CN116430008A - GNSS-IR soil humidity inversion method and system - Google Patents
GNSS-IR soil humidity inversion method and system Download PDFInfo
- Publication number
- CN116430008A CN116430008A CN202310370551.6A CN202310370551A CN116430008A CN 116430008 A CN116430008 A CN 116430008A CN 202310370551 A CN202310370551 A CN 202310370551A CN 116430008 A CN116430008 A CN 116430008A
- Authority
- CN
- China
- Prior art keywords
- dsnr
- sequence
- preset
- clipping
- gnss
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 239000002689 soil Substances 0.000 title claims abstract description 95
- 238000000034 method Methods 0.000 title claims abstract description 52
- 238000012876 topography Methods 0.000 claims abstract description 31
- 238000004590 computer program Methods 0.000 claims description 14
- 238000003860 storage Methods 0.000 claims description 8
- 238000012216 screening Methods 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 5
- 238000012935 Averaging Methods 0.000 claims description 4
- 238000012544 monitoring process Methods 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 description 9
- 238000004891 communication Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 230000000717 retained effect Effects 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 238000011065 in-situ storage Methods 0.000 description 3
- 239000000523 sample Substances 0.000 description 3
- 238000007796 conventional method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000002411 adverse Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000003673 groundwater Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000002310 reflectometry Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000011179 visual inspection Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/24—Earth materials
- G01N33/246—Earth materials for water content
-
- 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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/14—Receivers specially adapted for specific applications
-
- 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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/35—Constructional details or hardware or software details of the signal processing chain
- G01S19/37—Hardware or software details of the signal processing chain
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Computer Networks & Wireless Communication (AREA)
- Biochemistry (AREA)
- Analytical Chemistry (AREA)
- Geology (AREA)
- General Health & Medical Sciences (AREA)
- Medicinal Chemistry (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Environmental & Geological Engineering (AREA)
- Food Science & Technology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention provides a GNSS-IR soil humidity inversion method and system, which belong to the technical field of soil humidity data monitoring and comprise the following steps: collecting a DSNR sequence of the target relief topography; performing space clipping on the DSNR sequence by using preset topographic data and a preset elevation difference threshold value to obtain an initial clipping DSNR sequence; constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence; and inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography. According to the invention, through cutting the DSNR sequence in the GNSS observation data, the available data on the undulating terrain is reserved to the greatest extent, so that the influence of the terrain on the DSNR data quality is reduced, and the purpose of improving the soil humidity inversion precision is achieved.
Description
Technical Field
The invention relates to the technical field of soil humidity data monitoring, in particular to a GNSS-IR soil humidity inversion method and system.
Background
Soil humidity (Soil Moisture Content, SMC) is an important variable affecting land water circulation, and changes of the important variable reflect the response of an ecological system to climate change, and simultaneously influence the interaction between the earth surface and the atmosphere and the supply of groundwater, so that the accurate monitoring of the soil humidity has important significance on the research of the fields of climate change, ecological change, agricultural development and the like.
With the development of global navigation satellite system (GNSS-R) technology, a soil moisture inversion technology (GNSS-Interferometric Reflectometry, GNSS-IR) based on GNSS signal-to-noise ratio (Signal to Noise Raito, SNR) observation data is generated, which is commonly used for supplementing in-situ detection data and correcting satellite remote sensing soil moisture products, and has the advantages of low cost, high precision, high space-time resolution, continuous monitoring and weather protection. In the soil moisture inversion process, the topography fluctuation can cause the waveform of the observation data-detrending signal-to-noise ratio (Detrended Signal to Noise Raito, DSNR) sequence of the GNSS-IR to be distorted and unsuitable for soil moisture inversion, so that the application of the GNSS-IR in the fluctuation topography is limited. Since the topography relief distorts the waveform of the DSNR sequence, the inversion accuracy of the soil moisture will be severely affected, and the existing GNSS-IR soil moisture inversion technique is not suitable for the relief topography.
Disclosure of Invention
The invention provides a GNSS-IR soil humidity inversion method and system, which are used for solving the defect that in the prior art, the inversion accuracy of soil humidity is low because the GNSS-IR soil humidity inversion technology cannot eliminate images of undulating topography on DSNR sequences.
