CN115524687A - Satellite-borne single photon data classification precision evaluation method for forest research area - Google Patents
Satellite-borne single photon data classification precision evaluation method for forest research area Download PDFInfo
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Abstract
The invention provides a satellite-borne single photon data classification precision evaluation method for a forest research area, and particularly relates to the field of satellite-borne single photon laser radar remote sensing application. The method comprises the steps of firstly obtaining a track of the satellite-borne single photon laser radar, and preliminarily determining the position of a research area according to the situation of airborne data. Acquiring ATL03 and ATL08 data products corresponding to the satellite-borne single-photon laser radar and corresponding airborne verification data according to the position of the research area; according to the ATLAS data description document, the ground photons and the crown top photons in the ATL08 data product are classified into the single photon data in the ATL03 data product, and the ground photons and the crown top photons with the NASA classification algorithm label in the evaluation area range are obtained; and matching the satellite-borne single photon laser radar data with airborne classification precision evaluation data according to longitude and latitude information of the evaluation area, constructing a ground photon standard evaluation range and a canopy top photon standard evaluation range, and quantitatively evaluating the classification precision of the satellite-borne single photon classification precision.
Description
Technical Field
The invention belongs to the field of satellite-borne single photon laser radar remote sensing application, and particularly relates to a satellite-borne single photon classification precision evaluation method for a forest research area.
Background
The ice, cloud and land altitude satellite second-generation ICESat-2 has been successfully transmitted in 2018 in 9 months, an advanced terrain laser altimeter system ATLAS is carried on the ICESat-2, the technology adopted by the main load of the system is a micro-pulse single photon counting technology, the system has the characteristics of high repetition frequency and high sensitivity, photons reflected from the earth surface can be effectively detected, and the canopy condition of the earth surface is described by receiving returned photon signals. The laser transmitter of the ATLAS has the characteristics of high repetition frequency and high sensitivity, the frequency can reach 10kHz, the ATLAS can obtain approximate continuous air band information due to the characteristics, and technical support in the aspect of hardware is provided for completing scientific targets such as quantitative inversion of global forest structure parameters. According to photon counting characteristics, satellite-borne single photon laser radar data only records time information and position information of photon return and does not record attribute information of photon data. Based on the requirement, photon cloud classification algorithm research is carried out on satellite-borne photon clouds to distinguish whether signal photons in a forest research area are canopy photons or ground photons. Therefore, a classification algorithm research aiming at satellite-borne single photon data of a forest research area needs to be added to distinguish whether signal photons are ground photons, photons inside a canopy or photons on the top of the canopy. However, research has been focused on the consideration of accuracy of data inversion of ground features by satellite-borne single-photon laser radar, and the accuracy of a classification algorithm for forest research is not evaluated, so that the accuracy of the classification algorithm cannot be comprehensively measured.
The accurate classification of the satellite-borne single photon laser radar data is the basis of the application of the data in a forest research area, and a plurality of experts and scholars develop single photon classification algorithm research by using a mathematical principle, but do not research an evaluation method aiming at classification processing accuracy, so that the evaluation method aiming at objective data development of the forest research area is urgently needed to be provided. Therefore, the method has very important significance in developing classification precision evaluation aiming at the satellite-borne single photon classification algorithm in the forest research area.
The single photon classification precision evaluation method provided by the invention can objectively and systematically express the possible interval and forest structure conditions of the space-borne single photon ground photons and the canopy top photons in the research area, and accurately evaluate the precision condition of the space-borne single photon data classification algorithm.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a satellite-borne single photon data classification precision evaluation method for a forest research area, so as to improve the accuracy of satellite-borne single photon laser radar in forestry application. In order to measure the precision of the satellite-borne single photon laser radar classification algorithm, the invention takes the classification label of an ATL08 data product published by NASA as a research object to develop classification algorithm evaluation research.
