CN113720351A - Joint area network adjustment method for satellite-borne laser height measurement data and remote sensing stereo image - Google Patents
Joint area network adjustment method for satellite-borne laser height measurement data and remote sensing stereo image Download PDFInfo
- Publication number
- CN113720351A CN113720351A CN202111006411.8A CN202111006411A CN113720351A CN 113720351 A CN113720351 A CN 113720351A CN 202111006411 A CN202111006411 A CN 202111006411A CN 113720351 A CN113720351 A CN 113720351A
- Authority
- CN
- China
- Prior art keywords
- remote sensing
- image
- laser
- points
- point
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
-
- Y—GENERAL 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Image Processing (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention belongs to the technical field of remote sensing surveying and mapping, and particularly relates to a united area network adjustment method for satellite-borne laser height measurement data and remote sensing stereo images. Firstly, generating DSM of a survey area, and carrying out track matching on the DSM and satellite-borne laser height measurement data; then carrying out back projection on the matched track points on the DSM according to the image RPC parameters after the adjustment to obtain corresponding image point coordinates; screening the satellite-borne laser height measurement points by adopting various constraint conditions to obtain reliable laser height measurement point data; and finally, performing beam method combined area network adjustment considering laser height measurement point plane coordinate errors by using the screened laser height measurement point data and satellite remote sensing stereo image data. The invention utilizes the advantage of high coincidence precision in the stereo image in the measuring region after the adjustment of the free area network, reduces the influence of RPC parameter errors of the image, obtains accurate image point coordinates corresponding to the laser height measurement point, ensures the consistency of the object image, and effectively improves the adjustment precision and the positioning precision of the remote sensing stereo image under the uncontrolled condition.
Description
Technical Field
The invention belongs to the technical field of remote sensing surveying and mapping, and particularly relates to a united area network adjustment method for satellite-borne laser height measurement data and remote sensing stereo images.
Background
The satellite-borne laser height measurement is an active remote sensing detection technology, has the advantages of high precision, high speed and large-range acquisition of detection target elevation data and three-dimensional space information thereof, and is an indispensable means for earth and planet detection. ICESat-2(The Ice, Cloud and land Elevation Satellite-2) carries a micro-pulse photon counting Laser radar with The name of ATLAS (advanced Topographic Laser Altimeter system) to successfully emit in 2018 in 9 months, and continuously emits grading data in 2019 in 4 months, so that high-precision Laser foot points on The global land surface can be provided. Because of the characteristics of high satellite-borne laser measurement, the satellite-borne laser fully shows the advantages of scale and precision in the aspects of global elevation measurement, polar ice layer measurement and vegetation and biomass measurement, and therefore, the satellite-borne laser draws wide attention and research of scholars at home and abroad.
The method for positioning the ground target by utilizing the satellite three-dimensional remote sensing image is a main means of global mapping at present, but the traditional positioning method needs to actually measure ground control point data to ensure the precision of the data, and in some special areas where the ground control point is not easy to obtain, the laser height measurement data can be used as a control condition to effectively improve the image, and related researches are carried out by prior scholars.
The ATLAS obtains the laser height measurement point with the highest precision at present, which is beneficial to further improving the positioning precision of the satellite three-dimensional remote sensing image, but still has some problems: because the satellite-borne laser altimeter and the remote sensing stereo mapping camera are not carried on the same satellite, the laser points acquired by the satellite-borne laser altimeter do not have corresponding image point coordinates, and can only be calculated according to RPC parameters of the remote sensing stereo image. However, the RPC parameter accuracy of the remote sensing stereo image is lower than the measurement accuracy of the satellite-borne laser altimeter, and in addition, certain errors also exist in the plane coordinates of the laser points, so that obvious errors exist in the coordinates of image points corresponding to the laser points obtained by direct back projection calculation, and the problem of inconsistent object images exists when the laser points are used as control conditions, which can significantly affect the effect of joint area network adjustment. Namely: ATLAS has no footprint camera, and the plane position of a laser height measurement point cannot be accurately determined; because the orientation parameters of the satellite three-dimensional remote sensing image have errors, the positioning precision of the image is insufficient, and the object images of the laser height measurement points are inconsistent; the coordinates of the image points of the back projection of the laser points have errors, so that the image points with the same name are inconsistent.
The orientation parameters of the current high-resolution stereo remote sensing images are all provided in the form of Rational Function Model (RFM) parameters, and the RFM-based block adjustment is an important step for positioning the target. The rational function model is a more generalized expression of various sensor geometric models. From a mathematical perspective, the RFM can be understood as an expression that directly establishes a relationship between the coordinates of the image points and the ground points, as shown in equations (1) and (2).