In a first aspect, the present invention provides a GNSS-IR soil moisture inversion method, comprising:
collecting a DSNR sequence of the target relief topography;
performing space clipping on the DSNR sequence by using preset topographic data and a preset altitude difference threshold value to obtain an initial clipping DSNR sequence;
constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence;
and inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography.
According to the GNSS-IR soil humidity inversion method provided by the invention, the global navigation satellite system detrending signal-to-noise ratio DSNR sequence for collecting the target relief topography comprises the following steps:
acquiring GNSS observation data of the target relief topography;
extracting the DSNR sequence in the GNSS observation data.
According to the GNSS-IR soil humidity inversion method provided by the invention, the DSNR sequence is spatially cut by using preset topographic data and preset altitude difference threshold value to obtain an initial cut DSNR sequence, and the method comprises the following steps:
taking an observation station for collecting GNSS observation data as a center, determining a plurality of rays at preset interval angles in a clockwise direction, determining a plurality of concentric circles taking the observation station as a center along the plurality of rays at preset interval distances, and dividing a preset adjacent space of the observation station into a plurality of grids based on the plurality of rays and the plurality of concentric circles;
calculating the maximum height difference of each grid in the plurality of grids by adopting preset high-resolution topographic data;
and screening a first grid set with the maximum height difference smaller than a first preset height difference threshold by using the first preset height difference threshold to obtain the initial cutting DSNR sequence corresponding to the first grid set.
According to the GNSS-IR soil humidity inversion method provided by the invention, the DSNR sequence is spatially cut by using preset topographic data and preset altitude difference threshold value to obtain an initial cut DSNR sequence, and the method further comprises the following steps:
if the available arc segments in the initial cutting DSNR sequence are determined to be less than a preset arc segment threshold, screening a second grid set with the maximum height difference smaller than the second preset height difference threshold by using a second preset height difference threshold, and obtaining the initial cutting DSNR sequence corresponding to the second grid set;
wherein the second preset elevation difference threshold value is greater than the first preset elevation difference threshold value.
According to the GNSS-IR soil humidity inversion method provided by the invention, the construction of the reference cosine waveform comprises the following steps:
determining a cosine wave frequency by using a main frequency of a power spectrogram in the DSNR sequence, or determining the cosine wave frequency by taking an average value of frequencies of preset ranking before ranking of the power spectrograms;
averaging the preset cosine wave amplitudes in the DSNR sequence to determine the cosine wave amplitude;
the reference cosine waveform is constructed based on the cosine wave frequency and the cosine wave amplitude.
According to the GNSS-IR soil humidity inversion method provided by the invention, the initial clipping DSNR sequence is time clipped based on the reference cosine waveform to obtain a depth clipping DSNR sequence, which comprises the following steps:
comparing the reference cosine waveform with the initial clipping DSNR sequence, clipping a part with a sequence period larger than a preset period and a part with a sequence amplitude smaller than a preset proportion multiplied by cosine wave amplitude in the initial clipping DSNR sequence to obtain the depth clipping DSNR sequence.
In a second aspect, the present invention also provides a GNSS-IR soil moisture inversion system, comprising:
the acquisition module is used for acquiring a DSNR sequence of the target relief topography;
the initial cutting module is used for carrying out space cutting on the DSNR sequence by utilizing preset topographic data and a preset altitude difference threshold value to obtain an initial cutting DSNR sequence;
the depth clipping module is used for constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence;
and the processing module is used for inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography.
In a third aspect, the present invention also provides an electronic device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the GNSS-IR soil moisture inversion method as described in any of the above when executing the program.
In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a GNSS-IR soil moisture inversion method as described in any of the above.
In a fifth aspect, the invention also provides a computer program product comprising a computer program which when executed by a processor implements a GNSS-IR soil moisture inversion method as described in any of the above.
