Shadow measurement method for building height inversion

Abstract

The invention relates to a shadow measurement method for building height inversion, and belongs to the technical field of geographic space measurement. According to the method, the optimal division of the shadow is realized through the combination of a fishing net method and various constraint conditions; counting shadow length values of all divided areas, and determining an optimal shadow value by using a quartile method and a bidirectional approximation strategy; and finally, comprehensively evaluating the optimal values of all regions to determine the shadow length. According to the measurement method, preferential selection of a measurement area, preferential selection of statistical data and preferential selection of an optimal value are fully considered, the influence of unsmoothness and shielding of a shadow boundary on a measurement result can be reduced to the greatest extent, and the accuracy and robustness of calculating the building height by a shadow method are improved, so that large-scale and large-area urban building height measurement is realized, and the measurement efficiency is improved. And basic research data is provided for inversion and expansion of the urban height.

Description

Technical Field

[0001] The invention relates to a shadow measurement method for building height inversion, and belongs to the technical field of geographic space measurement. Background Art

[0002] In recent years, my country's urbanization process has been continuously advancing, which is not only reflected in the growth of urban area, but also in the growth of building height. On the one hand, the growth of height can overcome the bottleneck of scarce urban land resources as much as possible, and on the other hand, it can contribute to the optimization of urban structure and urban functions. In the field of urban remote sensing research, the extraction of urban building height has also become a research focus. The estimation and measurement of urban building height has become an important parameter for urban planning and expansion, urban disaster risk warning and assessment, and also provides basic surveying and mapping data for the establishment of digital city three-dimensional models. In recent years, the open source of many geospatial data such as satellite images, building footprint vector data and lidar point clouds is creating opportunities to generate large three-dimensional city models in a low-cost way.

[0003] Shadows in images have many negative effects on remote sensing interpretation, but some shadows can be used to calculate the height of target objects. In some areas where drones cannot reach or stereo pairs are lacking, inverting height information through building shadows has become a common technical means. For a single image, the height of the target object cannot be directly obtained, but the height information of the object can be calculated through the specific relationship between the shadow of the target object and the sun, satellite altitude angle and azimuth. Since 1989, researchers have been using shadow information to estimate building heights in aerial photogrammetry. Therefore, obtaining accurate shadow length is the key to inverting building heights.

[0004] At present, there are relatively few shadow measurement algorithms, mainly including the area and perimeter inverse algorithm, the corner point closest distance method, and the fishing net method. The area and perimeter inverse algorithm and the corner point closest distance method are limited to regular, unobstructed shadow areas, and are not applicable to irregularly shaped and obstructed building shadows. The fishing net method combines conditions such as pixel size and sun azimuth to generate a series of equally spaced fishing net lines in the shadow area, and reduces errors through multiple measurements. It has high relative accuracy and a wide range of applications. To this end, some people have proposed combining the building outline with the fishing net method to achieve a one-to-one correspondence between buildings and shadows, solving the problem of shadows sticking to each other in densely built areas. However, this method does not explore the impact of uneven shadow boundaries and occlusion on the measurement results in complex scenes, resulting in low measurement accuracy. Summary of the invention

[0005] The purpose of the present invention is to provide a shadow measurement method for building height inversion, so as to solve the problem of low measurement accuracy caused by occlusion in the current shadow measurement process.

[0006] In order to solve the above technical problems, the present invention provides a shadow measurement method for building height inversion, which comprises the following steps:

[0007] 1) Obtain the shadow vector of the building and perform point measurement on the obtained shadow vector;

[0008] 2) Determine the building corresponding to each shadow vector based on the point measurement results, and determine the segmentation ratio and segmentation point based on the building's boundaries and sampling interval;

[0009] 3) Use the segmentation point and the sun's position to segment the shadow vector, obtain multiple regions, and count the shadow length value in each region;

[0010] 4) Perform statistical processing on the shadow length values ​​of each area to determine the optimal length value of each area, classify the current building occlusion situation according to the difference in the optimal length values ​​of each area, and determine the shadow length value of the building according to the occlusion category and the optimal length value of the area.

