CN109613513A - A kind of potential landslide automatic identifying method of optical remote sensing for taking InSAR deformation into account - Google Patents
A kind of potential landslide automatic identifying method of optical remote sensing for taking InSAR deformation into account Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
- G01S17/90—Lidar systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/483—Details of pulse systems
- G01S7/486—Receivers
- G01S7/487—Extracting wanted echo signals, e.g. pulse detection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/491—Details of non-pulse systems
- G01S7/493—Extracting wanted echo signals
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N2021/1793—Remote sensing
Abstract
The invention belongs to potential landslide identification fields, it discloses a kind of potential landslide automatic identifying method of the optical remote sensing for taking InSAR deformation into account: obtaining the rate of deformation figure and optical remote sensing image data of target area, and the optical remote sensing image is pre-processed, obtain the optical remote sensing image figure of target area；The terrain information data of target area are calculated；According to the rate of deformation figure of target area, segmentation obtains multiple objects, and chooses terrain classification sample, obtains the characteristic of division element and its threshold value of all kinds of terrain classification samples；The potential landslide areas in target area for being utilized optical remote sensing image acquisition is rejected in classification；Potential landslide object is calculated, potential landslide object is merged with the potential landslide areas in obtained target area, finally obtains target area completely potential landslide areas；Present invention combination optical remote sensing and InSAR rate of deformation information, can quickly and effectively extract potential landslide, the degree of automation and high reliablity, provide technical support for prevention landslide disaster.
Description
Technical field
The invention belongs to potential landslide identification fields, and in particular to a kind of optical remote sensing for taking InSAR deformation into account is latent
In landslide automatic identifying method.
Background technique
Landslide is a kind of common natural calamity as caused by natural cause or mankind's activity, occurs mainly in mountain area and river
Valley floor band；Identification landslide is carried out to survey region using optical remote sensing Interpretation Technology, although its coverage area is big, and can be passed through
Human-computer interaction carries out identification landslide；But the method on traditional optical remote sensing image identification landslide is past when carrying out SURVEYING OF LANDSLIDE
Toward the landslide identification achievement of sxemiquantitative can only be provided, exists and fail to judge, misjudge phenomenon, and majority is the area after occurring for landslide
Domain positioning, it is difficult to realize and EARLY RECOGNITION is carried out to potential landslide areas, causing much to come down is difficult to obtain timely early warning and effectively
Prevention and treatment.It also include phase information since SAR image not only contains strength information, it is available by InSAR rate of deformation information
Centimeter Level even millimetre-sized Ground Deformation in survey region, to improve the reliability of landslide identification and monitoring in survey region
With accuracy；But InSAR rate of deformation information can only obtain one-dimensional deformation and be inverted and have an X-rayed there are shade, top bottom and shorten
Phenomena such as, can also exist to the failing to judge of landslide, misjudge phenomenon, be based particularly on InSAR rate of deformation information and directly come down
Identification needs artificial drafting, has subjectivity, and the degree of automation is low.
Summary of the invention
The landslide knowledge of sxemiquantitative can only be provided for the method on optical remote sensing image existing in the prior art identification landslide
Other achievement exists and fails to judge, misjudges phenomenon, and InSAR rate of deformation information carries out that subjectivity when landslide identification is strong, automatic degree not
High problem, the object of the present invention is to provide a kind of automatic knowledges in the potential landslide of optical remote sensing for taking InSAR deformation into account
Other method.
To achieve the goals above, the application, which adopts the following technical scheme that, is achieved:
A kind of potential landslide automatic identifying method of optical remote sensing for taking InSAR deformation into account, specifically includes the following steps:
Step 1, the SAR image collected to the SAR satellite in survey region are handled, and obtain the shape of survey region
Variable Rate figure；Choosing the doubtful landslide areas of one of them in covering survey region is target area, and cutting obtains target area
Rate of deformation figure；
The dem data of step 2, the optical remote sensing image data for obtaining target area and target area, the optical remote sensing
Image data includes panchromatic wave-band data and 4 wave band multispectral datas；According to the dem data of the target area of acquisition to the light
Learn remote sensing image data and carry out ortho-rectification, obtain include panchromatic wave-band data and 4 wave band multispectral datas just to penetrate optics distant
Feel image；It handles optical remote sensing image is just penetrated, obtains the optical remote sensing image figure of target area；The DEM refers to number
Elevation model；
Step 3, dem data definition projection and resampling to target area, the dem data after obtaining resampling；Counterweight
Dem data after sampling is cut out, and obtains the complete dem data in target area, and according to the complete DEM number in target area
According to the slope map, massif echo, surface relief degree figure, ground elevation figure of target area is calculated；
It is characterized by further comprising:
Step 4, rate of deformation figure definition projection and resampling to target area, the rate of deformation after obtaining resampling
Figure；Using multi-scale segmentation method, to the optical remote sensing of rate of deformation and target area in the rate of deformation figure after resampling
4 wave band multispectral datas in striograph are integrally split, and obtain multiple objects；
According to the slope map of target area, massif echo, surface relief figure, ground elevation figure and the optics of target area
4 wave band multispectral datas in remote sensing image, are calculated multiple object's property values；
Terrain classification sample is chosen as basic unit using obtained multiple objects, according to the terrain classification sample of selection and is obtained
To multiple object's property values be calculated all kinds of terrain classification samples characteristic of division element and characteristic of division element it is corresponding
Threshold value；
Step 5, according to the characteristic of division element and the corresponding threshold value of characteristic of division element of all kinds of terrain classification samples to mesh
The optical remote sensing image figure in mark region is classified, and the classification results of all kinds of atural objects are obtained；According to the classification results of all kinds of atural objects,
It is utilized the potential landslide areas of the target area of optical remote sensing image acquisition；
Step 6, according to the classification results of the rate of deformation figure of target area and all kinds of atural objects, extract and obtain the potential of leakage point
Come down object；By leakage point potential landslide object and using optical remote sensing image obtain target area potential landslide areas into
Row merges, and has been merged the potential landslide areas of the target area of optical remote sensing image and InSAR rate of deformation information.