According to the GNSS-IR soil humidity inversion method and system, the DSNR sequence in the GNSS observation data is cut, available data on undulating terrain is reserved to the greatest extent, so that influence of the terrain on DSNR data quality is reduced, the purpose of improving soil humidity inversion accuracy is achieved, application of GNSS-IR in undulating terrain is achieved, application range of GNSS-IR soil humidity inversion technology is expanded, good soil humidity inversion accuracy and reliability are obtained, and the problem that the existing GNSS-IR technology is only applicable to flat ground and limited to undulating terrain application is effectively solved.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a GNSS-IR soil moisture inversion method provided by the invention;
FIG. 2 is a second flow chart of the GNSS-IR soil moisture inversion method according to the present invention;
FIG. 3 is a graph showing a time series comparison of soil moisture calculated at 4 stations according to the conventional method provided by the present invention;
FIG. 4 is a schematic diagram of a GNSS-IR soil moisture inversion system according to the present invention;
fig. 5 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, 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 embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a schematic flow chart of a GNSS-IR soil humidity inversion method according to an embodiment of the present invention, as shown in fig. 1, including:
step 100: collecting a DSNR sequence of the target relief topography;
step 200: performing space clipping on the DSNR sequence by using preset topographic data and a preset altitude difference threshold value to obtain an initial clipping DSNR sequence;
step 300: constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence;
step 400: and inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography.
The embodiment of the invention aims to solve the problem that the GNSS-IR technology is only suitable for flat ground and cannot be well suitable for the limitation of undulating terrain, and performs a series of processing on the DSNR sequence of a single satellite in GNSS observation data, so that the DSNR sequence can be suitable for various terrains to obtain more accurate soil humidity inversion results.
Specifically, as shown in fig. 2, an original DSNR sequence is first obtained from GNSS observation data, and the DSNR sequence is extracted and processed from GNSS observation data of an undulating ground; then, performing spatial clipping on the DSNR sequence by using high-precision high-resolution topographic data and a preset height difference threshold value, deleting the DSNR sequence in the region with the overlarge height difference, for example, screening by taking 0.7 meter or 0.9 meter as the height difference threshold value, and obtaining an initial clipping DSNR sequence after spatial clipping; further constructing a reference waveform, namely performing time dimension cutting on the initial cutting DSNR sequence subjected to space cutting by using the reference cosine waveform to obtain a depth cutting DSNR sequence; and finally substituting the depth cutting DSNR sequence into a standard GNSS-IR inversion algorithm to obtain the soil humidity.
According to the invention, through cutting the DSNR sequence in the GNSS observation data, the available data on the undulating terrain is reserved to the greatest extent, so that the influence of the terrain on the DSNR data quality is reduced, the purpose of improving the soil humidity inversion precision is achieved, the application of GNSS-IR in the undulating terrain is realized, the application range of the GNSS-IR soil humidity inversion technology is expanded, good soil humidity inversion precision and reliability are obtained, and the problem that the conventional GNSS-IR technology is only applicable to flat ground and is limited to the application of the undulating terrain is effectively solved.
Based on the above embodiment, the global navigation satellite system detrending signal-to-noise ratio DSNR sequence for collecting the target relief topography includes:
acquiring GNSS observation data of the target relief topography;
extracting the DSNR sequence in the GNSS observation data.
Specifically, since all existing GNSS data processing software can directly read GNSS observation data, DSNR sequences can be directly extracted for the target undulating terrain to be processed, including various complex influencing factors in the undulating terrain.
Based on the above embodiment, the performing spatial clipping on the DSNR sequence by using preset topographic data and a preset altitude difference threshold value to obtain an initial clipping DSNR sequence includes:
taking an observation station for collecting GNSS observation data as a center, determining a plurality of rays at preset interval angles in a clockwise direction, determining a plurality of concentric circles taking the observation station as a center along the plurality of rays at preset interval distances, and dividing a preset adjacent space of the observation station into a plurality of grids based on the plurality of rays and the plurality of concentric circles;
calculating the maximum height difference of each grid in the plurality of grids by adopting preset high-resolution topographic data;
and screening a first grid set with the maximum height difference smaller than a first preset height difference threshold by using the first preset height difference threshold to obtain the initial cutting DSNR sequence corresponding to the first grid set.
The method comprises the steps of performing spatial clipping on the DSNR sequence by using preset topographic data and a preset altitude difference threshold value to obtain an initial clipping DSNR sequence, and further comprises the following steps:
if the available arc segments in the initial cutting DSNR sequence are determined to be less than a preset arc segment threshold, screening a second grid set with the maximum height difference smaller than the second preset height difference threshold by using a second preset height difference threshold, and obtaining the initial cutting DSNR sequence corresponding to the second grid set;
wherein the second preset elevation difference threshold value is greater than the first preset elevation difference threshold value.