In the formula, (Sample, Line) is the object point coordinate after the image space coordinate (P, L, H) normalization of the image; p is a radical ofiIs a general polynomial; LINE _ SCALE, LINE _ OFF, same _ SCALE, and same _ OFF are image normalization parameters.
Compared with a common adjustment method, the adjustment of the area network based on the rational function model directly acts on the image space, new parameters of the rational function model do not need to be solved, the rational function model is substituted into an affine transformation formula, normalized coordinates in a mathematical expression of the rational function model are converted into actual image space coordinates, and error equations shown in formulas (3) and (4) can be listed.
In the formula (I), the compound is shown in the specification,
measuring coordinates for the image points; a is0、aS、aL、b0、bSAnd bLIs an affine transformation coefficient; epsilonL、εSRandom non-observed errors; and p and r are image space coordinates calculated by the rational function model.
After the error equation is linearized, iterative calculation is carried out by using the least square principle until a convergence condition is met.
However, the area network adjustment method based on the rational function model cannot solve the problems of inconsistent object images, unmatched homonymous points and the like existing in satellite-borne laser height measurement data assisted stereo remote sensing image measurement.
Disclosure of Invention
The invention provides a united area network adjustment method for satellite-borne laser height measurement data and remote sensing stereo images, which is used for solving the problems of inconsistent object images and unmatched homonymy points of the satellite-borne laser height measurement data during adjustment.
In order to solve the technical problems, the technical scheme and the corresponding beneficial effects of the technical scheme are as follows:
the invention provides a combined block adjustment method of satellite-borne laser height measurement data and remote sensing stereo images, which comprises the following steps:
1) carrying out free area network adjustment on the remote sensing stereo image of the measured area to obtain a corrected remote sensing stereo image RPC parameter;
2) according to the RPC parameters of the corrected remote sensing stereo image, carrying out dense matching on the remote sensing stereo image to obtain a DSM (digital surface model) of the remote sensing stereo image of the measured area;
3) track matching is carried out on each orbit satellite-borne laser height measurement point in the measurement area and the DSM, and a corresponding track of each orbit satellite-borne laser height measurement point on the DSM is obtained;
4) according to the space coordinates of the track points corresponding to the satellite-borne laser height finding points on the DSM, carrying out back projection on the track points by using the corrected RPC parameters of the remote-sensing stereo image to obtain the coordinates of image points on the corresponding image of the track points, and using the coordinates as the coordinates of the corresponding image points of the satellite-borne laser height finding points on the remote-sensing stereo image;
5) and screening a plurality of laser height measurement points as control points, and performing united block adjustment in conjunction with the remote sensing stereo image to obtain an adjustment result.
The beneficial effects of the above technical scheme are: the remote sensing stereo image and the laser height measurement data are subjected to combined adjustment, the laser height measurement point is subjected to three-dimensional matching with the DSM by using a track matching technology, and the advantage of high coincidence precision in the remote sensing stereo image in the measurement area after adjustment of the free area network is utilized, so that the influence of RPC parameter errors of the image can be remarkably reduced, accurate image point coordinates corresponding to the laser height measurement point are obtained, and the consistency of an object image is ensured. Therefore, the problems of inconsistent object images, unmatched homonymy points and the like are effectively solved, the adjustment precision is effectively improved, and the positioning precision of the remote sensing stereoscopic image under an uncontrolled condition is effectively improved.
Further, the method for obtaining the corresponding track of each orbit satellite-borne laser altimeter point on the DSM in the step 3) comprises the following steps:
3.1) generating a corresponding ground curve according to the difference value of the plane coordinates of the monorail laser height measurement points on the DSM;
3.2) moving the ground curve in parallel in a search area according to a set step length to obtain a matching curve, and calculating the elevation correlation between the matching curve and the ground curve; the search area is an area defined in a set interval range around the ground curve;
3.3) selecting a matching curve with the strongest elevation correlation as a final matching result to obtain a corresponding track of the single-track laser altimetry point on the DSM.
Further, in step 3.2), the shape of the search area is a parallelogram, and the size of the search area is 5R × 5R, where R is a set precision requirement.
Further, in step 3.2), the elevation correlation is an elevation correlation coefficient, and the elevation correlation coefficient is calculated by using the following formula:
in the formula, N is the number of monorail laser ground points contained in the monorail laser height measurement points; a. theiIs the elevation value of the ith monorail laser ground point; mu.sAAnd σARespectively is the mean value and standard deviation of the elevation value of the monorail laser ground point curve; cijThe elevation value of the ith monorail laser ground point on the jth matching curve is obtained; mu.sCjAnd σCjRespectively, the mean and standard deviation of the elevation values of the jth matching curve.
