CN107180448A - A kind of mining area DEM change detecting methods based on earth's surface invariant features - Google Patents
A kind of mining area DEM change detecting methods based on earth's surface invariant features Download PDFInfo
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Abstract
The invention discloses a kind of mining area DEM change detecting methods based on earth's surface invariant features, pass through the similarity measurement to the features of terrain primitive such as point, line, surface, set up the earth's surface invariant features judgment rule for being adapted to mining area lineament, accurate reference information can not only be provided for DEM change detection, and can resolve and provide initially and basic parameter with adjustment for the foundation of the registering normal equations of DEM, then realize DEM change information resolving;Introduce mining area surface invariant features and set up the registration model for taking DEM topographic structures into account, earth's surface invariant features and the geometrical constraint of feature are used to build DEM registration models, landform geometrical feature can be both taken into account, registering accuracy can be improved again;It can be realized using features of terrain primitive similarity measurement method and earth's surface invariant features are judged with extraction synchronous with variation characteristic, be particularly suitable for use in changeable mining area with a varied topography.
Description
Technical field
It is specifically that one kind is applied to the crust deformation caused by mining activity the present invention relates to a kind of DEM change detecting methods
Change, the DEM change detecting methods based on earth's surface invariant features of destruction of surface critical regions, belong to mining area topographic survey and monitoring
Technical field.
Background technology
Digital elevation model (Digital Elevation Model) vehicle economy M, is by limited terrain elevation data
The digitized simulation (i.e. the digital expression of topographical surface form) to ground surface or terrain is realized, it is with one group of orderly array of values
Form represents a kind of actual ground model of ground elevation, and DEM is usually as the base for carrying out terrain analysis and related science research
Plinth data model.
Mining area surface is due to by exploitation disturbing influence, causing Ground Deformation disaster to take place frequently, topography variation is relative complex, so
And revision of topographic map is far unable to catch up with the pace of change on the spot of ground object target, carries out DEM changes using satellite remote-sensing image and detect, no
Existing cycle topographic survey can only be shortened, moreover it is possible to ensure that the disaster relief is taken precautions against natural calamities and kept the safety in production and the promptness of data is required.
Mining area DEM is to carry out the basic data that mining area surface deformation disaster monitoring is administered with environmental planning, is often used as height
Journey benchmark carries out ortho-rectification to image, but dem data and be changed the used image of detection generally can not while obtain,
If elevation information changes, the result for changing detection on two dimension is produced influence by it.
Existing landform three dimensional change uses D-InSAR or LiDAR methods mostly, and the former can realize high-precision deformation inspection
Survey, but difficult in the violent region phase unwrapping of hypsography, during high-resolution D-InSAR is implemented, often using outside DEM to subtract
Few phase unwrapping error and geocoding error;The latter's ground observation is limited in scope, and a wide range of airborne LiDAR observes current price
It is expensive, it is difficult to which that large area is implemented, and the DEM precision set up currently with high-resolution satellite image is also not enough to reach centimetre
Level, but No. three (ZY-3) satellite geometry positioning precisions of the resource of China's independent development can reach plane better than 2m, elevation is better than
3m positioning precision, higher than ASTER GDEM (the Advanced Spaceborne Thermal Emission being often used
And Reflection Radiometer Global Digital Elevation Model) and SRTM (Shuttle Radar
Topography Mission) data precision, therefore using periodicity satellite stereo image research DEM change, it is not only three
The strong supplement of dimension change detection, moreover it is possible to provide more accurate reference data for the research of other related sciences.
Traditional DEM changes detection is typically to be carried out asking poor acquisition according to the DEM before and after topography variation, first to DEM registrations, so
After be changed detection, do not account for influence of the topography variation to registration Algorithm, do not account for yet horizontal level change it is high to DEM
The influence of journey;Due to the difference such as acquiring way, imaging mode and time, orbit parameter, Image Matching, yardstick, DEM interpolation, no
Simultaneously alternate DEM registrations are not strict, cause DEM false change occur;In addition, physical relief is handed over artificial landform in mining area
Mistake, discontinuous terrain and gradual change landform symbiosis, with a varied topography changeable, the control point even laid also can be by exploitation disturbing influence
And change, influence DEM and change accuracy of detection.
