CN113420717A - Three-dimensional monitoring method, device and equipment for ice and snow changes and readable storage medium - Google Patents
Three-dimensional monitoring method, device and equipment for ice and snow changes and readable storage medium Download PDFInfo
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- CN113420717A CN113420717A CN202110809008.2A CN202110809008A CN113420717A CN 113420717 A CN113420717 A CN 113420717A CN 202110809008 A CN202110809008 A CN 202110809008A CN 113420717 A CN113420717 A CN 113420717A
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Abstract
The invention discloses a method, a device and equipment for three-dimensional monitoring of ice and snow changes and a readable storage medium, wherein the method comprises the following steps: acquiring a multi-temporal satellite stereoscopic image; extracting an ice and snow DEM from the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase; cutting the ice and snow DEM of each time phase to obtain the ice and snow DEM of each time phase with the same area range; correcting the satellite stereoscopic image of each corresponding time phase by using the ice and snow DEM of each time phase, and cutting the corrected satellite stereoscopic image of each time phase to obtain the satellite stereoscopic image of each time phase with the consistent area range; constructing an irregular grid DEM based on the ice and snow DEM of each time phase with consistent area range; calculating the ice and snow lifting variation of adjacent time phases according to the irregular grid DEM; and calculating to obtain the ice and snow coverage area variation according to the satellite stereoscopic images of each time phase with the consistent region range by adopting a support vector machine classification method. The invention can realize three-dimensional monitoring of ice and snow coverage change.
Description
Technical Field
The invention belongs to the technical field of stereoscopic image identification, and particularly relates to a method, a device and equipment for stereoscopic monitoring of ice and snow changes and a readable storage medium.
Background
Ice and snow are one of the most active natural factors on the earth surface, and three quarters of fresh water resources on the earth exist in the form of ice and snow. The northern hemisphere is 4600 km in winter each year2The land is covered with seasonal ice and snow. Ice and snow have high albedo and low thermal conductivity characteristics, which strongly influence the ground surface energy and radiation balance, and thus the ground-gas interaction, and are therefore important parameters in weather forecasting and climate patterns.
Monitoring of ice and snow coverage changes by using stereoscopic images is always a very concerned and difficult task to do in the photogrammetry community. In the past decades, there have been many studies on the extraction of ice and snow information and the monitoring of ice and snow using remote sensing images, but at present, there are few studies on the monitoring of the amount of change in ice and snow coverage area and the amount of change in ice and snow elevation using stereoscopic images. The published patent application No. CN201610304072.4 discloses an SAR image ice and snow coverage information extraction method based on an InSAR technology, a plurality of single-view complex SAR images without ice and snow information are preprocessed, registered and baseline estimated, the single-view complex SAR images containing the ice and snow information are subjected to radiometric calibration to obtain a backscattering coefficient map, two interference groups are respectively selected according to the lengths of a time baseline and a space baseline in the SAR image baseline information, the coherence coefficients of two images in each interference group are respectively calculated through a coherence coefficient formula to obtain a coherence coefficient map, and finally, threshold values are set for the two coherence coefficient maps and the backscattering coefficient map containing the SAR image containing the ice and snow information to realize the extraction of the ice and snow coverage information. However, there is no monitoring of ice and snow cover changes, and thus the field is open.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a three-dimensional monitoring method, a device, equipment and a readable storage medium for ice and snow changes, which can realize monitoring of ice and snow coverage changes.
In order to solve the technical problems, the invention is realized by the following technical scheme:
a three-dimensional monitoring method for ice and snow change comprises the following steps:
acquiring a multi-temporal satellite stereoscopic image;
extracting an ice and snow DEM from the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase;
cutting the ice and snow DEM of each time phase to obtain the ice and snow DEM of each time phase with the same area range;
correcting the satellite stereoscopic image of each corresponding time phase by using the ice and snow DEM of each time phase, and cutting the corrected satellite stereoscopic image of each time phase to obtain the satellite stereoscopic image of each time phase with the consistent area range; after cutting, the ice and snow DEM of each time phase is consistent with the area range of the satellite stereoscopic image of each time phase;
constructing an irregular grid DEM based on the ice and snow DEM of each time phase with consistent area range;
calculating the ice and snow lifting variation of adjacent time phases according to the irregular grid DEM;
and calculating to obtain the ice and snow coverage area variation according to the satellite stereoscopic images of each time phase with the consistent region range by adopting a support vector machine classification method.