Further, the step 4 specifically comprises the following steps:
Step 41 defines projection using rate of deformation figure of map projection's method to target area, obtains having projection letter
The rate of deformation figure of breath, and sit the projection of the optical remote sensing image figure of the rate of deformation figure with projection information and target area
Mark system is consistent；Resampling is carried out to the rate of deformation figure with projection information using the method for cubic convolution, obtains resampling
Rate of deformation figure afterwards, and keep the resolution ratio of the optical remote sensing image figure of rate of deformation figure and target area after resampling
Unanimously；
Step 42, using the rate of deformation in the rate of deformation figure after resampling as a wave band data, use is multiple dimensioned
Dividing method, to 4 waves in the optical remote sensing image figure of rate of deformation and target area in the rate of deformation figure after resampling
Section multispectral data is integrally split, and obtains multiple objects, the object refers to the pixel set with homogeney；
Step 43, respectively from the slope map of target area, massif echo, surface relief degree, ground elevation figure and target
All pixels that object is formed in each object are acquired in 4 wave band multispectral datas in the optical remote sensing image figure in region
Value of slope, ground elevation value, massif shading value, hypsography angle value and the multispectral value of 4 wave bands, and calculate separately to obtain each
The average value of value of slope of all pixels of object, the average value of ground elevation value, massif shading value is formed in object to be averaged
The average value of value, the average value of hypsography angle value and the multispectral value of 4 wave bands；Each object is calculated separately by formula (4) (5)
NDVI value and NDWI value；
The average value of value of slope, the average value of ground elevation value, mountain of all pixels of object will be formed in each object
The NDVI value of the average value of body shading value, the average value of hypsography angle value, the average value of the multispectral value of 4 wave bands and each object
With NDWI value as each object's property value, multiple object's property values are obtained；
In formula, NDVIiIndicate the normalized differential vegetation index of i-th of object, NDWIiIndicate the normalization water body of i-th of object
Index；ρi(NIR)、ρi(RED)、ρi(GREEN) respectively indicate near infrared band in the 4 wave band multispectral datas of i-th of object,
Reflectance value at red wave band and green wave band, value range are [0,1], and i indicates that i-th of object, i are the natural number greater than 0；
Step 44 chooses terrain classification sample, the terrain classification sample packet as basic unit using obtained multiple objects
Include water body, vegetation, basement rock, bare area, artificial surface, deposit, shade sample；Using post-class processing algorithm to the atural object of selection
Classification samples and obtained multiple object's property values are calculated, obtain all kinds of terrain classification samples characteristic of division element and
The corresponding threshold value of characteristic of division element.
Further, the step 5 specifically:
By the corresponding threshold value composition and classification rule of the characteristic of division element and characteristic of division element of all kinds of atural objects, with classification
Rule classifies to the optical remote sensing image figure of target area, obtains the classification results of all kinds of atural objects；It rejects in multiple objects
The classification results of all kinds of atural objects are utilized the potential landslide areas of the target area of optical remote sensing image acquisition.
Further, the step 6 specifically comprises the following steps:
The rate of deformation figure of target area and the classification results of all kinds of atural objects are overlapped by step 61, obtain target area
The rate of deformation of each pixel in the optical remote sensing image figure in domain；Calculate being averaged for the rate of deformation of all pixels of composition object
Value, using obtained average value as the rate of deformation of object, obtains the rate of deformation of multiple objects；
Step 62, two threshold values m, n that rate of deformation is arranged, wherein m<0, n>0 are extracted each by the method for threshold classification
Object of rate of deformation k in the range of k≤m or k >=n in the classification results of class atural object, the potential landslide object as leakage point；
The potential landslide of step 63, the potential landslide object that leakage is divided and the target area obtained using optical remote sensing image
Region is merged using union, has been merged the target area of optical remote sensing image and InSAR rate of deformation information
Potential landslide areas.
Further, the step 1 is specific as follows:
To the SAR image that the SAR satellite in covering survey region collects, using the relevant point target in InSAR point
Analysis method handles SAR image, obtains the rate of deformation figure of survey region；One of in selection covering survey region
Doubtful landslide areas is that target area cuts the rate of deformation figure of survey region, obtain mesh along the boundary of target area
Mark the rate of deformation figure in region.
Further, the step 2 specifically comprises the following steps:
Step 21, the optical remote sensing image data that coverage goal region is obtained by remote sensing satellite, the optical remote sensing shadow
As the 4 wave band multispectral datas that data include the panchromatic wave-band data that resolution ratio is 0.61m and resolution ratio is 2.44m, 4 wave
Section includes red, green, blue and near infrared band；
Step 22, the dem data that target area is obtained by Space Shuttle Radar Topographic Mapping Mission system；Utilize optics
The included RPC file of remote sensing image data and RPC model shape obtain complete RPC model；Utilize dem data and complete RPC
Model carries out ortho-rectification to panchromatic wave-band data and 4 wave band multispectral datas respectively, obtains including panchromatic wave-band data and 4 waves
Section multispectral data just penetrates optical remote sensing image, and the RPC refers to rational polynominal coefficient；
Step 23, using NNDiffuse Pan Sharpening algorithm to include panchromatic wave-band data and 4 wave bands mostly light
The optical remote sensing image of just penetrating of modal data is merged, the optical remote sensing image merged；
Step 24 obtains target area vector boundary graph to target area range vector quantization；Along target area vector boundary
The boundary of figure cuts the optical remote sensing image of fusion, obtains the optical remote sensing image figure of target area.