DEM changes detection is inseparable with DEM registrations, and current method for registering is generally based on point feature registration, such as often
The nearest neighbor point algorithm (Iterative Closest Point, ICP) and innovatory algorithm used, with point, the similar consistency of line or
Person's line feature realizes that Aerial Image of Urban Area is registering with airborne laser radar point cloud;Also have and improved using the method for virtual controlling point
Traditional correlation coefficient matching method algorithm is used for automatic of the aviation image tie point that airborne LiDAR point cloud and POS data are aided in jointly
Match somebody with somebody;Or build building corner characteristics and the linear feature progress on image using the three-dimensional contour line of building in cloud data
Registration realizes that LiDAR point cloud is registering with aviation image, but existing registration is mostly based on the global registration of least square, not
Have and consider influence of the change information to registration accuracy under the conditions of different phases.
The content of the invention
In view of the above-mentioned problems, the present invention provides a kind of mining area DEM change detecting methods based on earth's surface invariant features, pass through
To the similarity measurement of the features of terrain primitive such as point, line, surface, the earth's surface invariant features judgement rule for being adapted to mining area lineament are set up
Then, can not only provide accurate reference information for DEM change detection, and can for the registering normal equations of DEM foundation with putting down
Difference, which is resolved, to be provided initially and basic parameter, then realizes that DEM change information is resolved.
To achieve the above object, this mining area DEM change detecting method based on earth's surface invariant features specifically includes following step
Suddenly:
A. mining area position is chosen, mining area topography and geomorphology feature, geological mining, exploitation, existing DEM region of variation is collected
Information;
B. the mining area dem data modeling based on the constant GCP features of earth's surface;
Generate with changing detection demand, obtained according to the moonscope time in correspondence mining area first against mining area landform DEM
The stereoscopic image data of two different phases of Ti and Tj, is created as geometrical model;
Secondly on the basis of analysis mining area lineament, ground control point is laid at the position for having obvious terrestrial reference thing, and
Invariant features judgement is carried out to GCP;
Finally according to imaging geometry model and constant GCP, using block adjustment technology to forward sight, face, rearview picture
Carry out RPC models to refine, obtain a wide range of interior basic geological study DEM in mining area;
C. the edge detection method in the method and image procossing extracted using digital Terrain Analysis mesorelief form is extracted
Point, line, surface feature primitive in step b in two different phase DEM landform;
D. similarity measurement is carried out to the features of terrain primitive of two phases in step c, built by Hierarchy Analysis Method
The geometric properties measurement model of the features of terrain primitive extracted in step c, carries out features of terrain primitive similarity measurement, and according to this
Earth's surface invariant features judgment rule is set up, variation characteristic and invariant features are extracted;
E. the earth's surface invariant features determined according to step d, build between different phase DEM registration model and carry out adjustment solution
Calculate, with reference to the variation characteristic extracted in step d, obtain DEM changes;
F., DEM after registration and benchmark DEM are directly asked to the DEM change informations of the difference acquisition phase, the DEM change informations
Together with the variation characteristic extracted in step d, DEM change informations in the mining area are collectively formed.
The method for carrying out invariant features judgement in scheme as a further improvement on the present invention, described step b to GCP has
Body comprises the following steps:
Image space coordinates of each GCP on two phase images is extracted first;
Next extracts and calculates GCP plane coordinates, height value, the gradient and curvature parameters corresponding on two phase DEM;
The difference of two period parameters is finally calculated respectively, if difference is within set threshold range, the GCP is constant
GCP。
Scheme as a further improvement on the present invention, described step d specifically includes following steps:
1. two phase dem datas are carried out with the consistent resampling of yardstick according to identical spatial resolution yardstick, utilizes arest neighbors
Point algorithm realizes the initial matching of two phase DEM features of terrain primitives;
2. similarity measurement is carried out to the geometric properties of the features of terrain primitive in scope using local window searching method,
Set up point feature similarity S1, line characteristic similarity S2 and region feature similarity S3;
3. the similarity S of feature of the same name is calculated;
4. the matching to features of terrain is realized by way of similarity maximum is chosen and combined with threshold decision.
Scheme as a further improvement on the present invention, the similarity of described step 2. middle point, line, surface features of terrain primitive
Index component includes elevation, horizontal level, curvature, the gradient, length, flexibility, area, boundary length, boundary shape.
Scheme as a further improvement on the present invention, the specific method of described step 3. includes:
Assuming that feature l has n to compare characteristic component l=[l1...ln], then phase of any one feature on two phase DEM
It is like degree
Wherein, li(i=1 ..., n), li' (i=1 ..., n) be respectively corresponding i-th characteristic value on two phase DEM, then
The similarity of this feature is
Wherein, piFor correspondence S (li) weights.