Specifically, a ray is drawn every 1 degree in a clockwise direction by taking an observation station as a center, a circle taking the observation station as a center is drawn every 5 meters along the ray direction, so that the adjacent space of the observation station can be divided into a plurality of grids, the maximum height difference in each grid is calculated by utilizing high-resolution topographic data, and the grids with the maximum height difference smaller than 0.7 meter are screened by utilizing a threshold value of 0.7 meter (a first preset height difference threshold value);
if the final retained DSNR data is too small, for example, when there are fewer than 10 available arcs in the final retained DSNR sequence, the threshold of the maximum difference in elevation is raised to equal to or more than 10 available arcs in the final retained DSNR sequence, where the threshold may be suitably relaxed to 0.9 meters (the second preset difference in elevation threshold) and then screened to obtain the initial cropped DSNR sequence.
Based on the above embodiment, the constructing the reference cosine waveform includes:
determining a cosine wave frequency by using a main frequency of a power spectrogram in the DSNR sequence, or determining the cosine wave frequency by taking an average value of frequencies of preset ranking before ranking of the power spectrograms;
averaging the preset cosine wave amplitudes in the DSNR sequence to determine the cosine wave amplitude;
the reference cosine waveform is constructed based on the cosine wave frequency and the cosine wave amplitude.
Specifically, after the initial clipping DSNR sequence is obtained, a reference cosine waveform is constructed by using waveform information in the DSNR sequence.
The frequency of the reference cosine waveform is determined by the main frequency in the power spectrogram of the DSNR by utilizing the Lomb-Scargle method, and if the main frequency cannot be determined, the frequency of the cosine wave is determined by taking the average value of the frequency corresponding to the top 3 strong in the power spectrogram of the DSNR.
Correspondingly, the cosine wave amplitude is determined by averaging the amplitudes of the typical cosine wave portions of the DSNR sequence.
And combining the determined cosine wave frequency and the cosine wave amplitude to form a reference cosine waveform.
Based on the above embodiment, the performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence includes:
comparing the reference cosine waveform with the initial clipping DSNR sequence, clipping a part with a sequence period larger than a preset period and a part with a sequence amplitude smaller than a preset proportion multiplied by cosine wave amplitude in the initial clipping DSNR sequence to obtain the depth clipping DSNR sequence.
Specifically, by comparing the reference cosine waveform with each DSNR arc segment in the DSNR sequence, DSNR data with period difference larger than 1 week and amplitude smaller than 1/5 class main amplitude are deleted, and finally the residual DSNR sequence at least comprises 1 cosine period and ensures that the power value corresponding to the main frequency is larger than the main frequency power value of the original DSNR sequence as much as possible. Under visual inspection, it is ensured that the retained DSNR sequence exhibits a typical cosine waveform.
After all the arc segments are cut and edited, the edited arc segments are processed by the existing soil humidity inversion algorithm, and the soil humidity inversion value is obtained.
Based on the embodiment, the embodiment of the invention carries out actual measurement on 3 GNSS measuring stations in a certain area, and has the guiding function on soil humidity inversion applied to other undulating areas.
In this embodiment, the numbers of the 3 stations are respectively: p183, P341, P476; the 3 measuring stations are all fluctuation measuring stations; this example uses root mean square error (Root Mean Square Error, RMSE) to evaluate the performance of the invention in soil moisture inversion, reference data probe in-situ observations. An experiment of performing soil humidity inversion by using GNSS DSNR data acquired by undulating terrain is carried out in a certain area, so that the performance of the method and the traditional method in soil humidity inversion is evaluated, and specific soil humidity inversion precision information is shown in the following table 1;
TABLE 1
As can be seen from Table 1, the root mean square error (Root Mean Squared Error, RMSE) of the difference between the soil moisture sequence and the reference value (i.e., the data probe in-situ observation data) obtained by inversion of the embodiment of the invention is from 0.062cm 3 cm -3 Reduced to 0.044cm 3 cm -3 Compared with the traditional method, the soil humidity inversion accuracy of the embodiment of the invention is improved by about 29.0%. The results show that the accuracy of the inversion result can be improved when the signal reflection ground is fluctuant, and further the fact that the arc section editing method (namely the arc section time and the space cutting method) can effectively relieve adverse effects of the topography fluctuant on soil humidity inversion is proved, so that the method has important significance in application expansion of the GNSS-IR technology on fluctuant topography.