Further, the step 3 specifically comprises the following steps:
Step 31 defines projection to the dem data using map projection's method, obtains the DEM number with projection information
According to making have the dem data of projection information consistent with the projection coordinate system of optical remote sensing image figure of target area；Using three
The method of secondary convolution carries out resampling to the dem data with projection information, and the dem data after obtaining resampling makes resampling
The resolution ratio of the optical remote sensing image figure of dem data and target area afterwards is consistent；
Step 32, along the boundary of target area vector boundary graph, the dem data after resampling is cut, mesh is obtained
Mark the complete dem data in region；According to the complete dem data in target area, the slope of target area is calculated using formula (1)
Degree figure；Massif echo is obtained using formula (2)；Surface relief degree figure is obtained using formula (3)；Ground elevation value is DEM number
Value, obtains ground elevation figure；
Wherein, slope is the gradient, fxFor X-direction elevation change rate in the complete dem data in target area, fyFor target area
Y-direction elevation change rate in the complete dem data in domain；
Wherein, hillshade is massif shade, zenithradFor the sun in the optical remote sensing image data of target area
The radian number of zenith angle, sloperadFor gradient radian number in the complete dem data in target area, azimuthradFor target area
Optical remote sensing image data in sunray direction radian number, aspectradFor in the complete dem data in target area
Slope aspect radian number；
R=Hmax-Hmin, R > 0, Hmax, Hmin∈R (3)
Wherein, R is topographic relief amplitude, HmaxIt is high to fix the maximum in analysis window in the complete dem data in target area
Journey, HminTo fix the lowest elevation in analysis window described in the complete dem data in target area.
Compared with prior art, the beneficial effects of the present invention are:
1, the present invention is using multi-scale segmentation method to the rate of deformation and target area in the rate of deformation figure after resampling
4 wave band multispectral datas in the optical remote sensing image figure in domain are split, and are finally obtained and are utilized optical remote sensing image acquisition
The potential landslide areas of target area, and by according to the rate of deformation figure of target area obtain leakage point potential landslide object with
The potential landslide areas of the target area obtained using optical remote sensing image is merged, and is finally obtained target area and is completely dived
In landslide areas；Present invention incorporates optical remote sensing technologies and InSAR rate of deformation information, can quickly and effectively identify simultaneously
Potential landslide, the degree of automation and high reliablity are extracted, is positioned particular for landslide areas does not occur, for potential
Monitoring, the early warning on landslide are of great significance.
2, the present invention is compared to the method on traditional optical remote sensing identification landslide, and the potential landslide areas identified is more
Completely, reduce the phenomenon that failing to judge, misjudging appearance；Drafting is interpreted by visual observation compared to single InSAR rate of deformation information to slide
Slope boundary graph, result is more accurate, high degree of automation, field investigation is not necessarily to, for the geology knowledge of practitioner
It is required that lower, the personnel of being particularly suitable for are difficult to the landslide identification reached research, provide skill for prevention landslide disaster in time
Art support.
Detailed description of the invention
Fig. 1 is flow chart of the invention；
Fig. 2 is the potential boundary of landslide figure obtained using InSAR rate of deformation information identification landslide method；
Fig. 3 is the potential boundary of landslide figure extracted using the method on traditional optical remote sensing image identification landslide；
Fig. 4 is the potential boundary of landslide figure extracted using the present invention.
Specific embodiment
With reference to the accompanying drawing, specific embodiments of the present invention will be described in detail, it is to be understood that guarantor of the invention
Shield range is not limited by the specific implementation.
As shown in Figure 1, the present invention provides a kind of potential landslide automatic identifications of optical remote sensing for taking InSAR deformation into account
Method, specifically includes the following steps:
Step 1, the SAR image collected to the SAR satellite in survey region are handled, and obtain the shape of survey region
Variable Rate figure；Choosing the doubtful landslide areas of one of them in covering survey region is target area, and cutting obtains target area
Rate of deformation figure；
The dem data of step 2, the optical remote sensing image data for obtaining target area and target area, the optical remote sensing
Image data includes panchromatic wave-band data and 4 wave band multispectral datas；According to the dem data of the target area of acquisition to the light
Learn remote sensing image data and carry out ortho-rectification, obtain include panchromatic wave-band data and 4 wave band multispectral datas just to penetrate optics distant
Feel image；It handles optical remote sensing image is just penetrated, obtains the optical remote sensing image figure of target area, the target area
Optical remote sensing image figure includes panchromatic wave-band data and 4 wave band multispectral datas；The DEM refers to digital elevation model；
Step 3, dem data definition projection and resampling to target area, the dem data after obtaining resampling；Counterweight
Dem data after sampling is cut out, and obtains the complete dem data in target area, and according to the complete DEM number in target area
According to the slope map, massif echo, surface relief degree figure, ground elevation figure of target area is calculated；
Step 4, rate of deformation figure definition projection and resampling to target area, the rate of deformation after obtaining resampling
Figure；Using the rate of deformation in the rate of deformation figure after resampling as a wave band data, using multi-scale segmentation method, counterweight
4 wave band multispectral datas in the optical remote sensing image figure of the rate of deformation and target area in rate of deformation figure after sampling are whole
Body is split, and obtains multiple objects；According to the slope map of target area, massif echo, surface relief figure, ground elevation figure
And 4 wave band multispectral datas in the optical remote sensing image figure of target area, multiple object's property values are calculated；To obtain
Multiple objects be that basic unit chooses terrain classification sample, according to the terrain classification sample of selection and obtained multiple objects
The characteristic of division element and the corresponding threshold value of characteristic of division element of all kinds of terrain classification samples is calculated in attribute value；
Step 5, according to the characteristic of division element and the corresponding threshold value of characteristic of division element of all kinds of terrain classification samples to mesh
The optical remote sensing image figure in mark region is classified, and the classification results of all kinds of atural objects are obtained；According to the classification results of all kinds of atural objects,
It is utilized the potential landslide areas of the target area of optical remote sensing image acquisition；
Step 6, according to the classification results of the rate of deformation figure of target area and all kinds of atural objects, extract and obtain the potential of leakage point
Come down object；By leakage point potential landslide object and using optical remote sensing image obtain target area potential landslide areas into
Row merges, and has been merged the potential landslide areas of the target area of optical remote sensing image and InSAR rate of deformation information.