Scheme as a further improvement on the present invention, 4. specific method includes described step:
It is [0,1] according to similarity S result of calculations scope, 1 representative does not change, 0 represents maximum change, then sets earth's surface
The span of invariant features is [δS, 1], δSFor similarity threshold,
Scheme as a further improvement on the present invention, described step e specific methods include:
Assuming that (x0,y0,z0)T(x, y, z)TFor the point on the two DEM invariant features subject to registration of areal, using area
Translation rotation zoom model, builds equation in the net of domain,
(x,y,z)T=T+sR (x0,y0,z0)T
In formula, s is zoom factor, R be coefficient of rotary (ω, κ), T is translation coefficient (tx, ty, tz)T;
The observational equation of m invariant features point is set up after Taylor series expansion linearisation,
- e=AX-l, P
In formula, A is coefficient pin, and X is registration parameter to be solved, and P is power battle array, and l is residual vector.Joint linear feature and face are special
Levy constraint observational equation:
Consider in the case of sane resolve, utilize the parameter to be solved in interative least square method Combined Calculation formula.
Compared with prior art, this mining area DEM change detecting method based on earth's surface invariant features passes through to point, line, surface
Etc. the similarity measurement of features of terrain primitive, the earth's surface invariant features judgment rule for being adapted to mining area lineament is set up, can not only
Change detection enough for DEM provides accurate reference information, and can be resolved for the foundation structure of the registering normal equations of DEM with adjustment
There is provided initially and basic parameter, then realize that DEM change information is resolved;This mining area DEM change based on earth's surface invariant features
Detection method introduces mining area surface invariant features and sets up the registration model for taking DEM topographic structures into account, by earth's surface invariant features and spy
The geometrical constraint levied is used to build DEM registration models, can both take landform geometrical feature into account, registering accuracy can be improved again;
This mining area DEM change detecting method based on earth's surface invariant features can be realized pair using features of terrain primitive similarity measurement method
Earth's surface invariant features judge extraction synchronous with variation characteristic, are particularly suitable for use in changeable mining area with a varied topography.
Brief description of the drawings
Fig. 1 is DEM change detection process process schematic of the present invention based on earth's surface invariant features;
Fig. 2 is the mining area dem data modeling procedure figure of the constant GCP features of earth's surface of the present invention;
Fig. 3 is the similarity measurement process schematic of features of terrain primitive of the present invention.
Embodiment
For different phase DEM, it is necessary to which all kinds of characteristic elements used in ensureing registration are constant, the present invention
By the similarity measurement to the features of terrain primitive such as point, line, surface, the earth's surface invariant features for setting up suitable mining area lineament are sentenced
Disconnected rule, can not only provide accurate reference information, and can be the foundation of the registering normal equations of DEM for DEM change detection
Resolve and provided initially and basic parameter with adjustment, then realize that DEM change information is resolved.
The present invention will be further described below in conjunction with the accompanying drawings.
The present invention is when carrying out mining area DEM change detections, in advance according to the existing image in mining area or dem data, it is determined that simultaneously
Earth's surface invariant features are extracted, then according to the parameter of invariant features, alternate DEM registration models when setting up different obtain DEM and become
Change.
As shown in figure 1, this mining area DEM change detecting method based on earth's surface invariant features specifically includes following steps:
A. mining area position is chosen, mining area topography and geomorphology feature, geological mining, exploitation, existing DEM region of variation is collected
Information.
B. the mining area dem data modeling based on the constant GCP features of earth's surface;
Generate with changing detection demand, obtained according to the moonscope time in correspondence mining area first against mining area landform DEM
The stereoscopic image data of two different phases of Ti and Tj, is created as geometrical model;
Secondly on the basis of analysis mining area lineament, ground control point is laid at the position for having obvious terrestrial reference thing, is
Avoid GCP from shift in position occurred by exploitation disturbing influence, invariant features judgement is carried out to GCP, determination methods are as follows:First
Extract image space coordinates of each GCP on two phase images;Next extracts and calculates GCP planes corresponding on two phase DEM and sits
Mark, height value, the gradient and curvature parameters;The difference of two period parameters is finally calculated respectively, if difference is in set threshold range
Within, then the GCP is constant GCP;
Finally according to imaging geometry model and constant GCP, using block adjustment technology to forward sight, face, rearview picture
Carry out RPC models to refine, as shown in Fig. 2 obtaining a wide range of interior basic geological study DEM in mining area.
C. the edge detection method in the method and image procossing extracted using digital Terrain Analysis mesorelief form is extracted
Point, line, surface feature primitive in step b in two different phase DEM landform.
