CN113720351B - Combined regional network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic image - Google Patents
Combined regional network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic image Download PDFInfo
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Abstract
The invention belongs to the technical field of remote sensing mapping, and particularly relates to a joint area network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic images. Firstly, generating DSM of a measuring area, and performing track matching on the DSM and satellite-borne laser altimetry data; then, carrying out back projection on the matching track points on the DSM according to the RPC parameters of the image after adjustment to obtain corresponding image point coordinates; screening the satellite-borne laser altimeter by adopting various constraint conditions to obtain reliable laser altimeter data; and finally, carrying out beam method combined area network adjustment considering the plane coordinate error of the laser altimeter by using the screened laser altimeter data and satellite remote sensing stereoscopic image data. The invention uses the advantage of high coincidence precision in the stereoscopic image in the region after the free region adjustment, reduces the influence of the RPC parameter error of the image, obtains the accurate image point coordinates corresponding to the laser height measurement points, ensures the consistency of the object images, and effectively improves the adjustment precision and the positioning precision of the remote sensing stereoscopic image under the uncontrolled condition.
Description
Technical Field
The invention belongs to the technical field of remote sensing mapping, and particularly relates to a joint area network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic images.
Background
The spaceborne laser altimetry is an active remote sensing detection technology, has the advantages of high precision and high speed, acquires the elevation data of a detection target and the three-dimensional space information of the detection target in a large range, and is an indispensable means for earth and planet detection. ICESat-2 (The Ice, cloud and land Elevation Satellite-2) carries a micropulse photon counting laser radar named ATLAS (Advanced Topographic Laser Altimeter System), which successfully emits in month 9 of 2018 and sequentially distributes grading data in month 4 of 2019, so that high-precision laser footpoints on The global land surface can be provided. Because of various characteristics of satellite-borne laser altimetry, the satellite-borne laser altimeter fully shows advantages in scale and precision in the aspects of global elevation measurement, polar ice layer measurement and vegetation and biomass measurement, and therefore brings great attention and research to students at home and abroad.
The satellite three-dimensional remote sensing image is used for positioning the ground target, which is the main means of global mapping at present, but the traditional positioning method needs to actually measure the ground control point data to ensure the precision, and in certain special areas where the ground control point is not easy to obtain, the laser height measurement data can be used as control conditions to effectively improve the image, and related researches are carried out by the prior scholars.
The ATLAS obtains the laser altimeter with highest current precision, which is helpful for further improving the positioning precision of satellite three-dimensional remote sensing images, but has some problems: because the satellite-borne laser altimeter and the remote sensing stereoscopic mapping camera are not carried on the same satellite, the laser point acquired by the satellite-borne laser altimeter does not have corresponding image point coordinates and can be calculated only according to RPC parameters of the remote sensing stereoscopic image. However, the RPC parameter precision of the remote sensing stereoscopic image is lower than the measurement precision of the satellite-borne laser altimeter, and certain errors 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 through direct back projection calculation, and the problem of inconsistent object images exists when the laser points are used as control conditions, and the effect of joint area network adjustment can be obviously affected. Namely: the ATLAS has no footprint camera, and the laser altimeter plane position cannot be accurately determined; because of errors of orientation parameters of the satellite three-dimensional remote sensing image, the positioning accuracy of the image is insufficient, and the object images of the laser altimeter are inconsistent; there is an error in the coordinates of the image points of the laser spot back projection, resulting in inconsistent image points of the same name.
The orientation parameters of the current high-resolution stereo remote sensing image are provided in the form of a Rational Function Model (RFM) parameter, and the regional network adjustment based on RFM is an important step for target positioning. The rational function model is a representation of a wide variety of sensor geometric models. From a mathematical perspective, RFM can be understood as an expression that directly establishes the relationship between the coordinates of an image point and the ground point, as shown in equations (1), (2).
Wherein (Sample, line) is the object point coordinate normalized by the image space coordinate (P, L, H) of the image; p is p i Is a general polynomial; line_SCALE, line_OFF, SAMP_SCALE, SAMPLE_OFF are the image normalization parameters.
Compared with a general adjustment method, the regional network adjustment based on the rational function model directly acts on the image side, new rational function model parameters do not need to be solved, the rational function model is substituted into an affine transformation formula, and normalized coordinates in a mathematical expression of the rational function model are converted into actual image side coordinates, so that error equations can be listed as shown in formulas (3) and (4).