The present invention using multi-scale segmentation method in the rate of deformation figure after resampling rate of deformation and target area
Optical remote sensing image figure in 4 wave band multispectral datas be split, finally obtain using optical remote sensing image obtain mesh
The potential landslide object and benefit marked the potential landslide areas in region, and the leakage obtained according to the rate of deformation figure of target area is divided
The potential landslide areas of the target area obtained with optical remote sensing image merges, and it is completely potential to finally obtain target area
Landslide areas；Present invention incorporates optical remote sensing technologies and InSAR rate of deformation information, quickly and effectively can identify and mention
Potential landslide is taken, strong, high reliablity is automated, is positioned particular for landslide areas does not occur, for potential landslide
Monitoring, early warning is of great significance.
Specifically, the step 1 is specific as follows:
To the SAR image that the SAR satellite in covering survey region collects, using the IPTA method in InSAR to SAR
Image is handled, and the rate of deformation figure of survey region is obtained；The doubtful landslide area of one of them in selection covering survey region
Domain is target area, along the boundary of target area, cuts to the rate of deformation figure of survey region, obtains the shape of target area
Variable Rate figure；
The InSAR indicates synthetic aperture radar interferometry technology；IPTA full name is Interferometric Point
Target Analysis indicates coherent point target analysis.
Which is cut out by the rate of deformation figure to survey region, obtains the rate of deformation figure and shape of target area
Variable Rate.
Specifically, the step 2 specifically comprises the following steps:
Step 21, the optical remote sensing image data that coverage goal region is obtained by remote sensing satellite, the optical remote sensing shadow
As the 4 wave band multispectral datas that data include the panchromatic wave-band data that resolution ratio is 0.61m and resolution ratio is 2.44m, 4 wave
Section includes red, green, blue and near infrared band；
Step 22, the dem data of target area is obtained by SRTM system；It is carried according to optical remote sensing image data
RPC file and RPC model form to obtain complete RPC model；Using dem data and complete RPC model respectively to Total coloring
Carry out ortho-rectification according to 4 wave band multispectral datas, obtain include full-colored data and 4 wave band multispectral datas just to penetrate optics distant
Feel image, 4 wave band includes red, green, blue and near infrared band；
The SRTM indicates Space Shuttle Radar Topographic Mapping Mission；The DEM indicates digital elevation model；The RPC
Full name is Rationale Polynomial Coefficients, indicates rational polynominal coefficient；
Step 23, using NNDiffuse (Nearest Neighbor Diffusion) Pan Sharpening algorithm pair
Optical remote sensing image of just penetrating including panchromatic wave-band data and 4 wave band multispectral datas is merged, and the optics merged is distant
Feel image；
Step 24, target area vector boundary graph is obtained to target area range vector quantization；Along target area vector boundary
The boundary of figure cuts the optical remote sensing image of fusion, obtains the optical remote sensing image figure of target area, the target area
The optical remote sensing image figure in domain includes panchromatic wave-band data and 4 wave band multispectral datas.
By carrying out ortho-rectification to full-colored data and 4 wave band multispectral datas in which, correct because landform causes
Height displacement；By the fusion of the panchromatic image and 4 wave band multispectral images just penetrated in optical remote sensing image, target knowledge is improved
The reliability of other image environment and interpretation reaches raising optical remote sensing image space while retaining multi light spectrum hands information
The purpose of resolution ratio finally obtains the optical remote sensing image figure of target area.
Specifically, the step 3 specifically comprises the following steps:
Step 31 defines projection to the dem data using map projection's method, obtains the DEM number with projection information
According to making have the dem data of projection information consistent with the projection coordinate system of optical remote sensing image figure of target area；Using three
The method of secondary convolution carries out resampling to the dem data with projection information, and the dem data after obtaining resampling makes resampling
The resolution ratio of the optical remote sensing image figure of dem data and target area afterwards is consistent；
Step 32, along the boundary of target area vector boundary graph, the dem data after resampling is cut, mesh is obtained
Mark the complete dem data in region；According to the complete dem data in target area, the slope of target area is calculated using formula (1)
Degree figure；Massif echo is obtained using formula (2)；Surface relief degree figure is obtained using formula (3)；Ground elevation value is DEM number
Value, obtains ground elevation figure；Terrain information includes the gradient, elevation, massif shade, topographic relief amplitude；
Wherein, slope is the gradient, fxFor X-direction elevation change rate in the complete dem data in target area, fyFor target area
Y-direction elevation change rate in the complete dem data in domain；
Wherein, hillshade is massif shade, zenithradFor the sun in the optical remote sensing image data of target area
The radian number of zenith angle, sloperadFor gradient radian number in the complete dem data in target area, azimuthradFor target area
Optical remote sensing image data in sunray direction radian number, aspectradFor in the complete dem data in target area
Slope aspect radian number；
R=Hmax-Hmin, R > 0, Hmax, Hmin∈R (3)
Wherein, R is topographic relief amplitude, HmaxIt is high to fix the maximum in analysis window in the complete dem data in target area
Journey, HminTo fix the lowest elevation in analysis window described in the complete dem data in target area.
Which obtains the complete dem data of target area, and obtained target by handling dem data and cutting
Slope map, massif echo, the surface relief degree figure, ground elevation figure in region.