FIG. 3 is a graph comparing the time series of soil moisture calculated at 3 stations according to the present invention with the conventional method. As can be seen from the more visual results of FIG. 3, the soil humidity time sequence obtained by inversion of the method is more consistent with the field observation time sequence of the data probe, and the improvement effect is very remarkable compared with the traditional GNSS-IR soil humidity inversion method, so that the soil humidity inversion accuracy is improved by the method, and good soil humidity inversion accuracy and reliability are obtained.
The GNSS-IR soil moisture inversion system provided by the invention is described below, and the GNSS-IR soil moisture inversion system described below and the GNSS-IR soil moisture inversion method described above can be referred to correspondingly.
FIG. 4 is a schematic structural diagram of a GNSS-IR soil moisture inversion system according to an embodiment of the present invention, as shown in FIG. 4, including: an acquisition module 41, an initial cropping module 42, a depth cropping module 43, and a processing module 44, wherein:
the acquisition module 41 is used for acquiring a DSNR sequence of the global navigation satellite system with the trend removed by the target relief topography; the initial clipping module 42 is configured to spatially clip the DSNR sequence by using preset topographic data and a preset altitude difference threshold value, to obtain an initial clipped DSNR sequence; the depth clipping module 43 is configured to construct a reference cosine waveform, and time clip the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence; the processing module 44 is configured to input the depth cutting DSNR sequence into a preset standard soil humidity inversion model, so as to obtain the soil humidity of the target relief topography.
Fig. 5 illustrates a physical schematic diagram of an electronic device, as shown in fig. 5, which may include: processor 510, communication interface (Communications Interface) 520, memory 530, and communication bus 540, wherein processor 510, communication interface 520, memory 530 complete communication with each other through communication bus 540. The processor 510 may invoke logic instructions in the memory 530 to perform a GNSS-IR soil moisture inversion method comprising: collecting a DSNR sequence of the target relief topography; performing space clipping on the DSNR sequence by using preset topographic data and a preset altitude difference threshold value to obtain an initial clipping DSNR sequence; constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence; and inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography.
Further, the logic instructions in the memory 530 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of performing the GNSS-IR soil moisture inversion method provided by the above methods, the method comprising: collecting a DSNR sequence of the target relief topography; performing space clipping on the DSNR sequence by using preset topographic data and a preset altitude difference threshold value to obtain an initial clipping DSNR sequence; constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence; and inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the GNSS-IR soil moisture inversion method provided by the above methods, the method comprising: collecting a DSNR sequence of the target relief topography; performing space clipping on the DSNR sequence by using preset topographic data and a preset altitude difference threshold value to obtain an initial clipping DSNR sequence; constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence; and inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A GNSS-IR soil moisture inversion method, comprising:
collecting a trending signal-to-noise ratio DSNR sequence of the target relief topography;
performing space clipping on the DSNR sequence by using preset topographic data and a preset altitude difference threshold value to obtain an initial clipping DSNR sequence;
constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence;
and inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography.
2. The GNSS-IR soil moisture inversion method of claim 1, wherein the DSNR sequence of the acquisition target relief terrain comprises:
acquiring Global Navigation Satellite System (GNSS) observation data of the target relief terrain;
extracting the DSNR sequence in the GNSS observation data.
3. The GNSS-IR soil moisture inversion method according to claim 1, wherein the spatially clipping the DSNR sequence using the predetermined terrain data and the predetermined altitude difference threshold to obtain an initial clipped DSNR sequence comprises:
taking an observation station for collecting GNSS observation data as a center, determining a plurality of rays at preset interval angles in a clockwise direction, determining a plurality of concentric circles taking the observation station as a center along the plurality of rays at preset interval distances, and dividing a preset adjacent space of the observation station into a plurality of grids based on the plurality of rays and the plurality of concentric circles;
calculating the maximum height difference of each grid in the plurality of grids by adopting preset high-resolution topographic data;
and screening a first grid set with the maximum height difference smaller than a first preset height difference threshold by using the first preset height difference threshold to obtain the initial cutting DSNR sequence corresponding to the first grid set.
