CN111551956B - Geological disaster detection and identification method based on airborne laser radar - Google Patents

Geological disaster detection and identification method based on airborne laser radar Download PDF

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CN111551956B
CN111551956B CN202010601466.2A CN202010601466A CN111551956B CN 111551956 B CN111551956 B CN 111551956B CN 202010601466 A CN202010601466 A CN 202010601466A CN 111551956 B CN111551956 B CN 111551956B
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point cloud
grid
surface point
laser radar
airborne laser
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CN111551956A (en
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谭德军
王勇
任世聪
宋强辉
刘满乾
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Chongqing Institute of Geology and Mineral Resources
Army Service Academy of PLA
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88Lidar systems specially adapted for specific applications
    • G01S17/89Lidar systems specially adapted for specific applications for mapping or imaging
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02ATECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
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Abstract

The invention belongs to the technical field of address disaster detection, and particularly relates to a geological disaster detection and identification method based on an airborne laser radar, which comprises the following steps: an acquisition step, acquiring environmental point cloud data; a classification step, classifying the environmental point cloud data according to the surface point cloud and the interference point cloud, and extracting the surface point cloud; a delineating step, namely performing area delineation on the ground surface point cloud by using a preset grid, and performing two-dimensional gridding processing on the ground surface point cloud; encrypting, namely calculating the number of the surface point clouds in each grid, and when the number of the surface point clouds in each grid is less than N, performing surface point cloud density increasing processing on the grids according to a preset algorithm; and a display step, namely outputting and displaying the ground surface point cloud after the density increasing treatment. By using the method, the earth surface state can be detected more accurately.

Description

基于机载激光雷达的一种地质灾害探测识别方法A Geological Hazard Detection and Identification Method Based on Airborne Lidar

技术领域technical field

本发明属于地址灾害探测技术领域,尤其涉及基于机载激光雷达的一种地质灾害探测识别方法。The invention belongs to the technical field of address disaster detection, in particular to a geological disaster detection and identification method based on airborne laser radar.

背景技术Background technique

目前,新技术在地质灾害防治工作中应用得越来越广泛,高分辨率遥感技术、无人机倾斜摄影技术、insar技术、机载激光雷达技术等遥感探测技术在地质灾害识别与监测中应用的越来越广。At present, new technologies are being used more and more widely in geological disaster prevention and control. High-resolution remote sensing technology, UAV oblique photography technology, insar technology, airborne lidar technology and other remote sensing detection technologies are used in geological disaster identification and monitoring. more and more widely.

但是各种方法都有技术瓶颈,尤其是在高植被覆盖的西南山区,受植被的影响很多识别方法都存在不同的技术瓶颈。主要表现为:(1)高分遥感技术主要是解决平面二维识别,通过建立遥感解译标志进行地质灾害识别,对危岩崩塌主要是通过解译崩塌范围进行识别,无法对危岩体进行识别和量测。(2)无人机倾斜摄影测量实现了三维识别,可以获取危岩体和崩塌范围,实现危岩体和崩塌范围的识别和量测,但是无法除去植被信息,获取原始的地表信息。(3)insar技术主要受地形的影响,受地形遮挡,存在数据盲区,虽然具有一定的植被穿透能力,主要缺点是空间分辨率低,存在数据盲区。(4)无人机机载激光雷达技术,相对于其余三种技术具有很强的优势,主要缺点是设备昂贵,植被还是存在一定的影响,高植被覆盖区还是存在部分地面点不足,影响判别。However, various methods have technical bottlenecks, especially in the southwestern mountainous areas covered by high vegetation, many identification methods have different technical bottlenecks due to the influence of vegetation. The main performances are as follows: (1) High-resolution remote sensing technology mainly solves the problem of two-dimensional identification of planes, and identifies geological hazards by establishing remote sensing interpretation marks. Identify and measure. (2) UAV oblique photogrammetry realizes three-dimensional identification, which can obtain dangerous rock mass and collapse range, and realize identification and measurement of dangerous rock mass and collapse range, but it cannot remove vegetation information and obtain original surface information. (3) The insar technology is mainly affected by the terrain, blocked by the terrain, and has data blind spots. Although it has a certain ability to penetrate vegetation, the main disadvantage is that the spatial resolution is low, and there are data blind spots. (4) UAV airborne lidar technology has strong advantages over the other three technologies. The main disadvantage is that the equipment is expensive, the vegetation still has a certain impact, and there are still some ground points in the high vegetation coverage area, which affects the discrimination. .

