disasters such as road interruptions and vehicle and human casualties. Gully-type avalanches show a strong unexpectedness and occur frequently in winter and spring, severely restricting the development of regional economy and the safety of vehicles and personnel. Such avalanches often show the characteristics of repeated occurrence in the same gully, with significant repeatability. Therefore, in addition to the amount of snowfall, geomorphic factors become an important basis for identifying gully-type avalanches.

[0004] In order to better prevent snow avalanche disasters and reduce losses, it is necessary to scientifically and accurately identify early snow avalanche disasters, and there are mainly two identification methods at the present stage:

[0005] 1. An avalanche-prone evaluation system is constructed by using many factors such as snow thickness, water content, depth and type of frost, density, size and shape of snow crystals, snow layer structure, hardness, snow temperature and temperature gradient, slope, vegetation type and coverage, wind, snowfall and blowing snow, length of stable snow period, terrain cutting depth, and other external factors (such as human and animal walking, rock rolling, etc.), and finally a high-prone avalanche gully is identified according to the weight scoring method. However, this method has the technical problems of difficulty in determining the influencing factors and incompleteness or weakening of the importance of the main controlling factors.

[0006] 2. High-prone avalanche gullies are determined by installing radar, high-definition cameras and other monitoring instruments in the avalanche gully, or by using SAR remote sensing images combined with avalanche traces. This method has high precision, but has the problems of difficulty in large-area popularization and application, difficulty in remote sensing identification of avalanche traces, high cost, and incompleteness of important main controlling factors.

[0007] In addition, it is found that the trench-type avalanches often occur repeatedly in the same area, so the development of such avalanches is controlled to a large extent by the landform. It is found in practice that the channel of the trench-type avalanche has obvious characteristics of snow collection area, snow accumulation area, flow-through area and accumulation area, wherein the snow collection area, flow-through area and accumulation area are located at the top, middle and bottom of the slope respectively, and the snow accumulation area is located in the snow collection area. The snow collection area of the trench-type avalanche is similar to the formation area of the debris flow channel, and plays an important role in the process of avalanche formation. At the same time, through the statistics of 47 avalanches in Yixiula Mountain, Bokonla Mountain and Galongla Mountain, it is found that the slope of the snow accumulation area and the area ratio of the snow collection area to the snow accumulation area can well represent the occurrence degree of the trench-type avalanche. Therefore, it is necessary to further consider the slope of the snow accumulation area and the area ratio of the snow collection area to the snow accumulation area on the basis of the existing specification standard, and a new technology for identifying high-risk avalanche trench is proposed, so as to more accurately, conveniently and efficiently identify the high-risk avalanche trench. SUMMARY

[0008] The purpose of the present application is to overcome the above-mentioned problems existing in the prior art, and to provide a method for identifying high-risk avalanche trench, which combines the slope of the snow accumulation area and the area ratio of the snow collection area to the snow accumulation area to identify the avalanche trench. Not only the main controlling factor of the landform of the trench-type avalanche is directly considered, but also the risk degree of the trench-type avalanche in the to-be-identified basin can be identified from a macroscopic point of view through high-precision remote sensing data, and the target area for the installation of subsequent avalanche monitoring instruments is determined, thereby solving the technical problems of the existing identification method, such as incomplete main controlling indicators of landform, high identification difficulty, high cost and inconvenience for subsequent installation of monitoring instruments.

[0009] To achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows:

[0010] A method for identifying high-risk avalanche trench, comprising the following steps:

[0011] Step S1, obtaining high-precision DEM elevation data and multi-period remote sensing image data in the mountain ridge line on both sides of the road along the to-be-identified area;

[0012] Step S2, finding all the trenches and the heads of the trenches in the mountain ridge line on both sides according to the high-precision DEM elevation data or the multi-period remote sensing image data, determining the snow collection area and the flow-through area of each trench according to the head, and calculating the snow collection area A （汇雪区） of each trench;

[0013] Step S3, screening the area with relatively gentle and concave topography in the snow collection area as the snow accumulation area, calculating the average slope i （积雪区） of the snow accumulation area of each trench and the snow accumulation area A （积雪区） of each trench, and obtaining the area ratio of the snow collection area to the snow accumulation area in each trench ;

[0014] Step S4, when the area ratio of the snow collection area and the snow accumulation area is greater than or equal to a set ratio, and the average slope i of the snow accumulation area is greater than or equal to a set slope, it is determined that the corresponding gully is a high-risk avalanche gully. （积雪区） When the area ratio of the snow collection area and the snow accumulation area is greater than or equal to a set ratio, and the average slope i of the snow accumulation area is greater than or equal to a set slope, it is determined that the corresponding gully is a high-risk avalanche gully.