A satellite-borne single photon data classification precision evaluation method for a forest research area is characterized by comprising the following steps:
step 1: according to satellite track running information of the satellite-borne single-photon laser radar, selecting a superposed area of a satellite-borne single-photon laser radar track and an airborne point cloud data track as a research area, taking airborne digital ground model Data (DTM) as a classification standard interval of ground photons, and taking combined DTM data and canopy height model data (CHM) as a classification standard interval of canopy top photons; according to the position of a research area, acquiring a global photon positioning data product ATL03 and a land and vegetation height data product ATL08 corresponding to the satellite-borne single photon laser radar;
the method comprises the following specific steps:
step 1.1: preliminarily determining an approximate running track of the satellite-borne single photon data according to longitude and latitude information of a satellite-borne single photon laser radar track;
step 1.2: selecting an area with airborne precision evaluation data according to the satellite-borne single-photon laser radar track, and finishing the initial selection of a research area by taking the area as the research area;
step 1.3: according to latitude and longitude data of a satellite-borne single photon laser radar track, combining track data of airborne research data to finish accurate determination of coverage data of a research area;
and 2, step: extracting parameter information of single photon data in an ATL03 data product in an evaluation area, wherein the specific parameter information comprises the following steps: longitude, latitude, elevation information, geoid correction information. Extracting ground photonic label data and canopy top photonic label data of a NASA classification algorithm in an ATL08 data product;
the method comprises the following specific steps:
step 2.1: downloading and acquiring an ATL03 data product and an ATL08 data product of the spaceborne single-photon laser radar in the evaluation area through a NASA (network-assisted Access) website;
step 2.2: extracting photon cloud data information in an ATL03 data product according to the latitude and longitude information of the precisely determined evaluation area data, wherein the specific parameters comprise: latitude information lat _ ph of the single photon event, longitude information lon _ ph of the single photon event, elevation information h _ ph of the single photon event and ground level correction information geoid of the single photon event;
step 2.3: extracting photon cloud data information in an ATL08 data product according to the accurately determined longitude and latitude information of the evaluation area data, wherein the specific parameters comprise: the photon cloud classification algorithm label information of the NASA official algorithm is classified _ pc _ flag, wherein classified _ pc _ flag =1 is a ground photon label, classified _ pc _ flag =2 is a top layer photon label, and classified _ pc _ flag =3 is a top layer photon label, an identifier information classified _ pc _ index matching the ATL08 classification label and the ATL03 photon event, and an identifier field number ph _ segment _ id matching the ATL08 classification label and the ATL03 photon event;
and 3, step 3: and correcting the ground level correction information of the ATL03 data to ensure that the satellite-borne single-photon laser radar data and the airborne classification precision evaluation data are both in a WGS84 coordinate system. According to the NASA ATLAS data description document, assigning the ground photons and the top photons of the canopy in the ATL08 data product to the single photon data in the ATL03 data product to obtain the ground photons and the top photons of the canopy with NASA classification algorithm labels in the evaluation area range;
the method comprises the following specific steps:
step 3.1, matching the elevation information of the single photon event extracted from the ATL03 with corresponding ground level correction information one by one to obtain single photon data with the ground level correction information;
3.2, associating the ATL03 and the ATL08 one by using classified _ pc _ index and ph _ segment _ id, giving photon cloud ground classification labels and canopy top classification labels in the ATL08 to photon data of the ATL03, and obtaining ground photon data and canopy top photon data with NASA classification algorithm labels;
3.3, storing the photon data with the NASA official classification algorithm label into an np file, so as to facilitate subsequent verification;
and 4, step 4: and according to the longitude and latitude information condition of the evaluation area, CHM data and DTM data corresponding to the airborne data products are acquired as precision evaluation data of the classification result. The method specifically comprises the following steps: acquiring longitude and latitude information of the precisely determined evaluation data of the evaluation area, acquiring CHM data and DTM data of airborne data corresponding to the longitude and latitude, and storing the CHM data and the DTM data with the evaluation data of the evaluation area into an np file so as to facilitate the subsequent development of classification precision evaluation work;