Further, in order to improve the matching precision to further ensure the matching of the object image consistent type and the homonymy point, after the step 3.3), the method further comprises a step 3.4): and controlling to reduce the set step length and/or the search area, repeating the steps 3.2) to 3.3), and taking the latest obtained matching result as the corresponding track of the monorail laser height measurement point on the DSM data.
Further, before the step 3.1), a step of performing gross error elimination on the monorail laser height measurement points is also included: and replacing the laser points with over three times of median absolute deviation by adopting a linear interpolation algorithm.
And further, calculating by adopting a bicubic convolution interpolation method to obtain an elevation value of the monorail laser ground point on the matching curve.
Further, in order to eliminate the error of the image RPC parameter and the plane coordinate error of the laser height measurement point to obtain a more accurate correction value of the RPC parameter and the plane coordinate of the laser height measurement point, the method for performing joint block adjustment in step 5) includes:
5.1) extracting characteristic points of the remote sensing stereo image, matching the characteristic points with the image to obtain a plurality of connection points, and obtaining initial space coordinates of the connection points through space forward intersection according to original RPC parameters of the remote sensing stereo image;
5.2) back projecting the satellite-borne laser height measurement point to a multi-scene remote sensing stereo image to obtain a plurality of corresponding image points, and selecting and determining a reference image point and a same-name image point coordinate corresponding to the satellite-borne laser height measurement point;
5.3) determining an error equation of the connecting point, an error equation of the laser height measuring point and an additional equation considering the plane coordinate with errors;
5.4) carrying out legal solution on the error equation and the additional equation of the laser height measuring point listed in the step 5.3) and the error equation of the connecting point to obtain a new RPC parameter, a spatial coordinate of the connecting point and a correction value of a plane coordinate of the laser height measuring point; and judging whether the threshold condition is met, if not, re-executing the step 5.2) -the step 5.4) until the threshold condition is met, and outputting the finally obtained correction values of the RPC parameters, the spatial coordinates of the connecting points and the plane coordinates of the laser height measuring points.
Further, in step 5.2), the image point on the downward-looking image with the smallest side-looking angle is selected as the reference image point, and the corresponding coordinates of the image points with the same name on other images are correspondingly matched and corrected.
Further, the error equation of the laser height measurement point and the additional equation considering the plane coordinate with the error are as follows:
in the formula, i is the serial number of a point, and j is the serial number of a remote sensing stereo image; deltajAnd ΔiRespectively an affine transformation coefficient of the remote sensing stereo image RPC parameter and a correction number of a laser height measurement point plane coordinate; a. theijAnd BijRespectively are coefficient matrixes of affine transformation coefficients of remote sensing stereo image RPC parameters and correction numbers of plane coordinates of laser height measuring points; l isijIs a constant term; xiAnd YiIs a calculated value, X ', of a plane coordinate of a laser height measurement point'iAnd Y'iAn observed value of a laser height measurement point plane coordinate is obtained; pij、pxi、pyiAre the corresponding weight matrix and weight value.
Drawings
FIG. 1 is a flow chart of a united area network adjustment method of satellite-borne laser altimetry data and remote sensing stereo images of the invention;
FIG. 2(a) is a top view of the match search area of the present invention;
FIG. 2(b) is a perspective view of the matching search area of the present invention;
FIG. 3 is a flow chart of a trajectory matching method of the present invention;
FIG. 4 is a flowchart of an iterative solution method of the present invention that accounts for the coordinate error of laser altimetry points.
Detailed Description
The invention provides a novel method for jointly adjusting satellite-borne laser height measurement data and remote sensing stereo images. The concrete improvement points comprise:
firstly, in order to solve the problem of inconsistent object images of satellite-borne laser height measurement data and obviously improve the precision of adjustment results, the invention provides a track matching method, which specifically comprises the following steps: matching the single-rail laser height measurement points with DSMs (digital surface models) generated by dense matching after the image free area network is leveled to obtain the corresponding position of each laser height measurement point on the DSM, and then calculating the image point coordinates corresponding to the laser height measurement points according to the point coordinates on the DSMs and the image orientation parameters after the image free area network is leveled. According to the method, through three-dimensional matching of the laser height measurement track and the DSM, and by utilizing the advantage of high coincidence precision in the remote sensing stereo image in the measurement area after adjustment of the free area network, the RPC parameter error of the image can be remarkably reduced, accurate image point coordinates corresponding to the laser height measurement point are obtained, and object image consistency is ensured.