[0015] In step S1, the high-precision DEM elevation data is ASTER GDEM data obtained through a geographic spatial data cloud platform, or DEM data obtained through an unmanned aerial vehicle through field investigation; and the multi-period remote sensing image data is Sentinel data obtained through a Google Earth platform or a European Space Agency platform.

[0016] In step S1, the resolution of the high-precision DEM elevation data is 30 m or 12.5 m.

[0017] In step S2, the method for determining the gully head in the gully according to the high-precision DEM elevation data is: first, according to the high-precision DEM elevation data, the gully is segmented every 100 m, the slope of each segment from upstream to downstream is calculated, and then the sudden inflection point where the slope changes from small to large from upstream to downstream is found, which is the gully head.

[0018] In step S2, the method for determining the gully head in the gully according to the multi-period remote sensing image data is: according to the multi-period remote sensing image data, the turning point where the main gully of the gully changes from nothing to something from upstream to downstream is found, which is the gully head.

[0019] In step S2, the calculation method of the snow collection area A （汇雪区） is: first, the snow collection area range is circled according to the multi-period remote sensing image data in the ArcGIS software, then the projection coordinates are assigned, and the area is calculated through the area calculation module of the field calculator in the attribute table.

[0020] In step S3, the snow accumulation area is an area with a slope of 20°-35° and a concave groove topography in the snow collection area.

[0021] In step S4, the set ratio is 1.71, which is based on the statistical value of 25% quantile of the occurred avalanches; and the set slope is 30°, which is based on the comprehensive statistics of the occurred avalanches.

[0022] The advantages of the present application are:

[0023] ​1. According to the characteristics of the snow accumulation area, the snow accumulation area, the flow-through area and the accumulation area of the groove type avalanche, the present application carries out in-depth research from the area ratio of the snow accumulation area and the snow accumulation area and the average slope of the snow accumulation area. Not only the geomorphic main control factor of the groove type avalanche is directly considered, but also the risk size of the groove type avalanche in the to-be-identified basin can be identified from the macro through high-precision remote sensing data. The present application has the advantages of high identification accuracy, simple identification process, low identification cost and convenience for determining the target area of the subsequent avalanche monitoring instrument.

[0024] 2. The research object and scene identified by the present application are relatively special. Since large-scale groove type avalanche disasters occur repeatedly in space, it is particularly important to scientifically predict the avalanche groove along the important road in the high-cold high-altitude engineering area at the present stage. Then, based on the characteristics of 47 grooves of Yixiula Mountain, Bukongla Mountain and Galongla Mountain, the geomorphic characteristics of the grooves on both sides of the mountain slope along the important road are studied, the head position of the corresponding groove is identified, the snow accumulation area and the snow accumulation area of the groove type avalanche are further determined, the ratio index of the snow accumulation area and the snow accumulation area for representing the size of the snow accumulation area is calculated, and the high-risk avalanche groove identification is carried out according to the statistical identification index threshold, which is beneficial to more accurately realize the effective identification of the groove type avalanche disaster.

[0025] 3. The high-precision DEM elevation data in the present application is set as ASTER GDEM data which can be obtained through geographic spatial data cloud platform, and DEM data with higher precision can also be obtained through on-site investigation unmanned aerial vehicle. The advantage is that multi-channel data source adapts to more scenes, especially the open source DEM data is convenient and fast to obtain and has low cost, which can overcome the problem of difficult on-site measurement in high-altitude unmanned area.

[0026] 4. The determination method of the head in the present application can find the turning point of the main groove profile from upstream to downstream channel from nothing to something according to the remote sensing image, and can also find the mutation inflection point of the slope from upstream to downstream channel by analyzing the channel slope. The two methods can determine the position of the head respectively and comprehensively determine, which ensures the reliability of the determination of the head position and has strong operability.