Further, the acquisition criteria of the multi-temporal satellite stereoscopic image are as follows:
selecting a cloud-free or few-cloud covered image, wherein the ice and snow part is covered without clouds, and the cloud amount of the image is less than 2%;
the image has no missing, noise and abnormal pixels;
and the image has no obvious aerosol coverage;
and no rainfall is present before and after the imaging date of the image.
Further, the method for extracting the ice and snow DEM of the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase includes:
and extracting the ice and snow DEM of the satellite stereoscopic image of each time phase by adopting a DEM extraction functional module in ENVI software in the remote sensing image processing platform to obtain the ice and snow DEM of each time phase.
Further, the irregular grid DEM is constructed based on the ice and snow DEM of each time phase with the consistent region range, and the method specifically comprises the following steps:
selecting sampling points on the ice and snow DEM of each time phase with the consistent area range, wherein the sampling points are required to be uniformly distributed on the ice and snow DEM;
and establishing an irregular triangulation network model according to the selected sampling points, and selecting a linear interpolation algorithm based on Delaunay triangulation on the irregular triangulation network model to perform elevation interpolation to complete the construction of the irregular grid DEM.
Further, the ice and snow lifting variation of adjacent time phases is calculated according to the irregular grid DEM, and the following calculation formula is specifically adopted:
wherein Δ V is the amount of change in the ascending and descending of ice and snow in adjacent time phases; d is the grid interval; Δ HijCorresponding to the height difference on the i, j grid.
Further, the satellite stereo images of each time phase with the consistent region range are calculated by using a support vector machine classification method to obtain the ice and snow coverage area variation, which is specifically as follows:
interpreting a satellite stereoscopic image by visual observation, and defining a training sample on the interpreted satellite stereoscopic image, wherein the training sample comprises ice and snow and non-ice and snow;
adopting a remote sensing image processing platform, executing a support vector machine classification method, loading an ice and snow satellite stereoscopic image, inputting the training sample, setting parameters, and outputting a classification result, wherein the classification result comprises an ice and snow covered area and a non-ice and snow covered area;
obtaining an ice and snow covered area according to the classification result, wherein the amount of change of the ice and snow covered area
The method is obtained by the ice and snow coverage area difference of adjacent time phases, and the formula is as follows:
in the formula, S1 represents the ice and snow covered area before the ice and snow covering change, and S2 represents the ice and snow covered area after the ice and snow covering change.
A three-dimensional monitoring device for ice and snow changes comprises:
the acquisition module is used for acquiring a satellite stereoscopic image with multiple time phases;
the extraction module is used for extracting the ice and snow DEM of the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase;
the first cutting module is used for cutting the ice and snow DEM of each time phase to obtain the ice and snow DEM of each time phase with the same area range;
the second cutting module is used for correcting the satellite stereoscopic image of each corresponding time phase by using the ice and snow DEM of each time phase, and cutting the corrected satellite stereoscopic image of each time phase to obtain satellite stereoscopic images of each time phase with consistent area ranges; after cutting, the ice and snow DEM of each time phase is consistent with the area range of the satellite stereoscopic image of each time phase;
the building module is used for building an irregular grid DEM based on the ice and snow DEM of each time phase with consistent area range;
the first calculation module is used for calculating the ice and snow lifting variation of adjacent time phases according to the irregular grid DEM;
and the second calculation module is used for calculating the variation of the ice and snow coverage area by adopting a support vector machine classification method according to the satellite stereoscopic images of each time phase with the consistent region range.
Further, the building module comprises:
the sampling point selecting unit is used for selecting sampling points on the ice and snow DEM of each time phase with the consistent area range, and the sampling points are required to be uniformly distributed on the ice and snow DEM;
and the irregular grid DEM construction unit is used for establishing an irregular triangulation network model according to the selected sampling points, selecting a linear interpolation algorithm based on Delaunay triangulation on the irregular triangulation network model for performing elevation interpolation, and completing construction of the irregular grid DEM.
An apparatus comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the stereoscopic ice and snow monitoring method when executing the computer program.
A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of a method for stereoscopic monitoring of ice and snow variations.
Compared with the prior art, the invention has at least the following beneficial effects: the invention relates to a three-dimensional monitoring method for ice and snow changes, which comprises the steps of obtaining satellite three-dimensional images of multiple time phases; extracting an ice and snow DEM from the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase; cutting the ice and snow DEM of each time phase to obtain the ice and snow DEM of each time phase with the same area range; correcting the satellite stereoscopic image of each corresponding time phase by using the ice and snow DEM of each time phase, and cutting the corrected satellite stereoscopic image of each time phase to obtain the satellite stereoscopic image of each time phase with the consistent area range; after cutting, the ice and snow DEM of each time phase is consistent with the area range of the satellite stereoscopic image of each time phase; constructing an irregular grid DEM based on the ice and snow DEM of each time phase with consistent area range; calculating the ice and snow lifting variation of adjacent time phases according to the irregular grid DEM; and calculating to obtain the ice and snow coverage area variation according to the satellite stereoscopic images of each time phase with the consistent region range by adopting a support vector machine classification method. Therefore, the method for solving the ice and snow variation based on the ice and snow DEM at the same time phase is realized by using the satellite stereo image to extract the ice and snow DEM, the ice and snow variation is obtained by using the elevation difference value of the ice and snow DEM, and the ice and snow coverage area variation is obtained by using a support vector machine classification method aiming at the satellite stereo image. Through satellite stereoscopic image three-dimensional observation ice and snow cover area variation and ice and snow lift variation, can realize the monitoring to ice and snow cover change, it is also more convenient and effective to use the ice and snow DEM of different time phases to obtain ice and snow lift variation, can provide the data basis for the estimation of high mountain area intensification range in basin.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a three-dimensional monitoring method for ice and snow changes according to an embodiment of the present invention;
fig. 2 is a diagram illustrating a DEM result of extracting ice and snow before ice and snow coverage change in a three-dimensional ice and snow change monitoring method according to an embodiment of the present invention;
fig. 3 is a diagram illustrating a DEM result of extracting ice and snow after ice and snow coverage change in a three-dimensional ice and snow change monitoring method according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As a specific embodiment of the present invention, as shown in fig. 1, a stereoscopic monitoring method for ice and snow change is implemented based on a satellite stereoscopic image, and includes the following steps:
step 1: and acquiring multi-temporal satellite stereoscopic images.
In a preferred embodiment, the acquisition criteria of the satellite stereoscopic images in multiple phases are:
selecting a cloud-free or few-cloud covered image, wherein the ice and snow part is covered without clouds, and the cloud amount of the image is less than 2%;
the image has no missing, noise and abnormal pixels;
and the image has no obvious aerosol coverage;
and no rainfall is present before and after the imaging date of the image.
Step 2: and extracting the ice and snow DEM of the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase.
As a preferred embodiment, a DEM extraction function module in the ENVI software in the remote sensing image processing platform is specifically adopted to extract the ice and snow DEM of the satellite stereoscopic image of each time phase, so as to obtain the ice and snow DEM of each time phase.
More specifically, in this embodiment, with the help of the ENVI software in the remote sensing image processing platform, according to default settings, a small amount of manual adjustment is added to complete the ice and snow DEM extraction, which is specifically as follows:
calling the satellite stereo image into a stereo pair according to left and right images, and calling RPC parameters;
defining a ground control point by combining the image area characteristics, and then defining a connection point; preferably, in one embodiment, the following method is adopted for the image with large ice and snow coverage: because the ice and snow covered area always has naked big stones, the naked stones can be used as ground control points; when a satellite stereoscopic image in a research area selects a connection point, the parallax of the Y direction is required to be less than 2 pixels, so that the parallax of the connection point in the Y direction is as small as possible, and the problem that the matching of the same-name points is difficult is solved;
and according to the connecting point, setting a epipolar line image, setting an ice and snow DEM output projection parameter, finally setting a generated ice and snow DEM parameter, and outputting the ice and snow DEM. FIG. 2 is a DEM result diagram for extracting ice and snow before the ice and snow cover change; fig. 3 is a DEM result diagram of the extracted ice and snow after the ice and snow coverage change.
In this embodiment, when generating the ice and snow DEM, experience obtained by an experiment is as follows: the size of the moving window is 13 × 13, the terrain detail is Level 5, the Y research area is a mountain area, and the terrain and landform are High.
And step 3: cutting the ice and snow DEM of each time phase to obtain the ice and snow DEM of each time phase with the consistent area range, which is concretely as follows:
firstly, manually drawing an interesting region of the ice and snow DEM of the previous time phase and cutting the interesting region to obtain a cut DEM file, wherein the drawn interesting region is stored as an ROI format file;
and cutting the ice and snow DEM of the rear time phase by using the region of interest drawn in the front to obtain the ice and snow DEM of each time phase with the same region range.