In the method, in the process of the invention,measuring coordinates for the image point; a, a 0 、a S 、a L 、b 0 、b S And b L Is an affine transformation coefficient; epsilon L 、ε S Is a random non-observed error; and p and r are the image space coordinates calculated by the rational function model.
And after linearizing the error equation, carrying out iterative calculation by utilizing a least square principle until the convergence condition is met.
However, the regional network adjustment method based on the rational function model cannot solve the problems of inconsistent object images, mismatching of homonymous points and the like in satellite-borne laser altimetry data auxiliary three-dimensional remote sensing image measurement.
Disclosure of Invention
The invention provides a united area network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic images, which is used for solving the problems of inconsistent object images and mismatching homonymous points of the satellite-borne laser altimetry 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 joint regional network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic images, which comprises the following steps:
1) Carrying out free region adjustment on the remote sensing stereoscopic image of the region to obtain corrected remote sensing stereoscopic image RPC parameters;
2) Performing dense matching on the remote sensing stereoscopic image according to the RPC parameters of the corrected remote sensing stereoscopic image to obtain DSM of the remote sensing stereoscopic image of the area;
3) Performing track matching on each track satellite-borne laser height measurement point in the measuring area and the DSM to obtain a corresponding track of each track satellite-borne laser height measurement point on the DSM;
4) Back projecting the track points by utilizing the corrected remote sensing stereoscopic image RPC parameters according to the space coordinates of the track points corresponding to the satellite laser height measurement points on the DSM, obtaining the image point coordinates of the track points corresponding to the images, and taking the image point coordinates as the image point coordinates of the satellite laser height measurement points corresponding to the remote sensing stereoscopic images;
5) And screening a plurality of laser height measurement points as control points, and carrying out united area network adjustment in parallel with the remote sensing stereoscopic image to obtain adjustment results.
The beneficial effects of the technical scheme are as follows: according to the invention, the remote sensing stereoscopic image and the laser height measurement data are subjected to joint adjustment, the laser height measurement points and the DSM are subjected to three-dimensional matching by utilizing a track matching technology, and the advantage of high coincidence precision in the remote sensing stereoscopic image in the region after adjustment of the free region network is utilized, so that the influence of RPC parameter errors of the image can be remarkably reduced, the accurate image point coordinates corresponding to the laser height measurement points are obtained, and the object image consistency is ensured. Therefore, the problems of inconsistent object images, mismatch of homonymous points and the like are effectively solved, the adjustment precision is effectively improved, and the positioning precision of the remote sensing stereoscopic image under the uncontrolled condition is effectively improved.
Further, the method adopted in the step 3) for obtaining the corresponding track of each track of the satellite-borne laser altimeter on the DSM comprises the following steps:
3.1 Generating a corresponding ground curve according to the difference value of the plane coordinates of the monorail laser altimeter point on the DSM;
3.2 Parallel moving the ground curve in the search area according to a set step length to obtain a matching curve, and calculating the high Cheng Xiangguan property between the matching curve and the ground curve; the searching 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 monorail laser altimeter on the DSM.
Further, in step 3.2), the search area is parallelogram in shape, 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 a high Cheng Xiangguan coefficient, and the elevation correlation coefficient is calculated using the following formula:
wherein N is the number of monorail laser ground points contained in the monorail laser height measurement points; a is that i Is the elevation value of the ith monorail laser ground point; mu (mu) A Sum sigma A The mean value and standard deviation of the elevation values of the monorail laser ground point curve are respectively; c (C) ij Is the elevation value of the ith monorail laser ground point on the jth matching curve; mu (mu) Cj Sum sigma Cj The mean value and standard deviation of the elevation value of the j-th matching curve are respectively.
Further, in order to improve the matching precision to further ensure the object image consistency and the homonymy point matching, after the step 3.3), the method further comprises the following steps of 3.4): and (3) controlling to reduce a set step length and/or a search area, repeating the steps 3.2) to 3.3), and taking the latest obtained matching result as a corresponding track of the monorail laser altimeter on DSM data.
Further, before the step 3.1), the method further comprises the step of performing rough difference elimination on the monorail laser altimeter: the laser spot with an absolute deviation of the median of more than three times is replaced by a linear interpolation algorithm.
Further, the elevation value of the monorail laser ground point on the matching curve is calculated by adopting a double-triple convolution interpolation method.