[0027] 5. The threshold index of high risk in the present application is determined as , In particular, the snow collection area provides the necessary material conditions for the formation of avalanches, and the relatively flat groove area above the head is the snow accumulation area for the initiation of avalanches. The ratio of the snow collection area to the snow accumulation area is derived from the median value of the statistical data of 47 avalanches in Yixiushan Mountain, Bukon Mountain and Galong Mountain, and the slope threshold is derived from industry standards and basic understanding. The advantage is that it combines the slope indicators in existing research and industry standard specifications, and focuses on the key control indicators that can represent the supply source of the groove type avalanche based on field cases . BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 is a flowchart of the present application;

[0029] Figure 2 is a statistical graph based on 47 avalanches in Yixiushan Mountain, Bukon Mountain and Galong Mountain. DETAILED DESCRIPTION

[0030] Example 1

[0031] As shown in Figure 1 , the present application provides a method for identifying high-risk avalanche grooves, which comprises the following steps:

[0032] Step S1, obtaining high-precision DEM elevation data and multi-period remote sensing image data within the ridge line on both sides of the road along the identified area.

[0033] Specifically, the resolution of the above-mentioned high-precision DEM elevation data is 30m or 12.5m, and the high-precision DEM elevation data can be ASTER GDEM data obtained through geographic spatial data cloud platform, etc., or DEM data with higher precision obtained through on-site investigation and unmanned aerial vehicle; the multi-period remote sensing image data is Sentinel data obtained through Google Earth platform or European Space Agency platform.

[0034] Step S2, finding out all the grooves and the heads in each groove within the ridge line on both sides according to the high-precision DEM elevation data or the multi-period remote sensing image data, determining the snow collection area and the flow-through area of each groove according to the head, and calculating the snow collection area A （汇雪区） .

[0035] Specifically, the calculation method of the above-mentioned snow collection area A （汇雪区） is as follows: first, the range of the snow collection area is circled in the ArcGIS software according to the multi-period remote sensing image data, then the projected coordinates are assigned, and the area is calculated through the area calculation module of the field calculator in the attribute table. It should be noted that this calculation method is a conventional technical means, and will not be described in detail.

[0036] Step S3, screening the area with relatively gentle and concave topography in the snow collection area as the snow accumulation area, calculating the average slope i of each groove snow accumulation area （积雪区） and the snow accumulation area A of each groove （积雪区） and obtaining the area ratio of the snow collection area to the snow accumulation area in each groove .

[0037] Specifically, the snow accumulation area is an area with a slope of 20° to 35° and a concave topography in the snow collection area.

[0038] Step S4, when the area ratio of the snow collection area to the snow accumulation area is greater than or equal to a set ratio, and the average slope i of the snow accumulation area （积雪区） is greater than or equal to a set slope, it is determined that the corresponding groove is a high-risk avalanche groove, indicating that the small watershed is at high risk of groove-type avalanche, and the possibility of large-scale avalanche disaster in winter and spring in the future is higher.

[0039] Specifically, the set ratio is 1.71, which is based on the 25% quantile of the statistical value of 47 avalanches in Yixiulashan, Bukunlashan and Galonglashan; the set slope is 30°, which is based on the comprehensive statistics of the data of the avalanches that have occurred.

[0040] According to a preferred embodiment of the present embodiment, in step S2, the position of the gully head can be determined by two methods, as follows:

[0041] First: determining the position of the gully head in the gully according to high-precision DEM elevation data, the specific method being: first, according to the high-precision DEM elevation data, the gully is segmented every 100m, the slope of each segment from upstream to downstream is calculated, and then the sudden inflection point where the slope changes from small to large from upstream to downstream is found, which is the gully head. It should be noted that the method for calculating the slope of each segment is a conventional technical means and will not be described here.

[0042] Second: determining the position of the gully head in the gully according to multi-period remote sensing image data, the specific method being: finding the turning point of the main gully from no to have from upstream to downstream according to multi-period remote sensing image data, which is the gully head.

[0043] It should be noted that in actual application, the position of the gully head can also be determined comprehensively according to the above two methods.

[0044] The identification method in this invention is applicable to gully-type avalanches, i.e., gullies with clearly defined snow catchment areas, snow accumulation areas, flow areas, and deposition areas. This method identifies whether gullies on both sides of the road are high-risk avalanche gullies by comprehensively considering the ratio of the snow catchment area to the snow accumulation area, as well as the average slope of the snow accumulation area. It is more accurate, simpler, lower in cost, and more practical.

[0045] Example 2

[0046] This embodiment verifies the identification method of Embodiment 1. The specific process is as follows:

[0047] S1. Centered on the sections along National Highway 219 where avalanches #1 and #2 occurred, DEM elevation data with a resolution of 12.5m was acquired, covering the avalanche gullies (from the ridges on both sides of the Gongrigabu River) of avalanches #1 and #2. Additionally, high-resolution remote sensing imagery of the gullies was obtained using Google Earth.