Specifically, the step 4 specifically comprises the following steps:
Step 41 defines projection using rate of deformation figure of map projection's method to target area, obtains having projection letter
The rate of deformation figure of breath, and sit the projection of the optical remote sensing image figure of the rate of deformation figure with projection information and target area
Mark system is consistent；Resampling is carried out to the rate of deformation figure with projection information using the method for cubic convolution, obtains resampling
Rate of deformation figure afterwards, and keep the resolution ratio of the optical remote sensing image figure of rate of deformation figure and target area after resampling
Unanimously；
Step 42, using the rate of deformation in the rate of deformation figure after resampling as a wave band data, use is multiple dimensioned
Dividing method, to 4 waves in the optical remote sensing image figure of rate of deformation and target area in the rate of deformation figure after resampling
Section multispectral data is integrally split, and obtains multiple objects, the object refers to the pixel set with homogeney；
Step 43, respectively from the slope map of target area, massif echo, surface relief degree, ground elevation figure and target
All pixels that object is formed in each object are acquired in 4 wave band multispectral datas in the optical remote sensing image figure in region
Value of slope, ground elevation value, massif shading value, hypsography angle value and the multispectral value of 4 wave bands, and calculate separately to obtain each
The average value of value of slope of all pixels of object, the average value of ground elevation value, massif shading value is formed in object to be averaged
The average value of value, the average value of hypsography angle value and the multispectral value of 4 wave bands；Each object is calculated separately by formula (4) (5)
NDVI value and NDWI value；
The average value of value of slope, the average value of ground elevation value, mountain of all pixels of object will be formed in each object
The NDVI value of the average value of body shading value, the average value of hypsography angle value, the average value of the multispectral value of 4 wave bands and each object
With NDWI value as each object's property value, multiple object's property values are obtained；
In formula, NDVIiIndicate the normalized differential vegetation index of i-th of object, NDWIiIndicate the normalization water body of i-th of object
Index；ρi(NIR)、ρi(RED)、ρi(GREEN) respectively indicate near infrared band in the 4 wave band multispectral datas of i-th of object,
Reflectance value at red wave band and green wave band, value range are [0,1], and i indicates that i-th of object, i are the natural number greater than 0；
Step 44 chooses terrain classification sample, the terrain classification sample as basic unit using obtained multiple objects
Including water body, vegetation, basement rock, bare area, artificial surface, deposit, shade sample, using CART algorithm to the terrain classification of selection
Sample and obtained multiple object's property values are calculated, and the characteristic of division element and classification of all kinds of terrain classification samples are obtained
The corresponding threshold value of characteristic element；
The CART full name is Classification and Regression Tree, presentation class regression tree；
Which participates in segmentation by the rate of deformation figure of target area, participates in dividing with dem data in the prior art
It compares, can clearly sketch the contours the boundary of atural object, choose terrain classification sample, reduce calculation amount, be conducive to subsequent classification.
Specifically, the step 5 specifically:
By the corresponding threshold value composition and classification rule of the characteristic of division element and characteristic of division element of all kinds of atural objects, with classification
Rule classifies to the optical remote sensing image figure of target area, obtains the classification results of all kinds of atural objects；It rejects in multiple objects
The classification results of all kinds of atural objects are utilized the potential landslide areas of the target area of optical remote sensing image acquisition.
Which by the characteristic of division element and the corresponding threshold value of characteristic of division element according to all kinds of terrain classification samples,
It is utilized the potential landslide areas of the target area of optical remote sensing image acquisition, is conducive to subsequent and InSAR deformation data knot
It closes identification and obtains complete landslide areas.
Specifically, the step 6 specifically comprises the following steps:
The rate of deformation figure of target area and the classification results of all kinds of atural objects are overlapped by step 61, obtain target area
The rate of deformation of each pixel in the optical remote sensing image figure in domain；Calculate being averaged for the rate of deformation of all pixels of composition object
Value, using obtained average value as the rate of deformation of object, obtains the rate of deformation of multiple objects；
Step 62, two threshold values m, n that rate of deformation is arranged, wherein m<0, n>0 are extracted each by the method for threshold classification
Object of rate of deformation k in the range of k≤m or k >=n in the classification results of class atural object, the potential landslide object as leakage point；
The potential landslide of step 63, the potential landslide object that leakage is divided and the target area obtained using optical remote sensing image
Region is merged using union, has been merged the target area of optical remote sensing image and InSAR rate of deformation information
Potential landslide areas.
Which has merged optical remote sensing image and InSAR deformation data identifies potential landslide, compared to traditional optics
The method on remote sensing image identification landslide, the potential landslide areas identified is more complete, reduces the phenomenon that failing to judge, misjudging and goes out
It is existing；It being interpreted by visual observation compared to single InSAR deformation data and draws boundary of landslide figure, result is more in line with landform tendency,
More accurate, high degree of automation is not necessarily to field investigation, lower for the geology requested knowledge of practitioner, especially suitable
It is difficult to the landslide identification reached research for personnel, provides technical support for prevention landslide disaster in time.
Embodiment
The present invention acquires the ALOS/PALSAR rail lift data of covering Drainage Area of Jinsha River crow East Germany reservoir area and covers double dragon's pools
The QuickBird-02 data of potential landslide areas.Wherein, the ALOS/PALSAR rail lift data of acquisition share 20 scapes, image day
Phase range is in January, 2007 in March, 2011；The QuickBird-02 data of acquisition have 1 scape, include the complete of 0.61m resolution ratio
For chromatic number according to the multispectral data with 2.44m resolution ratio, the acquisition date is on November 15th, 2009, and solar elevation is 43.6 °, too
Positive azimuth is 162.7 °, and cloud amount is covered as 0.00%.
Experimentation
Step 1 handles the SAR image of collected black East Germany reservoir area, obtains the rate of deformation of black East Germany reservoir area
Figure, in black East Germany reservoir area, common recognition is clipped to 22 doubtful landslide areas；The doubtful landslide areas for choosing one of them is target area,
Obtain the rate of deformation figure of target area.
The dem data of step 2, the optical remote sensing image data for obtaining target area and target area, the optical remote sensing
Image data includes panchromatic wave-band data and 4 wave band multispectral datas；According to the dem data of the target area of acquisition to the light
Learn remote sensing image data and carry out ortho-rectification, obtain include panchromatic wave-band data and 4 wave band multispectral datas just to penetrate optics distant
Feel image；It handles optical remote sensing image is just penetrated, obtains the optical remote sensing image figure of target area；
Step 3, dem data definition projection and resampling to target area, the dem data after obtaining resampling；Counterweight
Dem data after sampling is cut out, and obtains the complete dem data in target area, according to the complete dem data in target area,
The slope map of target area is calculated using formula (1)；Massif echo is obtained using formula (2)；It is obtained using formula (3)
Surface relief degree figure；Ground elevation value is DEM numerical value, obtains ground elevation figure；
Wherein, slope is the gradient, fxFor X-direction elevation change rate in the complete dem data in target area, fyFor target area
Y-direction elevation change rate in the complete dem data in domain；
Wherein, hillshade is massif shade, zenithradFor the sun in the optical remote sensing image data of target area
The radian number of zenith angle, sloperadFor gradient radian number in the complete dem data in target area, azimuthradFor target area
Optical remote sensing image data in sunray direction radian number, aspectradFor in the complete dem data in target area
Slope aspect radian number；
R=Hmax-Hmin, R > 0, Hmax, Hmin∈R (3)
Wherein, R is topographic relief amplitude, HmaxIt is high to fix the maximum in analysis window in the complete dem data in target area
Journey, HminTo fix the lowest elevation in analysis window described in the complete dem data in target area.