D. similarity measurement is carried out to the features of terrain primitive in step c, by being carried in Hierarchy Analysis Method construction step c
The geometric properties measurement model of the features of terrain primitive taken, carries out features of terrain primitive similarity measurement, and set up earth's surface according to this
Invariant features judgment rule, extracts variation characteristic and invariant features, concretely comprises the following steps:
1. two phase dem datas are carried out with the consistent resampling of yardstick according to identical spatial resolution yardstick, utilizes arest neighbors
Point algorithm (Iterative Closest Point, ICP) realizes the initial matching of two phase DEM features of terrain primitives;
2. similarity measurement is carried out to the geometric properties of the features of terrain primitive in scope using local window searching method,
Point feature similarity S1, line characteristic similarity S2 and region feature similarity S3 are set up, as shown in figure 3, point, line, surface features of terrain
The index of similarity component of primitive includes elevation, horizontal level, curvature, the gradient, length, flexibility, area, boundary length, side
Boundary's shape etc.;
3. the similarity S of feature of the same name is calculated, specific method includes:
Assuming that feature l has n to compare characteristic component l=[l1...ln], then phase of any one feature on two phase DEM
It is like degree
Wherein, li(i=1 ..., n), li' (i=1 ..., n) be respectively corresponding i-th feature on two phase DEM, then should
The similarity of feature is
Wherein, piFor correspondence S (li) weights;
4. the matching to features of terrain is realized by way of similarity maximum is chosen and combined with threshold decision, according to phase
It is [0,1] like degree S result of calculations scope, 1 representative does not change, 0 represents maximum change, then sets the value of earth's surface invariant features
Scope is [δS, 1], δSFor similarity threshold,
E. the earth's surface invariant features determined according to step d, build between different phase DEM registration model and carry out adjustment solution
Calculate, with reference to the variation characteristic extracted in step d, obtain DEM changes, specific method includes:
Assuming that (x0,y0,z0)T(x, y, z)TFor the point on the two DEM invariant features subject to registration of areal, using area
Translation rotation zoom model, builds equation in the net of domain,
(x,y,z)T=T+sR (x0,y0,z0)T
In formula, s is zoom factor, R be coefficient of rotary (ω, κ), T is translation coefficient (tx, ty, tz)T;
The observational equation of m invariant features point is set up after Taylor series expansion linearisation,
- e=AX-l, P
In formula, A is coefficient pin, and X is registration parameter to be solved, and P is power battle array, and l is residual vector.Joint linear feature and face are special
Levy constraint observational equation:
Consider in the case of sane resolve, utilize the parameter to be solved in interative least square method Combined Calculation formula.
F., DEM after registration and benchmark DEM are directly asked to the DEM change informations of the difference acquisition phase, the DEM change informations
Together with the variation characteristic extracted in step d, DEM change informations in the mining area are collectively formed.
This mining area DEM change detecting method based on earth's surface invariant features based on multi_temporal images DEM mining area application,
In the case of mining area surface disturbance frequently, mining area surface invariant features are introduced, the DEM registrations based on earth's surface invariant features are set up
With the technical scheme of change detection, analyzed by the extraction and similarity measurement of the features of terrain primitive such as mining area point, line, surface, more
Plus mining area DEM change time space distributions are disclosed exactly, provide new thinking and method for the fusion of mining area multi-source terrain data.
Claims (7)
1. a kind of mining area DEM change detecting methods based on earth's surface invariant features, it is characterised in that specifically include following steps:
A. mining area position is chosen, mining area topography and geomorphology feature, geological mining, exploitation, existing DEM region of variation letter is collected
Breath;
B. the mining area dem data modeling based on the constant GCP features of earth's surface;
First against mining area landform DEM generate with change detection demand, according to the moonscope time obtain correspondence mining area in Ti and
The stereoscopic image data of the different phases of Tj two, is created as geometrical model;
Secondly on the basis of analysis mining area lineament, ground control point is laid at the position for having obvious terrestrial reference thing, and to GCP
Carry out invariant features judgement;
Finally according to imaging geometry model and constant GCP, using block adjustment technology to forward sight, face, rearview picture is carried out
RPC models are refined, and obtain a wide range of interior basic geological study DEM in mining area;
C. the edge detection method extraction step b in the method and image procossing of digital Terrain Analysis mesorelief form extraction is utilized
In point, line, surface feature primitive in two different phase DEM landform;
D. similarity measurement is carried out to the features of terrain primitive of two phases in step c, passes through Hierarchy Analysis Method construction step c
The geometric properties measurement model of the features of terrain primitive of middle extraction, carries out features of terrain primitive similarity measurement, and set up according to this
Earth's surface invariant features judgment rule, extracts variation characteristic and invariant features;
E. the earth's surface invariant features determined according to step d, build between different phase DEM registration model and carry out adjustment resolving, tie
The variation characteristic extracted in step d is closed, DEM changes are obtained;
F. difference is directly asked to obtain the DEM change informations of the phase DEM after registration and benchmark DEM, the DEM change informations are with walking
The variation characteristic extracted in rapid d together, collectively forms DEM change informations in the mining area.
2. the mining area DEM change detecting methods according to claim 1 based on earth's surface invariant features, it is characterised in that institute
Following steps are specifically included to the GCP methods for carrying out invariant features judgement in the step b stated:
Image space coordinates of each GCP on two phase images is extracted first;
Next extracts and calculates GCP plane coordinates, height value, the gradient and curvature parameters corresponding on two phase DEM;
The difference of two period parameters is finally calculated respectively, if difference is within set threshold range, the GCP is constant GCP.
3. the mining area DEM change detecting methods according to claim 1 based on earth's surface invariant features, it is characterised in that institute
The step d stated specifically includes following steps:
1. two phase dem datas are carried out with the consistent resampling of yardstick according to identical spatial resolution yardstick, is counted using arest neighbors
Method realizes the initial matching of two phase DEM features of terrain primitives;
2. similarity measurement is carried out to the geometric properties of the features of terrain primitive in scope using local window searching method, set up
Point feature similarity S1, line characteristic similarity S2 and region feature similarity S3;
3. the similarity S of feature of the same name is calculated;
4. the matching to features of terrain is realized by way of similarity maximum is chosen and combined with threshold decision.
4. the mining area DEM change detecting methods according to claim 3 based on earth's surface invariant features, it is characterised in that institute
The step of stating 2. middle point, line, surface features of terrain primitive index of similarity component include elevation, horizontal level, curvature, the gradient,
Length, flexibility, area, boundary length, boundary shape.
5. the mining area DEM change detecting methods according to claim 3 based on earth's surface invariant features, it is characterised in that institute
The specific method of the step of stating 3. includes:
Assuming that feature l has n to compare characteristic component l=[l1 ... ln], then any one feature is similar on two phase DEM
Spend and be
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Wherein, li(i=1 ..., n), li' (i=1 ..., n) is respectively corresponding i-th characteristic value on two phase DEM, then the spy
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6. the mining area DEM change detecting methods according to claim 3 based on earth's surface invariant features, it is characterised in that institute
4. specific method includes the step of stating:
It is [0,1] according to similarity S result of calculations scope, 1 representative does not change, 0 represents maximum change, then sets earth's surface constant
The span of feature is [δS, 1], δSFor similarity threshold,
7. the mining area DEM change detecting methods according to claim 1 based on earth's surface invariant features, it is characterised in that institute
The step e specific methods stated include:
Assuming that (x0,y0,z0)T(x, y, z)TFor the point on the two DEM invariant features subject to registration of areal, using regional network
Interior translation rotation zoom model, builds equation,
(x,y,z)T=T+sR (x0,y0,z0)T
In formula, s is zoom factor, and R is coefficient of rotaryT is translation coefficient (tx, ty, tz)T;
The observational equation of m invariant features point is set up after Taylor series expansion linearisation,
- e=AX-l, P
In formula, A is coefficient pin, and X is registration parameter to be solved, and P is power battle array, and l is residual vector.Joint linear feature and region feature are about
Beam observational equation:
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Consider in the case of sane resolve, utilize the parameter to be solved in interative least square method Combined Calculation formula.
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CN108446637A (en) * | 2018-03-21 | 2018-08-24 | 合肥工业大学 | SAR image change detection based on three-dimensional graph model |
CN108921174A (en) * | 2018-06-04 | 2018-11-30 | 中国矿业大学 | Based on the big gradient deformation extracting method in mining area under the constraint of multistage match window |
CN109785318A (en) * | 2019-01-25 | 2019-05-21 | 南京泛在地理信息产业研究院有限公司 | Method for detecting change of remote sensing image based on upper thread primitive interconnection constraint |
CN111856459A (en) * | 2020-06-18 | 2020-10-30 | 同济大学 | Improved DEM maximum likelihood constraint multi-baseline InSAR phase unwrapping method |
CN115031674A (en) * | 2022-04-28 | 2022-09-09 | 四川大学 | Method for monitoring surface deformation under complex terrain |
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CN111856459A (en) * | 2020-06-18 | 2020-10-30 | 同济大学 | Improved DEM maximum likelihood constraint multi-baseline InSAR phase unwrapping method |
CN111856459B (en) * | 2020-06-18 | 2022-07-05 | 同济大学 | Improved DEM maximum likelihood constraint multi-baseline InSAR phase unwrapping method |
CN115031674A (en) * | 2022-04-28 | 2022-09-09 | 四川大学 | Method for monitoring surface deformation under complex terrain |
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