[0048] S2, such as Figure 1 As shown, the location of the gully head within the gully was determined using remote sensing imagery. The calculated area of ​​the snow catchment area of ​​the No. 1 avalanche gully located on the right bank of the Gongrigabu River was 54,657 m², the snow accumulation area was 31,939 m², and the average slope of the snow accumulation area was 35.71°. The area of ​​the snow catchment area of ​​the No. 2 avalanche gully located on the right bank of the Gongrigabu River was 156,590 m², the snow accumulation area was 76,214 m², and the average slope was 32.21°.

[0049] S3, such as Figure 2 As shown, the area ratio of the snow catchment area to the snow accumulation area of ​​avalanche gully #1 was calculated. The ratio of the area of ​​the snow catchment area to the area of ​​the snow accumulation area in avalanche gully #2 is 1.71. It is 2.05.

[0050] S4. Based on the results of S2 and S3, the #1 avalanche gully... The slope is 1.71, satisfying the condition of being greater than or equal to 1.71; the slope of the snow-covered area is 35.71°, satisfying the condition of being greater than or equal to 30°. (Avalanche gully #2) The value is 2.05, which meets the condition of being greater than or equal to 1.71; the slope of the snow-covered area is 32.21°, which meets the condition of being greater than or equal to 30°. Therefore, both avalanche gullies #1 and #2 are identified as high-risk avalanche gullies, thus proving that the accuracy of the present invention is higher.

[0051] The above merely provides a specific implementation of the present application, and any feature disclosed in the specification can be replaced by other equivalent or similar purpose replacement features unless specifically stated; all features disclosed, or steps in all methods or processes, can be combined in any manner unless mutually exclusive features and / or steps.

Claims

1. A method of identifying high-risk avalanche gullies, characterized in that The method comprises the following steps: Step S1, obtaining high-precision DEM elevation data and multi-period remote sensing image data in the ridge line on both sides of the identified area road; Step S2, find out all the gullies and the gully heads in the two side ridge lines according to the high-precision DEM elevation data or multi-period remote sensing image data, determine the snow collection area and flow-through area of each gully according to the gully head, and calculate the snow collection area A of each gully （汇雪区） ; Step S3, screening the area with relatively gentle and concave topography in the snow collection area as the snow accumulation area, the snow accumulation area is the area with 20°~35° slope and concave topography in the snow collection area, the average slope i of each groove snow accumulation area is calculated （积雪区） and the snow accumulation area A of each groove （积雪区） , and the area ratio of the snow collection area to the snow accumulation area in each groove is obtained ; Step S4, when the area ratio of the accumulation area to the snow accumulation area is greater than or equal to a set ratio, and the average slope i of the snow accumulation area is greater than or equal to a set slope, the corresponding gully is determined as a high-risk snow avalanche gully. （积雪区） Step S4, when the area ratio of the accumulation area to the snow accumulation area is greater than or equal to a set ratio, and the average slope i of the snow accumulation area is greater than or equal to a set slope, the corresponding gully is determined as a high-risk snow avalanche gully.​ In step S4, the ratio is set to 1.71, which is based on the statistical value of 25% quantile of the occurred avalanches; the slope is set to 30°, which is based on the comprehensive statistics of the occurred avalanches.

2. The method of claim 1, wherein: In step S1, the high-precision DEM elevation data is ASTER GDEM data obtained through a geographic spatial data cloud platform, or DEM data obtained through an unmanned aerial vehicle by field investigation; the multi-period remote sensing image data is Sentinel data obtained through a Google Earth platform or a European Space Agency platform.

3. The method of claim 1, wherein: In step S1, the resolution of the high-precision DEM elevation data is 30 m or 12.5 m.

4. The method of claim 1, wherein: In step S2, the method for determining the gully head in the gully according to the high-precision DEM elevation data is: first, according to the high-precision DEM elevation data, the gully is segmented every 100 m, the slope of each segment from upstream to downstream is calculated, and then the sudden inflection point where the slope changes from small to large from upstream to downstream is found, which is the gully head.

5. The method of claim 1, wherein: In step S2, the method for determining the gully head in the gully according to the multi-period remote sensing image data is: according to the multi-period remote sensing image data, the turning point of the main gully from nothing to something from upstream to downstream is found, which is the gully head.

6. The method of claim 1, wherein: In step S2, the area A of the snow collection area （汇雪区） The calculation method is as follows: first, the range of the snow collection area is determined according to multi-period remote sensing image data in ArcGIS software, then the area is calculated through the area calculation module of the field calculator in the attribute table after assigning the projection coordinates.

Images