Step 4, rate of deformation figure definition projection and resampling to target area, the rate of deformation after obtaining resampling
Figure；Using the rate of deformation in the rate of deformation figure after resampling as a wave band data, using multi-scale segmentation method, counterweight
4 wave band multispectral datas in the optical remote sensing image figure of the rate of deformation and target area in rate of deformation figure after sampling are whole
Body is split, and obtains multiple objects；
Respectively from the slope map of target area, massif echo, surface relief degree, ground elevation figure and the light of target area
Learn the gradient that all pixels that object is formed in each object are acquired in 4 wave band multispectral datas in remote sensing image
Value, ground elevation value, massif shading value, hypsography angle value and the multispectral value of 4 wave bands, and calculate separately to obtain in each object
Form the average value of value of slope, the average value of ground elevation value, the average value of massif shading value, landform of all pixels of object
The average value of the average value of fluctuating angle value and the multispectral value of 4 wave bands；The NDVI of each object is calculated separately by formula (4) (5)
Value and NDWI value；
The average value of value of slope, the average value of ground elevation value, mountain of all pixels of object will be formed in each object
The NDVI value of the average value of body shading value, the average value of hypsography angle value, the average value of the multispectral value of 4 wave bands and each object
With NDWI value as each object's property value, multiple object's property values are obtained；
In formula, NDVIiIndicate the normalized differential vegetation index of i-th of object, NDWIiIndicate the normalization water body of i-th of object
Index；ρi(NIR)、ρi(RED)、ρi(GREEN) respectively indicate near infrared band in the 4 wave band multispectral datas of i-th of object,
Reflectance value at red wave band and green wave band, value range are [0,1], and i indicates that i-th of object, i are the natural number greater than 0；
Terrain classification sample is chosen by basic unit of object, using post-class processing algorithm to the terrain classification sample of selection
This and its attribute value are calculated, and the characteristic of division element and the corresponding threshold of characteristic of division element of all kinds of terrain classification samples are obtained
Value；
Step 5, according to the characteristic of division element and the corresponding threshold value of characteristic of division element of all kinds of terrain classification samples to mesh
The optical remote sensing image figure in mark region is classified, and the classification results of all kinds of atural objects are obtained；According to the classification results of all kinds of atural objects,
It is utilized the potential landslide areas of the target area of optical remote sensing image acquisition；
Step 6, according to the classification results of the rate of deformation figure of target area and all kinds of atural objects, extract and obtain the potential of leakage point
Come down object；By leakage point potential landslide object and using optical remote sensing image obtain target area potential landslide areas into
Row merges, and obtains the target for having merged optical remote sensing image and InSAR rate of deformation information as drawn in Fig. 4 with black lines
The potential landslide areas in region.
The potential landslide as drawn in Fig. 2 with black lines is obtained using InSAR rate of deformation information identification landslide method
Boundary graph；The present invention identifies landslide method compared to using InSAR rate of deformation information, and it is distant that the present invention obtained has merged optics
The potential landslide areas of the target area of sense image and InSAR rate of deformation information is more in line with landform tendency, more accurately, from
Dynamicization degree is high.
It extracts to obtain using the method on traditional optical remote sensing image identification landslide as latent in drawn in Fig. 3 with black lines
In boundary of landslide figure；The present invention is extracted compared to the method on traditional optical remote sensing image identification landslide and utilizes traditional optical
The potential landslide object of leakage point when remote sensing image identification landslide, what is obtained has merged optical remote sensing image and InSAR rate of deformation
The potential landslide areas of the target area of information is more complete, reduces the phenomenon that failing to judge, misjudging appearance.
Disclosed above is only specific embodiments of the present invention, and still, the embodiment of the present invention is not limited to this, Ren Heben
What the technical staff in field can think variation should all fall into protection scope of the present invention.
Claims (7)
1. a kind of potential landslide automatic identifying method of optical remote sensing for taking InSAR deformation into account, specifically includes the following steps:
Step 1, the SAR image collected to the SAR satellite in survey region are handled, and obtain the deformation speed of survey region
Rate figure；Choosing the doubtful landslide areas of one of them in covering survey region is target area, and cutting obtains the shape of target area
Variable Rate figure；
The dem data of step 2, the optical remote sensing image data for obtaining target area and target area, the optical remote sensing image
Data include panchromatic wave-band data and 4 wave band multispectral datas；It is distant to the optics according to the dem data of the target area of acquisition
Feel image data and carry out ortho-rectification, obtains including that panchromatic wave-band data and 4 wave band multispectral datas just penetrate optical remote sensing shadow
Picture；It handles optical remote sensing image is just penetrated, obtains the optical remote sensing image figure of target area；The DEM refers to digital elevation
Model；
Step 3, dem data definition projection and resampling to target area, the dem data after obtaining resampling；To resampling
Dem data afterwards is cut out, and obtains the complete dem data in target area, and according to the complete dem data in target area, meter
Calculation obtains the slope map, massif echo, surface relief degree figure, ground elevation figure of target area；
It is characterized by further comprising:
Step 4, rate of deformation figure definition projection and resampling to target area, the rate of deformation figure after obtaining resampling；It adopts
With multi-scale segmentation method, to the optical remote sensing image figure of rate of deformation and target area in the rate of deformation figure after resampling
In 4 wave band multispectral datas be integrally split, obtain multiple objects；
According to the slope map of target area, massif echo, surface relief figure, ground elevation figure and the optical remote sensing of target area
4 wave band multispectral datas in striograph, are calculated multiple object's property values；
By basic unit of obtained multiple objects terrain classification sample is chosen, according to the terrain classification sample of selection and obtained
The characteristic of division element and the corresponding threshold of characteristic of division element of all kinds of terrain classification samples is calculated in multiple object's property values
Value；
Step 5, according to the characteristic of division element and the corresponding threshold value of characteristic of division element of all kinds of terrain classification samples to target area
The optical remote sensing image figure in domain is classified, and the classification results of all kinds of atural objects are obtained；According to the classification results of all kinds of atural objects, obtain
Utilize the potential landslide areas for the target area that optical remote sensing image obtains；
Step 6, according to the classification results of the rate of deformation figure of target area and all kinds of atural objects, extract and obtain the potential landslide of leakage point
Object；The potential landslide areas of the potential landslide object of leakage point and the target area obtained using optical remote sensing image is closed
And the potential landslide areas of the target area of optical remote sensing image and InSAR rate of deformation information is merged.