Further, in order to eliminate the error of the RPC parameter of the image and the plane coordinate error of the laser altimeter to obtain a more accurate correction value of the RPC parameter and the plane coordinate of the laser altimeter, the method for performing the joint area network adjustment in step 5) includes:
5.1 Performing feature point extraction and image matching on the remote sensing stereoscopic image to obtain a plurality of connection points, and obtaining initial space coordinates of the connection points through space front intersection according to original RPC parameters of the remote sensing stereoscopic image;
5.2 Back projecting the satellite-borne laser altimetric points onto a multi-view remote sensing stereoscopic image to obtain a plurality of corresponding image points, and selecting and determining reference image points and homonymous image point coordinates corresponding to the satellite-borne laser altimetric points;
5.3 Determining an error equation of the connection point, an error equation of the laser altimeter and an additional equation considering that the plane coordinates have errors;
5.4 Performing methodological solution on the error equation and the additional equation of the laser altimeter and the error equation of the connecting point listed in the step 5.3) to obtain new RPC parameters, the space coordinates of the connecting point and correction values of the plane coordinates of the laser altimeter; and judging whether the threshold condition is met, if the threshold condition is not met, re-executing the steps 5.2) to 5.4) until the threshold condition is met, and outputting the finally obtained correction values of the RPC parameter, the space coordinates of the connecting point and the plane coordinates of the laser altimeter.
Further, in step 5.2), an image point on the lower view image with the smallest side view angle is selected as the reference image point, and corresponding coordinates of the same-name image points on other images are correspondingly matched and corrected.
Further, the error equation for measuring the height of the laser and the additional equation considering that the plane coordinates have errors are:
wherein i is the serial number of the point, j is the serial number of the remote sensing stereoscopic image; delta j And delta i Respectively obtaining affine transformation coefficients of RPC parameters of the remote sensing stereoscopic image and correction numbers of plane coordinates of the laser altimeter; a is that ij And B ij The coefficient matrixes are respectively affine transformation coefficients of RPC parameters of the remote sensing stereoscopic image and correction values of plane coordinates of the laser altimeter points; l (L) ij Is a constant term; x is X i And Y i For measuring the calculated value of the plane coordinates of the high point by laser, X' i And Y' i The method comprises the steps of measuring an observed value of plane coordinates of a high point by laser; p (P) ij 、p xi 、p yi Is the corresponding weight matrix and weight.
Drawings
FIG. 1 is a flow chart of a joint area network adjustment method of satellite-borne laser altimetry data and a remote sensing stereoscopic image of the invention;
FIG. 2 (a) is a top view of a matching search region of the present invention;
fig. 2 (b) is a perspective view of a matching search region of the present invention;
FIG. 3 is a flow chart of the track matching method of the present invention;
FIG. 4 is a flow chart of an iterative solution method of the invention that accounts for laser altimeter coordinate errors.
Detailed Description
The invention provides a novel method for jointly adjusting satellite-borne laser altimetry data and a remote sensing stereoscopic image. The specific improvement points comprise:
firstly, in order to solve the problem of inconsistent object images of satellite-borne laser altimetry data so as to remarkably improve the precision of adjustment results, the invention provides a track matching method, which specifically comprises the following steps: matching the monorail laser height measurement points with DSMs generated by dense matching after the free area network adjustment of the images to obtain corresponding positions of each laser height measurement point on the DSMs, and then calculating 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 free area network adjustment. 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 stereoscopic image in the region after the free region network adjustment, the image of RPC parameter errors of the image can be obviously lightened, the accurate image point coordinates corresponding to the laser height measurement points are obtained, and the object image consistency is ensured.
Secondly, although the influence of inconsistent object images of the laser altimeter points is relieved by a track matching method, the errors of the RPC parameters of the images and the plane coordinate errors of the laser altimeter points are not completely eliminated, so that the invention adopts an iterative solving method taking the laser altimeter point coordinate errors into consideration in the joint adjustment solving of the area network, and more accurate correction of the PRC parameters of the images and the plane coordinates of the laser altimeter points can be obtained.
The method for adjusting the united area network of the satellite-borne laser altimetry data and the remote sensing stereoscopic image can be realized based on the two-point improvement. The method will be described in detail with reference to the accompanying drawings and examples.
Method embodiment:
the invention discloses an embodiment of a united area network adjustment method for satellite-borne laser altimetry data and remote sensing stereoscopic images, and the whole flow of the united area network adjustment method is shown in figure 1.
And step one, performing free net adjustment on remote sensing stereoscopic image data of the measuring area to obtain corrected remote sensing stereoscopic image RPC parameters.
And step two, performing dense matching on the remote sensing stereoscopic image according to the corrected remote sensing stereoscopic image RPC parameters to obtain the DSM of the area.
And thirdly, performing track matching on each satellite-borne laser altimeter in the measuring area and the DSM to obtain a corresponding track of each satellite-borne laser altimeter on the DSM.
The idea of matching the monorail satellite-borne laser altimeter with the high-precision reference DSM data is as follows: firstly, generating a corresponding ground curve by interpolation of DSM generated after the plane coordinates of a monorail laser spot are adjusted in a free area network, and setting a certain displacement interval in the longitude and latitude directions by taking the ground point curve as the center to form a parallelogram searching area as shown in fig. 2 (a), wherein m and n respectively represent the moving times in the latitude and longitude directions, and Deltab and Deltal respectively represent the moving step length in the latitude and longitude directions; and then, parallel moving a matching curve with the same size as the single-track laser spot in a search area according to a certain step length, calculating an elevation correlation system (shown in fig. 2 (b)) between the matching curve and the single-track laser spot, selecting a curve with the largest correlation coefficient as a matching result, and obtaining a corresponding track of each track of laser height measurement point on the DSM, namely obtaining a corresponding coordinate of each laser spot on the DSM. The specific flow of track matching is shown in fig. 3:
1) And selecting 2-3 km-length monorail laser altimeter, performing coarse difference elimination, and replacing laser points with absolute deviation exceeding three times of median by adopting a linear interpolation algorithm.
2) And interpolating the initial plane coordinates of the height measurement points by the laser to obtain the elevation coordinates of the corresponding DSM.
3) And determining a parallelogram search area with a certain size according to the precision requirement, wherein the size of the search area is generally 5R when the precision requirement is R.
4) And taking the original plane coordinates of the laser altimeter as an initial value, moving a corresponding ground curve in a search area according to a certain step length, and enabling the moved ground curve to be 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 a high Cheng Xiangguan coefficient between the shift match curve and the ground curve using equation (5):
wherein N is the number of monorail laser ground points contained in the monorail laser height measurement points; a is that i Is the elevation value of the ith monorail laser ground point; mu (mu) A Sum sigma A The mean value and standard deviation of the elevation values of the monorail laser ground point curve are respectively; c (C) ij Is the ith sheet on the jth matching curveElevation values of the rail laser ground points; mu (mu) Cj Sum sigma Cj The mean value and standard deviation of the elevation value of the j-th matching curve are respectively.
7) And traversing the search area, and determining a matching curve with the largest correlation coefficient.
8) If the precision is required to be further improved, the R and the moving step length (or only the R is reduced or only the moving step length) can be reduced, and the steps 3) to 7) are repeated until the precision requirement is met.
9) And obtaining the corresponding track of the track laser altimeter on the free area network DSM.
And fourthly, carrying out back projection on the corrected remote sensing stereoscopic image RPC parameters according to the space coordinates of the corresponding track of each track of the satellite-borne laser altimeter on the DSM, and obtaining the image point coordinates on the corresponding image.
And fifthly, screening all satellite-borne laser altimetric data according to constraint conditions such as the category of the altimetric points, the category confidence level, the local terrain gradient and the like, and reserving the ground laser altimetric points with high confidence level and flat local terrain as control points.
And step six, taking the screened laser altimetric points as control conditions, and carrying out beam method combined regional adjustment taking the plane coordinate errors of the laser altimetric points into consideration with the remote sensing stereoscopic images in a combined mode to obtain correction values of RPC parameters, the space coordinates of the connecting points and the plane coordinates of the laser altimetric points of the remote sensing stereoscopic images with higher precision.
The process of combining the area network adjustment by the beam method taking into consideration the plane coordinate error of the laser altimeter is shown in fig. 4:
1) And inputting data, namely remote sensing stereoscopic images, space-borne laser altimeter three-dimensional coordinates and corresponding image point coordinates.
2) By means ofAnd performing image matching by using the SIFT isocenter 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 initial space coordinates of the connection point through front intersection according to the RPC parameters of the image.
4) Considering that the satellite-borne laser altimetric points may be back projected onto the multi-view stereoscopic image, at this time, selecting an image point on a lower view image with the minimum side view angle in the multi-view image as a reference image point, and obtaining the coordinates of the same-name image points on other view images by using a least square matching algorithm.
5) And respectively constructing an error equation for the laser altimeter and the stereoscopic image connection point.