And 4, step 4: correcting the satellite stereoscopic image of each corresponding time phase by using the ice and snow DEM of each time phase, and cutting the corrected satellite stereoscopic image of each time phase to obtain the satellite stereoscopic image of each time phase with the consistent area range; after cutting, the ice and snow DEM of each time phase is consistent with the area range of the satellite stereoscopic image of each time phase;
specifically, the corrected satellite stereoscopic image of each time phase is clipped to obtain satellite stereoscopic images of each time phase with the same area range, which is specifically as follows:
and converting the region of interest drawn in the front into a vector format EVF from an ROI format, and then respectively cutting the corrected satellite stereoscopic image of each time phase by using vector data to obtain the satellite stereoscopic image of each time phase with consistent region range.
And 5: and constructing the irregular grid DEM based on the ice and snow DEM of each time phase with the consistent area range.
As a preferred embodiment, the irregular grid DEM is constructed based on the ice and snow DEM of each time phase with the consistent area range, and the specific steps are as follows:
sampling points are selected from the ice and snow DEM of each time phase with the consistent area range, and the sampling points are required to be uniformly distributed on the ice and snow DEM; preferably, selecting sampling points in a manual selection mode;
establishing an Irregular triangular net model (triangular Irregular net) according to the selected sampling points, specifically, connecting sampling point data into triangles which cover the whole research area and are not overlapped according to a certain rule, selecting a linear interpolation algorithm based on Delaunay triangulation on the Irregular triangular net model to perform elevation interpolation, and completing the construction of the DEM of the Irregular grid.
Step 6: and calculating the ice and snow lifting variation of adjacent time phases according to the irregular grid DEM.
As a preferred embodiment, the amount of change in the ice and snow lifting in the adjacent time phase is calculated by using the following calculation formula:
wherein Δ V is the amount of change in the ascending and descending of ice and snow in adjacent time phases; d is the grid interval; Δ HijCorresponding to the height difference on the i, j grid.
That is to say, the IDL language in the ENVI software in the remote sensing image processing platform is adopted to read the ice and snow DEM file of each time phase respectively, the ice and snow DEM grid points are read, the grid elevation difference value is obtained, the elevation difference value is multiplied by the area value corresponding to each grid, and then the volume changes on all the grids are accumulated, so that the ice and snow variation of the two time phases can be obtained.
And 7: and calculating to obtain the ice and snow coverage area variation according to the satellite stereoscopic images of each time phase with the consistent region range by adopting a support vector machine classification method.
In a preferred embodiment, the amount of change in the ice and snow coverage area is calculated from the satellite stereoscopic images in multiple time phases by using a support vector machine classification method, which is specifically as follows:
interpreting a satellite stereoscopic image by visual observation, and defining a training sample on the interpreted satellite stereoscopic image, wherein the training sample comprises ice and snow and non-ice and snow; preferably, after the training samples are defined, the training samples are manually selected and evaluated, the training samples are guaranteed to be qualified samples, whether the training samples are qualified samples or not is judged by calculating the separability of the ROI, namely, the statistical distance between ice and snow and non-ice and snow is calculated, and the distance is used for determining the difference degree between the two categories. Mainly calculating a Jeffries-Matusita distance and a Transformed diversity, wherein the values of the Jeffries-Matusita distance and the Transformed diversity are 0-2.0, and the values of the Jeffries-Matusita distance and the Transformed diversity are greater than 1.9, so that the separability between samples is good, and the samples belong to qualified samples; less than 1.8, requiring a re-selection of samples; less than 1, the two types of samples are considered to be combined into one type of sample. In the example, by calculating the separability of the ROI, the values of the two parameters are both greater than 1.9, and the samples belong to qualified samples;
adopting a remote sensing image processing platform, executing a support vector machine classification method, loading an ice and snow satellite stereoscopic image, inputting a training sample and setting parameters, and outputting a classification result, wherein the classification result comprises an ice and snow covered area and a non-ice and snow covered area; preferably, a confusion matrix-based method is adopted to evaluate the classification result and output a confusion matrix report, wherein the confusion matrix report comprises the elements of overall classification precision, Kappa coefficient, misclassification error, omission error, drawing precision and user precision. After the support vector machine classification method is adopted in the embodiment, the overall classification precision and the Kappa coefficient of the classification result reach more than 90%, the misclassification error and the misclassification error are lower than 3%, and the drawing precision and the user precision reach 90%; more preferably, the parts extracted by mistake or missed are manually identified and processed, so that the accuracy of the classification result is ensured;
obtaining the covered area of ice and snow and the variation of the covered area of ice and snow according to the classification result
The method is obtained by the ice and snow coverage area difference of adjacent time phases, and the formula is as follows:
in the formula, S1 represents the ice and snow covered area before the ice and snow covering change, and S2 represents the ice and snow covered area after the ice and snow covering change.
As a specific embodiment of the present invention, there is provided an ice and snow change stereoscopic monitoring device for implementing the ice and snow change stereoscopic monitoring method based on satellite stereoscopic images, including:
the acquisition module is used for acquiring a satellite stereoscopic image with multiple time phases;
and the extraction module is used for extracting the ice and snow DEM from the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase.
The first cutting module is used for cutting the ice and snow DEM of each time phase to obtain the ice and snow DEM of each time phase with the same area range;
the second cutting module is used for correcting the satellite stereoscopic image of each corresponding time phase by using the ice and snow DEM of each time phase, and cutting the corrected satellite stereoscopic image of each time phase to obtain satellite stereoscopic images of each time phase with consistent area ranges; after cutting, the ice and snow DEM of each time phase is consistent with the area range of the satellite stereoscopic image of each time phase;
the building module is used for building an irregular grid DEM based on the ice and snow DEM of each time phase with consistent area range; preferably, the building block comprises:
the sampling point selecting unit is used for selecting sampling points on the ice and snow DEM of each time phase with the consistent area range, and the sampling points are required to be uniformly distributed on the ice and snow DEM;
and the irregular grid DEM construction unit is used for establishing an irregular triangulation network model according to the selected sampling points, and selecting a linear interpolation algorithm based on Delaunay triangulation on the irregular triangulation network model to perform elevation interpolation so as to complete construction of the irregular grid DEM.
And the first calculation module is used for calculating the ice and snow lifting variation of adjacent time phases according to the irregular grid DEM.
And the second calculation module is used for calculating the variation of the ice and snow coverage area by adopting a support vector machine classification method according to the satellite stereoscopic images of each time phase with the consistent region range.
The present invention provides, in one embodiment, a computer device comprising a processor and a memory for storing a computer program comprising program instructions, the processor for executing the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is adapted to implement one or more instructions, and is specifically adapted to load and execute one or more instructions to implement a corresponding method flow or a corresponding function; the processor provided by the embodiment of the invention can be used for operating the ice and snow change three-dimensional monitoring method based on the satellite three-dimensional image.
In one embodiment of the present invention, a three-dimensional monitoring method for ice and snow changes can be stored in a computer readable storage medium if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. Computer-readable storage media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data.
The computer storage media may be any available media or data storage device that can be accessed by a computer, including but not limited to magnetic memory (e.g., floppy disks, hard disks, magnetic tape, magneto-optical disks (MOs), etc.), optical memory (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor memory (e.g., ROMs, EPROMs, EEPROMs, non-volatile memories (NANDFLASH), Solid State Disks (SSDs)), etc.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A three-dimensional monitoring method for ice and snow changes is characterized by comprising the following steps:
acquiring a multi-temporal satellite stereoscopic image;
extracting an ice and snow DEM from the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase;
cutting the ice and snow DEM of each time phase to obtain the ice and snow DEM of each time phase with the same area range;
correcting the satellite stereoscopic image of each corresponding time phase by using the ice and snow DEM of each time phase, and cutting the corrected satellite stereoscopic image of each time phase to obtain the satellite stereoscopic image of each time phase with the consistent area range; after cutting, the ice and snow DEM of each time phase is consistent with the area range of the satellite stereoscopic image of each time phase;
constructing an irregular grid DEM based on the ice and snow DEM of each time phase with consistent area range;
calculating the ice and snow lifting variation of adjacent time phases according to the irregular grid DEM;
and calculating to obtain the ice and snow coverage area variation according to the satellite stereoscopic images of each time phase with the consistent region range by adopting a support vector machine classification method.
2. The method according to claim 1, wherein the acquisition criteria of the multi-temporal satellite stereoscopic images are as follows:
selecting a cloud-free or few-cloud covered image, wherein the ice and snow part is covered without clouds, and the cloud amount of the image is less than 2%;
the image has no missing, noise and abnormal pixels;
and the image has no obvious aerosol coverage;
and no rainfall is present before and after the imaging date of the image.
3. An ice and snow change three-dimensional monitoring method according to claim 1, wherein the ice and snow DEM of each time phase is obtained by extracting the satellite three-dimensional image of each time phase, and the specific method is as follows:
and extracting the ice and snow DEM of the satellite stereoscopic image of each time phase by adopting a DEM extraction functional module in ENVI software in the remote sensing image processing platform to obtain the ice and snow DEM of each time phase.
4. An ice and snow change three-dimensional monitoring method as claimed in claim 1, wherein the irregular grid DEM is constructed based on the ice and snow DEM of each time phase with the consistent area range, specifically as follows:
selecting sampling points on the ice and snow DEM of each time phase with the consistent area range, wherein the sampling points are required to be uniformly distributed on the ice and snow DEM;
and establishing an irregular triangulation network model according to the selected sampling points, and selecting a linear interpolation algorithm based on Delaunay triangulation on the irregular triangulation network model to perform elevation interpolation to complete the construction of the irregular grid DEM.
5. An ice and snow change three-dimensional monitoring method according to claim 4, wherein the ice and snow lifting change amount of the adjacent time phase is obtained by calculation according to an irregular grid DEM, and the following calculation formula is specifically adopted:
wherein Δ V is the amount of change in the ascending and descending of ice and snow in adjacent time phases; d is the grid interval; Δ HijCorresponding to the height difference on the i, j grid.
6. The method for three-dimensional monitoring of ice and snow change according to claim 1, wherein the satellite three-dimensional images of each time phase with the same area range are classified by a support vector machine to calculate the amount of change of ice and snow coverage area, specifically as follows:
interpreting a satellite stereoscopic image by visual observation, and defining a training sample on the interpreted satellite stereoscopic image, wherein the training sample comprises ice and snow and non-ice and snow;
adopting a remote sensing image processing platform, executing a support vector machine classification method, loading an ice and snow satellite stereoscopic image, inputting the training sample, setting parameters, and outputting a classification result, wherein the classification result comprises an ice and snow covered area and a non-ice and snow covered area;
obtaining an ice and snow covered area according to the classification result, wherein the amount of change of the ice and snow covered area
The method is obtained by the ice and snow coverage area difference of adjacent time phases, and the formula is as follows:
in the formula, S1 represents the ice and snow covered area before the ice and snow covering change, and S2 represents the ice and snow covered area after the ice and snow covering change.
7. The utility model provides an ice and snow change stereoscopic monitoring device which characterized in that includes:
the acquisition module is used for acquiring a satellite stereoscopic image with multiple time phases;
the extraction module is used for extracting the ice and snow DEM of the satellite stereoscopic image of each time phase to obtain the ice and snow DEM of each time phase;
the first cutting module is used for cutting the ice and snow DEM of each time phase to obtain the ice and snow DEM of each time phase with the same area range;
the second cutting module is used for correcting the satellite stereoscopic image of each corresponding time phase by using the ice and snow DEM of each time phase, and cutting the corrected satellite stereoscopic image of each time phase to obtain satellite stereoscopic images of each time phase with consistent area ranges; after cutting, the ice and snow DEM of each time phase is consistent with the area range of the satellite stereoscopic image of each time phase;
the building module is used for building an irregular grid DEM based on the ice and snow DEM of each time phase with consistent area range;
the first calculation module is used for calculating the ice and snow lifting variation of adjacent time phases according to the irregular grid DEM;
and the second calculation module is used for calculating the variation of the ice and snow coverage area by adopting a support vector machine classification method according to the satellite stereoscopic images of each time phase with the consistent region range.
8. An ice and snow three-dimensional monitoring device according to claim 7, wherein said construction module comprises:
the sampling point selecting unit is used for selecting sampling points on the ice and snow DEM of each time phase with the consistent area range, and the sampling points are required to be uniformly distributed on the ice and snow DEM;
and the irregular grid DEM construction unit is used for establishing an irregular triangulation network model according to the selected sampling points, selecting a linear interpolation algorithm based on Delaunay triangulation on the irregular triangulation network model for performing elevation interpolation, and completing construction of the irregular grid DEM.
9. An apparatus comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program implements a stereoscopic ice and snow monitoring method as claimed in any one of claims 1 to 6.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of a method for stereoscopic monitoring of ice and snow variations as claimed in any one of claims 1 to 6.
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