[0011] The present invention determines the segmentation ratio and the segmentation point according to the four boundaries of the building and the sampling interval to achieve the optimal division of the shadow; statistical processing is performed on the shadow length value of each area to determine the optimal length value of each area, and the shadow length value of the building is determined according to the difference in the optimal length values ​​of each area, the shading condition of the current building and the optimal length value of the area. The measurement process of the present invention fully considers the optimization of the measurement area, the optimization of the statistical data, and the optimization of the optimal value, which can minimize the influence of the uneven shadow boundary and shading on the measurement result, and improve the accuracy and robustness of the shadow method to calculate the building height.

[0012] Furthermore, in the step 4), if the difference in the optimal length values ​​of each area is less than a set threshold, it belongs to the first type of scene, otherwise it is a second type of scene. The first type of scene refers to a building that is unobstructed or fully obstructed, and the second type of scene refers to a building that is partially obstructed; if the current scene is the first type of scene, if the building is unobstructed, the average value of the optimal length values ​​of each area is used as the shadow length of the building; if it is fully obstructed, a nearest neighbor search algorithm is used to search, and the shadow length corresponding to the nearest unobstructed building or the shadow length corresponding to the partially obstructed building is used as the shadow length value of the building; if the current scene is the second type of scene, the maximum value of the optimal length values ​​of each area is used as the shadow length of the building.

[0013] The present invention classifies the scene where the building is located according to the difference in the optimal length value of each area to indicate the occlusion of the building. When the building is not occluded, the average value of the optimal length value of each area is the shadow length of the building; when it is partially occluded, the maximum value is selected as the shadow length of the building; when it is fully occluded, the search range is expanded to the surroundings, and the shadow length of the nearest unobstructed building or partially obstructed building is used as the shadow length of the building. This method fully considers the occlusion of the building, and further optimizes and adjusts the optimal value of each area according to the occlusion, further improving the accuracy of building shadow measurement.

[0014] Furthermore, the step 1) uses a fishnet method to perform point measurement on the entire shadow mask.

[0015] The present invention adopts the fishing net method to carry out point measurement and can accurately achieve the correspondence between shadows and buildings.

[0016] Furthermore, the calculation formula for the segmentation ratio in step 2) is:

[0017]

[0018] Where seg is the segmentation ratio, d is the sampling interval of the point measurement, η is the buffer distance, BX max With BX min is the maximum and minimum longitude of the building envelope rectangle, and SR is the image resolution.

[0019] The present invention uses the ratio of the sampling interval of the point measurement plus a certain buffer distance to the width of the building outer rectangle as the segmentation ratio. The determined segmentation ratio is more reasonable, avoiding the problem that the segmentation ratio is too large, resulting in low measurement results, and the segmentation ratio is too small, resulting in unreliable calculation results.

[0020] Furthermore, the segmentation points are determined according to the number of areas to be divided, the segmentation ratio, and the boundaries of the buildings.

[0021] Furthermore, each region is determined by the solar azimuth, the maximum and minimum latitudes of the shadow bounding rectangle, and the dividing point.

[0022] The present invention determines each statistical area based on the solar azimuth, the maximum and minimum latitudes of the shadow outer rectangle, and the segmentation points. The determined statistical areas are of appropriate size, which can further improve the measurement result of the shadow length.

[0023] Furthermore, the optimal length value of each region is determined as follows:

[0024] The quartile method was used to eliminate outliers in the shadow length values ​​within each region;

[0025] The two-way approximation method is used to select a group of highly similar values ​​from the shadow length values ​​in each area, and the average value of this group of shadow length values ​​is taken as the optimal value of the area.

[0026] The present invention uses the quartile method to eliminate outliers in the shadow length values ​​in each area to avoid interference caused by outliers; the shadow lengths of each area are further screened by the two-way approximation method to find highly similar measurement values, so that the selected optimal value can represent the measurement results of the area.

[0027] Furthermore, the threshold value set in step 4) refers to the shadow length corresponding to the allowable error of the building height.

[0028] Furthermore, the classification basis in step 4) is:

[0029]

[0030] where opt max with opt min is the maximum and minimum value of the four statistical results, δ is the allowable error of the building height, α is the solar altitude angle, 1 represents the first type of scene, and 2 represents the second type of scene. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is the technical roadmap of the shadow measurement method for building height inversion of the present invention;

[0032] Figure 2a This is a diagram of the first ideal shadow distribution in a real scene;

[0033] Figure 2b This is a schematic diagram of the second more ideal shadow distribution in a real scene;

[0034] Figure 2c This is a schematic diagram of the holes inside the shadow caused by the shadow boundary being affected by vegetation in a real scene;

[0035] Figure 2d This is a schematic diagram of the uneven shadow boundary in a real scene;

[0036] Figure 2e It is a schematic diagram of shadow occlusion and extension in real scenes;

[0037] Figure 2f This is a schematic diagram of the situation where the shadow is blocked by the first level of the building in the real scene;

[0038] Figure 2g This is a schematic diagram of the situation where the shadow is blocked by the secondary building in the real scene;

[0039] Figure 2hThis is a schematic diagram of the three-level occlusion of shadows by buildings in real scenes;

[0040] Figure 2i This is a schematic diagram of the shadow being blocked by four levels of buildings in a real scene;

[0041] Figure 2j This is a schematic diagram of the situation where shadows stick to each other in a real scene;

[0042] Figure 3a is a schematic diagram of determining a segmentation point in an embodiment of the present invention;

[0043] Figure 3b is a schematic diagram of region segmentation in an embodiment of the present invention;

[0044] Figure 3c is a schematic diagram of regional measurement in an embodiment of the present invention;

[0045] Figure 4 Schematic diagram of determining optimal values ​​for each region in an embodiment of the present invention;

[0046] Figure 5 It is a schematic diagram of the optimal value evaluation technology route in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The specific implementation of the present invention will be further described below in conjunction with the accompanying drawings.

[0048] The present invention first obtains the shadow vector of the building, performs point measurement on the obtained shadow vector, and determines the shadow vector corresponding to each building vector according to the point measurement result, and determines the segmentation point according to the four-dimensional range of the building and the spacing of the sampling points; then the shadow vector is segmented by using the segmentation point and the sun's position, and the shadow length value in each area is counted; then the shadow length value of each area is statistically processed to determine the optimal length value of each area, and the current shadow scene is classified according to the difference in the optimal length values ​​of each area.

[0049] This method implements the route as Figure 1 As shown, the specific description is given below.

[0050] 1. Partition measurement

[0051] Existing methods for inversely calculating building heights based on shadow information are usually based on the three assumptions of regularized shadows, flat terrain, and idealized distribution. The idealized assumptions also lead to low robustness of most algorithms in practical applications. The reason is that the actual shadow situation is complex, buildings are connected, and the occlusion is serious, which makes the shadow measurement results inaccurate. Common shadow forms in real scenes are as follows: Figure 2a-2j As shown, Figure 2a and Figure 2bThe ideal shadow distribution is shown respectively; Figure 2c , Figure 2d and Figure 2e They are the situations where the shadow boundary is affected by vegetation, resulting in holes inside the shadow, uneven shadow boundary, and shadow occlusion and extension; Figure 2f to Figure 2j They represent the different degrees of shadows being blocked by buildings, and the situations where shadows are stuck to each other. It can be seen that for the shadows of blocked buildings, only part of the area can be used to calculate the building height. This part of the area is called the optimal measurement area, and the value calculated using it is the optimal value. Therefore, it is necessary to focus on the optimal measurement area of ​​the shadow in order to obtain an accurate and reliable shadow length value.