Secondly, although the influence of the problem of inconsistent images of the laser height measurement points is reduced by a track matching method, the error of the RPC parameters of the images and the plane coordinate error of the laser height measurement points are not completely eliminated, so that the invention adopts an iterative solution method considering the laser height measurement point coordinate error in the area network joint adjustment solution, and can obtain more accurate PRC parameters of the images and correction numbers of the plane coordinates of the laser height measurement points.
The invention can realize a united area network adjustment method of satellite-borne laser height measurement data and remote sensing stereo images based on the two improvements. The method is described in detail below with reference to the accompanying drawings and examples.
The method comprises the following steps:
the overall process of the embodiment of the united block adjustment method for satellite-borne laser height measurement data and remote sensing stereo images is shown in fig. 1.
Step one, carrying out free net adjustment on remote sensing stereo image data of a measuring area to obtain corrected remote sensing stereo image RPC parameters.
And secondly, carrying out dense matching on the remote sensing stereo image according to the corrected RPC parameter of the remote sensing stereo image to obtain a DSM of the measuring area.
And step three, performing track matching on each orbit satellite-borne laser height measurement point and the DSM in the measurement area to obtain a corresponding track of each orbit satellite-borne laser height measurement point on the DSM.
The idea of matching the monorail satellite-borne laser altimetry point with the high-precision reference DSM data is as follows: firstly, generating a corresponding ground curve by interpolation of DSM (digital surface model) generated after adjustment of a free area network according to plane coordinates of a monorail laser point, and respectively setting certain displacement intervals in the latitude and longitude directions by taking the ground point curve as a center to form a parallelogram search area as shown in figure 2(a), wherein m and n respectively represent the moving times in the latitude and longitude directions, and delta b and delta l respectively represent the moving steps in the latitude and longitude directions; then, according to a certain step length, a matching curve with the size consistent with that of the single-track laser point is moved in parallel in the search area, an elevation correlation system (shown in fig. 2 (b)) between the matching curve and the single-track laser point is calculated, the curve with the largest correlation coefficient is selected as a matching result, a corresponding track of each track of laser height measurement points on the DSM is obtained, and a corresponding coordinate of each laser point on the DSM is obtained. The specific process of performing the trajectory matching is shown in fig. 3:
1) selecting a single-track laser height measurement point with the length of 2-3km, carrying out gross error elimination, and replacing a laser point with the absolute deviation exceeding three times of median by adopting a linear interpolation algorithm.
2) And interpolating the initial plane coordinates of the laser height measuring points to obtain the elevation coordinates corresponding to the DSM.
3) And determining a parallelogram search area with a certain size according to the precision requirement, wherein the precision requirement is R, and the size of the search area is generally 5R by 5R.
4) And moving the corresponding ground curve in the search area according to a certain step length by taking the original plane coordinate of the laser height measuring point as an initial value, wherein the moved ground curve is called a matching curve.
5) And calculating to obtain the elevation value corresponding to the matching curve point by using a bicubic convolution interpolation method.
6) Calculating an elevation correlation coefficient between the mobile matching curve and the ground curve by using the formula (5):
in the formula, N is the number of monorail laser ground points contained in the monorail laser height measurement points; a. theiIs the elevation value of the ith monorail laser ground point; mu.sAAnd σARespectively is the mean value and standard deviation of the elevation value of the monorail laser ground point curve; cijThe elevation value of the ith monorail laser ground point on the jth matching curve is obtained; mu.sCjAnd σCjRespectively for the elevation values of the jth matching curveMean and standard deviation.
7) And traversing the search area to determine a matching curve with the maximum correlation coefficient.
8) If the precision needs to be further improved, R and the moving step length can be reduced (or only R is reduced or only the moving step length is reduced), and the steps 3) to 7) can be repeated until the precision requirement is met.
9) And obtaining the corresponding track of the track laser height measuring point on the free area network DSM.
And fourthly, according to the space coordinate of the corresponding track of each rail satellite-borne laser height measurement point on the DSM, carrying out back projection on the track by using the corrected RPC parameters of the remote sensing stereo image to obtain the image point coordinate of the corresponding image.
And step five, screening all satellite-borne laser height measurement data according to the constraint conditions of the height measurement points such as categories, category confidence degrees, local terrain slopes and the like, and reserving the ground laser height measurement points with high confidence degrees and flat local terrains as control points.
And step six, taking the screened laser height measurement points as control conditions, and simultaneously performing beam method combined area network adjustment considering laser height measurement point plane coordinate errors with the remote sensing stereo image to obtain remote sensing stereo image RPC parameters, connection point space coordinates and laser height measurement point plane coordinate correction values with higher precision.
The process of beam method combined block adjustment considering laser height measurement point plane coordinate error is shown in fig. 4:
1) and inputting data, namely a remote sensing stereo image, a satellite-borne laser height measurement point three-dimensional coordinate and a corresponding image point coordinate.
2) By using
And carrying out image matching by using an SIFT (scale invariant feature transform) equal-point feature extraction operator and a correlation coefficient gray scale and least square matching algorithm to obtain a large number of connection points.
3) And obtaining the initial space coordinate of the connecting point through forward intersection according to the RPC parameter of the image.
4) Considering that the satellite-borne laser height measurement point may be back projected onto a multi-view stereoscopic image, an image point on a downward-view image with the minimum side view angle is selected as a reference image point in the multi-view image, and coordinates of image points with the same name on other views are obtained by using a least square matching algorithm.
5) And respectively establishing an error equation for the laser height measurement point and the three-dimensional image connecting point.
For the laser height measurement point, an error equation and an additional equation considering the plane coordinate error are listed according to equation (6):
in the formula, i is the serial number of a point, and j is the serial number of a remote sensing stereo image; deltajAnd ΔiRespectively, the affine transformation coefficient of the remote sensing stereo image RPC parameter and the correction number of the laser height measuring point plane coordinate, AijAnd BijCoefficient matrixes L of affine transformation coefficients of remote sensing stereo image RPC parameters and correction numbers of laser height measuring point plane coordinatesijIs a constant term; xiAnd YiIs a calculated value, X ', of a plane coordinate of a laser height measurement point'iAnd Y'iAn observed value of a laser height measurement point plane coordinate is obtained; pij、pxi、PyiAre the corresponding weight matrix and weight value.
For the remote sensing stereo image connection point, an error equation is listed according to the formula (7):
Vkj＝AkjΔj+BkjΔk-Lkj Pkj (7)
in the formula, k is the serial number of a point, and j is the serial number of a remote sensing stereo image; deltajAnd ΔkRespectively an affine transformation coefficient of the remote sensing stereo image RPC parameter and a correction number of a connection point plane coordinate; a. thekjAnd BkjCoefficient matrixes of affine transformation coefficients of remote sensing stereo image RPC parameters and correction numbers of connection point plane coordinates are respectively; l iskjIs a constant term; pkjIs the corresponding weight matrix.
6) And (3) carrying out normal solution on the error equation and the additional equation of the formula (6) and the error equation of the formula (7) to obtain the RPC parameters, the spatial coordinates of the connecting points and the correction number of the plane coordinates of the laser height measuring points.
7) And (4) judging the calculation results of the correction numbers of the RPC parameters, the space coordinates of the connecting points and the plane coordinates of the laser height measuring points according to a set threshold, if the calculation results do not meet the threshold condition, calculating new RPC parameters, space coordinates of the connecting points and plane coordinates of the laser height measuring points, and repeating the steps 3-7).
8) If the threshold condition is met, calculating new RPC parameters, spatial coordinates of the connecting points and plane coordinates of the laser height measuring points, and outputting adjustment results.
In conclusion, the method carries out track matching through the monorail satellite-borne laser height measurement point and DSM generated by the stereo remote sensing image free net adjustment, obtains the image point coordinate corresponding to the laser height measurement point through a back projection algorithm, and then obtains the high-precision remote sensing stereo image orientation parameter by adopting a light beam method taking the plane coordinate error of the laser height measurement point into consideration and combining the block adjustment scheme. The satellite-borne laser height measurement and object space and image space coordinate errors of the satellite remote sensing stereo image are comprehensively considered, the problems of inconsistent object images, unmatched homonymy points and the like are mainly solved by using key technologies such as track matching, united area network adjustment and the like, adjustment precision can be effectively improved, and uncontrolled positioning precision of the remote sensing stereo image is effectively improved.
Claims (10)
1. A joint block adjustment method for satellite-borne laser height measurement data and remote sensing stereo images is characterized by comprising the following steps:
1) carrying out free area network adjustment on the remote sensing stereo image of the measured area to obtain a corrected remote sensing stereo image RPC parameter;
2) according to the corrected RPC parameters of the remote sensing stereo image, carrying out dense matching on the remote sensing stereo image to obtain a DSM of a measuring area;
3) track matching is carried out on each orbit satellite-borne laser height measurement point in the measurement area and the DSM, and a corresponding track of each orbit satellite-borne laser height measurement point on the DSM is obtained;
4) according to the space coordinates of the track points corresponding to the satellite-borne laser height finding points on the DSM, carrying out back projection on the track points by using the corrected RPC parameters of the remote-sensing stereo image to obtain the coordinates of image points on the corresponding image of the track points, and using the coordinates as the coordinates of the corresponding image points of the satellite-borne laser height finding points on the remote-sensing stereo image;
5) and screening a plurality of laser height measurement points as control points, and performing united block adjustment in conjunction with the remote sensing stereo image to obtain an adjustment result.
