JP7770893B2 - Ground surface generation system - Google Patents

Description

This invention relates to technology that determines ground elevation based on measurement results obtained by a laser measuring device, and more specifically, to a ground surface generation system that can generate ground surfaces while actively utilizing data that is normally removed as noise.

Up until now, aerial photogrammetry has been the mainstream method for measuring features over a wide area, but recently, various measurement methods have emerged, such as airborne laser measurement, measurement using satellite photos, and measurement using synthetic aperture radar, making it possible to select the most appropriate method depending on the situation. Note that "features" here refers to all "objects" that exist on the ground, including man-made objects such as bridges and office buildings, and natural objects such as rivers, oceans, and forests.

Among these, airborne laser measurement is a technique in which an aircraft flies over the target area to be measured and measures the reflected waves of laser pulses emitted from features within the target area. Aircraft are typically equipped with a positioning device such as a Global Navigation Satellite System (GNSS) and an inertial measurement device such as an IMU (Inertial Measurement Unit), and the GNSS and IMU can be used to record the irradiation position (x, y, z) and irradiation attitude (ω, φ, κ) when the laser pulse is emitted.

When a laser pulse is emitted from an aircraft, the time of emission is recorded, and when the laser pulse is reflected from a feature, it is received by a sensor on board the aircraft, and the time of reception is recorded. Therefore, the distance to the measurement point (the point where the laser pulse is reflected) can be obtained from the time difference between the emission time and the reception time. Since the irradiation position (x, y, z) and irradiation attitude (ω, φ, κ) at the time of laser pulse emission are also recorded, it is possible to obtain three-dimensional coordinate data (hereinafter referred to as "measurement point data") of the laser pulse irradiation point (i.e., the measurement point). Furthermore, when the sensor on board the aircraft receives a laser pulse, it records the intensity of the reflected wave (hereinafter referred to as "reflection intensity"). This reflection intensity is, in a sense, the magnitude of the energy of the received reflected wave (the amplitude of the laser pulse) and is measured directly as a voltage. The energy magnitude can be obtained by converting this voltage.

Conventional airborne laser measurement uses a near-infrared laser (wavelength 1064 nanometers: nm), but the laser pulse reflects off the water surface, making it impossible to measure features on the underwater floor. However, airborne laser measurement, which can also obtain features on the underwater floor (i.e., water depth), has recently come into use. This technique, called ALB (Airborne Laser Bathymetry), uses a green laser (wavelength 532 nm) from an aircraft in addition to a near-infrared laser. The green laser penetrates water and reflects off the bottom, making it possible to measure depth. This means that land areas are measured with a near-infrared laser, and water areas are measured with a green laser. In any case, airborne laser measurement, which uses near-infrared and green lasers, is one of the measurement technologies widely used to obtain features over a wide area.

As explained so far, airborne laser measurement is a method of obtaining measurement point data by irradiating features with laser pulses from an aircraft in flight. These laser pulses are emitted 100,000 to 2,000,000 times per second, so a huge number of measurement point data are obtained in one measurement (flight). Furthermore, when measuring forests and other areas, it is naturally impossible to irradiate laser pulses only onto the ground as they pass through the trees (in other words, to aim the laser pulses at the ground), so in addition to measurement point data obtained by irradiating the ground, measurement point data obtained is also data obtained from reflections on tree leaves and trunks.

In many cases, airborne laser measurements are performed to determine the ground level of the target area, and so measurement point data reflected by tree leaves and trunks is essentially unnecessary data, or noise data. For this reason, filtering is commonly performed to remove noise data reflected by tree leaves and other elements, and various improved filtering techniques have been proposed. For example, Patent Document 1 proposes a technique for comparing a terrain model (a so-called surface model) obtained through photometry with measurement point data obtained through airborne laser measurement, and removing noise by assuming that measurement point data that approximates the terrain model obtained through photometry has been reflected by tree leaves and trunks (equivalent to a surface).

JP 2011-158278 A

As mentioned above, measurement point data reflected by leaves and other objects is typically filtered to remove it as noise data. However, it is not realistic to manually remove the vast amount of measurement point data obtained from a single measurement. For this reason, noise removal is currently performed automatically based on certain requirements. A typical example of filtering is filtering that removes measurement point data where the reflection intensity (amplitude of the laser pulse) of the received laser pulse falls below a predetermined threshold as noise data. It is known that the reflection intensity of a laser pulse reflected by leaves and other objects is lower than that of a laser pulse reflected by the ground, and therefore measurement point data related to laser pulses with low (weak) reflection intensity is unconditionally treated as noise data. In fact, much software that processes measurement point data employs filtering processes that use this reflection intensity as a requirement.

However, laser pulses with a small reflection intensity (below the threshold) (hereinafter referred to as "weak-intensity laser pulses") may also be properly reflected by the ground depending on the conditions. In other words, current filtering processes remove useful measurement point data without utilizing it. In areas where measurement point data can be acquired at a considerable density after filtering, measurement point data related to such weak-intensity laser pulses (hereinafter referred to as "weak-intensity measurement point data") is not particularly needed. However, in areas where almost no measurement point data remains after filtering, such as under broadleaf trees, such weak-intensity measurement point data becomes extremely valuable.

The objective of the present invention is to solve the problems faced by conventional technology, namely, to provide a ground surface generation system that can extract data reflected by the ground from weak intensity measurement point data and use it to generate a ground surface.

The present invention makes effective use of weak-intensity measurement point data that has traditionally been discarded, focusing on the point that data reflected by the ground is selected from among the weak-intensity measurement point data, and is an invention based on a previously unconventional concept.

The ground surface generation system of the present invention generates a ground surface based on point cloud data consisting of multiple measurement point data acquired by an airborne laser scanner while flying multiple courses. It includes a primary filtering means, a secondary filtering means, an adjustment calculation means, a tertiary filtering means, a provisional ground surface generation means, and a quasi-optimal data filtering means. The primary filtering means extracts measurement point data from the point cloud data where the reflection intensity of the laser received during measurement is below a predetermined intensity threshold as "primary noise data," and extracts measurement points from the point cloud data after removing the primary noise data as "primary appropriate data." The secondary filtering means extracts "secondary noise data" from the primary appropriate data and primary noise data according to their relative positions with neighboring points, and classifies measurement point data obtained by removing the secondary noise data from the primary appropriate data as "secondary appropriate data" and measurement point data obtained by removing the secondary noise data from the primary noise data as "quasi-optimal data." The adjustment calculation means is a means for calculating "adjusted secondary optimum data" by performing adjustment calculations between courses on the secondary optimum data, and the tertiary filtering means is a means for extracting "tertiary noise data" from the adjusted secondary optimum data according to its positional relationship with neighboring points, and classifying the measurement point data obtained by removing the tertiary noise data from the adjusted secondary optimum data as "optimal data." The provisional ground surface generation means is a means for generating a "provisional ground surface" based on the optimum data, and the quasi-optimal data filtering means is a means for extracting "applied quasi-optimal data" from the quasi-optimal data according to its positional relationship with the provisional ground surface. The provisional ground surface is then supplemented with the applied quasi-optimal data to generate a ground surface.

The ground surface generation system of the present invention can also extract measurement point data as noise data if the distance between the measurement point data and other nearby measurement point data or the angle between the measurement point data and that measurement point data exceeds a predetermined noise threshold.

The ground surface generation system of the present invention can also extract measurement point data whose distance from the provisional ground surface is below a predetermined ground threshold as quasi-appropriate data for application.

The ground surface generation system of the present invention may further include a missing area setting means. This missing area setting means sets an area where the density of the appropriate data that makes up the provisional ground surface falls below a predetermined point density threshold as a point cloud missing area. In this case, the ground surface is generated by extracting and complementing the applicable quasi-appropriate data included in the point cloud missing area.

The ground surface generation system of the present invention may further include a manual removal means. The manual removal means allows the operator to remove desired appropriate data or applicable quasi-appropriate data while visually inspecting the ground surface displayed on the display means.