4. The GNSS-IR soil moisture inversion method according to claim 3, wherein said spatially clipping said DSNR sequence using a predetermined terrain data and a predetermined elevation difference threshold to obtain an initial clipped DSNR sequence, further comprising:
if the available arc segments in the initial cutting DSNR sequence are determined to be less than a preset arc segment threshold, screening a second grid set with the maximum height difference smaller than the second preset height difference threshold by using a second preset height difference threshold, and obtaining the initial cutting DSNR sequence corresponding to the second grid set;
wherein the second preset elevation difference threshold value is greater than the first preset elevation difference threshold value.
5. The GNSS-IR soil moisture inversion method according to claim 1, wherein said constructing a reference cosine waveform includes:
determining a cosine wave frequency by using a main frequency of a power spectrogram in the DSNR sequence, or determining the cosine wave frequency by taking an average value of frequencies of preset ranking before ranking of the power spectrograms;
averaging the preset cosine wave amplitudes in the DSNR sequence to determine the cosine wave amplitude;
the reference cosine waveform is constructed based on the cosine wave frequency and the cosine wave amplitude.
6. The GNSS-IR soil moisture inversion method according to claim 1, wherein said time cropping the initial cropping DSNR sequence based on the reference cosine waveform, obtaining a depth cropping DSNR sequence, comprises:
comparing the reference cosine waveform with the initial clipping DSNR sequence, clipping a part with a sequence period larger than a preset period and a part with a sequence amplitude smaller than a preset proportion multiplied by cosine wave amplitude in the initial clipping DSNR sequence to obtain the depth clipping DSNR sequence.
7. A GNSS-IR soil moisture inversion system, comprising:
the acquisition module is used for acquiring a DSNR sequence of the target relief topography;
the initial cutting module is used for carrying out space cutting on the DSNR sequence by utilizing preset topographic data and a preset altitude difference threshold value to obtain an initial cutting DSNR sequence;
the depth clipping module is used for constructing a reference cosine waveform, and performing time clipping on the initial clipping DSNR sequence based on the reference cosine waveform to obtain a depth clipping DSNR sequence;
and the processing module is used for inputting the depth cutting DSNR sequence into a preset standard soil humidity inversion model to obtain the soil humidity of the target relief topography.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the GNSS-IR soil moisture inversion method according to any of claims 1 to 6 when the program is executed.
9. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the GNSS-IR soil moisture inversion method according to any of claims 1 to 6.
10. A computer program product comprising a computer program which, when executed by a processor, implements the GNSS-IR soil moisture inversion method according to any of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310370551.6A CN116430008A (en) | 2023-04-07 | 2023-04-07 | GNSS-IR soil humidity inversion method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310370551.6A CN116430008A (en) | 2023-04-07 | 2023-04-07 | GNSS-IR soil humidity inversion method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116430008A true CN116430008A (en) | 2023-07-14 |
Family
ID=87079192
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310370551.6A Pending CN116430008A (en) | 2023-04-07 | 2023-04-07 | GNSS-IR soil humidity inversion method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116430008A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102034994B1 (en) * | 2019-06-19 | 2019-10-21 | 세종대학교산학협력단 | Apparatus and method for calculating soil moisture content using GPS reflection signal |
| CN110389208A (en) * | 2018-04-17 | 2019-10-29 | 金华航大北斗应用技术有限公司 | Based on GNSS-IR multi-spectrum fusion soil moisture monitoring method and device |
| CN111337548A (en) * | 2020-03-13 | 2020-06-26 | 山东航向电子科技有限公司 | High-precision signal-to-noise ratio fitting model and soil humidity inversion method based on same |
| CN111474209A (en) * | 2020-03-13 | 2020-07-31 | 山东航向电子科技有限公司 | Real-time soil humidity measuring method based on intelligent terminal equipment |
| US20210285895A1 (en) * | 2020-03-13 | 2021-09-16 | Shandong Orientation Electronic Technology Co., Ltd. | Soil humidity microwave remote sensing device with multi-mode compatibility via gnss-r and a method of using the same |