2. taking the potential landslide automatic identifying method of optical remote sensing of InSAR deformation, feature into account as described in claim 1
It is, the step 4 specifically comprises the following steps:
Step 41 defines projection using rate of deformation figure of map projection's method to target area, obtains having projection information
Rate of deformation figure, and make the projected coordinate system of the optical remote sensing image figure of the rate of deformation figure with projection information and target area
It is unified to cause；Resampling is carried out to the rate of deformation figure with projection information using the method for cubic convolution, after obtaining resampling
Rate of deformation figure, and the resolution ratio of the optical remote sensing image figure of rate of deformation figure and target area after resampling is made to keep one
It causes；
Step 42, using the rate of deformation in the rate of deformation figure after resampling as a wave band data, using multi-scale division
Method is more to 4 wave bands in the optical remote sensing image figure of rate of deformation and target area in the rate of deformation figure after resampling
Spectroscopic data is integrally split, and obtains multiple objects, and the object refers to the pixel set with homogeney；
Step 43, respectively from the slope map of target area, massif echo, surface relief degree, ground elevation figure and target area
Optical remote sensing image figure in 4 wave band multispectral datas in acquire in each object form object all pixels slope
Angle value, ground elevation value, massif shading value, hypsography angle value and the multispectral value of 4 wave bands, and calculate separately to obtain each object
The average value of value of slope of all pixels of middle composition object, the average value of ground elevation value, massif shading value average value,
The average value of shape fluctuating angle value and the average value of the multispectral value of 4 wave bands；Each object is calculated separately by formula (4) (5)
NDVI value and NDWI value；
The average value of value of slope, the average value of ground elevation value, massif yin of all pixels of object will be formed in each object
The average value of shadow value, the average value of hypsography angle value, the average value of the multispectral value of 4 wave bands and each object NDVI value and
NDWI value obtains multiple object's property values as each object's property value；
In formula, NDVIiIndicate the normalized differential vegetation index of i-th of object, NDWIiIndicate that the normalization water body of i-th of object refers to
Number；ρi(NIR)、ρi(RED)、ρi(GREEN) near infrared band in the 4 wave band multispectral datas of i-th of object, red is respectively indicated
Reflectance value at wave band and green wave band, value range are [0,1], and i indicates that i-th of object, i are the natural number greater than 0；
Step 44 chooses terrain classification sample as basic unit using obtained multiple objects, and the terrain classification sample includes water
Body, vegetation, basement rock, bare area, artificial surface, deposit, shade sample；Using post-class processing algorithm to the terrain classification of selection
Sample and obtained multiple object's property values are calculated, and the characteristic of division element and classification of all kinds of terrain classification samples are obtained
The corresponding threshold value of characteristic element.
3. taking the potential landslide automatic identifying method of optical remote sensing of InSAR deformation, feature into account as described in claim 1
It is, the step 5 specifically:
By the corresponding threshold value composition and classification rule of the characteristic of division element and characteristic of division element of all kinds of atural objects, with classifying rules
Classify to the optical remote sensing image figure of target area, obtains the classification results of all kinds of atural objects；It rejects all kinds of in multiple objects
The classification results of atural object are utilized the potential landslide areas of the target area of optical remote sensing image acquisition.
4. taking the potential landslide automatic identifying method of optical remote sensing of InSAR deformation, feature into account as described in claim 1
It is, the step 6 specifically comprises the following steps:
The rate of deformation figure of target area and the classification results of all kinds of atural objects are overlapped by step 61, obtain target area
The rate of deformation of each pixel in optical remote sensing image figure；The average value of the rate of deformation of all pixels of composition object is calculated, it will
Rate of deformation of the obtained average value as object, obtains the rate of deformation of multiple objects；
Step 62, two threshold values m, n that rate of deformation is arranged, wherein m<0, n>0 are extracted all kinds ofly by the method for threshold classification
Object of rate of deformation k in the range of k≤m or k >=n in the classification results of object, the potential landslide object as leakage point；
The potential landslide areas of step 63, the potential landslide object that leakage is divided and the target area obtained using optical remote sensing image
It is merged using union, has been merged the potential of the target area of optical remote sensing image and InSAR rate of deformation information
Landslide areas.
5. taking the potential landslide automatic identifying method of optical remote sensing of InSAR deformation, feature into account as described in claim 1
It is, the step 1 is specific as follows:
To the SAR image that the SAR satellite in covering survey region collects, using the coherent point target analysis side in InSAR
Method handles SAR image, obtains the rate of deformation figure of survey region；One of them is doubtful in selection covering survey region
Landslide areas is target area, along the boundary of target area, cuts to the rate of deformation figure of survey region, obtains target area
The rate of deformation figure in domain.