The ground surface generation system of the present invention has the following effects.
(1) By utilizing measurement point data (weak intensity measurement point data) that was previously removed, it is possible to generate a more precise ground surface. In particular, in areas where almost no measurement point data remains after filtering, such as under broadleaf trees, the ground surface can be generated more effectively.
(2) Conventional airborne laser scanners and data processing software can be used as they are without modification, meaning that the system can be applied to general-purpose airborne laser measurements without incurring any special costs.

1 is a block diagram showing the main configuration of a ground surface generation system according to the present invention. 1A is a side view model diagram that schematically shows the distance between a line segment connecting two pieces of nearby measurement point data and the measurement point data, and FIG. 1B is a side view model diagram that schematically shows the angle formed by a line segment connecting two pieces of nearby measurement point data and a line segment connecting the measurement point data and one of the pieces of nearby measurement point data. FIG. 10 is a side view model diagram schematically showing quasi-optimal data, secondary optimal data, and secondary noise data. A side model diagram showing the layout relationship between the quasi-appropriate data and the provisional ground surface. 1 is a flowchart showing the main processing flow when using the ground surface generation system of the present invention.

An example of an implementation of the ground surface generation system of the present invention will be described with reference to the accompanying drawings. One of the features of the ground surface generation system of the present invention is that it effectively utilizes measurement point data (weak intensity measurement point data) related to laser pulses with small (weak) reflection intensity to generate the ground surface.

Figure 1 is a block diagram showing the main components of the ground surface generation system 100 of the present invention. As shown in this figure, the ground surface generation system 100 of the present invention is configured to include a primary filtering means 101, a secondary filtering means 102, an adjustment calculation means 103, a tertiary filtering means 104, a provisional ground surface generation means 105, and a quasi-appropriate data filtering means 107, and can also be configured to include a missing area setting means 106, a ground surface generation means 108, a manual removal means 109, a point cloud data storage means 110, etc.

The primary filtering means 101, secondary filtering means 102, adjustment calculation means 103, tertiary filtering means 104, provisional ground surface generation means 105, missing area setting means 106, quasi-appropriate data filtering means 107, ground surface generation means 108, and manual removal means 109 that make up the ground surface generation system 100 can be manufactured as dedicated devices, or general-purpose computer devices can be used. This computer device is equipped with a processor such as a CPU and memory such as ROM and RAM, and some also include input means such as a mouse and keyboard, and a display. Examples of such devices include portable terminal devices such as tablet computers (such as iPads (registered trademarks)) and smartphones, as well as personal computers (PCs) and servers.

The point cloud data storage means 110 can be a storage device of a computer device, or can be built on a database server. If built on a database server, it can be placed on a local network (LAN: Local Area Network), or it can be a cloud server that stores data via the Internet (wired or wireless communication).

Below, we will explain in detail each of the main elements that make up the ground surface generation system 100.

(Point cloud data storage means)
The point cloud data storage means 110 is a means for storing a large number of measurement point data (i.e., point cloud data) obtained as a result of measuring a target area using airborne laser measurement with a near-infrared laser or airborne laser measurement with a green laser. Each measurement point data is a so-called three-dimensional coordinate consisting of plane coordinate values and height information at the point where the laser pulse is reflected (measurement point). Here, plane coordinate values are coordinates on a horizontal plane expressed by latitude and longitude or X coordinates and Y coordinates, and height information means the vertical distance from a predetermined reference horizontal plane such as altitude.

(Primary filtering means)
The primary filtering means 101 is a means for reading out point cloud data from the point cloud data storage means 110 (FIG. 1) and performing primary filtering processing on the point cloud data. This primary filtering is a conventional process in which measurement point data in which the reflection intensity of the laser pulse (amplitude of the laser pulse) is below a predetermined threshold (hereinafter referred to as the "intensity threshold") is extracted and the extracted measurement point data is classified as "primary noise data." However, this data is merely classified as primary noise data and is not immediately removed, but is stored separately in a storage means (for example, the point cloud data storage means 110).

The primary filtering means 101 also extracts measurement point data from the point cloud data, removing primary noise data, and classifies the extracted measurement point data as "primary appropriate data." This primary appropriate data is also stored separately in a storage means (e.g., point cloud data storage means 110).

(Secondary filtering means)
The secondary filtering means 102 is a means for performing secondary filtering processing on the primary noise data and the primary correct data (i.e., point cloud data). This secondary filtering is a conventional process in which relevant measurement point data (hereinafter referred to as "relevant measurement point data") is extracted based on the positional relationship between the target measurement point data and measurement point data (hereinafter referred to as "neighboring measurement point data") located near the target measurement point data, and the extracted measurement point data is classified as "secondary noise data." Specifically, as shown in FIG. 2( a), measurement point data in which the distance L (distance) between a line segment connecting two neighboring measurement point data and the target measurement point data exceeds a predetermined length threshold (hereinafter referred to as "noise threshold") is extracted and classified as secondary noise data. Furthermore, as shown in FIG. 2( b), measurement point data in which the angle a between a line segment connecting two neighboring measurement point data and a line segment connecting the target measurement point data and one of the neighboring measurement point data exceeds the noise threshold (in this case, an angle) is also classified as secondary noise data.

The secondary filtering means 101 also classifies the measurement point data obtained by removing the secondary noise data from the primary noise data as "quasi-optimal data," and classifies the measurement point data obtained by removing the secondary noise data from the primary optimal data as "secondary optimal data." Figure 3 shows a schematic diagram of the quasi-optimal data, secondary optimal data, and secondary noise data. This quasi-optimal data and secondary optimal data are stored separately in a storage means (for example, the point cloud data storage means 110).

(Adjustment calculation means)
Airborne laser measurements typically cover a wide area, so they fly multiple courses (routes) to cover the entire range. To avoid missing any areas, measurements are taken on adjacent courses with a certain degree of overlap (sidelap). In other words, two types of measurements are taken on different courses within the sidelap range. Airborne laser measurements are known to have errors dependent on equipment such as GNSS and IMU, as well as errors caused by the laser pulse passing through the atmosphere. Therefore, discrepancies may occur between the two measurement results obtained within the sidelap range, resulting in inconsistencies. Therefore, when airborne laser measurements are performed, a so-called inter-course verification is performed, in which the two measurement results within the sidelap range are compared to determine consistency. If inconsistency is determined, inter-course adjustment is performed to reconcile the two measurement results.

The adjustment calculation means 103 is a means for performing inter-course adjustments on measurement point data obtained by flying multiple courses. However, secondary optimum data is used for this inter-course adjustment. Here, the measurement point data after inter-course adjustments have been performed on the secondary optimum data is stored separately in a storage means (e.g., the point cloud data storage means 110) as "adjusted secondary optimum data."

(Third-order filtering means)
The tertiary filtering means 104 is a means for executing secondary filtering processing on the adjusted secondary correct data. This tertiary filtering is also a conventional processing, and like the secondary filtering processing (FIG. 2), it is a processing for extracting corresponding measurement point data according to the positional relationship between the measurement point data and neighboring measurement point data, and classifying the extracted measurement point data as "tertiary noise data."

The tertiary filtering means 104 also classifies the measurement point data obtained by removing the tertiary noise data from the adjusted secondary appropriate data as "appropriate data." This appropriate data is stored separately in a storage means (e.g., point cloud data storage means 110).

(Temporary ground surface generation means)
The provisional ground surface generating means 105 is a means for generating a ground surface using the appropriate data classified by the tertiary filtering means 104. However, the ground surface at this stage is only provisional and not complete. Therefore, for convenience, the ground surface generated by the provisional ground surface generating means 105 will be referred to as the "provisional ground surface" here.

(Insufficient area setting means)
The missing area setting means 106 is a means for setting a "missing area" based on the appropriate data constituting the provisional ground surface. Here, a missing area refers to an area (FIG. 3) where the point density (number of measurement points per unit area) of the appropriate data is low. More specifically, it refers to an area where the point density of the appropriate data is below a predetermined threshold (hereinafter referred to as the "point density threshold"). As mentioned above, there are no particular problems in generating a ground surface in areas where measurement point data can be acquired at a sufficient density. However, in areas where measurement point data is scarce, such as under broadleaf forests, applicable quasi-appropriate data (described below) becomes extremely valuable. Therefore, it is preferable to set a missing area in advance using the missing area setting means 106 and then supplement the missing area with applicable quasi-appropriate data. Of course, it is also possible to supplement the entire target range with applicable quasi-appropriate data without setting a missing area using the missing area setting means 106. In this case, the missing area setting means 106 can be omitted.

(Quasi-optimal data filtering means)
The quasi-appropriate data filtering means 107 extracts "applicable quasi-appropriate data" by filtering the quasi-appropriate data. The applicable quasi-appropriate data is measurement point data generated by laser pulses reflected from the ground, and is useful for generating a ground surface. The filtering process extracts the relevant quasi-appropriate data based on its positional relationship with the provisional ground surface (constructed by the appropriate data) generated by the provisional ground surface generating means 105, and classifies the extracted quasi-appropriate data as "applicable quasi-appropriate data." Specifically, as shown in FIG. 4 , quasi-appropriate data whose distance L (distance) from the provisional ground surface is less than a predetermined length threshold (hereinafter referred to as the "ground threshold") is extracted and classified as applicable quasi-appropriate data. Furthermore, quasi-appropriate data whose angle a between the line segment connecting two neighboring suitability data points and the line segment connecting the quasi-appropriate data to one of the neighboring suitability data points is less than the ground threshold (in this case, the angle) can also be classified as applicable quasi-appropriate data. This application quasi-appropriate data is separately stored in a storage means (for example, the point cloud data storage means 110).

(Ground surface generation means)
The ground surface generating means 108 is a means for generating a ground surface using the provisional ground surface (i.e., appropriate data) generated by the provisional ground surface generating means 105 and the applicable quasi-appropriate data classified by the quasi-appropriate data filtering means 107. In other words, the ground surface is completed by supplementing the insufficient areas of the provisional ground surface with the applicable quasi-appropriate data.

(Manual removal means)
The manual removal means 109 is a means for making adjustments to the ground surface generated by the ground surface generation means 108. Specifically, while visually checking the ground surface displayed on the display means (such as a display), the operator can use a pointing device (such as a mouse, touch panel, pen tablet, touchpad, trackpad, trackball, etc.) or a keyboard to perform editing operations such as removal and movement of the appropriate data and applied quasi-appropriate data that make up the ground surface.

(Processing flow)
Next, the main processing flow when using the ground surface generation system 100 of the present invention will be explained with reference to Figure 5. In this flow chart, the action to be performed is shown in the center column, the items necessary for that action are shown in the left column, and the items resulting from that action are shown in the right column.

First, the primary filtering means 101 reads point cloud data from the point cloud data storage means 110 and performs primary filtering on the point cloud data to extract "primary noise data" and "primary appropriate data" (Step 201 in Figure 5). Next, the secondary filtering means 102 performs secondary filtering on the primary noise data and primary appropriate data to extract "secondary noise data," "quasi-appropriate data," and "secondary appropriate data" (Step 202 in Figure 5).

Once the secondary optimum data is extracted, the adjustment calculation means 103 performs inter-course adjustment on the secondary optimum data to calculate "adjusted secondary optimum data" (Step 203 in Figure 5). Then, the tertiary filtering means 104 performs tertiary filtering on the adjusted secondary optimum data to extract "tertiary noise data" and "optimal data" (Step 204 in Figure 5).

Once the appropriate data is extracted, the provisional ground surface generation means 105 generates a "provisional ground surface" based on the appropriate data (Step 205 in Figure 5), and the missing area setting means 106 sets a "missing area" based on the appropriate data that constitutes the provisional ground surface (Step 206 in Figure 5).

Once the missing areas have been set, the quasi-appropriate data filtering means 107 extracts "applicable quasi-appropriate data" by filtering the quasi-appropriate data (Step 207 in Figure 5). Then, once the provisional ground surface (i.e., appropriate data) and applicable quasi-appropriate data have been obtained, the ground surface generation means 108 completes the ground surface by filling in the missing areas (or the entire area) of the provisional ground surface with the applicable quasi-appropriate data (Step 208 in Figure 5). If necessary, the operator can use the manual removal means 109 (e.g., a pointing device) to perform editing operations on the appropriate data and applicable quasi-appropriate data while visually checking the ground surface displayed on the display means (e.g., a display) (Step 209 in Figure 5).

The ground surface generation system of the present invention can be used to obtain ground elevations in a variety of locations, including mountainous areas, coastal areas, and urban areas, and is particularly suitable for use in locations with forested areas. Because the present invention can obtain ground elevations with high accuracy, it can be effectively used in social infrastructure planning and disaster prevention planning, making it an invention that can be used industrially and is also expected to make a significant contribution to society.

100 Ground surface generation system of the present invention 101 Primary filtering means (of ground surface generation system) 102 Secondary filtering means (of ground surface generation system) 103 Adjustment calculation means (of ground surface generation system) 104 Tertiary filtering means (of ground surface generation system) 105 Provisional ground surface generation means (of ground surface generation system) 106 Missing area setting means (of ground surface generation system) 107 Quasi-appropriate data filtering means (of ground surface generation system) 108 Ground surface generation means (of ground surface generation system) 109 Manual removal means (of ground surface generation system) 110 Point cloud data storage means (of ground surface generation system)

Claims (5)

A system for generating a ground surface based on point cloud data consisting of a plurality of measurement point data acquired by an airborne laser scanner by flying a plurality of courses such that adjacent courses overlap ,
a primary filtering means for extracting, from the point cloud data, measurement point data in which the reflection intensity of the laser received during measurement is below a predetermined intensity threshold as primary noise data, and classifying the measurement point data obtained by removing the primary noise data from the point cloud data into primary proper data;
a secondary filtering means for extracting secondary noise data from the primary optimum data and the primary noise data according to a positional relationship with neighboring points, and classifying the measurement point data obtained by removing the secondary noise data from the primary optimum data as secondary optimum data, and the measurement point data obtained by removing the secondary noise data from the primary noise data as quasi-optimal data;
an adjustment calculation means for calculating adjusted secondary optimum data by performing an adjustment calculation between the courses on the secondary optimum data;
a tertiary filtering means for extracting tertiary noise data from the adjusted secondary optimum data in accordance with the positional relationship with neighboring points, and classifying the measurement point data obtained by removing the tertiary noise data from the adjusted secondary optimum data into optimum data;
A temporary ground surface generating means for generating a temporary ground surface based on the appropriate data;
and a quasi-appropriate data filtering means for extracting applicable quasi-appropriate data from the quasi-appropriate data according to a layout relationship with the provisional ground surface,
generating the ground surface by complementing the provisional ground surface with the applied quasi-adequate data;
A ground surface generation system characterized by: The secondary filtering means and the tertiary filtering means extract, as noise data, measurement point data in which the distance between the measurement point data and other nearby measurement point data and/or the angle between the measurement point data and other nearby measurement point data exceeds a predetermined noise threshold.
2. The ground surface generation system according to claim 1. The quasi-appropriate data filtering means extracts the measurement point data whose distance from the provisional ground surface is less than a predetermined ground threshold value as the applicable quasi-appropriate data.
3. The ground surface generation system according to claim 1 or 2. Further provided is a missing area setting means for setting an area where the density of the appropriate data constituting the provisional ground surface is below a predetermined point density threshold as a point cloud missing area,
The ground surface is generated by extracting and complementing the application quasi-appropriate data included in the point cloud shortage region.
4. The ground surface generation system according to claim 1, wherein the ground surface generation system is a ground surface generation system. Further provided is a manual removal means by which an operator can remove desired appropriate data and/or applied quasi-appropriate data while visually checking the ground surface displayed on the display means,
5. The ground surface generation system according to claim 1, wherein the ground surface generation system is a ground surface generation system.