| CN114167033A (en) * | 2021-12-06 | 2022-03-11 | 北京大学 | GNSS-R based soil humidity inversion method, device, medium and computing equipment |
| CN115047499A (en) * | 2022-05-31 | 2022-09-13 | 武汉大学 | Inversion method and system for satellite-borne GNSS-R soil temperature and humidity |
-
2023
- 2023-04-07 CN CN202310370551.6A patent/CN116430008A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110389208A (en) * | 2018-04-17 | 2019-10-29 | 金华航大北斗应用技术有限公司 | Based on GNSS-IR multi-spectrum fusion soil moisture monitoring method and device |
| KR102034994B1 (en) * | 2019-06-19 | 2019-10-21 | 세종대학교산학협력단 | Apparatus and method for calculating soil moisture content using GPS reflection signal |
| CN111337548A (en) * | 2020-03-13 | 2020-06-26 | 山东航向电子科技有限公司 | High-precision signal-to-noise ratio fitting model and soil humidity inversion method based on same |
| CN111474209A (en) * | 2020-03-13 | 2020-07-31 | 山东航向电子科技有限公司 | Real-time soil humidity measuring method based on intelligent terminal equipment |
| US20210285895A1 (en) * | 2020-03-13 | 2021-09-16 | Shandong Orientation Electronic Technology Co., Ltd. | Soil humidity microwave remote sensing device with multi-mode compatibility via gnss-r and a method of using the same |
| CN114167033A (en) * | 2021-12-06 | 2022-03-11 | 北京大学 | GNSS-R based soil humidity inversion method, device, medium and computing equipment |
| CN115047499A (en) * | 2022-05-31 | 2022-09-13 | 武汉大学 | Inversion method and system for satellite-borne GNSS-R soil temperature and humidity |
Non-Patent Citations (2)
| Title |
|---|
| QISHUN RAN ET AL.: "Editing arcs to improve the capacity of GNSS‑IR for soil moisture retrieval in undulating terrains", GPS SOLUTIONS, vol. 26, 4 December 2021 (2021-12-04), pages 1 - 11, XP037635714, DOI: 10.1007/s10291-021-01206-y * |
| 陈?;沈飞;曹新运;朱逸凡;: "基于深度置信网络的GNSS-IR土壤湿度反演", 测绘通报, no. 09, 25 September 2020 (2020-09-25), pages 103 - 108 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP1643263B1 (en) | Device and method for determining an atmosphere condition | |
| Kunitsyn et al. | Ionospheric radio tomography based on the GPS/GLONASS navigation systems | |
| Draper et al. | The impact of near-surface soil moisture assimilation at subseasonal, seasonal, and inter-annual timescales | |
| CN109100719B (en) | Terrain map joint mapping method based on satellite-borne SAR (synthetic aperture radar) image and optical image | |
| Ran et al. | Editing arcs to improve the capacity of GNSS-IR for soil moisture retrieval in undulating terrains | |
| CN107479045B (en) | Method and system for eliminating short vegetation based on full-waveform laser radar point cloud data | |
| CN103927737A (en) | SAR image change detecting method based on non-local mean | |
| Crisologo et al. | Enhancing the consistency of spaceborne and ground-based radar comparisons by using beam blockage fraction as a quality filter | |
| CN113281749A (en) | Time sequence InSAR high-coherence point selection method considering homogeneity | |
| CN112882032A (en) | Gas pipeline key area geological disaster SAR dynamic monitoring method and device | |
| CN116931101A (en) | Method and device for detecting underground shallow disease body, electronic equipment and storage medium | |
| Shaw et al. | A front-following algorithm for AVHRR SST imagery | |
| Zeng et al. | Interpreting estimated observation error statistics of weather radar measurements using the ICON-LAM-KENDA system | |
| Gorbunov et al. | Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals | |
| Nielsen et al. | Estimation of refractivity uncertainties and vertical error correlations in collocated radio occultations, radiosondes, and model forecasts | |
| Lindsley et al. | Adapting the SIR algorithm to ASCAT | |
| Hofton et al. | Algorithm Theoretical Basis Document (ATBD) | |
| CN116430008A (en) | GNSS-IR soil humidity inversion method and system | |
| CN114594503B (en) | Shallow sea topography inversion method, computer equipment and storage medium | |
| Schumann et al. | Evaluating uncertain flood inundation predictions with uncertain remotely sensed water stages | |
| CN115311532A (en) | Ground penetrating radar underground cavity target automatic identification method based on ResNet network model | |
| CN114527465A (en) | Ground control point automatic selection method based on permanent scatterer | |
| CN116028480B (en) | Filling method for improving space-time coverage of remote sensing soil moisture product | |
| CN117610791B (en) | Method and device applied to large-scale hydrologic drought monitoring | |
| KR101352528B1 (en) | Gridding system of radar data and method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |