CN113238282B - Method for extracting seismic microwave radiation abnormity by combining multi-source auxiliary data - Google Patents
Method for extracting seismic microwave radiation abnormity by combining multi-source auxiliary data Download PDFInfo
- Publication number
- CN113238282B CN113238282B CN202110787048.1A CN202110787048A CN113238282B CN 113238282 B CN113238282 B CN 113238282B CN 202110787048 A CN202110787048 A CN 202110787048A CN 113238282 B CN113238282 B CN 113238282B
- Authority
- CN
- China
- Prior art keywords
- data
- microwave radiation
- earth surface
- matrix
- earthquake
- 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.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
Abstract
The invention discloses a method for extracting seismic microwave radiation abnormity by combining multi-source auxiliary data, which comprises the following steps: A) acquiring historical contemporaneous multisource auxiliary data such as microwave radiation remote sensing image data, earth surface coverage classification data, earth surface temperature data, earth surface humidity data and the like according to the year, date and place of earthquake occurrence; B) calculating the correlation between the non-earthquake-year earth surface temperature and humidity data and the earthquake-year earth surface temperature and humidity data in each earth surface coverage classification area by combining earth surface coverage classification data, selecting earth surface temperature and humidity data with high correlation in each earth surface coverage classification area as preferred historical auxiliary data, and selecting microwave radiation remote sensing image data which are in the same day as the preferred historical auxiliary data in each earth surface coverage classification area to obtain microwave radiation background field data; C) and differentiating the microwave radiation image data of the earthquake year and the microwave radiation background field data to obtain earthquake microwave radiation abnormal data. The method has high accuracy and strong anti-interference performance.
Description
Technical Field
The invention relates to a seismic anomaly research method, in particular to a method for extracting seismic microwave radiation anomaly by combining multi-source auxiliary data.
Background
Passive microwave satellite remote sensing data has been successfully applied to extraction and identification of seismic activity-related thermal radiation anomalies, and a large number of existing studies show that relatively significant surface microwave radiation changes commonly exist before and after inland violent shocks occur.
Because the earth surface coverage types of the research area are relatively complex, the earth surface coverage types are often several or even more than ten, and meanwhile, the earth surface meteorological factors in the research area change along with time and space, so that the satellite microwave sensor has great difference on the microwave radiation change response of different earth surface coverage types under different earth surface meteorological conditions.
At present, the method for extracting the seismic microwave radiation anomaly mainly comprises the steps of directly establishing an arithmetic average background field or a weighted average background field by using data of a past year and a researched earthquake in the same period, and then subtracting the background value from a microwave radiation image of the earthquake year to obtain a microwave radiation anomaly value related to earthquake activity. In the prior art, although the background value of the microwave radiation image in the earthquake year can be removed by subtracting the historical mean background field, the earth surface meteorological condition state of the microwave radiation data in the earthquake year is not considered, so that the interference value of non-earthquake factors is introduced into the extraction result, and the anti-interference performance of the technology and the accuracy of the abnormal extraction of the earthquake microwave radiation are reduced.
In view of the above, there is a need to provide a method for extracting seismic microwave radiation anomalies by combining multi-source auxiliary data.
Disclosure of Invention
The invention provides a method for extracting seismic microwave radiation abnormality by combining multi-source auxiliary data, which has strong anti-interference performance and high accuracy and has higher reference value for researching earthquake based on radiation abnormality.
In order to achieve the above object, the present invention provides a method for extracting seismic microwave radiation anomaly from multi-source auxiliary data, comprising the following steps: A) acquiring microwave radiation remote sensing image data and historical contemporaneous multisource auxiliary data in the earthquake region according to the year, date and place of earthquake occurrence, wherein the historical contemporaneous multisource auxiliary data comprises earth surface coverage classification data, earth surface temperature data and earth surface humidity data; B) calculating the correlation between the earth surface temperature data and the earth surface humidity data in the single earth surface coverage area and the earthquake year temperature data and the earthquake year humidity data based on the earth surface coverage classification data, and accordingly selecting a plurality of groups of earth surface temperature data and earth surface humidity data with highest correlation with the earthquake day temperature data and the earthquake day humidity data in the historical contemporaneous multisource auxiliary data of the single earth surface coverage area as preferred historical auxiliary data, selecting the microwave radiation remote sensing image data in a single earth surface coverage classification area on the same day as the preferred historical auxiliary data, synthesizing a plurality of microwave radiation remote sensing image data into incomplete microwave radiation background field data of a single earth surface covering classification area, and repeating the operation to construct complete microwave radiation background field data of all the earth surface covering classification areas; C) acquiring earthquake year microwave radiation image data, and differentiating the earthquake year microwave radiation image data and the complete microwave radiation background field data to obtain earthquake microwave radiation abnormal data.
Specifically, the year of the earthquake occurrence is Y, the date is T, the year Y of the microwave remote sensing image data and the historical contemporaneous multi-source auxiliary data includes Y and years before Y, and the date T of the microwave remote sensing image data and the historical contemporaneous multi-source auxiliary data includes days before or after the date T.
Further specifically, the step of synthesizing the complete microwave radiation background field data in the step B) includes: a) preprocessing the surface temperature data and the surface humidity data in the microwave radiation remote sensing image data and the historical contemporaneous multi-source auxiliary data and the surface coverage classification data of the earthquake occurrence area; b) according to the ground surface coverage classification data, combining the ground surface temperature data and the ground surface humidity data to construct an incomplete microwave radiation background field of a single ground surface coverage classification area; c) and constructing the incomplete microwave radiation background fields of all the earth surface covering and classifying areas, and fusing and constructing the incomplete microwave radiation background fields of all the earth surface covering and classifying areas into complete microwave radiation background field data with the year of Y and the date of T.
Further specifically, the preprocessing in step a) comprises unifying the resolution of the data and unifying the study area.
Further specifically, the step of constructing the incomplete microwave radiation background field in step b) includes:
b1) establishing a ground surface coverage mask matrix with the ground surface coverage type i in the research area according to the ground surface coverage classification data
Combining all the surface temperature data and the surface humidity data with the surface coverage type i, the year y and the date t to obtain a set of surface temperature matrix with the surface coverage type i
Collection of matrix of surface humidity
}; combining the earth surface temperature data and the earth surface humidity data of the current earthquake day to obtain an earth surface temperature matrix of the current earthquake day
And earthquake day earth surface humidity matrix
；
b2) Calculating the surface temperature matrix set (a) with the surface coverage type i one by one
Every earth surface temperature matrix in the earth surface temperature matrix and the earth surface temperature matrix of the earthquake day
Matrix correlation between the two and the surface humidity matrix set
And each earth surface humidity matrix in the earth surface humidity matrix and the earth surface humidity matrix of the earthquake day
Matrix correlation between;
b3) selecting the surface temperature matrix set according with the correlation requirement according to the correlation of the matrix
Great face and the surface humidity matrix set
And according to the earth surface temperature matrix set conforming to the correlation requirement
Great face and the surface humidity matrix set
The collection of the year and date (y ', t ') } corresponding to the acquisition of the collection of the microwave radiation remote sensing image data of which all the earth surface covering types are i years, y ' and t ', and the collection of the microwave radiation remote sensing image data of which the earth surface covering type is i years, y ' and the date is t { (y ', t ') }
}；
b4) Subjecting said set to a mapping
Calculating all the microwave radiation remote sensing image data in the previous step to obtain the incomplete microwave radiation background field of the single earth surface coverage classification area
。
Further specifically, the surface temperature matrix in step b 2)
And the earth surface temperature matrix of the earthquake on the day
The matrix correlation between them is expressed as a temperature correlation value
：
Where j and p are the matrix dimensions,
is the surface temperature matrix
Is calculated as the arithmetic mean of the average of the values,
for the earth surface temperature matrix of the earthquake day
Is calculated as the arithmetic mean of (1).
Further specifically, the surface humidity matrix in step b 2)
And the earth surface humidity matrix of the earthquake on the day
The matrix correlation between them is expressed as a humidity correlation value
：
Where j and p are the matrix dimensions,
is the ground surface humidity matrix
Is calculated as the arithmetic mean of the average of the values,
for the earth surface humidity matrix of the earthquake on the day
Is calculated as the arithmetic mean of (1).
Further specifically, the incomplete microwave radiation background field in step b4)
Is that it isIs derived from the following formula:
wherein the content of the first and second substances,N 1is a said collection
The number of matrices in (1).
Further specifically, the step of constructing the complete microwave radiation background field in step c) includes:
c1) repeating the operations from step b1) to step b4) to obtain a set of incomplete microwave radiation background fields for all terrain coverage classification areas
}；
c2) According to the ground surface covering classification data, the set of the incomplete microwave radiation background fields of all the ground surface covering classification areas is ready
Combine into a complete microwave radiation background field
。
Further specifically, the complete microwave radiation background field data in step c2)
Is derived from the following formula:
wherein q is the total classification number in the land cover classification data, and n is the union operation sign.
Further specifically, the seismic microwave radiation abnormal data in the step C)
Is derived from the following formula:
wherein the content of the first and second substances,
and the microwave radiation image data of the earthquake year is referred to.