[0052] The present invention takes the building polygon as an additional condition and designs a partition measurement method, such as Figure 3a , Figure 3b and Figure 3c As shown, this method can solve the problem of inaccurate measurement caused by horizontal and vertical shadows and shadow obstruction in areas with dense buildings.

[0053] First, the fishing net method is used to measure the entire shadow mask. The principle is: seed points are placed within the shadow range at a certain sampling interval (in pixels), such as Figure 3a As shown in the figure, the distance of the shadow boundary in the sun's direction is measured; secondly, the nearest neighbor search algorithm is used to determine the shadow corresponding to each building; then, the segmentation ratio point is determined according to the four boundaries of the building's outer rectangle and the sampling point spacing. Figure 3b For example, if the segmentation ratio is too large, the statistical area will be larger, and more measurement values ​​affected by occlusion will be included in the set, resulting in a lower measurement result; if the segmentation ratio is too small, only a small number or no measurement values ​​will be included in the set, resulting in unreliable calculation results. Therefore, in order to ensure that a certain number of measurement results are included in the statistical set in the horizontal direction, the present invention uses the ratio of the horizontal measurement interval plus a certain buffer distance to the width of the building outer rectangle as the minimum segmentation ratio, as shown in formula (1):

[0054]

[0055] Where seg is the segmentation ratio, d is the sampling interval, η is the buffer distance, BX max With BX min is the maximum and minimum longitude of the building envelope rectangle, and SR is the image resolution.

[0056] In order to reduce the impact of occlusion measurement values ​​on the final statistical results, this embodiment defines four measurement areas: the left and right measurement areas are determined with the minimum segmentation ratio (the segmentation points are div1_L, div1_B, div3_L, div3_B) to reduce the ratio of occlusion measurement values ​​in the measurement area and improve the measurement capability of occlusion situations. Dividing the middle measurement area into two (the segmentation points are div2_L and div2_B) can effectively avoid the situation where more measurement values ​​affected by occlusion are included in the set due to the middle measurement area being too large, resulting in low measurement results. The measurement areas divided in this way can effectively take into account different degrees of occlusion. The longitude and latitude coordinates of the segmentation points are shown in formula (2):

[0057]

[0058] In the formula, BY max BY min is the maximum latitude and minimum latitude of the building envelope rectangle, div1_L and div1_B ​​are the longitude and latitude coordinates of the first division point, and the same applies to div2_L, div2_B, div3_L, and div3_B.

[0059] Formula (2) is the calculation formula for the coordinates of the division points when the region is divided into 4 time points. When the region is divided into n time points, the calculation formula for the coordinates of the division points is:

[0060] div1_L=BX min +(BX max -BX min )·seg

[0061] M

[0062] divm_L=div1_L+(m-1)(BX max -BX min )(1-2seg) / (n-2)

[0063] M

[0064] divn-1_L=BX max -(BX max -BX min )·seg

[0065] div1_B=L=divm_B=L=divn-1_B=(BY max +BY min ) / 2

[0066] Where n is the number of segmented regions, m is the mth segmentation point, and its value range is [2, n-2].

[0067] Then, the segmentation starting point is determined by the coordinates of the four sides of the building and the coordinates of the segmentation ratio point, and the segmentation area is formed according to the sun's position and the segmentation length (the shadow length plus half of the building length). The part where the segmentation area intersects with the shadow is the measurement area. is a closed polygon, and the four measurement areas are shown in formula (3):

[0068]

[0069] Where S(i), (i = 1, 2, 3, 4) is the measurement statistical area, γ is the solar azimuth, Hbuf is the segmentation height, SY max , SY min is the maximum and minimum latitude of the shadow rectangle. BX min , div1_L, div1_B, γ, Hbuf, and the rest are the same, Poly shadow The shaded polygon.

[0070] Finally, according to the measurement results of the fishing net method, the measurement values ​​in each area are counted and the shadow length set L is constructed. i ={l1,l2,K,l n}(i=1,2,3,4), such as Figure 3c shown.

[0071] There is no definite basis for the number of area divisions n, which is an experimental value. It is the result of comprehensive consideration of different occlusion situations and building widths in order to reduce the proportion of the shadow measurement values ​​in the measurement set. The number of measurement statistical areas should be as small as possible. The fewer the number of measurements, the less the amount of calculation. However, if the measurement area is too large, the proportion of erroneous measurements will increase. The four areas in this embodiment are the result of a large number of experiments.

[0072] 2. Highest quality evaluation.

[0073] 1) Determine the optimal value for each region.

[0074] The present invention firstly adopts a statistical method to eliminate L in each region. i Specifically, the present invention uses the quartile method in statistics to eliminate the outliers in each region. i The quartile method can analyze the degree of data dispersion or the degree of two-level differentiation by segmenting the data, eliminating the influence of the maximum and minimum outliers, and judging the data density to determine the interval where the data is mainly concentrated. Then, a two-way approximation strategy is adopted to select a group of highly similar measurements by setting the optimal threshold T, and take their average value as the optimal value of the statistical area, such as Figure 4For this embodiment, the implementation process of this step is as follows:

[0075] (1) L i The values ​​are arranged from small to large, and the quartile method is used to eliminate gross errors.

[0076] (2) Take L i The median is taken as the reference value l med , set the optimal threshold T, which is an empirical value used to control the neatness of the data. The smaller the value, the more neat the screening results will be, but the number will also be smaller. It is usually set to the allowable error of the building height.

[0077] (3) Calculate L i Middle max With l min If the difference is greater than T, it is further eliminated according to formula (4).

[0078]

[0079] (4) Iterate (3) until L i Middle max With l min The difference is less than T, and the mean is taken as the optimal value opt of the region according to formula (5).

[0080]

[0081] Where n is the number of measurements after screening by the bidirectional approximation strategy

[0082] 2) Classify shadow scenes according to the differences in the optimal values ​​of each area.

[0083] The partition measurement method can effectively solve the problem of poor measurement accuracy of existing shadow measurement algorithms when the top boundary of the shadow is partially blocked by surrounding buildings. However, when the top boundary of the shadow is completely blocked by surrounding buildings, the image cannot show the complete shadow length, so the building height value measured by it is not reliable. In practical applications, the target buildings that are completely blocked by the shadow need to be screened out and further analyzed manually or in combination with other auxiliary information.

[0084] This embodiment classifies shadow scenes based on the difference in opt values ​​in the four measurement areas. The four opts for unobstructed and fully obstructed shadows are relatively close due to the relatively smooth boundaries. The four opts for shadows partially obstructed by buildings, trees and other objects will have obvious differences, and the largest statistical result is the most reliable. Therefore, according to the difference in opt values ​​in different statistical areas, shadow scenes are divided into two categories: unobstructed and fully obstructed shadows are the first category of scenes; partially obstructed shadows are the second category of scenes.

[0085] The present invention uses the shadow length corresponding to the allowable error of the building height as the difference threshold, calculates the difference between the maximum and minimum values ​​of the four statistical results, and makes scene discrimination according to formula (6).

[0086]

[0087] Where: opt max with opt min is the maximum and minimum value of the four statistical results, δ is the allowable error of the building height, α is the solar altitude angle, 1 represents the first type of scene, and 2 represents the second type of scene.

[0088] 3) Determine the shadow of the building according to the shadow scene category to which it belongs.

[0089] like Figure 5 As shown in the figure, the present invention designs an optimal value evaluation strategy based on the classification results. For the second type of scenario, directly take opt max The corresponding measurement area is taken as the optimal area, opt max The shadow length value of the building will also be represented, that is, the largest optimal value is selected from the optimal values ​​of the four areas as the shadow length value of the building. For the first type of scene, first perform occlusion judgment to determine whether the building is in an unobstructed state or a fully obstructed state. If it is in an unobstructed state, select the average opt of each area as the shadow length value of the building, that is, calculate the average of the optimal values ​​of the four areas, and use the average as the shadow length value of the building; if the building is in a fully obstructed state, expand the search range to the surrounding areas, and use the opt corresponding to the nearest unobstructed building or the opt corresponding to the second type of building. max As the shadow length value of the building, and mark it.

[0090] The present invention realizes the optimal division of shadows by combining the fishing net method with multiple constraints; then the shadow length values ​​of all divided areas are counted, and the optimal shadow value is determined by using the quartile method and the two-way approximation strategy. The building height estimated by the shadow measurement result of the present invention is compared with the building height of the three-dimensional intersection, and the absolute error of more than 90% of the building heights is better than 5m. Therefore, the shadow length obtained by the present invention has a higher accuracy, can meet the measurement of different types of complex shadows, improves the accuracy of the shadow method inversion of building height, and lays a research foundation for the inversion of urban height and the expansion of urban height.

Claims

1. A shadow measurement method for building height inversion, characterized in that: The method comprises the following steps: 1) Obtain the shadow vector of the building and perform point measurement on the obtained shadow vector; 2) Determine the building corresponding to each shadow vector based on the point measurement results, and determine the segmentation ratio and segmentation point based on the building's boundaries and sampling interval; 3) Use the segmentation point and the sun's position to segment the shadow vector, obtain multiple regions, and count the shadow length value in each region; 4) Perform statistical processing on the shadow length values ​​of each area to determine the optimal length value of each area, classify the current building occlusion situation according to the difference in the optimal length values ​​of each area, and determine the shadow length value of the building according to the occlusion category and the optimal length value of the area.

2. The shadow measurement method for building height inversion according to claim 1, characterized in that: In the step 4), if the difference in the optimal length values ​​of each area is less than the set threshold, it belongs to the first type of scene, otherwise it is a second type of scene. The first type of scene refers to a building that is unobstructed or fully obstructed, and the second type of scene refers to a building that is partially obstructed. If the current scene is the first type of scene, if the building is unobstructed, the average value of the optimal length values ​​of each area is used as the shadow length of the building. If it is fully obstructed, a nearest neighbor search algorithm is used to search, and the shadow length corresponding to the nearest unobstructed building or the shadow length corresponding to the partially obstructed building is used as the shadow length value of the building. If the current scene is the second type of scene, the maximum value of the optimal length values ​​of each area is used as the shadow length of the building.

3. The shadow measurement method for building height inversion according to claim 1 or 2, characterized in that: The step 1) uses a fishnet method to measure the entire shadow mask.

4. The shadow measurement method for building height inversion according to claim 1 or 2, characterized in that: The calculation formula of the segmentation ratio in step 2) is: Where seg is the segmentation ratio, d is the sampling interval of the point measurement, η is the buffer distance, BX max With BX min is the maximum and minimum longitude of the building envelope rectangle, and SR is the image resolution.

5. The shadow measurement method for building height inversion according to claim 4, characterized in that: The segmentation points are determined based on the number of areas to be divided, the segmentation ratio, and the boundaries of the buildings.

6. The shadow measurement method for building height inversion according to claim 4, characterized in that: Each region is determined by the solar azimuth, the maximum and minimum latitudes of the shadow rectangle, and the division point.

7. The shadow measurement method for building height inversion according to claim 1, characterized in that: The process of determining the optimal length value for each region is as follows: The quartile method was used to eliminate outliers in the shadow length values ​​within each region; The two-way approximation method is used to select a group of highly similar values ​​from the shadow length values ​​in each area, and the average value of this group of shadow length values ​​is taken as the optimal value of the area.

8. The shadow measurement method for building height inversion according to claim 2, characterized in that: The threshold value set in step 4) refers to the shadow length corresponding to the allowable error of the building height.

9. The shadow measurement method for building height inversion according to claim 2, characterized in that: The classification basis in step 4) is: where opt max with opt min is the maximum and minimum value of the four statistical results, δ is the allowable error of the building height, α is the solar altitude angle, 1 represents the first type of scene, and 2 represents the second type of scene.

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