除此,机载激光雷达获取虽然获取了很多点云数据,通过分类后发现很多是植被点云,尤其是高植被覆盖区,地表点云部分区域十分稀疏,尤其是夏季阔叶植被可能遮挡点云,导致植被下无地表点云。受覆盖植被的影响导致部分地表点云空白,不能真实反映地表信息。In addition, although airborne lidar has acquired a lot of point cloud data, after classification, it is found that many of them are vegetation point clouds, especially in areas with high vegetation coverage, and some areas of surface point clouds are very sparse, especially in summer, broad-leaved vegetation may block points Cloud, resulting in no surface point cloud under vegetation. Affected by vegetation cover, some surface point clouds are blank, which cannot truly reflect the surface information.

因此,需要基于机载激光雷达的一种地质灾害探测识别方法,能够更加精确的探测地表状态。Therefore, there is a need for a geological hazard detection and identification method based on airborne lidar, which can detect the surface state more accurately.

发明内容SUMMARY OF THE INVENTION

本发明的目的在于,提供了基于机载激光雷达的一种地质灾害探测识别方法,能够更加精确的探测地表状态。The purpose of the present invention is to provide a geological disaster detection and identification method based on airborne laser radar, which can detect the surface state more accurately.

本发明提供的基础方案为:The basic scheme provided by the present invention is:

基于机载激光雷达的一种地质灾害探测识别方法,包括:A method for detecting and identifying geological hazards based on airborne lidar, including:

采集步骤,采集环境点云数据;The collection step is to collect environmental point cloud data;

分类步骤,按地表点云及干扰点云对环境点云数据进行分类,并提取地表点云;The classification step is to classify the environmental point cloud data according to the surface point cloud and the interference point cloud, and extract the surface point cloud;

圈定步骤,用预设的网格对地表点云进行区域圈定,将地表点云进行二维格网化处理;The delineation step is to delineate the surface point cloud with a preset grid, and perform two-dimensional grid processing on the surface point cloud;

加密步骤,计算每个网格内的地表点云数量,当网格内的地表点云数量小于N时,按照预设的算法,对网格进行地表点云密度增加处理;In the encryption step, the number of surface point clouds in each grid is calculated, and when the number of surface point clouds in the grid is less than N, the grid is processed to increase the density of surface point clouds according to a preset algorithm;

展示步骤,对密度增加处理后的地表点云进行输出展示。The display step is to output and display the surface point cloud after density increase processing.

基础方案工作原理及有益效果:The working principle and beneficial effects of the basic scheme:

由于地表点云及干扰点云皆为三维坐标,在采集环境点云数据后,可以根据点云数据的特点,将点云数据分成地表点云和干扰点云(如树木),并将地表点云提取出来。通过这样的方式,能够将采集的点云数据进行筛分,选出真正有用的地表点云数据。Since both the surface point cloud and the interference point cloud are three-dimensional coordinates, after collecting the environmental point cloud data, the point cloud data can be divided into the surface point cloud and the interference point cloud (such as trees) according to the characteristics of the point cloud data, and the surface points Cloud extraction. In this way, the collected point cloud data can be sieved, and the truly useful surface point cloud data can be selected.

之后,用预设的网格对地表点云进行区域圈定,将地表点云进行二维格网化处理,并计算每个网格内的地表点云密度,若某个网格内的点云数量小于N,说明该网格所在区域的地表点云过少,该区域被植被遮挡的比例过大,仅凭采集的地表数据难以充分展示完整的地形。因此,按照预设的算法,对该网格所在区域进行地表点云密度增加处理,使该网格内拥有足够的地表点云数据。After that, use the preset grid to delineate the area of the surface point cloud, perform two-dimensional grid processing on the surface point cloud, and calculate the surface point cloud density in each grid. If the number is less than N, it means that there are too few surface point clouds in the area where the grid is located, and the proportion of the area occluded by vegetation is too large. Therefore, according to the preset algorithm, the area where the grid is located is processed to increase the density of the surface point cloud, so that there is enough surface point cloud data in the grid.

