CN115731361A - Geological disaster enhanced display method based on laser LiDAR data - Google Patents

Abstract

The invention discloses a geological disaster enhanced display method based on laser LiDAR data, which comprises the following steps: loading DEM data of a research area and generating a gradient map, a positive opening map and an SVF map in RVT software; setting the RVT software mixed mode as Nomal and the opacity as 100% by using the gradient map as a base map to obtain a processed base map; fusing the processed base map and the positive opening map by adopting a multiplex mode in a mixing module, and setting the opacity to be 70% to obtain a result map; fusing the result image and the SVF image by adopting a Screen mode in a mixing module, and setting the opacity to be 50% to obtain a final result image; and carrying out geological disaster remote sensing identification according to the final result map. The data storage capacity is small; the data processing flow is relatively simple, and the identification characteristics of the geological disasters are enhanced in a targeted manner; and the application limitation caused by the defects of the image layer is broken through.

Description

Geological disaster enhancement display method based on laser LiDAR data

Technical Field

The invention relates to the technical field of information acquisition and processing, in particular to a geological disaster enhanced display method based on laser LiDAR data.

Background

China is one of the countries with the most serious geological disasters and the most threatened population in the world. According to data display of natural resource department, the number of potential geological disaster points found in China reaches more than 33 thousands by the end of 2020. 70% of more serious geological disasters which occur in the last decade are out of the range of the found hidden dangers, and have the common characteristics of high position and high concealment, and are difficult to find by traditional manual investigation and traditional means. With the development of remote sensing technology, the airborne LiDAR technology provides a new solution for the early identification of high-position and high-concealment geological disasters. The airborne LiDAR has the advantages of penetrating through vegetation, acquiring real ground elevation data information, revealing slope historical damage and the like. After the point cloud data acquired using onboard LiDAR is filtered to obtain real earth model (DEM) data, it is typically visualized as a gray image or color image to help identify potential geological hazards in the area of interest.

The current mainstream visualization method comprises a mountain shadow Map and a Red Relief Image Map (RRIM) Map, which have different degrees of defects in the enhanced display effect of the geological disaster.

One of the most common visualization methods is the mountain shadow map

The proposed and established standards have been used to date,the principle is that the distribution, fluctuation and morphological characteristics of the landform realize a stereoscopic enhanced display by utilizing the continuous change of the brightness degree of the surface generated by the irradiation of the virtual sunlight to the ground at a specific angle.

However, a single light beam cannot reveal a linear structure parallel to the light beam, if the direction of the light source is changed, a completely inverted concave-convex feeling is obtained, small terrain can be shaded by shadows, and in geological disaster identification work, mountain shadows in multiple directions are often switched to avoid identification omission, so that the identification process and data storage become more complicated.

The Red Relief Image Map (RRIM) is proposed by foreign scholars Chiba and the like and is formed by multiplying three landform element layers of terrain gradient, positive opening and negative opening. The method comprises the steps of firstly calculating a terrain positive opening degree, a terrain negative opening degree and a terrain gradient in SAGA and Arcgis respectively according to a DEM, then calculating a ridge-valley index I by adopting a grid calculator, superposing gradient layers on ridge-valley index layers, adjusting color bands and transparencies of the two layers, and finally obtaining an RRIM image. The technical method has the advantages of more complicated processing flow and higher cost; the method is used for enhancing and displaying the terrains in the archaeological region, and professional enhancing and displaying research is not carried out on the identification characteristics of various geological disasters.

Disclosure of Invention

Aiming at the defects in the prior art, the geological disaster enhancement display method based on the laser LiDAR data solves the problems that the mountain shadow under different illumination conditions loses disaster boundary details, the mountain shadow data storage capacity in multiple directions is large, and the identification characteristics of the geological disaster are not subjected to special enhancement processing.

