JP2005172634A - Method for measuring occupancy classified by altitude, and method for compensating flooded depth using the same - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method for measuring occupancy, classified by altitude, and to provide a method for compensating flooded depth using the same, in order to accurately understand behaviors of flooding, even in a dense urban area, such as a metropolitan area. <P>SOLUTION: In the method, the total number N of measurement points in a mesh is calculated from three-dimensional point group data obtained by three-dimensional measurements, and the point group data of the measurement points are separated into a ground section and a feature section through a filtering process. Flat planes, parallel to the ground, are set at every prescribed spacing along the vertical direction from the ground, and the point group data of the feature section are projected to respective flat planes located under the vertical position where the point group data exist, and each total number Mi of the point group data is calculated at each flat plane. Then, the rate of area occupancy of the feature section in each flat plane is calculated from the ratio of Mi to N at each flat plane, including the ground, a rate curve of feature occupancy is obtained from each rate of area occupancy, and a curve of flooding quantity versus flooded depth is compensated, by using the rate curve of feature occupancy. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an elevation-specific feature occupancy measurement method that obtains a feature occupancy for each elevation from elevation random data acquired by an airborne laser scanner, and a flood depth correction method using the same.

  Since terrain information is required for inundation simulation and inundation analysis, 3D data with elevation surface data obtained from the laser scanner mounted on the aircraft is acquired. The ground elevation data is extracted by removing the feature data such as trees and cars, and this ground elevation data is used.

JP 2002-269656 A

However, in the above-described conventional technique, in particular, in a dense urban area such as an urban area, it is impossible to grasp the inundation state in consideration of the volume of the building, and it is impossible to perform an accurate flood simulation.
In recent years, urban floods, which are urgently taken as a new water disaster, include inundation simulations and hazard maps that take into account the effects of volumetric exclusion of inundation flows caused by urban buildings.
However, in the previous inundation analysis, there was no method for determining the feature occupancy rate by altitude, so the influence on the behavior of inundation water such as buildings was only considered as a roughness coefficient.

  The present invention was devised to solve the above-described problems, and is based on altitude occupancy by altitude from altitude point data (elevation random data) on the surface of the ground surface including buildings acquired by an airborne laser scanner. By calculating the occupancy rate, it is possible to effectively use the data, and to accurately understand the behavior of flood water even in dense urban areas such as urban areas, and the inundation depth using this method The purpose is to provide a correction method.

  In order to achieve the above object, the invention according to claim 1 is a feature occupancy measurement method according to elevation, which obtains the occupancy of the feature portion in a predetermined section from the three dimensional point cloud data obtained by three dimensional measurement. The first step of separating the three-dimensional point cloud data in the predetermined section into the point cloud data of the ground part and the point cloud data of the feature part, and the total number of data points of the three-dimensional point cloud data in the predetermined section And a third step of measuring the number of data points of the point cloud data of the feature portion projected from the ground portion into a two-dimensional region at a predetermined height on the basis of the height of the ground portion. And a fourth stage for determining the area occupancy ratio of each feature at each elevation from the ratio between the number of data points measured in the second stage and the number of data points measured in the third stage. This is a feature occupancy measurement method.

  Further, the invention according to claim 2 is an inundation depth correction for correcting the inundation depth in the predetermined section by obtaining the occupancy ratio of the feature portion in the predetermined section from the three-dimensional point cloud data obtained by three-dimensional measurement for each altitude. In the method, a first step of separating the three-dimensional point cloud data in the predetermined section into the point group data of the ground part and the point cloud data of the feature part, and the number of data points of the three-dimensional point cloud data in the predetermined section A second step of measuring the total number, and a third step of measuring the number of data of point cloud data of the feature portion projected from the ground portion into a two-dimensional region at a predetermined height with reference to the height of the ground portion. A fourth stage for determining the area occupancy ratio of each feature at each altitude from the ratio of the stage, the number of data points measured in the second stage and the number of data points measured in the third stage, and the area obtained in the fourth stage Occupancy rate and immersion flowing into the predetermined compartment A flood depth correction method characterized by comprising a fifth step of determining the immersion depth in the predetermined compartment and a quantity.

  According to the present invention, it is possible to obtain the occupation ratio of a feature such as a building in the height direction, which has been difficult to obtain until now. In addition, in flood simulations of densely built-up areas, which are considered to be important for urban flood damage, which has been increasing in recent years, even if there are features such as buildings, a simulation should be performed that takes into account the volume of flood water due to those features. Can provide disaster prevention information with high accuracy.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a schematic view showing a measuring method of the present invention.
In FIG. 1, an aircraft 1 is equipped with a laser scanner, and laser light 2 emitted from the laser scanner is irradiated to the ground, and the ground in the measurement region 3 and the features on the ground (artificial buildings, trees, Measure the distance by measuring the time it takes to reflect back from the car.

  The measurement region 3 is divided into meshes 4 such as a square mesh or an irregular mesh. As the size of the mesh 4, a square shape of about 1 m to 50 m, a rectangle of about 1 m to 50 m on one side, an irregular mesh, or the like is used.

  The laser beam 2 emitted from the laser scanner is a pulse laser beam having a constant pulse rate and a scan rate, and the entire measurement region 3 is scanned at equal intervals. As a result, a fixed sampling point (measurement point) is formed in each mesh 4 in the measurement region 3. This is elevation point data (elevation random data).

  FIG. 2 shows the distribution state of the measurement points (three-dimensional point group data). As shown in FIG. 2, the measurement points 5 by the laser beam 2 are distributed three-dimensionally, and when these measurement points 5 are projected on the ground 6 (Z = 0), they are arranged at a constant interval. Here, the Z axis represents the height direction.

  In this figure, the total number of measurement points 5 distributed three-dimensionally in the mesh 4 is N, the size (area) of the mesh 4 is Δx × Δy, and the height of Δz is in the center. An example in which a rectangular parallelepiped feature 7 is present is shown. As shown in the figure, the measurement points 5 on the feature 7 are present on the surface from the ground height with respect to the ground 6 of the mesh 4 to the height Δz, and the number thereof is M. As the size of the mesh 4 is reduced, the ground 6 can be regarded as a substantially flat surface as shown in the figure, and the average ground elevation of the mesh is often used as the ground elevation.

  When the laser scanner measurement is performed uniformly, the measurement points 5 exist at regular intervals in the vertical direction and the horizontal direction. Therefore, the total number N of the measurement points 5 is the area of the measured mesh 4 (Δx × Δy), and the total number M of the measurement points 5 on the feature 7 is equivalent to the cross-sectional area of the measured feature 7 at the height Δz.

  Therefore, in order to obtain the area occupancy ratio of the feature 7 on the plane on the height Δz, it is necessary to know the total number of measurement points 5 in the mesh 4 and the total number of measurement points on the feature 7.

  By the way, the features 7 actually include various structures such as large structures such as high-rise buildings, small structures such as ordinary houses, other artificial structures, trees, cars, etc. In order to separate the three-dimensional point cloud data of the measurement points into the ground part and the feature part, a filtering process is performed.

  Examples of the filtering process include a method using a last pulse, a statistical method, a method using FFT (Fast Fourier Transform), and the like. In the method using the last pulse, the last pulse often passes through the gaps between the buildings and trees and reaches the ground. Therefore, only the last pulse is used to extract the three-dimensional point cloud data of the ground portion.

  In the statistical method, the terrain is approximated by a curved surface, point cloud data exceeding a threshold set in accordance with the curved surface is removed, and point cloud data of the ground portion is extracted. In the method using FFT, the frequency analysis is performed to extract the target frequency component, thereby extracting the point group data of the corresponding ground portion. In the figure, the total number of three-dimensional point cloud data is N, and when the above filtering process is performed, M point cloud data of the feature 7 are removed and (N−M) points of the ground 6 are removed. Group data remains.

  After separating the point cloud data on the ground 6 and the point cloud data on the feature 7 using any of the above-described filtering processes, the area occupancy rate of the feature 7 is obtained for each altitude.

  Since the feature 7 having the height Δz shown in FIG. 2 has a rectangular parallelepiped shape, the measurement point 5 on the feature exists on the plane on the height Δz, and the number of measurement points on the plane is M. The total number of measurement points, which is the sum of the M measurement points on the feature and the measurement points on the ground (Z = 0), is N.

  Therefore, the area occupation ratio S of the feature in the plane on Δz is expressed by S = M / N. As shown in FIG. 3, this concept is similarly performed on an intermediate plane from the ground 6 (Z = 0) to the height of Z = Δz where the measurement point of the feature 7 exists in the space in the mesh 4. As long as the feature has a rectangular parallelepiped shape, the measurement point data of the feature projected onto the plane of Δz1 is M, so the area occupation ratio S1 of the feature on the plane of Δz1 is S1 = M / N. Similarly, the area occupation rate S2 of the feature on the plane of Δz2 is S2 = M / N.

  As described above, not only the planes at Δz1 and Δz2, but also the number of planes parallel to the ground at fine intervals between Z = 0 and Δz, and the area occupation of the features on the planes The rate can be determined.

  The upper diagram of FIG. 4 shows the feature occupancy rate (area occupancy rate) S on the vertical axis, the height Z from the ground on the horizontal axis, and according to the height from the ground (Z = 0), The feature occupancy rate curve 8 shows how the area occupancy rate of the feature changes.

  In this example, the feature occupancy changes at each of the points H1, H2, and H3, and the feature occupancy in each section from 0 to H1, H1 to H2, and H2 to H3 is the same. The feature occupancy rate is 75% on the ground (Z = 0), but the feature occupancy rate changes to 50% in H1, the feature occupancy rate is 25% in H2, and the feature occupancy in H3. It shows how the rate changes to 0%.

  On the other hand, the lower diagram in FIG. 4 shows how the depth H of the inundation in the mesh 4 changes when a predetermined amount of water such as flood water flows into the mesh 4. The curve K shows the relationship between the inundation amount V and the inundation depth H when no feature is present on the ground. The heights H1, H2, and H3 from the ground correspond to the depths h1, h2, and h3 of the inundation depth, and the corresponding symbols indicate the same height. The curve K is obtained in advance for each of the plurality of meshes 4 by calculation or simulation. In this example, the curve K is a straight line for easy understanding.

  By the way, when a feature is present in the mesh 4, volume removal due to the feature occurs, and therefore, a constant inundation depth is reached with a smaller amount of water immersion than when no feature is present. Therefore, in order to consider the influence of the volume exclusion effect by the feature, a curve C is obtained by correcting the straight line K from the feature occupancy curve shown in the upper diagram of FIG.

  For example, when water of the inundation amount V1 flows into the mesh, the inundation depth is h1 when there is no influence of the feature, but the inundation depth is t1 when there is an influence of the feature. Yes. Assuming that the bottom area of the mesh 4 is B and the amount of inundation is V1, the inundation depth t1 when there is no influence of the feature is t1 = V1 / B. Since the bottom area in the case of 75% is 0.25B, the inundation depth h1 in this case is h1 = V1 / 0.25B, h1 = 4 × t1, and the feature occupancy is 75%. It can be seen that the inundation depth reaches 4 times with the same inundation amount compared with the case where there is no influence of the feature. Similarly, for the amount of inundation required to reach the inundation depth of h1, the inundation amount V2 when there is no influence of the feature is V2 = h1 × B, and the inundation amount V1 when the feature occupation ratio is 75% is V1 = h1 × 0.25B, so that the amount of water V2 is four times V1. That is, when the slope of the straight line K is 1, the slope of the correction curve C is 0.25 in the 0 to h1 section, 0.5 in the section h1 to h2, and 0.75 in the section h2 to h3.

  Thus, the curve C which correct | amended the influence by a feature can be drawn by calculating | requiring the inundation depth (h1, h2, h3) with respect to the change point (H1, H2, H3) of the feature occupancy curve 8. .

  FIG. 5 shows an example in which the feature occupancy rate curve 8 does not become a stepped graph as shown in the upper diagram of FIG. 4, and several heights from the ground are selected (H1, H2, H3). ,..., Hn), the area occupancy rate of the feature on the plane at each height is obtained, the points are plotted, and the feature occupancy curve 8 is drawn by fitting an approximate curve.

  Similar to FIG. 4, if the inundation depth for each of the points H 1, H 2, H 3,... Hn in the feature occupancy curve 8 is obtained and an approximate curve is applied, the amount of inundation in the absence of the feature—the inundation depth A curve C obtained by correcting the curve K in consideration of the volume exclusion effect by the feature is obtained.