and 5: matching the satellite-borne single photon laser radar data with airborne classification precision evaluation data according to longitude and latitude information of an evaluation area, constructing a ground photon standard evaluation range and a canopy top photon standard evaluation range, and quantitatively evaluating the classification precision of the satellite-borne single photon classification precision;
the method comprises the following specific steps:
step 5.1: extracting CHM data and DTM data of airborne data corresponding to longitude and latitude in an evaluation area in an np file, constructing an evaluation area ground photon and canopy top photon classification precision evaluation area according to the CHM data and the DTM data, constructing a buffer area with the upper width and the lower width of 0.5m by using the DTM data as an evaluation standard area of ground photon data, and constructing a buffer area with the upper width of 1m by combining DSM data generated by the DTM and the CHM data as an evaluation standard area of canopy top photon data;
step 5.2: selecting single photon data with a ground photon label, judging that the classification algorithm is effective if the single photon data with the ground label falls in a ground photon data evaluation standard interval, and otherwise, judging that the classification algorithm is invalid. Selecting single photon data with the crown top photon label, judging that the classification algorithm is effective if the single photon data with the crown top label falls in the crown top photon data evaluation standard interval, and otherwise, judging that the classification algorithm is invalid. And (3) recording effective photon events processed by the statistical classification algorithm in the ground photon classification and the canopy top photon classification as evaluation information, and finishing the quantitative evaluation of the research zone classification algorithm according to the evaluation information.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in: the invention provides a satellite-borne single photon data classification precision evaluation method for a forest research area, which realizes scientific evaluation of classification precision of a satellite-borne single photon counting radar, carries out classification precision verification work of satellite-borne single photon laser radar data by using high-precision airborne data, and quantitatively evaluates the accuracy of a NASA classification algorithm. The method can quantitatively analyze the classification precision of the satellite-borne single photon classification algorithm and has strong practical application value.
Drawings
FIG. 1 is a flow chart of a satellite-borne single photon laser radar classification precision evaluation method for a forest research area according to the invention;
FIG. 2 is a schematic diagram of a satellite-borne single photon laser radar before data classification in the embodiment of the invention;
fig. 3 is a schematic diagram of an evaluation criterion interval of ground photons of a research area generated in an embodiment of the present invention.
Fig. 4 is a schematic diagram of an evaluation criterion interval of canopy top photons generated in the study region in the embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention, but are not intended to limit the scope of the invention.
As shown in fig. 1, the method of this embodiment includes the following steps:
step 1: according to the satellite-borne single photon laser radar track information, selecting a superposed area of a satellite-borne single photon laser radar track and an airborne data flight track as a research area, and taking airborne DTM data and CHM data of the research area as classification precision evaluation data. The method comprises the following specific steps:
step 1.1: observing the track condition of the satellite-borne single-photon laser radar, and preliminarily determining the approximate track of satellite-borne data;
step 1.2: selecting an area with airborne research data according to the satellite-borne single photon laser radar track, and finishing the initial selection of the research area by taking the area as the research area; in the embodiment of the invention, the evaluation forest region is located in the state of Colorado in the United states, and the type of the intraplant vegetation in the evaluation forest region comprises the following steps: forest (95.3%), grass (4.6%). The landform of a research area is mainly hills and mountains, the hilly land and sloping land of a forest are more, and the elevation range is 2117.05m-2537.47m. Forest vegetation coverage ranged from 5% to 25%, with vegetation coverage for most footprint coverage areas of 25% (19.4%), 19% (18.7%), 16% (10.3%). The height range of the canopy is 0.1m-24.4m, and the maximum canopy height of the main forest stand is 14.97m. The main vegetation of the appraisal area comprises: yellow pine, larch, spruce, etc., with regional representatives.
And step 1.3, according to longitude and latitude data of the satellite-borne single-photon laser radar track, combining flight track data of airborne data to finish accurate determination of research data of an evaluation area.
In the embodiment of the invention, the airborne research data is G-LiHT data, the system is a portable airborne imaging system, and a functional diagram of a land ecosystem, CHM data and DTM data of the G-LiHT airborne data can be drawn by using LiDAR, imaging spectrum and thermal energy observation modes at the same time.
And 2, step: and acquiring an ATL03 data product and an ATL08 data product corresponding to the satellite-borne single-photon laser radar according to the position of the research area, and extracting longitude and latitude, elevation and ground level correction information in the ATL03 product and ground label data and canopy top label data of an NASA classification algorithm in the ATL08 product. The method comprises the following specific steps:
step 2.1: acquiring an ATL03 data product and an ATL08 data product of the satellite-borne single photon laser radar through a NASA (network administration and maintenance) website;
step 2.2: extracting photon cloud data information in an ATL03 data product according to the accurately determined latitude and longitude information of the research area data, wherein the specific parameters comprise: latitude information lat _ ph of the photon event, longitude information lon _ ph of the photon event, elevation information h _ ph of the photon event and ground level correction information geoid of the photon event;
step 2.3: extracting photon cloud data information in an ATL08 data product according to accurately determined longitude and latitude information of the position of the research area, wherein the specific parameters comprise: classified label information classified _ pc _ flag of the NASA classification algorithm, wherein classified _ pc _ flag =1 is a ground photon label, classified _ pc _ flag =2 is a crown layer internal photon label, classified _ pc _ flag =3 is a crown layer top light word label, identifier information classified _ pc _ index on ATL08 signal photons and ATL03 is matched, identifier field number ph _ segment _ id of ATL08 signal photons and ATL03 is matched, and data schematic diagrams of satellite borne photon cloud data ATL08 and ATL03 are shown;
in the embodiment of the invention, in order to facilitate data observation, ATLAS data is converted into a photon cloud schematic diagram along the track according to longitude and latitude information and elevation information of a photon event, and FIG. 2 is a schematic diagram of a section of satellite-borne laser radar photon cloud in a research area;
and step 3: and (3) correcting the WGS84 ground level correction information of the ATL03 data to ensure that the satellite-borne single photon laser radar and the airborne classification precision verification data are in a WGS84 coordinate system. According to the NASA official classification algorithm description document, the ground photon label and the canopy top photon label in the ATL08 data product are endowed with each photon cloud data in the ATL03 data product to obtain the classification result of the NASA official classification algorithm, and the method comprises the following specific steps:
step 3.1: matching the elevation information h _ ph of the photon event contained in the ATL03 data product with corresponding geolevel correction information geoid to obtain photon cloud data with WGS84 geolevel correction information;
step 3.2: the method comprises the steps of associating ATL03 with ATL08 by using classified _ pc _ indx and ph _ segment _ id, assigning ground photons and canopy top photon classification parameters in the ATL08 to photon cloud data of the ATL03, and obtaining photon data with a NASA classification algorithm label;
and 3.3, storing the photon data with the NASA classification algorithm label into an np file, so as to facilitate subsequent verification.
And 4, step 4: and according to the position of the research area, CHM data and DTM data corresponding to the airborne data product are acquired as classification precision evaluation data. The method specifically comprises the following steps: and acquiring latitude and longitude information of the accurately determined research area data, acquiring data of the CHM and the DTM corresponding to airborne data in the latitude and longitude, and storing the CHM and DTM data with the research area position into an np file for facilitating subsequent verification.
And 5: according to the longitude and latitude information, satellite-borne photon cloud LiDAR data and airborne verification data (CHM data and DTM data) are matched, and classification precision evaluation is conducted on the satellite-borne photon cloud LiDAR data. The method comprises the following specific steps:
step 5.1: CHM data and DTM data of airborne data corresponding to longitude and latitude in a research area are extracted, a ground photon and canopy top photon classification precision evaluation interval is constructed according to the CHM data and the DTM data, a buffer area with the upper width and the lower width of 0.5m is constructed according to the DTM data and serves as an evaluation standard interval of ground photon data, and a buffer area with the upper width of 1m is constructed according to DSM data generated by combining the DTM data and the CHM data and serves as an evaluation standard interval of canopy top photon data;
step 5.2: and selecting photon cloud data with ground photon labels, judging that the classification algorithm is effective if the photon cloud data with the ground labels fall in a ground photon evaluation interval, and otherwise, judging that the classification algorithm is invalid. And selecting photon cloud data with the crown top photon label, judging that the classification algorithm is effective if the photon cloud data with the crown top label falls in the crown top photon evaluation interval, and otherwise, judging that the classification algorithm is invalid. And counting and recording the effective photon events of the classification algorithm, taking the effective photon events as classification evaluation information, and finishing the evaluation of the research region classification algorithm according to the classification evaluation information.
In the embodiment of the invention, the DTM data and the CHM data of the G-LiHT data are combined to establish the classification precision evaluation standard of the forest research region, and the DTM data is used for establishing a buffer region with the upper and lower width of 0.5m as the evaluation standard interval of the ground light data, which is shown in figure 3. DSM data generated by combining the DTM and the CHM constructs a buffer area with the width of 1m as an evaluation standard interval of the canopy top photon data, and the evaluation standard interval is shown in FIG. 4.
In the embodiment of the invention, 4 statistical indexes including recall rate R, precision P, photon cloud classification precision accuracy and comprehensive evaluation index F value are adopted to quantitatively evaluate the precision of the classification algorithm. R is the proportion of the number of correctly extracted effective photons to the total number of the original photon signals, and is shown in a formula 1.P is the ratio of the number of the effective photon signals extracted correctly to the total number of the effective photon signals extracted, see formula 2, accuracycacy is the photon cloud classification accuracy, see formula 3, F is the harmonic mean value of the recall rate and the correct rate, see formula 4.
In the formula, TP represents the number of correctly divided positive examples, TN represents the number of correctly divided negative examples, FP represents the number of incorrectly divided positive examples, and FN represents the number of incorrectly divided negative examples.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.
Claims (7)
1. The satellite-borne single photon data classification precision evaluation method for the forest research area is characterized by comprising the following steps of:
step 1: acquiring a track of the satellite-borne single photon laser radar, and preliminarily determining the position of an evaluation area according to the condition of airborne data; according to the accurate longitude and latitude information of the satellite-borne single-photon laser radar track, selecting a superposition area with airborne point cloud data superposed with the track as an evaluation area, and taking high-precision airborne point cloud data of a forest research area as classified evaluation data; downloading a corresponding satellite-borne single photon data product covering the evaluation area; the specific data product comprises: ATL03 global positioning photon data products and ATL08 land and vegetation height data products;
and 2, step: according to the longitude and latitude position information of the evaluation area, extracting longitude and latitude of single photon data in an ATL03 data product, elevation information of the photon data, ground level correction information and classification label data of an NASA algorithm in an ATL08 data product corresponding to the longitude and latitude of the single photon data in the satellite-borne photon counting laser radar, and taking a classification algorithm in the ATL08 data product as a classification evaluation target method of the satellite-borne single photon data;
and 3, step 3: finishing correction of the ground level correction information in the ATL03 data product by using the ground correction information in the ATL03 data product, so that the satellite-borne single photon data and the airborne point cloud classified evaluation data are under a WGS84 coordinate system; correlating photon classification labels in the ATL08 data product with single photon data in the ATL03 data product to obtain classification results of ground photons, canopy photons and canopy top photons of the NASA algorithm in a forest research area;
and 4, step 4: acquiring canopy height model data CHM and digital earth surface model data DTM corresponding to airborne classified evaluation data as verification data of classification results according to the positions of the evaluation areas;
and 5: matching satellite-borne photon counting laser radar data with CHM and DTM data of airborne classification evaluation data according to longitude and latitude information, constructing a ground line classification evaluation standard by utilizing the DTM data, and combining the CHM and DTM data to form a canopy top line classification evaluation standard; and carrying out classification precision quantitative evaluation on the spaceborne photon counting laser radar data by using the quantitative evaluation parameters.
2. The method for evaluating the classification precision of the satellite-borne single photon laser radar data in the forest evaluation area according to the claim 1, which is characterized in that: the method for selecting the overlapping area of the trajectory of the satellite-borne photon counting laser radar and the airborne point cloud data trajectory of the forest research area as the evaluation area in the step 1 comprises the following steps:
step 1.1: according to the track of the satellite-borne photon counting laser radar, a region with an airborne point cloud data track is selected in a forest research area, and the region is used as an evaluation area to complete the initial selection of the evaluation area;
step 1.2: selecting the intersection position of the two data according to latitude and longitude data of the satellite-borne photon counting laser radar track and the mark language KML data of the airborne classification evaluation data to finish the accurate determination of an evaluation area;
step 1.3: downloading a corresponding satellite-borne single photon data product covering the evaluation area; the specific data products include: ATL03 global positioning photon data products and ATL08 land and vegetation height data products; downloading corresponding airborne data products covering the evaluation area; the specific data products include: DTM digital ground model, CHM canopy height model.
3. The precision evaluation method for the spaceborne single photon data classification algorithm of the forest research area according to the claim 1, which is characterized in that: the process of the step 2 is as follows:
step 2.1: extracting single photon data information in an ATL03 data product according to longitude and latitude information of the evaluation area position, wherein the specific parameters comprise: latitude information lat _ ph of the single photon data, longitude information lon _ ph of the single photon data, elevation information h _ ph of the single photon data and ground level correction information geoid of the single photon data;
step 2.2: extracting photon cloud data information in an ATL08 data product according to longitude and latitude information of the position of the evaluation area, wherein the specific parameters comprise: photon cloud classification label information of the NASA algorithm, matched signal photons in each ATL08 data product and identifier information classified _ pc _ indx on the ATL03 data product, and matched identifier field number ph _ segment _ id of each ATL08 data product, wherein the signal photons are traced to the ATL03 data product.
4. The method for evaluating the classification accuracy of the spaceborne photon counting lidar in the forest research area as claimed in claim 3, wherein the method comprises the following steps: the process of the step 3 is as follows:
step 3.1: matching elevation information h _ ph of photon events related to the ATL03 data product with ground level correction information geoid corresponding to the photon events to obtain photon cloud data with the ground level correction information, so that the satellite-borne photon counting laser radar and the airborne classification evaluation data are in a WGS84 coordinate system;
step 3.2: associating the ATL03 data product with the ATL08 data product by using classified _ pc _ index and ph _ segment _ id, assigning photon cloud classification parameters in the ATL08 data product to photon cloud data with ground level correction information in the ATL03 data product, and obtaining photon cloud data with a NASA classification algorithm label;
step 3.3: photon cloud data with NASA official classification algorithm labels are stored in an np file, so that subsequent verification is facilitated.
5. The satellite-borne single photon classification precision evaluation method for the forest research area according to claim 1, characterized in that: the method of the step 4 comprises the following steps:
and acquiring longitude and latitude information of the position of the evaluation area, acquiring data corresponding to the CHM and the DTM in the corresponding longitude and latitude, and storing the CHM and DTM data with the position of the evaluation area into an np file.
6. The satellite-borne photon counting lidar classification accuracy evaluation method for forest research areas as claimed in claim 1, wherein the method comprises the following steps: the process of the step 5 is as follows:
step 5.1: CHM data and DTM data of airborne data corresponding to longitude and latitude in an evaluation area are extracted, an evaluation area classification boundary line is constructed according to the CHM data and the DTM data, the DTM data is used as the lower boundary of a ground photon evaluation line, in consideration of the error condition of the single photon data, a buffer area with the upper width and the lower width of 0.5m is constructed according to the DTM data and is used as an evaluation standard interval of ground photon data, and a buffer area with the upper width of 1m is constructed according to DSM data generated by combining the DTM data and the CHM data and is used as an evaluation standard interval of canopy top photon data;
step 5.2: for the ground photons, selecting single photon data with NASA official classification algorithm labels, if the single photon data with the NASA official classification algorithm ground photon labels fall in an evaluation interval of the ground photons, judging that the classification algorithm is effective, otherwise, judging that the classification algorithm is invalid; for the photons at the top of the canopy, selecting single photon data with NASA official classification algorithm labels, if the single photon data with the NASA official classification algorithm crown photon labels fall in the evaluation interval of the photons at the top of the canopy, judging that the classification algorithm is effective, otherwise, judging that the classification algorithm is invalid;
step 5.3: and respectively counting photon events effective for the ground photons and the canopy top photons by the classification algorithm to serve as classification precision evaluation information, finishing a forest research region classification algorithm according to the evaluation information, and quantitatively evaluating the ground photons and the canopy top photons.
7. The precision evaluation method for the spaceborne single photon data classification algorithm of the forest research area as claimed in claim 6, wherein the precision evaluation method comprises the following steps: the evaluation of the precision of the satellite-borne single photon data classification algorithm for the forest research area comprises 4 statistical indexes which are respectively as follows: recall rate R, precision P, photon cloud classification precision accuracy and comprehensive evaluation index F value.
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| CN116663333B (en) * | 2023-07-28 | 2023-10-24 | 北京四象爱数科技有限公司 | Satellite-borne SAR imaging optimization method, device and medium based on simulation model |
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