2. The combined block adjustment method for satellite-borne laser altimetry data and remote sensing stereo images according to claim 1, wherein the method for obtaining the corresponding track of each rail satellite-borne laser altimetry point on the DSM in the step 3) comprises the following steps:
3.1) generating a corresponding ground curve by interpolation on the DSM according to the plane coordinates of the monorail laser height measurement point;
3.2) moving the ground curve in parallel in a search area according to a set step length to obtain a matching curve, and calculating the elevation correlation between the matching curve and the ground curve; the search area is an area defined in a set interval range around the ground curve;
3.3) selecting a matching curve with the strongest elevation correlation as a final matching result to obtain a corresponding track of the single-track laser altimetry point on the DSM.
3. The joint block adjustment method for satellite-borne laser altimetry data and remote sensing stereo images as claimed in claim 2, wherein in step 3.2), the shape of the search block is a parallelogram, the size of the search block is 5R × 5R, and R is a set precision requirement.
4. The combined block adjustment method for satellite-borne laser height measurement data and remote sensing stereo images according to claim 2, wherein in step 3.2), the elevation correlation is an elevation correlation coefficient, and the elevation correlation coefficient is calculated by using the following formula:
in the formula, N is the number of monorail laser ground points contained in the monorail laser height measurement points; a. theiIs the elevation value of the ith monorail laser ground point; mu.sAAnd σARespectively is the mean value and standard deviation of the elevation value of the monorail laser ground point curve; cijThe elevation value of the ith monorail laser ground point on the jth matching curve is obtained; mu.sCjAnd σCjRespectively, the mean and standard deviation of the elevation values of the jth matching curve.
5. The combined block adjustment method for satellite-borne laser altimetry data and remote sensing stereo images as claimed in claim 2, further comprising step 3.4) after step 3.3): and controlling to reduce the set step length and/or the search area, repeating the steps 3.2) to 3.3), and taking the latest obtained matching result as the corresponding track of the monorail laser height measurement point on the DSM data.
6. The combined block adjustment method for the satellite-borne laser altimetry data and the remote sensing stereo image according to claim 2, wherein before the step 3.1), the method further comprises the step of performing gross error elimination on the monorail laser altimetry points: and replacing the laser points with over three times of median absolute deviation by adopting a linear interpolation algorithm.
7. The combined block adjustment method for spaceborne laser height measurement data and remote sensing stereo images as claimed in claim 4, wherein the elevation value of the monorail laser ground point on the matching curve is calculated by adopting a bicubic convolution interpolation method.
8. The method for joint block adjustment of satellite-borne laser altimetry data and remote sensing stereo images according to claim 1, wherein the method for joint block adjustment in step 5) comprises:
5.1) extracting characteristic points of the remote sensing stereo image, matching the characteristic points with the image to obtain a plurality of connection points, and obtaining initial space coordinates of the connection points through space forward intersection according to original RPC parameters of the remote sensing stereo image;
5.2) back projecting the satellite-borne laser height measurement point to a multi-scene remote sensing stereo image to obtain a plurality of corresponding image points, and selecting and determining a reference image point and a same-name image point coordinate corresponding to the satellite-borne laser height measurement point;
5.3) determining an error equation of the connecting point, an error equation of the laser height measuring point and an additional equation considering the plane coordinate with errors;
5.4) carrying out legal solution on the error equation and the additional equation of the laser height measuring point listed in the step 5.3) and the error equation of the connecting point to obtain a new RPC parameter, a spatial coordinate of the connecting point and a correction value of a plane coordinate of the laser height measuring point; and judging whether the threshold condition is met, if not, re-executing the step 5.2) -the step 5.4) until the threshold condition is met, and outputting the finally obtained correction values of the RPC parameters, the spatial coordinates of the connecting points and the plane coordinates of the laser height measuring points.
9. The combined block adjustment method for spaceborne laser height measurement data and remote sensing stereo images as claimed in claim 8, wherein in the step 5.2), the image point on the downward-looking image with the smallest side view angle is selected as the reference image point, and the corresponding coordinates of the image points with the same name on other images are correspondingly matched and corrected.
10. The joint block adjustment method for satellite-borne laser altimetry data and remote sensing stereo images according to claim 8, wherein the error equation of the laser altimetry point and the additional equation considering the error of the plane coordinate are as follows:
in the formula, i is the serial number of a point, and j is the serial number of a remote sensing stereo image; deltajAnd ΔiRespectively an affine transformation coefficient of the remote sensing stereo image RPC parameter and a correction number of a laser height measurement point plane coordinate; a. theijAnd BijAre respectively provided withThe coefficient matrix is a coefficient matrix of affine transformation coefficients of remote sensing stereo image RPC parameters and correction numbers of plane coordinates of laser height measuring points; l isijIs a constant term; xiAnd YiIs a calculated value, X ', of a plane coordinate of a laser height measurement point'iAnd YiThe observation value of the laser height measurement point plane coordinate is' obtained; pij、pxi、pyiAre the corresponding weight matrix and weight value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111006411.8A CN113720351B (en) | 2021-08-30 | 2021-08-30 | Combined regional network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111006411.8A CN113720351B (en) | 2021-08-30 | 2021-08-30 | Combined regional network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113720351A true CN113720351A (en) | 2021-11-30 |
| CN113720351B CN113720351B (en) | 2023-10-03 |
Family
ID=78679262
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111006411.8A Active CN113720351B (en) | 2021-08-30 | 2021-08-30 | Combined regional network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113720351B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114966613A (en) * | 2022-06-09 | 2022-08-30 | 武汉大学 | Wave matching-based method and equipment for positioning foot points of satellite-borne laser altimeter in mountainous area |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102607533A (en) * | 2011-12-28 | 2012-07-25 | 中国人民解放军信息工程大学 | Block adjustment locating method of linear array CCD (Charge Coupled Device) optical and SAR (Specific Absorption Rate) image integrated local area network |
| CN102693542A (en) * | 2012-05-18 | 2012-09-26 | 中国人民解放军信息工程大学 | Image characteristic matching method |
| CN102735216A (en) * | 2011-04-08 | 2012-10-17 | 中国科学院国家天文台 | Adjustment processing method for CCD stereo camera three-line-array image data |
| CN104931022A (en) * | 2015-04-21 | 2015-09-23 | 国家测绘地理信息局卫星测绘应用中心 | Satellite image three-dimensional area network adjustment method based on satellite-borne laser height measurement data |
| CN106871932A (en) * | 2017-04-20 | 2017-06-20 | 国家测绘地理信息局卫星测绘应用中心 | The in-orbit sensing calibration method of satellite borne laser based on Pyramidal search terrain match |
| CN106960174A (en) * | 2017-02-06 | 2017-07-18 | 中国测绘科学研究院 | High score image laser radar vertical control point is extracted and its assisted location method |
| CN107167786A (en) * | 2017-06-05 | 2017-09-15 | 中国测绘科学研究院 | Laser satellite surveys high data assisted extraction vertical control point method |
| CN111174753A (en) * | 2019-12-28 | 2020-05-19 | 同济大学 | Optical image and laser height measurement data adjustment method based on rational function model |
| CN111505608A (en) * | 2020-05-06 | 2020-08-07 | 自然资源部国土卫星遥感应用中心 | Laser pointing on-orbit calibration method based on satellite-borne laser single-chip footprint image |
-
2021
- 2021-08-30 CN CN202111006411.8A patent/CN113720351B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102735216A (en) * | 2011-04-08 | 2012-10-17 | 中国科学院国家天文台 | Adjustment processing method for CCD stereo camera three-line-array image data |
| CN102607533A (en) * | 2011-12-28 | 2012-07-25 | 中国人民解放军信息工程大学 | Block adjustment locating method of linear array CCD (Charge Coupled Device) optical and SAR (Specific Absorption Rate) image integrated local area network |
| CN102693542A (en) * | 2012-05-18 | 2012-09-26 | 中国人民解放军信息工程大学 | Image characteristic matching method |
| CN104931022A (en) * | 2015-04-21 | 2015-09-23 | 国家测绘地理信息局卫星测绘应用中心 | Satellite image three-dimensional area network adjustment method based on satellite-borne laser height measurement data |
| CN106960174A (en) * | 2017-02-06 | 2017-07-18 | 中国测绘科学研究院 | High score image laser radar vertical control point is extracted and its assisted location method |
| CN106871932A (en) * | 2017-04-20 | 2017-06-20 | 国家测绘地理信息局卫星测绘应用中心 | The in-orbit sensing calibration method of satellite borne laser based on Pyramidal search terrain match |
| CN107167786A (en) * | 2017-06-05 | 2017-09-15 | 中国测绘科学研究院 | Laser satellite surveys high data assisted extraction vertical control point method |
| US20200103530A1 (en) * | 2017-06-05 | 2020-04-02 | Chinese Academy Of Surveying And Mapping | Method for extracting elevation control point with assistance of satellite laser altimetry data |
| CN111174753A (en) * | 2019-12-28 | 2020-05-19 | 同济大学 | Optical image and laser height measurement data adjustment method based on rational function model |
| CN111505608A (en) * | 2020-05-06 | 2020-08-07 | 自然资源部国土卫星遥感应用中心 | Laser pointing on-orbit calibration method based on satellite-borne laser single-chip footprint image |
Non-Patent Citations (6)
| Title |
|---|
| XINLEI ZHANG等: "Satellite Remote Sensing Image Stereoscopic Positioning Accuracy Promotion Based on Joint Block Adjustment With ICESat-2 Laser Altimetry", 《IEEE》, pages 113362 - 113376 * |
| 岳春宇等: "以交叉累积剩余熵为准则的星载激光测高仪大光斑波形数据与地形匹配法", 《测绘学报》, vol. 46, no. 3, pages 346 - 352 * |
| 张鑫磊等: "ATLAS数据与资源三号02星影像联合区域网平差", 《红外与激光工程》, vol. 49, no. 2, pages 1 - 8 * |
| 方勇等: "激光雷达测绘卫星发展及应用", 《红外与激光工程》, vol. 49, no. 11, pages 1 - 9 * |
| 曹宁;周平;王霞;唐新明;李国元;: "激光测高数据辅助卫星成像几何模型精化处理", 遥感学报, no. 04 * |
| 白彬;: "激光雷达与遥感数据的山区地理信息处理技术", 激光杂志, no. 04 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114966613A (en) * | 2022-06-09 | 2022-08-30 | 武汉大学 | Wave matching-based method and equipment for positioning foot points of satellite-borne laser altimeter in mountainous area |
| CN114966613B (en) * | 2022-06-09 | 2024-04-30 | 武汉大学 | Wave matching-based satellite-borne laser altimeter mountain area foot point positioning method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113720351B (en) | 2023-10-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107167786B (en) | Method for auxiliary extraction of elevation control points from satellite laser height measurement data | |
| KR101965965B1 (en) | A method of automatic geometric correction of digital elevation model made from satellite images and provided rpc | |
| CN102506824B (en) | Method for generating digital orthophoto map (DOM) by urban low altitude unmanned aerial vehicle | |
| CN101464149B (en) | POS auxiliary aviation image matching method | |
| CN107421501A (en) | A kind of cubic metre of earth and stone survey calculation method of combination oblique photograph, RTK and BIM technology | |
| CN108983239B (en) | Spaceborne interference SAR digital elevation model reconstruction method | |
| CN106960174A (en) | High score image laser radar vertical control point is extracted and its assisted location method | |
| CN114689015B (en) | Method for improving elevation precision of optical satellite stereoscopic image DSM | |
| CN113358091B (en) | Method for producing digital elevation model DEM (digital elevation model) by using three-linear array three-dimensional satellite image | |
| Zhang et al. | Block adjustment for satellite imagery based on the strip constraint | |
| CN112070891A (en) | Image area network adjustment method and system with digital ground model as three-dimensional control | |
| CN113720351B (en) | Combined regional network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic image | |
| CN111611525B (en) | Remote sensing data elevation calculation method based on object space matching elevation deviation iterative correction | |
| Li et al. | Improve the ZY-3 height accuracy using ICESat/GLAS laser altimeter data | |
| Zhou et al. | Geometric accuracy verification of GF-7 satellite stereo imagery without GCPs | |
| Zhou et al. | Combined block adjustment of stereo imagery and laser altimetry points of the ZY3-03 satellite | |
| KR102015817B1 (en) | A method of automatic correction of provided rpc of stereo satellite images | |
| CN115015931A (en) | Real-time differential stereo SAR geometric positioning method and system without external error correction | |
| CN111398956B (en) | Multi-base high-ratio space-borne SAR three-dimensional positioning RD equation optimization weight distribution method | |
| CN115346128A (en) | Optical three-dimensional satellite DEM elevation correction and fusion method | |
| Choi et al. | A comparison of accuracies of the RPC models: Homo-and hetero-type stereo pairs of GeoEye and WorldView images | |
| Pan et al. | A general method of generating satellite epipolar images based on RPC model | |
| Li et al. | Integration of orbital and ground images for enhanced topographic mapping in Mars landed missions | |
| Liu et al. | Evaluation of UAS Flight Configuration Factors and Their Impacts on Photogrammetric Survey Accuracy | |
| CN113280789B (en) | Method for taking laser height measurement points of relief area as image elevation control points |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |