AU2021439678A1 - Method for extracting three-dimensional surface deformation by combining unmanned aerial vehicle doms and satellite-borne sar images - Google Patents
Method for extracting three-dimensional surface deformation by combining unmanned aerial vehicle doms and satellite-borne sar images Download PDFInfo
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- G01B7/24—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring the deformation in a solid, e.g. by resistance strain gauge using change in magnetic properties
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Abstract
A method for extracting a three-dimensional surface deformation by combining unmanned aerial vehicle digital orthophoto maps (DOMs) and satellite-borne SAR images, which method is applicable to the field of surface deformation and geological disaster monitoring. The method comprises: acquiring an LOS-direction surface deformation of a target region by using SAR or InSAR technology; acquiring surface image data of the target region by using an unmanned aerial vehicle, and generating DOMs having the same resolution; by using a fine registration method, calculating coordinate offsets of homonymous pixel points on DOMs of two periods in the east-west direction and in the south-north direction, and in view of the resolution of the DOMs, obtaining horizontal movements of a surface point corresponding to each pixel point in the east-west and south-north directions; and substituting, into an SAR three-dimensional deformation model, the horizontal movements in the east-west and south-north directions that are acquired by using the DOMs, and the LOS-direction deformation, and calculating a vertical surface subsidence value W, so as to obtain a three-dimensional surface deformation. In the method, unmanned aerial vehicle DOMs are combined with satellite-borne SAR images to acquire a three-dimensional surface deformation, such that a wide range is covered, there is no need to come in contact with the surface, and a good effect is achieved, thereby providing a new method for monitoring a three-dimensional surface deformation.
Description
Description
Method for Extracting Three-Dimensional Surface Deformation by Combining Unmanned Aerial Vehicle DOMs and Satellite-Borne SAR Images
Technical Field
The present invention relates to a method for acquiring three-dimensional deformation of earth's surface by combining unmanned aerial vehicle digital orthophoto maps (DOMs) and satellite-borne SAR images, and belongs to the field of earth's surface deformation and disaster monitoring.
Background Art
China has a vast territory and diverse natural environments, and the earth's surface subsidence and geological disasters caused by the development of underground resources are in a large quantity and extensive every year. For example, the construction of earth's surface and underground projects and the development of underground water resources in urban areas lead to the earth's surface subsidence, which in turn affects the safe operation of buildings and constructions on the earth's surface; the exploitation of coal, oil, metal and other mineral resources causes serious damage to the environment in the mining areas and results in disasters such as earth's surface collapse, fractures and landslides. In western China, especially in Yunnan, Guizhou, Sichuan, Qinghai and other provinces, the terrains fluctuate greatly and various geological disasters occur frequently. These earth's surface deformations and geological disasters are essentially a comprehensive reflection of the movement trajectories of the earth's surface points, which can be projected in a three-dimensional space and decomposed into vertical movement and horizontal movement. The vertical movement is subsidence or upheaval, and the horizontal movement can be set vertically or parallel to a certain cross section, such as horizontal movement in a north-south direction and horizontal movement in an east-west direction.
Traditional earth's surface deformation monitoring methods, such as GNSS, leveling survey and total station instruments, etc., have some shortcomings, such as heavy workload, inadequate density of the points, damage-prone points, high cost, and inconvenience in continuous measurement and automatic measurement, etc. The Synthetic Aperture Radar (SAR) measurement technology has effectively made up for the shortcomings of the traditional monitoring technology since it was developed in 1990s. At present, SAR has been widely applied in the field of regional disaster detection and monitoring. However, since the SAR technology can only acquire the earth's surface deformation along the radar line of sight, it is difficult to acquire three-dimensional earth's surface deformation from mono-orbital SAR images without external data or a mathematical model. Consequently, the applicability of the SAR technology in the field of building/construction deformation and geological disaster monitoring is severely limited. As the unmanned aerial vehicle technology become matured and popular, unmanned aerial vehicle photogrammetry has been widely used in all walks of life. The unmanned aerial vehicle technology has advantages including high mobility and flexibility, non-contact with the object being photographed, high resolution, high speed, and high precision. However, it is difficult to acquire vertical subsidence of the earth's surface with the unmanned aerial vehicle technology, and the unmanned aerial vehicle technology has not been widely used to directly acquire horizontal movement of the earth's surface.
In view of the shortcomings, the present invention combines the advantages of unmanned aerial vehicle images and SAR images, and proposes a method for extracting three-dimensional deformation of the earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images, which can quickly and accurately acquire the three-dimensional deformation of the earth's surface and buildings/constructions, and has a broad application prospect.
Contents of the Invention
The technical problem to be solved by the present invention is to propose a method for extracting three-dimensional deformation of the earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images, which solves the problem that it is difficult to acquire three-dimensional deformation of the earth's surface with mono-orbital SAR images and difficult to obtain vertical surface subsidence with unmanned aerial vehicle images, and has advantages including high accuracy, low cost, non-contact with the object being measured, large coverage, and easy operation, etc.
To attain the above-mentioned technical object, the method for extracting three-dimensional deformation of the earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images provided by the present invention, characterized in that, comprising the following steps:
Si: resolving a line-of-sight deformation field of a target region by using satellite SAR/InSAR technology, and denoting as LOS;
S2: using an unmanned aerial vehicle to acquire the earth's surface image data of the target region in two different periods along the same air route, processing the unmanned aerial vehicle images and generating digital orthophoto maps (DOMs), and the DOMs of two periods have the same spatial resolution;
S3: using the DOM Iof the first period as a main image, using the DOM2 of the second period as a secondary image, calculating an pixel offset of the image points with the same names in the DOMs of two periods in a south-north direction and an east-west direction by using a fine registration method, and removing an overall offset of the images obtained with the unmanned aerial vehicle in two periods from the pixel offset to obtain a pixel offset caused by earth's surface movement; the overall offset of the images is an error offset generated in the two periods of aerial photography;
S4: calculating actual horizontal movement of the earth's surface corresponding to each image point with the same name by using the pixel offset in the south-north direction and the east-west direction obtained in the step S3 and the surface resolution of the images, wherein the actual horizontal movement corresponding to each image point with the same name includes: horizontal movement in the south-north direction UN and horizontal movement in the east-west direction UE
S5: resolving a vertical surface subsidence value W of the target region, according to a SAR three-dimensional deformation decomposition model, with the light-of-sight deformation field LOS, the horizontal movement in the south-north direction UN and the horizontal movement in the east-west direction UE that are acquired by means of the satellite, to obtain actual three-dimensional deformation of the earth's surface.
2. The method for extracting three-dimensional deformation of the earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images according to claim 1, characterized in that, the SAR/InSAR technology in the step S Iemploys classic offset tracking algorithm, sub-band interference method, DInSAR, and time-series InSAR, the above methods can be used to acquire the sight-of-line deformation of the earth's surface which denoted as LOS.
3. The method for extracting three-dimensional deformation of the earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images according to claim 1, characterized in that, the surface resolution of the DOMs of two periods generated in the step S2 should be the same as the resolution of the SAR images; otherwise the DOMs should be resampled.
The fine registration method in the step S3 includes: normalized cross-correlation matching method, least square matching method and feature matching method; the overall offset of the images is obtained from a quadric surface fitted from the offset of a non-deformed region, and is mainly a systematic error caused by the registration algorithm and noise.
In the step S4, the horizontal movement in the south-north direction UN and the horizontal movement in the east-west direction UE of the pixel points with the same names are calculated in unit of number of pixel points, specifically:
assuming that a point pair with the same name matched between a DOM1 of the first period and a DOM2 of the second period is point p(x,yi) and pointp2(x2,y2), the point pi(xi,yi) is located on the DOM Iof the first period and the pointp2(x2,y2) is located on the DOM2 of the second period
, (xi,yi) and (x2,y2) are the coordinates of the pointpi(xy)andpointp2(x2,y2) in respective image coordinate systems, the origin point of the image coordinate system is the top left corner of the DOM, the direction rightward from the origin point is the X-direction of the image coordinate system, and the direction downward from the origin point is the Y-direction of the image coordinate system; the horizontal movement of the earth's surface recorded in the DOM1 of the first period and the DOM2 of the second period are calculated respectively with formulae UN(x,y)=GSD*(y2-y1) and UE(x,y)=GSD*(x2-xi), UN(x,y) is the horizontal movement of the point pair with the same name pi(xi,yi) and p2(x2,y2) in the south-north direction, UE(x,y) is the horizontal movement of the point pair with the same name p(x,yi) andp2(x2,y2) in the east-west direction, and GSD is the surface resolution of the DOM.
The formula for resolving the vertical surface subsidence value W with the SAR three-dimensional deformation decomposition model in the step S5 is as follows:
LOS + sin 6 [UN cos(ah - 37r/2) + Esin(ath - 31r/2)] cos6
wherein, 6 is the incident angle of the radar satellite; ah is the heading angle of the satellite; UN and UE are horizontal movements in the north-south and east-west directions calculated from the unmanned aerial vehicle DOMs; and LOS is the deformation of line-of-sight direction of the radar towards the earth's surface obtained with the SAR/InSAR technology.
Beneficial Effects
With mono-orbital SAR technology, only high-precision deformation in the line-of-sight (LOS) direction of the radar can be obtained, but the deformation cannot be decomposed to three-dimensional deformation in the vertical direction, the east-west direction, and the south-north direction. Besides, only low-precision deformation in the vertical direction can be obtained by taking the difference between the DOMs of unmanned aerial vehicle images in two periods; there is few research and application on the horizontal movement. In the present invention, the advantages of unmanned aerial vehicle images and SAR images are utilized in combination. Specifically, the horizontal movement is obtained through fine registration of the unmanned aerial vehicle images; by substituting the horizontal movement into a SAR LOS-direction deformation decomposition equation, the LOS deformation can be decomposed to obtain high-precision deformation in the vertical direction. Thus, the method provided by the present invention makes up the shortcomings of the two traditional methods in obtaining high-precision three-dimensional deformation of the earth's surface by using either method solely, effectively obtains the three-dimensional deformation of the earth's surface and buildings/constructions, and solves the problem that only the LOS-direction deformation can be obtained from mono-orbital SAR images. In addition, the present invention expands the application scope of unmanned aerial vehicle photogrammetry, has the advantages of high precision, low cost, non-contact with the object being measured, wide coverage and easy operation, etc., and provides a novel technical means for extracting three-dimensional deformation information of the earth's surface and buildings/constructions, and monitoring and early warning of geological disasters.
Description of Drawings
FIG. 1 is a flow chart of the implementation of the method for extracting three-dimensional deformation of the earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images in the present invention;
FIG. 2 is a simulated three-dimensional deformation map of the earth's surface used in the present invention;
FIG. 3 is a three-dimensional deformation map of the earth's surface resolved with the method in the present invention.
Embodiments
The present invention will be further detailed below in connection with a specific implementation process.
As shown in FIG. 1, the method for extracting three-dimensional deformation of the earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images in the present invention, characterized in that, comprises the following steps:
Sl: resolving a line-of-sight deformation field of a target region by using satellite SAR/InSAR technology, and denoting as LOS; the SAR/InSAR technology employs classic offset tracking algorithm, sub-band interference method, DInSAR, and time-series InSAR, the above methods can be used to acquire the line-of-signt deformation of the earth's surface which denoted as LOS.
S2: using an unmanned aerial vehicle to acquire image data of the earth's surface of the target region in two different periods along the same air route, and the surface resolution of the generated DOMs of the two periods should be the same as the resolution of the SAR images, otherwise the DOMs should be resampled; processing the unmanned aerial vehicle images and generating digital orthophoto maps (DOMs), and the DOMs of two periods has the same spatial resolution;
S3: using the DOM Iof the first period as a main image, using the DOM2 of the second period as a secondary image, and calculating an pixel offset of image points with the same names in the DOMs of the two periods in the south-north direction and the east-west direction by using a fine registration method; the fine registration method includes: normalized cross-correlation matching method, least square matching method and feature matching method; the overall offset of the images is obtained from a quadric surface fitted from the offset of a non-deformed region, and is mainly a systematic error caused by the registration algorithm and noise; the overall offset of the images obtained by the unmanned aerial vehicle in the two periods is removed from the pixel offset to obtain an pixel offset caused by earth's surface movement; the overall offset of the images is an error offset generated in the two periods of aerial photography, the error offset is an overall pixel offset caused by the registration method and noise, etc.; an overall offset of the region is fitted from these offsets, and these offsets are removed from the entire image, so that a real offset of the deformed region is left.
S4: calculating actual horizontal movement of earth's surface corresponding to each image point with same name by using the pixel offset in the south-north direction and the east-west direction obtained in the step S3 and the earth's surface resolution of the images, wherein the actual horizontal movement corresponding to each image point with same name includes: horizontal movement in the south-north direction UN and horizontal movement in the east-west direction UE;
S5: resolving a vertical surface subsidence value W of the target region, according to a SAR three-dimensional deformation decomposition model, with the line-of-sight deformation field LOS, the horizontal movement in the south-north direction UN and the horizontal movement in the east-west direction UE that are acquired by means of the satellite, to obtain actual three-dimensional deformation of earth's surface.
Example 1
Here, an example of acquiring three-dimensional deformation of earth's surface from simulation data of coal mining is used. The strike length Di of a simulated mining working face is 155 m; the dip length D 2 is 110 m; the strike angle rp, of the coal seam is 0°; the dip angle a of the coal seam is 0°; the average mining depth H is 300 m; the mining thickness m of the coal seam is 4,000 mm; the incident angle of simulated SAR image radar satellite is 37.28°; and the heading angle of the satellite is 176.52°. The three-dimensional deformation of earth's surface u, ue and w of the simulated coal mine are calculated with a mining subsidence prediction model and simulation parameters; the resolution of the simulated SAR images is 0.221 m; the LOS data is simulated according to the SAR three-dimensional deformation decomposition model. For the unmanned aerial vehicle DOM at time ti in a mining area, the DOM is resampled according to the simulated three-dimensional deformation value of earth's surface, and the new DOM is taken as the DOM generated by the unmanned aerial vehicle image at time t2 .
A method for extracting three-dimensional deformation of earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images, comprising the following steps:
1) resolving a line-of-sight deformation field LOS of a target region by using SAR/InSAR technology;
The SAR images of the target region in different periods are acquired, and the deformation data LOS in the line-of-sight direction of the target region in two periods are obtained by using the classic offset tracking algorithm, sub-band interference method, DInSAR, time-series InSAR and other algorithms.
2) generating digital orthophoto maps (DOMs) from the earth's surface image data of the target region in the two periods acquired by the unmanned aerial vehicle;
The time interval between the two flight cycles of the unmanned aerial vehicle should be consistent with the time interval for acquiring SAR images, the flight altitude and camera parameters used in the two flight cycles should be consistent, at the same time the coordinates of the top left corners of the generated DOMs after the processing should be the same, and the surface resolution of the DOMs should be the same as the resolution of the SAR images; after the resampling, the surface resolution of the resulting DOMs is 0.221 m, and the size of the deformed region of interest is 1185 x 823 pixels.
3) matching the pixel points with same names in the DOMs of the two periods with a fine registration method;
Normalized cross-correlation matching method, feature matching method, least square image matching method and other matching methods for points with same names are used for the two periods of DOMs, to achieve rough registration and fine registration of the DOM.
4) calculating actual horizontal movements UN and UE of earth's surface corresponding to each pixel point;
For a matched point pair with same names pi(xi,yi) andp2(x2,y2), the point pi(xi,yi) is located on the DOM1 and the point p2(x2,y2) is located on the DOM2, (xi,yi) and (x2,y2) are the coordinates of the point pi(xi,yi) and point p2(x2,y2) in respective image coordinate systems, the origin point of the image coordinate system is the top left corner of the DOM, the direction rightward from the origin point is the X-direction of the image coordinate system, and the direction downward from the origin point is the Y-direction of the image coordinate system; the horizontal surface movements in the two periods are calculated with a formula Uv(x,y) = 22.1 x (y2 - yi) and UE(x,y) = 22.1 x (X2 - XI), UNv(x,y) is the horizontal movement of the point pair with same names p(x,y) andp2(x2,y2) in the south-north direction, and UE(,y) is the horizontal movement of the point pair with same names pi(xi,yi) and p2(x2,y2) in the east-west direction.
A vertical deformation value W of the earth's surface point is resolved;
The vertical deformation value W of each point of the earth's surface is calculated with the following formula, according to the SAR three-dimensional deformation decomposition model, from the LOS value and the horizontal movements in the east-west and south-north directions UN and UE resolved from the unmanned aerial vehicle DOMs:
LOS + sin 0 [UN COS(ah - 3ir/2) + LE sin(af - 3T/2)] cos9
wherein, 0 is the incident angle of the radar satellite; ah is the heading angle of the satellite; UN and UE are horizontal movements in the north-south and east-west directions calculated through registration of the unmanned aerial vehicle DOMs; and LOS is the surface deformation in the line-of-sight direction of the radar obtained with the SAR/InSAR technology.
5) The resolving result in the three directions UN, UE and W is shown in FIG. 3; the original simulated three-dimensional surface deformations un, ueand w are shown in FIG. 2. These root mean square errors are 12.16mm, 10.05mm and 7.56mm respectively. This is a calculation result after forty pixel points where the edge matching is poor are removed.
Claims (6)
- Claims1 A method for extracting three-dimensional deformation of earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images, characterized in that, comprising the following steps: Si: resolving a line-of-sight deformation field of a target region by using satellite SAR/InSAR technology, and denoting as LOS; S2: using an unmanned aerial vehicle to acquire surface image data of the target region in two different periods along the same air route, processing the unmanned aerial vehicle images and generating digital orthophoto maps (DOMs), and the DOMs of two periods has the same spatial resolution; S3: using the DOM Iof the first period as a main image, using the DOM2 of the second period as a secondary image, calculating an pixel offset of image points with same names in the DOMs of two periods in a south-north direction and an east-west direction by using a fine registration method, and removing an overall offset of the images from the pixel offset to obtain an pixel offset caused by earth's surface movement; the overall offset of the images is an error offset generated in the two cycles of aerial photography; S4: calculating actual horizontal movement of earth's surface corresponding to each image point with same name by using the pixel offset in the south-north direction and the east-west direction obtained in the step S3 and the surface resolution of the images, wherein the actual horizontal movement corresponding to each image point with same name includes: horizontal movement in the south-north direction UN and horizontal movement in the east-west direction UE;S5: resolving a vertical surface subsidence value W of the target region, according to a SAR three-dimensional deformation decomposition model, with the line-of-sight deformation field LOS, the horizontal movement in the south-north direction UN and the horizontal movement in the east-west direction UE that are acquired by means of the satellite, to obtain actual three-dimensional deformation of earth's surface.
- 2. The method for extracting three-dimensional deformation of earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images according to claim 1, characterized in that, the SAR/InSAR technology in the step SIemploys classic offset tracking algorithm, sub-band interference method, DInSAR, and time-series InSAR, the above methods can be used to acquire the line-of-sight surface deformation which denoted as LOS.
- 3. The method for extracting three-dimensional deformation of earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images according to claim 1, characterized in that, the surface resolution of the DOMs of two periods generated in the step S2 should be the same as the resolution of the SAR images, otherwise the DOMs should be resampled.
- 4. The method for extracting three-dimensional deformation of earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images according to claim 1, characterized in that, the fine registration method in the step S3 includes: normalized cross-correlation matching method, least square matching method and feature matching method; the overall offset of the images is obtained from a quadric surface fitted from the offset of a non-deformed region, and is mainly a systematic error caused by the registration algorithm and noise.
- 5. The method for extracting three-dimensional deformation of earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images according to claim 1, characterized in that, in the step S4, the horizontal movement in the south-north direction UN and the horizontal movement in the east-west direction UE of the pixel points with same names are calculated in unit of number of pixel points, specifically: assuming that a point pair with same names matched between a DOM Iof the first period and a DOM2 of the second period is p(xi,yi) and p2(x2,y2), the point pi(xi,yi) is located on the DOM1 of the first period and the pointp2(x2,y2) is located on the DOM2 of the second period, (xi,yi) and (x2,y2) are the coordinates of the point p(x,y) and pointp2(x2,y2) in respective image coordinate systems, the origin point of the image coordinate system is the top left corner of the DOM, the direction rightward from the origin point is the X-direction of the image coordinate system, and the direction downward from the origin point is the Y-direction of the image coordinate system; the horizontal surface movement recorded in the DOM1 of the first period and the DOM2 of the second period are calculated respectively with formulae UN(x,y)=GSD*(y2-y1) and UE(x,y)=GSD*(x2-x1), UN(x,y) is the horizontal movement of the point pair with same names p(x,y) andp2(x2,y2) in the south-north direction, UE(x,y) is the horizontal movement of the point pair with same names p(x,y) andp2(x2,y2) in the east-west direction, and GSD is the surface resolution of the DOM.
- 6. The method for extracting three-dimensional deformation of earth's surface by combining unmanned aerial vehicle DOMs and satellite-borne SAR images according to claim 5, characterized in that, the formula for resolving the vertical surface subsidence value W with the SAR three-dimensional deformation decomposition model in the step S5 is as follows:LOS + sin 0 [UN COS(ah - 31T/2) + E sin(aft - 3/2)] w= cosOwherein, 0 is the incident angle of the radar satellite; ah is the heading angle of the satellite; UN and UE are horizontal movements in the north-south and east-west directions calculated from the unmanned aerial vehicle DOMs; and LOS is the surface deformation in the line-of-sight direction of the radar obtained with the SAR/InSAR technology.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202110367713.1A CN113091599B (en) | 2021-04-06 | 2021-04-06 | Surface three-dimensional deformation extraction method fusing unmanned aerial vehicle DOM and satellite-borne SAR images |
| CN202110367713.1 | 2021-04-06 | ||
| PCT/CN2021/141462 WO2022213673A1 (en) | 2021-04-06 | 2021-12-27 | Method for extracting three-dimensional surface deformation by combining unmanned aerial vehicle doms and satellite-borne sar images |
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| CN113091599B (en) * | 2021-04-06 | 2021-12-03 | 中国矿业大学 | Surface three-dimensional deformation extraction method fusing unmanned aerial vehicle DOM and satellite-borne SAR images |
| CN113744393B (en) * | 2021-09-09 | 2023-05-30 | 北京建筑大学 | Multi-level slope landslide change monitoring method |
| CN114236541B (en) * | 2021-12-08 | 2023-05-16 | 电子科技大学 | Large-area earth surface three-dimensional deformation calculation method based on Sentinel-1 satellite SAR image |
| CN114199189B (en) * | 2021-12-09 | 2023-09-12 | 太原理工大学 | Mining subsidence monitoring method combining unmanned plane and DINSAR technology |
| CN114964028B (en) * | 2022-05-24 | 2023-03-10 | 长安大学 | Method for rapidly interpreting earthquake surface fractured zone by comprehensive remote sensing |
| CN115128609B (en) * | 2022-09-01 | 2022-12-06 | 中国科学院空天信息创新研究院 | Satellite-borne SAR three-dimensional product generation method and device |
| CN116049929B (en) * | 2022-10-26 | 2023-09-29 | 马培峰 | Urban building risk level InSAR evaluation and prediction method |
| CN115424155B (en) * | 2022-11-04 | 2023-03-17 | 浙江大华技术股份有限公司 | Illegal construction detection method, illegal construction detection device and computer storage medium |
| CN115713531B (en) * | 2023-01-05 | 2023-05-09 | 山东环宇地理信息工程有限公司 | InSAR-based earth surface image data processing system |
| CN116222411B (en) * | 2023-04-06 | 2023-10-20 | 山东环宇地理信息工程有限公司 | Surface deformation monitoring system, monitoring method and application |
| CN116485857A (en) * | 2023-05-05 | 2023-07-25 | 中山大学 | High-time-resolution glacier thickness inversion method based on multi-source remote sensing data |
| CN116416401B (en) * | 2023-06-02 | 2023-08-15 | 北京建工环境修复股份有限公司 | Polluted site assessment method and system based on unmanned aerial vehicle aerial photography |
| CN117031425A (en) * | 2023-06-26 | 2023-11-10 | 昆明理工大学 | Method and system for predicting large-gradient landslide instability time based on spaceborne SAR |
| CN116908789B (en) * | 2023-09-13 | 2023-12-05 | 长江空间信息技术工程有限公司(武汉) | Foundation synthetic aperture radar interferometry building elevation deformation information extraction method |
| CN117367429B (en) * | 2023-10-13 | 2024-05-14 | 黑龙江省水利科学研究院 | Remote sensing image-based working base map and unmanned aerial vehicle technology-based route image control point distribution algorithm |
| CN117132913B (en) * | 2023-10-26 | 2024-01-26 | 山东科技大学 | Ground surface horizontal displacement calculation method based on unmanned aerial vehicle remote sensing and feature recognition matching |
| CN117213443B (en) * | 2023-11-07 | 2024-03-19 | 江苏省地质调查研究院 | Construction and updating method of ground settlement monitoring network with integration of heaves, earth and depth |
| CN117572378B (en) * | 2024-01-17 | 2024-03-19 | 北京四象爱数科技有限公司 | Mountain settlement analysis method and device based on InSAR and Beidou data |
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| JP3098298B2 (en) * | 1991-11-19 | 2000-10-16 | 日本無線株式会社 | Target tracking device |
| KR101111689B1 (en) * | 2009-11-03 | 2012-02-14 | 연세대학교 산학협력단 | The method for three-dimensional deformation measurement and the apparatus thereof |
| CN101739677B (en) * | 2009-12-17 | 2013-08-07 | 中国测绘科学研究院 | SAR (synthetic aperture radar) ortho-image map elevating track fusing method |
| JP6696083B2 (en) * | 2016-05-20 | 2020-05-20 | 国際航業株式会社 | Area displacement calculation system, area displacement calculation method, and area displacement calculation program |
| DE102016119155A1 (en) * | 2016-09-15 | 2018-03-15 | Zoller + Fröhlich GmbH | laser scanner |
| CN109059849A (en) * | 2018-09-28 | 2018-12-21 | 中国科学院测量与地球物理研究所 | A kind of surface subsidence prediction technique based on InSAR technology in remote sensing |
| CN111553245A (en) * | 2020-04-24 | 2020-08-18 | 中国电建集团成都勘测设计研究院有限公司 | Vegetation classification method based on machine learning algorithm and multi-source remote sensing data fusion |
| CN112577438B (en) * | 2020-11-16 | 2021-12-28 | 中国矿业大学 | Coal mine area three-dimensional deformation monitoring method utilizing unmanned aerial vehicle image |
| CN113091599B (en) * | 2021-04-06 | 2021-12-03 | 中国矿业大学 | Surface three-dimensional deformation extraction method fusing unmanned aerial vehicle DOM and satellite-borne SAR images |
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