6. taking the potential landslide automatic identifying method of optical remote sensing of InSAR deformation, feature into account as described in claim 1
It is, the step 2 specifically comprises the following steps:
Step 21, the optical remote sensing image data that coverage goal region is obtained by remote sensing satellite, the optical remote sensing image number
The 4 wave band multispectral datas for being 2.44m according to the panchromatic wave-band data and resolution ratio that are 0.61m including resolution ratio, the 4 wave band packet
Include red, green, blue and near infrared band；
Step 22, the dem data that target area is obtained by Space Shuttle Radar Topographic Mapping Mission system；Utilize optical remote sensing
The included RPC file of image data and RPC model shape obtain complete RPC model；Utilize dem data and complete RPC model
Ortho-rectification is carried out to panchromatic wave-band data and 4 wave band multispectral datas respectively, obtains including that panchromatic wave-band data and 4 wave bands are more
Spectroscopic data just penetrates optical remote sensing image, and the RPC refers to rational polynominal coefficient；
Step 23, using NNDiffuse Pan Sharpening algorithm to include panchromatic wave-band data and the multispectral number of 4 wave bands
According to optical remote sensing image of just penetrating merged, the optical remote sensing image merged；
Step 24 obtains target area vector boundary graph to target area range vector quantization；Along target area vector boundary graph
Boundary cuts the optical remote sensing image of fusion, obtains the optical remote sensing image figure of target area.
7. taking the potential landslide automatic identifying method of optical remote sensing of InSAR deformation, feature into account as described in claim 1
It is, the step 3 specifically comprises the following steps:
Step 31 defines projection to the dem data using map projection's method, obtains the dem data with projection information, makes
Dem data with projection information is consistent with the projection coordinate system of optical remote sensing image figure of target area；Using three secondary volumes
Long-pending method carries out resampling to the dem data with projection information, the dem data after obtaining resampling, after making resampling
The resolution ratio of dem data and the optical remote sensing image figure of target area is consistent；
Step 32, along the boundary of target area vector boundary graph, the dem data after resampling is cut, target area is obtained
The complete dem data in domain；According to the complete dem data in target area, the gradient of target area is calculated using formula (1)
Figure；Massif echo is obtained using formula (2)；Surface relief degree figure is obtained using formula (3)；Ground elevation value is DEM numerical value,
Obtain ground elevation figure；
Wherein, slope is the gradient, fxFor X-direction elevation change rate in the complete dem data in target area, fyIt is complete for target area
Y-direction elevation change rate in whole dem data；
Hillshade=255 × ((cos (zenithrad)×cos(sloperad))+(sin(zenithrad)×sin
(sloperad)×cos(azimuthrad-aspectrad))
Wherein, hillshade is massif shade, zenithradFor the sun zenith in the optical remote sensing image data of target area
The radian number at angle, sloperadFor gradient radian number in the complete dem data in target area, azimuthradFor the light of target area
Learn the radian number in the sunray direction in remote sensing image data, aspectradFor slope aspect in the complete dem data in target area
Radian number；
R=Hmax-Hmin, R > 0, Hmax, Hmin∈R (3)
Wherein, R is topographic relief amplitude, HmaxTo fix the highest elevation in analysis window in the complete dem data in target area,
HminTo fix the lowest elevation in analysis window described in the complete dem data in target area.
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| CN112307901A (en) * | 2020-09-28 | 2021-02-02 | 国网浙江省电力有限公司电力科学研究院 | Landslide detection-oriented SAR and optical image fusion method and system |
| CN112200362A (en) * | 2020-09-30 | 2021-01-08 | 杭州鲁尔物联科技有限公司 | Landslide prediction method, device, equipment and storage medium |
| CN112200362B (en) * | 2020-09-30 | 2024-03-29 | 杭州鲁尔物联科技有限公司 | Landslide prediction method, landslide prediction device, landslide prediction equipment and storage medium |
| CN112541665A (en) * | 2020-12-08 | 2021-03-23 | 鞍钢集团矿业有限公司 | Slope stability refined evaluation method based on multi-source information fusion |
| CN112364849A (en) * | 2021-01-13 | 2021-02-12 | 四川省安全科学技术研究院 | High-order landslide geological disaster intelligent identification method |
| CN112986981A (en) * | 2021-02-18 | 2021-06-18 | 中国科学院西北生态环境资源研究院 | Method and device for monitoring freezing and thawing deformation of earth surface in permafrost region and electronic equipment |
| CN112986981B (en) * | 2021-02-18 | 2022-06-10 | 中国科学院西北生态环境资源研究院 | Method and device for monitoring freezing and thawing deformation of earth surface in permafrost region and electronic equipment |
| CN113192086B (en) * | 2021-05-11 | 2022-01-28 | 中国自然资源航空物探遥感中心 | Generation method of geological disaster hidden danger deformation intensity distribution diagram and storage medium |
| CN113192086A (en) * | 2021-05-11 | 2021-07-30 | 中国自然资源航空物探遥感中心 | Generation method of geological disaster hidden danger deformation intensity distribution diagram and storage medium |
| CN113450456A (en) * | 2021-06-28 | 2021-09-28 | 中国水利水电科学研究院 | DEM (digital elevation model) manufacturing method with high identifiability |
| CN113450456B (en) * | 2021-06-28 | 2023-10-03 | 中国水利水电科学研究院 | DEM manufacturing method with high recognition degree |
| CN113591700A (en) * | 2021-07-30 | 2021-11-02 | 兰州大学 | Prediction method for potential landslide and river blockage |
| CN113920026A (en) * | 2021-09-30 | 2022-01-11 | 应急管理部国家自然灾害防治研究院 | Method for removing noise of regional landslide deformation detection result |
| CN116994156A (en) * | 2023-09-27 | 2023-11-03 | 自然资源部第三地理信息制图院 | Landslide hidden danger comprehensive remote sensing identification method, system, equipment and medium |
| CN116994156B (en) * | 2023-09-27 | 2023-12-08 | 自然资源部第三地理信息制图院 | Landslide hidden danger comprehensive remote sensing identification method, system, equipment and medium |
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