最后,将对密度增加处理后的地表点云进行输出展示。这样,探测人员看到的输出画面,是已经将植被遮挡区域进行地表还原处理后的画面。这样的画面,能够更加真实、完整的反应真正的地表。Finally, the output of the surface point cloud after the density increase processing will be displayed. In this way, the output picture that the detector sees is the picture after the surface restoration processing has been carried out in the area covered by the vegetation. Such a picture can more realistically and completely reflect the real surface.

与现有技术相比,使用本方法,能够更加精确的探测地表状态。Compared with the prior art, using this method, the surface state can be detected more accurately.

进一步,加密步骤中,增加网格内点云密度的处理方法为,选取距离网格距离最近的M个点后,用曲面拟合的方式进行曲面拟合,再利用曲面反算提取网格中的特征拐点坐标信息,生成新的地表点云信息,使网格中的地表点云数量不小于预设数量。Further, in the encryption step, the processing method for increasing the density of the point cloud in the grid is to select the M points closest to the grid distance, use the surface fitting method to perform surface fitting, and then use the surface back-calculation to extract the points in the grid. The coordinate information of the characteristic inflection point is generated, and new surface point cloud information is generated, so that the number of surface point clouds in the grid is not less than the preset number.

采用这样的方式,能够充分利用已有的地表点云数据,同时,采用曲面拟合的方式,得到的拐点坐标信息,能够较为精确的将对应地表云点进行还原。除此,曲面拟合的模型较为常用,其技术较为成熟,运行效率也很高。In this way, the existing surface point cloud data can be fully utilized, and at the same time, the inflection point coordinate information obtained by using the surface fitting method can more accurately restore the corresponding surface cloud points. In addition, the surface fitting model is more commonly used, its technology is relatively mature, and its operating efficiency is also very high.

进一步,展示步骤中,将地表点云数据,利用点云处理软件构建三角网,生成效果图后,进行输出展示。Further, in the display step, the surface point cloud data is used to construct a triangulation network by using point cloud processing software, and after the rendering is generated, the output display is performed.

这样展示的内容,便于工作人员直观的了解地形的情况。The content displayed in this way is convenient for the staff to intuitively understand the situation of the terrain.

进一步,展示步骤中,生成的效果图包括DEM和坡度图。Further, in the display step, the generated renderings include DEM and slope maps.

通过DEM和坡度图,能够较好的还原原始地形地貌,便于工作人员进行地质灾害识别。Through DEM and slope map, the original topography can be better restored, which is convenient for the staff to identify geological hazards.

进一步,加密步骤中,若网格内的点云数量为0,则对网格进行等距离加密。Further, in the encryption step, if the number of point clouds in the grid is 0, the grid is equidistantly encrypted.

这样的加密方式,对于网格内点云数量为0的网格而言,能够较好的还原其地形。Such an encryption method can better restore the terrain for a grid with 0 point clouds in the grid.

进一步,N的数值大于3。Further, the value of N is greater than 3.

若N的数值太小,网格内的地表点云难以准确展示区域的完整地形。If the value of N is too small, it is difficult for the surface point cloud in the grid to accurately display the complete terrain of the area.

进一步,N的数值小于10。Further, the value of N is less than 10.

这样数量的地表点云,已经可以较好的对网格区域进行地形还原。Such a number of surface point clouds can already restore the grid area well.

进一步,M的数值大于3。Further, the value of M is greater than 3.

若M的数值太小,难以有效的进行曲面拟合,得到结果的可信度也难以保证。If the value of M is too small, it is difficult to effectively perform surface fitting, and the reliability of the obtained results is also difficult to guarantee.

进一步,网格的大小为2m*2m。Further, the size of the grid is 2m*2m.

这样大小的网格,在保证精细化的同时,能够兼顾采集的地表点云数据的有效利用率。Such a size of grid can ensure the effective utilization of the collected surface point cloud data while ensuring refinement.

进一步,采集步骤中,用机载激光雷达进行环境点云采集。Further, in the collection step, the airborne lidar is used to collect the environmental point cloud.

与其他的探测手段相比,机载激光雷达的数据获取灵活,数据量大,测量精度高,相对精度可以达到5cm,并且对植被具有一定的穿透能力。Compared with other detection methods, airborne lidar has flexible data acquisition, a large amount of data, and high measurement accuracy. The relative accuracy can reach 5cm, and it has a certain ability to penetrate vegetation.

附图说明Description of drawings

图1为本发明基于机载激光雷达的一种地质灾害探测识别方法实施例一的示意图。FIG. 1 is a schematic diagram of Embodiment 1 of a method for detecting and identifying geological hazards based on an airborne laser radar according to the present invention.

具体实施方式Detailed ways

下面通过具体实施方式进一步详细说明:The following is further described in detail by specific embodiments:

实施例一Example 1

如图1所示,基于机载激光雷达的一种地质灾害探测识别方法,包括:As shown in Figure 1, a method for detecting and identifying geological hazards based on airborne lidar includes:

采集步骤,采集环境点云数据。本实施例中,采集的工具为机载激光雷达,与其他的探测手段相比,机载激光雷达的数据获取灵活,数据量大,测量精度高,相对精度可以达到5cm,并且对植被具有一定的穿透能力。The collection step is to collect environmental point cloud data. In this embodiment, the collection tool is airborne lidar. Compared with other detection methods, airborne lidar has flexible data acquisition, a large amount of data, and high measurement accuracy. The relative accuracy can reach 5cm, and it has certain effects on vegetation. penetrating ability.

分类步骤,按地表点云及干扰点云对环境点云数据进行分类,并提取地表点云。In the classification step, the environmental point cloud data is classified according to the surface point cloud and the interference point cloud, and the surface point cloud is extracted.

圈定步骤,用预设的网格对地表点云进行区域圈定,将地表点云进行二维格网化处理。本实施例中,网格的大小为2m*2m。这样大小的网格,在保证精细化的同时,能够兼顾采集的地表点云数据的有效利用率。In the delineation step, a preset grid is used to delineate the area of the surface point cloud, and the surface point cloud is processed into a two-dimensional grid. In this embodiment, the size of the grid is 2m*2m. Such a size of grid can ensure the effective utilization of the collected surface point cloud data while ensuring refinement.

加密步骤,计算每个网格内的地表点云数量,当网格内的地表点云数量小于N时,按照预设的算法,对网格进行地表点云密度增加处理。N的数值大于3,若N的数值太小,网格内的地表点云难以准确展示区域的完整地形。且N的数值小于10,因为这样数量的地表点云,已经可以较好的对网格区域进行地形还原。本实施例中,N的数值为6。In the encryption step, the number of surface point clouds in each grid is calculated. When the number of surface point clouds in the grid is less than N, the grid is processed to increase the density of surface point clouds according to a preset algorithm. The value of N is greater than 3. If the value of N is too small, it is difficult for the surface point cloud in the grid to accurately display the complete terrain of the area. And the value of N is less than 10, because such a number of surface point clouds can already restore the grid area well. In this embodiment, the value of N is 6.

具体的,增加网格内点云密度的处理方法为,选取距离网格距离最近的M个点后,用曲面拟合的方式进行曲面拟合,再利用曲面反算提取网格中的特征拐点坐标信息,生成新的地表点云信息,使网格中的地表点云数量不小于预设数量,实现点云加密。若网格内的点云数量为0,则对网格进行等距离加密。其中,M的数值大于3。若M的数值太小,则难以有效的进行曲面拟合,得到结果的可信度也难以保证。Specifically, the processing method for increasing the density of point clouds in the grid is to select the M points closest to the grid distance, perform surface fitting by means of surface fitting, and then use the surface back calculation to extract the characteristic inflection points in the grid. Coordinate information, generate new surface point cloud information, make the number of surface point clouds in the grid not less than the preset number, and realize point cloud encryption. If the number of point clouds in the grid is 0, the grid is equidistantly refined. Among them, the value of M is greater than 3. If the value of M is too small, it is difficult to effectively perform surface fitting, and the reliability of the obtained results is also difficult to guarantee.

展示步骤,对密度增加处理后的地表点云进行输出展示。将地表点云数据,利用点云处理软件构建三角网,生成效果图后,进行输出展示。本实施例中,生成的效果图包括DEM和坡度图。The display step is to output and display the surface point cloud after density increase processing. The surface point cloud data is used to construct a triangular network with point cloud processing software, and after the rendering is generated, the output display is carried out. In this embodiment, the generated effect map includes a DEM and a gradient map.

具体实施过程如下:The specific implementation process is as follows:

由于地表点云及干扰点云皆为三维坐标,在用机载激光雷达采集环境点云数据后,可以根据点云数据的特点,将点云数据分成地表点云和干扰点云(如树木),并将地表点云提取出来。通过这样的方式,能够将采集的点云数据进行筛分,选出真正有用的地表点云数据。Since both the surface point cloud and the interference point cloud are three-dimensional coordinates, after collecting the environmental point cloud data with the airborne lidar, the point cloud data can be divided into the surface point cloud and the interference point cloud (such as trees) according to the characteristics of the point cloud data. , and extract the surface point cloud. In this way, the collected point cloud data can be sieved, and the truly useful surface point cloud data can be selected.

之后,用2m*2m的网格对地表点云进行区域圈定,将地表点云进行二维格网化处理,并计算每个网格内的地表点云密度,若某个网格内的点云数量小于6,说明该网格所在区域的地表点云过少,该区域被植被遮挡的比例过大,仅凭采集的地表数据难以充分展示完整的地形。因此,按照预设的算法,对该网格所在区域进行地表点云密度增加处理,使该网格内拥有足够的地表点云数据。若网格内的点云数量为0,则对网格进行等距离加密。这样的加密方式,对于网格内点云数量为0的网格而言,能够较好的还原其地形。After that, use a 2m*2m grid to delineate the surface point cloud, perform two-dimensional grid processing on the surface point cloud, and calculate the surface point cloud density in each grid. The number of clouds is less than 6, indicating that the surface point clouds in the area where the grid is located are too few, and the proportion of the area occluded by vegetation is too large. Therefore, according to the preset algorithm, the area where the grid is located is processed to increase the density of the surface point cloud, so that there is enough surface point cloud data in the grid. If the number of point clouds in the grid is 0, the grid is equidistantly refined. Such an encryption method can better restore the terrain for a grid with 0 point clouds in the grid.

最后,将对密度增加处理后的地表点云,利用点云处理软件构建三角网,生成的效果图包括DEM和坡度图后,进行输出展示。这样,探测人员看到的输出画面,是已经将植被遮挡区域进行地表还原处理后的画面,而通过DEM和坡度图,能够较好的还原原始地形地貌,便于工作人员进行地质灾害识别,能够更加真实、完整的反应真正的地表。Finally, the surface point cloud after density increase processing will be used to construct a triangulation network using point cloud processing software. In this way, the output picture seen by the detectors is the picture after the surface restoration processing has been carried out in the area covered by vegetation, and through DEM and slope map, the original topography can be better restored, which is convenient for the staff to identify geological hazards, and can be more A true, complete response to the real surface.

与现有技术相比,使用本方法,能够更加精确的探测地表状态。Compared with the prior art, using this method, the surface state can be detected more accurately.

实施例二Embodiment 2

与实施例一不同的是,本实施例中,分类步骤中,还提取干扰点云;圈定步骤中,还用同样的网格对干扰云点进行区域圈定,将干扰云点进行二维格网化处理。Different from the first embodiment, in this embodiment, in the classification step, the interference point cloud is also extracted; in the delineation step, the same grid is used to delineate the area of the interference cloud point, and the interference cloud point is subjected to a two-dimensional grid. processing.

加密步骤中,当网格内的地表点云数量小于N时,还根据网格内的干扰点云,识别区域内的植被,并结合周边网格的干扰点云数据,模拟出植被外形特征,外形特征包括种类、树径和地面以上高度;还根据模拟出的植被外形特征,对新生成的地表云点进行坐标修正。In the encryption step, when the number of surface point clouds in the grid is less than N, the vegetation in the area is also identified according to the interference point cloud in the grid, and the shape characteristics of the vegetation are simulated by combining the interference point cloud data of the surrounding grid. The shape features include species, tree diameters and heights above the ground; the coordinates of the newly generated surface cloud points are also corrected according to the simulated vegetation shape features.

具体实施过程如下:The specific implementation process is as follows:

当植被较为高大且枝叶密度较大时,有时会将其底部的区域完全遮挡,该区域可能由若干个网格组成。如果该树木的生长点与周边相比存在特异性(如生长在坑内或者扎根的地方有小高台)。这时,采用实施例一的方式,还原的地形虽然能够保证一定的精确性,但这些特殊的地形却难以进行还原。When vegetation is taller and denser in foliage, it sometimes completely blocks the area at its bottom, which may consist of several meshes. If the growth point of the tree is specific compared to the surrounding area (eg growing in a pit or having a small plateau where the roots are rooted). At this time, using the method of the first embodiment, although the restored terrain can ensure a certain accuracy, it is difficult to restore these special terrains.

使用本实施例中的方法,在加密时,能够根据网格内的干扰点云,识别区域内的植被,并结合周边网格的干扰点云数据,模拟出植被外形特征,外形特征包括种类、树径和地面以上高度。并还根据模拟出的植被外形特征,对新生成的地表云点进行坐标修正。Using the method in this embodiment, when encrypting, the vegetation in the area can be identified according to the interference point cloud in the grid, and combined with the interference point cloud data of the surrounding grid, the vegetation shape features can be simulated, and the shape features include types, Tree diameter and height above ground. The coordinates of the newly generated surface cloud points are also corrected according to the simulated vegetation shape characteristics.

通过植被的外形特征,再结合加密得到的新的地表云点,可以有效的分析该地表云点的精确性是否合适。如:某棵树分析出其地面以上高度为25米,但按照网格内对应的新生成的地表点云计算,该树木的地面以上高度只有24米,则说明该树生成在一个坑内。因此,对新生成的地表点云进行修正,使其更加符合真实的地表云点。Through the shape characteristics of vegetation, combined with the new surface cloud points obtained by encryption, it is possible to effectively analyze whether the accuracy of the surface cloud points is appropriate. For example, if a tree is analyzed and its height above the ground is 25 meters, but according to the corresponding newly generated surface point cloud calculation in the grid, the height of the tree above the ground is only 24 meters, which means that the tree is generated in a pit. Therefore, the newly generated surface point cloud is corrected to make it more in line with the real surface cloud points.

使用本方法,即使树木的生长点与周边相比存在特异性,本方法同样能够识别并进行还原。Using this method, even if the growth point of a tree is specific compared to its surroundings, this method can also identify and restore.

以上所述的仅是本发明的实施例,方案中公知的具体结构及特性等常识在此未作过多描述,所属领域普通技术人员知晓申请日或者优先权日之前发明所属技术领域所有的普通技术知识,能够获知该领域中所有的现有技术,并且具有应用该日期之前常规实验手段的能力,所属领域普通技术人员可以在本申请给出的启示下,结合自身能力完善并实施本方案,一些典型的公知结构或者公知方法不应当成为所属领域普通技术人员实施本申请的障碍。应当指出,对于本领域的技术人员来说,在不脱离本发明结构的前提下,还可以作出若干变形和改进,这些也应该视为本发明的保护范围,这些都不会影响本发明实施的效果和专利的实用性。本申请要求的保护范围应当以其权利要求的内容为准,说明书中的具体实施方式等记载可以用于解释权利要求的内容。The above are only the embodiments of the present invention, and the common knowledge such as the well-known specific structures and characteristics in the scheme has not been described too much here. Those of ordinary skill in the art know that the invention belongs to the technical field before the filing date or the priority date. Technical knowledge, can know all the prior art in this field, and have the ability to apply conventional experimental means before the date, those of ordinary skill in the art can improve and implement this scheme in combination with their own ability under the enlightenment given in this application, Some typical well-known structures or well-known methods should not be an obstacle to those skilled in the art from practicing the present application. It should be pointed out that for those skilled in the art, some modifications and improvements can be made without departing from the structure of the present invention. These should also be regarded as the protection scope of the present invention, and these will not affect the implementation of the present invention. Effectiveness and utility of patents. The scope of protection claimed in this application shall be based on the content of the claims, and the descriptions of the specific implementation manners in the description can be used to interpret the content of the claims.