For laser altimetry points, the error equation and the additional equation that considers the existence of errors in plane coordinates are listed as equation (6):
wherein i is the serial number of the point, j is the serial number of the remote sensing stereoscopic image; delta j And delta i The correction of affine transformation coefficient and laser height measurement point plane coordinate of remote sensing stereoscopic image RPC parameter is respectively A ij And B ij Coefficient matrix of affine transformation coefficient of remote sensing stereoscopic image RPC parameter and correction of laser altimeter point plane coordinate, L ij Is a constant term; x is X i And Y i For measuring the calculated value of the plane coordinates of the high point by laser, X' i And Y' i The method comprises the steps of measuring an observed value of plane coordinates of a high point by laser; p (P) ij 、p xi 、P yi Is the corresponding weight matrix and weight.
For the remote sensing stereoscopic image connection point, the error equation is listed according to equation (7):
V kj ＝A kj Δ j +B kj Δ k -L kj P kj (7)
wherein k is the serial number of the point, and j is the serial number of the remote sensing stereoscopic image; delta j And delta k The correction of affine transformation coefficients of RPC parameters of the remote sensing stereoscopic image and plane coordinates of the connecting points are respectively obtained; a is that kj And B kj The coefficient matrixes are affine transformation coefficients of RPC parameters of the remote sensing stereoscopic image and the correction of the plane coordinates of the connecting point respectively; l (L) kj Is a constant term; p (P) kj Is the corresponding weight matrix.
6) And (3) solving the error equation and the additional equation of the formula (6) and the error equation of the formula (7) in a method to obtain the correction of the RPC parameter, the space coordinates of the connecting points and the plane coordinates of the laser altimeter.
7) Judging the correction calculation results of the RPC parameter, the connecting point space coordinate and the laser altimeter point plane coordinate according to the set threshold value, if the threshold value condition is not met, calculating new RPC parameter, connecting point space coordinate and laser altimeter point plane coordinate, and repeating the steps 3-7).
8) If the threshold condition is met, calculating a new RPC parameter, a space coordinate of a connecting point and a plane coordinate of a laser altimeter, and outputting a adjustment result.
In conclusion, the method carries out track matching through DSM generated by single-track satellite-borne laser altimeter and free net adjustment of the stereoscopic remote sensing image, obtains image point coordinates corresponding to the laser altimeter through a back projection algorithm, and then obtains the remote sensing stereoscopic image orientation parameters with higher precision by adopting a beam method combined with regional net adjustment scheme taking plane coordinate errors of the laser altimeter into consideration. The method comprehensively considers the object space and image space coordinate errors of the satellite-borne laser altimeter and the satellite remote sensing stereoscopic image, and mainly solves the problems of inconsistent object images, mismatch of homonymous points and the like by utilizing key technologies such as track matching and joint area network adjustment, so that adjustment precision can be effectively improved, and uncontrolled positioning precision of the remote sensing stereoscopic image is effectively improved.
Claims (8)
1. The method for measuring the united area network adjustment of the data and the remote sensing stereoscopic image by the satellite-borne laser is characterized by comprising the following steps of:
1) Carrying out free region adjustment on the remote sensing stereoscopic image of the region to obtain corrected remote sensing stereoscopic image RPC parameters;
2) Performing dense matching on the remote sensing stereoscopic image according to the RPC parameters of the corrected remote sensing stereoscopic image to obtain DSM of the area;
3) Performing track matching on each track satellite-borne laser height measurement point in the measuring area and the DSM to obtain a corresponding track of each track satellite-borne laser height measurement point on the DSM;
4) Back projecting the track points by utilizing the corrected remote sensing stereoscopic image RPC parameters according to the space coordinates of the track points corresponding to the satellite laser height measurement points on the DSM, obtaining the image point coordinates of the track points corresponding to the images, and taking the image point coordinates as the image point coordinates of the satellite laser height measurement points corresponding to the remote sensing stereoscopic images;
5) Screening a plurality of laser height measurement points as control points, and carrying out united area network adjustment by combining with the remote sensing stereoscopic image to obtain adjustment results;
the method adopted in the step 3) for obtaining the corresponding track of each track of the satellite-borne laser altimeter on the DSM comprises the following steps:
3.1 Interpolation is carried out on the DSM according to the plane coordinates of the monorail laser altimeter to generate a corresponding ground curve;
3.2 Parallel moving the ground curve in the search area according to a set step length to obtain a matching curve, and calculating the high Cheng Xiangguan property between the matching curve and the ground curve; the searching 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 monorail laser altimeter on the DSM;
in step 3.2), the elevation correlation is a high Cheng Xiangguan coefficient and the elevation correlation coefficient is calculated using the following formula:
wherein N is the number of monorail laser ground points contained in the monorail laser height measurement points; a is that i Is the elevation value of the ith monorail laser ground point; mu (mu) A Sum sigma A The mean value and standard deviation of the elevation values of the monorail laser ground point curve are respectively; c (C) ij Is the elevation value of the ith monorail laser ground point on the jth matching curve; mu (mu) Cj Sum sigma Cj The mean value and standard deviation of the elevation value of the j-th matching curve are respectively.