FIG. 6 shows the above series of operations in a flowchart.
First, the three-dimensional coordinates of the measurement points on the ground surface measured by the laser beam 2 of the laser scanner mounted on the aircraft 1 are read into the computer system, and the measurement area is divided into meshes (ST1). Next, the total number N of measurement points in the mesh is calculated (ST2), and the point cloud data of the measurement points is separated into the ground portion and the feature portion by the filtering process described above (ST3).

  As shown in FIG. 3, a plane parallel to the ground is set at predetermined intervals from the ground in the height direction (ST4), and the point cloud data of the feature portion separated in step ST3 is present. Projected onto each plane (including the ground) located below the height to be performed, and the total number Mi (i = 1, 2, 3,... N: n) of the point cloud data is set for each plane. (This number includes the ground surface) (ST5).

  From the ratio of Mi and N for each plane including the ground, the area occupation ratio of the feature portion in each plane is calculated (ST6). The feature occupancy rate curve is obtained by plotting the ground occupancy rate in step ST6 and the area occupancy rate of the feature at a predetermined height from the ground as shown in FIGS. 4 and 5 (ST7). Using this feature occupancy curve, the inundation amount-inundation depth curve is corrected as shown in FIGS. 4 and 5 (ST8).

  Next, it is determined whether or not the processing from step ST2 to ST8 (the correction amount of the inundation amount-infiltration depth curve) has been performed for all the meshes dividing the measurement region 3 (ST9), and the steps are performed for all the meshes. When the processes of ST2 to ST8 are finished (ST9 YES), the operation is finished.

  On the other hand, when the processes of steps ST2 to ST8 have not been completed for all meshes (ST9 NO), the process returns to step ST2 and the processes of steps ST2 to ST8 are continued.

  After completion of the correction process of the inundation amount-infiltration depth curve for all the meshes, if a flood simulation is performed using the infiltration amount-infiltration depth correction curve obtained for each mesh, disaster prevention information with high accuracy can be provided.

It is a figure which shows the measuring method by the laser beam in this invention. It is a figure which shows the distribution condition of a measurement point when a feature exists in the mesh of a measurement area | region. It is a figure which shows the state which provided the plane in the height direction at predetermined intervals from the ground. It is a figure which shows the feature occupancy rate curve and the water immersion amount-water immersion depth curve corresponding to this. It is a figure which shows the feature occupancy rate curve and the water immersion amount-water immersion depth curve corresponding to this. It is a flowchart figure which shows a series of operation | movement of this invention.

Explanation of symbols

1 Aircraft 2 Laser Light 3 Measurement Area 4 Mesh 5 Measurement Point 6 Ground 7 Feature 8 Feature Occupancy Curve

Claims (2)

In the feature occupancy measurement method according to elevation, which determines the occupancy rate of the feature part in a predetermined section from the three-dimensional point cloud data obtained by three-dimensional measurement, according to elevation,
Separating the three-dimensional point cloud data in the predetermined section into point cloud data of the ground portion and point cloud data of the feature portion;
A second step of measuring the total number of data points of the three-dimensional point cloud data in the predetermined section;
A third step of measuring the number of data points of point cloud data of a feature portion projected into a two-dimensional region at a predetermined height from the ground portion with reference to the height of the ground portion;
A feature according to elevation characterized by comprising a fourth step of determining the area occupancy of the feature for each elevation from the ratio of the number of data points measured in the second step and the number of data points measured in the third step. Occupancy measurement method. In the inundation depth correction method for correcting the inundation depth in the predetermined section by obtaining the occupancy rate of the ground part in the predetermined section from the three-dimensional point cloud data obtained by three-dimensional measurement according to the altitude,
Separating the three-dimensional point cloud data in the predetermined section into point cloud data of the ground portion and point cloud data of the feature portion;
A second step of measuring the total number of data points of the three-dimensional point cloud data in the predetermined section;
A third step of measuring the number of data points of point cloud data of a feature portion projected into a two-dimensional region at a predetermined height from the ground portion with reference to the height of the ground portion;
A fourth stage for determining the area occupancy rate of each feature from the ratio of the number of data points measured in the second stage and the number of data points measured in the third stage;
An inundation depth correction method comprising: a fifth step of determining an inundation depth in the predetermined section from the area occupancy obtained in the fourth stage and the amount of inundation flowing into the predetermined section.

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