In order to achieve the purpose of the invention, the invention adopts the technical scheme that: a geological disaster enhanced display method based on laser LiDAR data comprises the following steps:

s1, loading DEM data of a research area and generating a gradient map, a positive opening map and an SVF map in RVT software;

s2, using the gradient graph as a base graph, setting the RVT software mixed mode as Nomal, and setting the opacity as 100% to obtain a processed base graph;

s3, fusing the processed base map and the positive opening map in a multiplex mode in a mixing module, and setting the opacity to be 70% to obtain a result map;

s4, fusing the result image and the SVF image by adopting a Screen mode in a mixing module, and setting the opacity to be 50% to obtain a final result image;

and S5, carrying out geological disaster remote sensing identification according to the final result image.

The beneficial effects of the invention are as follows:

1. the problem of single light source direction massif shadow lose disaster boundary detail and a plurality of light source direction massif shadow data memory volume is big is solved.

2. The method solves the problems that the RRIM graph data processing flow is complicated and the characteristic information of the geological disaster is not exclusively enhanced in the prior art.

3. The defects of a plurality of visual factor layers are made up, and application limitation caused by the defects of the layers is broken through.

Drawings

FIG. 1 is a flow chart of the present invention.

Detailed Description

The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.

As shown in fig. 1, a method for enhancing display of geological disasters based on laser LiDAR data comprises the following steps:

s1, loading DEM data of a research area and generating a gradient map, a positive opening map and an SVF map in RVT software;

s2, using the slope diagram as a base diagram, setting the RVT software mixed mode as Nomal, setting the opacity as 100%, and obtaining a processed base diagram;

s3, fusing the processed base map and the positive opening map by adopting a multiplex mode in a mixing module, and setting the opacity to be 70% to obtain a result map;

s4, fusing the result image and the SVF image by adopting a Screen mode in a mixing module, and setting the opacity to be 50% to obtain a final result image;

and S5, carrying out geological disaster remote sensing identification according to the final result image.

In one embodiment of the invention, the method is applied to landslide, collapse and debris flow identification and information extraction, and better visualization enhancement effect is obtained compared with mountain shadow, SVF and RRIM.

In remote sensing interpretation and identification of landslide, microscopical features such as landslide walls, landslide sills, humps, local bulges and the like left on the earth surface after deformation and damage of landslide are very important interpretation marks. The point cloud data is obtained by using an airborne LiDAR technology, after a DEM is obtained after vegetation is filtered, three mainstream visualization methods of a mountain shadow map, an SVF map and an RRIM map are selected to carry out remote sensing interpretation comparison with the result map layer. For an interpreter with rich interpretation experience, the mountain shadow map can preliminarily identify the existence of potential landslide bodies, but has the problems that the landslide boundary is shielded by illumination shadow, cracks are not obvious and the like; the SVF image eliminates the influence of shadow, and gives black tone to the landslide boundary to achieve the enhancement effect, but the large-area black image elements and the lack of plasticity influence the proceeding of the identification work; the RRIM picture changes the color tone into red, the enhancement of the landslide wall is shown as dark red, the enhancement of the flat ground is shown as nearly white, the effect is good, but the steps are complicated. The result layer of the invention not only supplements the plasticity of SVF, but also improves the performance of the crack and the secondary sliding trace in the layer, and the result is shown in Table 1:

TABLE 1

In addition to landslide, the main type of geological disaster, collapse is also common and one of the more influential types of geological disaster. The collapse identification elements comprise dangerous rock masses before collapse and collapsed accumulation bodies after collapse.

Three mainstream visualization methods, namely a mountain shadow map, an SVF map and an RRIM map, are selected to carry out remote sensing interpretation comparison with the result map layer of the invention. The mountain shadow map is a commonly used mountain shadow map with a 45-degree elevation angle and a 315-degree illumination angle, and the shadow caused by illumination directly interferes with accurate identification of the boundaries of dangerous rock masses and collapsed accumulation bodies; the layer after SVF visualization processing removes the influence of illumination, can roughly distinguish the collapsed form, the excessive black pixels cause the low brightness of the whole image, and the contrast of the image needs to be further enhanced; the RRIM image has a good reinforcing effect on the exposed area of the dangerous rock mass and has insufficient characteristic reinforcing performance on the collapsed accumulation body; in the result map layer of the invention, the part of the mountain shadow map where the edge details are shielded is highlighted, and simultaneously has higher brightness than SVF and stronger layering sense than RRIM map, this method not only enhances the outline details of dangerous rock and collapse accumulation, but also weakens the identification interference of other elements of the slope on the collapse, and the result is shown in Table 2:

TABLE 2

The debris flow is one of common geological disasters in mountainous areas and has the characteristics of large impact destructive power, rapid development, strong flow capacity and the like. When a disaster is interpreted as a debris flow on a remote sensing image, the following three conditions are generally required to be met: (1) good catchment condition (2) collapse slide material source, rich channel material source (3) channel mouth development with pile fan. The identification of a formation area and a stacking area is crucial, the formation area is generally in a ladle shape, a hillside is steep, and loose solid matters are abundant; the deposition area is positioned at the outlet of the valley, the longitudinal slope is gentle, a flood fan or a rushing-out cone is often formed, the fan surface has no fixed groove, and the fan surface is mostly in a diffuse flow state.

Remote sensing interpretation comparison is carried out by three mainstream visualization methods of mountain shadow, SVF and RRIM. The mountain shadow map only enables the color tone of the accumulation area to be obviously different from the color tone of the periphery, and the enhancement effect is gradually weakened from the channel of the flow-through area to the formation area; the SVF image eliminates the influence of illumination, morphological characteristics of the whole debris flow are initially displayed, but the brightness of the SVF image is too low, and the contrast of the SVF image needs to be further enhanced; the RRIM image sets the main tone to be red, the enhancement effect is similar to that of the SVF image, but the process is more complicated; in the result map layer of the present invention, the identification of the multiple collapsed accumulations in the formation area is not disturbed by the shadow, the extraction of finer boundaries is helpful for the accurate calculation of the amount of the source, the channels in the circulation area have a clearer outline representation, the accumulation area is fan-shaped, and a plurality of undulating ridges approximately parallel to the channels exist, so that the river ahead is redirected, and the result is shown in table 3:

TABLE 3

The fusion map layer obtained by the method realizes an enhancement effect on the identification characteristics of various geological disasters, integrates the enhancement effects of various Visualization factors such as gradient, sky vision field factors and normal opening degree on different geological disaster characteristic details in one result map layer, and can be operated in one key mode through Relief Visualization Toolbox software, so that the problems of data redundancy, difficulty in storage and complex steps are solved, and meanwhile, the detail characteristic elements required in geological disaster identification are enhanced.

The method solves the problems that the mountain shadow in the direction of a single light source loses disaster boundary details and the mountain shadow data storage capacity in the directions of a plurality of light sources is large; the problems that in the prior art, the RRIM image data processing flow is complicated, and the characteristic information of the geological disaster is not specially enhanced are solved; the defects of a plurality of visual factor layers are made up, and application limitation caused by the defects of the layers is broken through.

Claims (1)

1. A geological disaster enhanced display method based on laser LiDAR data is characterized by comprising the following steps:

s1, loading DEM data of a research area and generating a gradient map, a positive opening map and an SVF map in RVT software;

s2, using the gradient graph as a base graph, setting the RVT software mixed mode as Nomal, and setting the opacity as 100% to obtain a processed base graph;

s3, fusing the processed base map and the positive opening map by adopting a multiplex mode in a mixing module, and setting the opacity to be 70% to obtain a result map;

s4, fusing the result image and the SVF image by adopting a Screen mode in a mixing module, and setting the opacity to be 50% to obtain a final result image;

and S5, carrying out geological disaster remote sensing identification according to the final result image.

Images