2. The method for united area network adjustment of satellite-borne laser altimetry data and remote sensing stereoscopic images according to claim 1, wherein in step 3.2), the search area is in a parallelogram shape, the size of the search area is 5r x 5r, and r is a set precision requirement.
3. The method for united area network adjustment of satellite borne laser altimetry data and remote sensing stereoscopic images according to claim 1, further comprising, after step 3.3), step 3.4): and (3) controlling to reduce a set step length and/or a search area, repeating the steps 3.2) to 3.3), and taking the latest obtained matching result as a corresponding track of the monorail laser altimeter on DSM data.
4. The method for united area network adjustment of satellite borne laser altimetry data and remote sensing stereoscopic images according to claim 1, wherein before the step 3.1), the method further comprises the step of performing rough adjustment rejection on monorail laser altimetry points: the laser spot with an absolute deviation of the median of more than three times is replaced by a linear interpolation algorithm.
5. The method for combining regional adjustment of satellite-borne laser altimetry data and remote sensing stereoscopic images according to claim 1, wherein the elevation value of the monorail laser ground point on the matching curve is calculated by adopting a bicubic convolution interpolation method.
6. The method for performing united area network adjustment of satellite borne laser altimetry data and remote sensing stereoscopic images according to claim 1, wherein the method for performing united area network adjustment in step 5) comprises the following steps:
5.1 Performing feature point extraction and image matching on the remote sensing stereoscopic image to obtain a plurality of connection points, and obtaining initial space coordinates of the connection points through space front intersection according to original RPC parameters of the remote sensing stereoscopic image;
5.2 Back projecting the satellite-borne laser altimetric points onto a multi-view remote sensing stereoscopic image to obtain a plurality of corresponding image points, and selecting and determining reference image points and homonymous image point coordinates corresponding to the satellite-borne laser altimetric points;
5.3 Determining an error equation of the connection point, an error equation of the laser altimeter and an additional equation considering that the plane coordinates have errors;
5.4 Performing methodological solution on the error equation and the additional equation of the laser altimeter and the error equation of the connecting point listed in the step 5.3) to obtain new RPC parameters, the space coordinates of the connecting point and correction values of the plane coordinates of the laser altimeter; and judging whether the threshold condition is met, if the threshold condition is not met, re-executing the steps 5.2) to 5.4) until the threshold condition is met, and outputting the finally obtained correction values of the RPC parameter, the space coordinates of the connecting point and the plane coordinates of the laser altimeter.
7. The method for joint area network adjustment of satellite borne laser altimetry data and remote sensing stereoscopic images according to claim 6, wherein in step 5.2), an image point on a lower view image with a minimum side view angle is selected as the reference image point, and corresponding homonymous image point coordinates on other images are correspondingly matched and corrected.
8. The method for united area network adjustment of satellite borne laser altimetry data and remote sensing stereoscopic images according to claim 6, wherein the error equation of the laser altimetry points and the additional equation considering that errors exist in plane coordinates are:
wherein i is the serial number of the point, j is the serial number of the remote sensing stereoscopic image; delta j And delta i Respectively obtaining affine transformation coefficients of RPC parameters of the remote sensing stereoscopic image and correction numbers of plane coordinates of the laser altimeter; a is that ij And B ij The coefficient matrixes are respectively affine transformation coefficients of RPC parameters of the remote sensing stereoscopic image and correction values of plane coordinates of the laser altimeter points; l (L) ij Is a constant term; x is X i And Y i For measuring the calculated value of the plane coordinates of the high point by laser, X' i And Y' i The method comprises the steps of measuring an observed value of plane coordinates of a high point by laser; p (P) ij 、p xi 、p yi Is the corresponding weight matrix and weight.
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