Claims (7)

1.基于机载激光雷达的一种地质灾害探测识别方法,其特征在于,包括:1. a kind of geological disaster detection and identification method based on airborne laser radar, is characterized in that, comprises: 采集步骤,采集环境点云数据;The collection step is to collect environmental point cloud data; 分类步骤,按地表点云及干扰点云对环境点云数据进行分类,并提取地表点云;The classification step is to classify the environmental point cloud data according to the surface point cloud and the interference point cloud, and extract the surface point cloud; 圈定步骤,用预设的网格对地表点云进行区域圈定,将地表点云进行二维格网化处理;The delineation step is to delineate the surface point cloud with a preset grid, and perform two-dimensional grid processing on the surface point cloud; 加密步骤,计算每个网格内的地表点云数量,当网格内的地表点云数量小于N时,按照预设的算法,对网格进行地表点云密度增加处理;增加网格内点云密度的处理方法为,选取距离网格距离最近的M个点后,用曲面拟合的方式进行曲面拟合,再利用曲面反算提取网格中的特征拐点坐标信息,生成新的地表点云信息,使网格中的地表点云数量不小于预设数量;In the encryption step, the number of surface point clouds in each grid is calculated. When the number of surface point clouds in the grid is less than N, the grid is processed to increase the density of surface point clouds according to the preset algorithm; The processing method of cloud density is to select M points with the closest distance from the grid, and then perform surface fitting by means of surface fitting, and then use the surface inverse calculation to extract the coordinate information of characteristic inflection points in the grid to generate new surface points. Cloud information, so that the number of surface point clouds in the grid is not less than the preset number; 展示步骤,对密度增加处理后的地表点云进行输出展示;将地表点云数据,利用点云处理软件构建三角网,生成效果图后,进行输出展示;生成的效果图包括DEM和坡度图;The display step is to output and display the surface point cloud after density increase processing; use the point cloud processing software to construct a triangulation network with the surface point cloud data, and generate the effect map, and then output and display; the generated effect map includes DEM and slope map; 其中,分类步骤中,还提取干扰点云;圈定步骤中,还用同样的网格对干扰云点进行区域圈定,将干扰云点进行二维格网化处理;Among them, in the classification step, the interference point cloud is also extracted; in the delineation step, the same grid is used to delineate the area of the interference cloud point, and the interference cloud point is subjected to two-dimensional grid processing; 加密步骤中,当网格内的地表点云数量小于N时,还根据网格内的干扰点云,识别区域内的植被,并结合周边网格的干扰点云数据,模拟出植被外形特征,外形特征包括种类、树径和地面以上高度;还根据模拟出的植被外形特征,对新生成的地表云点进行坐标修正。In the encryption step, when the number of surface point clouds in the grid is less than N, the vegetation in the area is also identified according to the interference point cloud in the grid, and the shape characteristics of the vegetation are simulated by combining the interference point cloud data of the surrounding grid. The shape features include species, tree diameters and heights above the ground; the coordinates of the newly generated surface cloud points are also corrected according to the simulated vegetation shape features. 2.根据权利要求1所述的基于机载激光雷达的一种地质灾害探测识别方法,其特征在于:加密步骤中,若网格内的点云数量为0,则对网格进行等距离加密。2. A kind of geological disaster detection and identification method based on airborne laser radar according to claim 1, is characterized in that: in the encryption step, if the number of point clouds in the grid is 0, then the grid is equidistantly encrypted . 3.根据权利要求1所述的基于机载激光雷达的一种地质灾害探测识别方法,其特征在于:N的数值大于3。3 . The method for detecting and identifying geological hazards based on airborne laser radar according to claim 1 , wherein the value of N is greater than 3. 4 . 4.根据权利要求1所述的基于机载激光雷达的一种地质灾害探测识别方法,其特征在于:N的数值小于10。4 . The method for detecting and identifying geological hazards based on airborne laser radar according to claim 1 , wherein the value of N is less than 10. 5 . 5.根据权利要求1所述的基于机载激光雷达的一种地质灾害探测识别方法,其特征在于:M的数值大于3。5 . The method for detecting and identifying geological hazards based on airborne laser radar according to claim 1 , wherein the value of M is greater than 3. 6 . 6.根据权利要求5所述的基于机载激光雷达的一种地质灾害探测识别方法,其特征在于:网格的大小为2m*2m。6 . The method for detecting and identifying geological hazards based on airborne laser radar according to claim 5 , wherein the size of the grid is 2m*2m. 7 . 7.根据权利要求6所述的基于机载激光雷达的一种地质灾害探测识别方法,其特征在于:采集步骤中,用机载激光雷达进行环境点云采集。7 . The method for detecting and identifying geological hazards based on airborne laser radar according to claim 6 , wherein in the collecting step, the airborne laser radar is used to collect environmental point clouds. 8 .
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