The invention relates to a method for extracting seismic microwave radiation abnormity by combining multisource auxiliary data, which compares surface temperature data and surface humidity data in historical contemporaneous multisource auxiliary data with seismic current day temperature data and seismic current day humidity data of the current day of an earthquake to select a plurality of groups of surface temperature data and surface humidity data which are most similar to the meteorological conditions of the seismic current day in the historical contemporaneous data of a single surface coverage type area, determines the year and date which are similar to the meteorological conditions of the seismic current day in the historical contemporaneous data according to the year and date of the selected groups of surface temperature data and surface humidity data, extracts microwave radiation remote sensing image data of the corresponding year and date to obtain incomplete microwave radiation background field data of the single surface coverage type area by calculating a plurality of microwave remote sensing image data in the single surface coverage type area, the operation is repeated to obtain incomplete microwave radiation background field data of all earth surface coverage type areas, the incomplete microwave radiation background field data are fused into complete microwave radiation background field data of earthquake occurrence areas, and difference is made between the complete microwave radiation background field data and earthquake year microwave radiation image data to obtain earthquake microwave radiation abnormal data.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
Drawings
FIG. 1 is a schematic diagram of a method of extracting seismic microwave radiation anomalies in conjunction with multi-source auxiliary data in accordance with the present invention;
FIG. 2 is a microwave radiation remote sensing image of a seismic research area in the method for extracting seismic microwave radiation anomaly by combining multi-source auxiliary data according to the invention;
FIG. 3 is a diagram of the type of surface coverage of a seismic study area in the method for extracting seismic microwave radiation anomalies in combination with multi-source auxiliary data of the present invention;
FIG. 4 is a complete microwave radiation background field for all surface coverage classification regions within a seismic study area in a method for extracting seismic microwave radiation anomalies in combination with multi-source auxiliary data according to the present invention;
FIG. 5 is a diagram of seismic microwave radiation anomalies for a seismic research area in a method for extracting seismic microwave radiation anomalies in combination with multi-source auxiliary data according to the invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
As shown in fig. 1, in an embodiment of the method for extracting seismic microwave radiation anomaly by combining multi-source auxiliary data according to the present invention, the method includes the following steps:
A) acquiring microwave radiation remote sensing image data in the earthquake region according to the year, date and place of earthquake occurrence
(microwave radiation remote sensing image is shown in FIG. 2) and historical contemporaneous multi-source auxiliary data, including earth surface coverage classification dataLC(the surface coverage type map is shown in FIG. 3), surface temperature data
And surface moisture data
；
B) Classification based on surface coverage as i: (LC i) Surface temperature data of
And surface moisture data
Surface temperature data classified as i from seismic annual surface coverage
And humidity data
The correlation between the data and the temperature data is selected from historical contemporaneous multisource auxiliary data, wherein the temperature data is classified as i by earth surface coverage on the same day as the earthquake
And earthquake current day humidity data
Set of multiple groups of surface temperature data with highest correlation
Collection of data of land surface humidity
Using the obtained data as the preferred historical auxiliary data of the earth surface coverage classification i to select the set of microwave radiation remote sensing image data which is the same day as the preferred historical auxiliary data
And collecting a plurality of microwave radiation remote sensing image data with the earth surface coverage classified as i
SynthesisRepeating the operation for the incomplete microwave radiation background field data classified as i covered by the earth surface, and further obtaining all the incomplete microwave radiation background field data classified as i covered by the earth surface and combining the incomplete microwave radiation background field data into a complete microwave radiation background field;
C) acquiring earthquake year microwave radiation image data
And microwave radiation image data of earthquake year
And carrying out difference on the data and the complete microwave radiation background field data to obtain seismic microwave radiation abnormal data.
The invention relates to a method for extracting seismic microwave radiation abnormity by combining multisource auxiliary data, which is based on different surface coverage classifications i and is realized by using surface temperature data in historical contemporaneous multisource auxiliary data
And surface moisture data
Temperature data of the day of the earthquake corresponding to the day of the earthquake
And earthquake current day humidity data
Comparing to select sets of surface temperature data closest to the meteorological conditions on the current day of the earthquake in the historical contemporaneous data in the single surface coverage classification area
Collection of data of land surface humidity
And according to the selected set of surface temperature data
Collection of data of land surface humidity
Determining the year and date of the historical contemporaneous data which are similar to the weather conditions of the earthquake on the same day, and extracting a set of microwave radiation remote sensing image data of the corresponding year and date
Great
Calculating to obtain incomplete microwave radiation background field data of single earth surface coverage classification, repeating the above operations to obtain complete microwave radiation background field data of all earth surface coverage classification areas, and obtaining complete microwave radiation background field data of all earth surface coverage classification areas and microwave radiation image data of earthquake year
According to the technical scheme, the influence of surface humidity and surface temperature on microwave radiation is considered, the influence of surface meteorological factors on microwave radiation background field data is greatly reduced, the anti-interference performance of the method is improved, the accuracy is greatly improved, the obtained seismic microwave radiation abnormity can better meet the actual situation, and therefore the method has higher reference value for researching the earthquake based on the radiation abnormity.
Specifically, if the year of the earthquake is Y and the date is T, the year Y of the microwave radiation remote sensing image data and the year Y of the historical contemporaneous multi-source auxiliary data include Y and years before Y, and the date T of the historical contemporaneous multi-source auxiliary data includes days before or after the date T, for example, taking a study of a wenchuan earthquake occurring in 12/5 of 2008, the year of the microwave radiation remote sensing image data and the historical contemporaneous multi-source auxiliary data which need to be acquired may beFrom 2003 to 2008, and the specific date of the historical contemporaneous multi-source auxiliary data in each year may be from 5 months 2 days to 5 months 22 days (the year 2008 does not include 5 months 12 days). Of course, the earth surface temperature data of the current day of the earthquake also needs to be acquired
Earth surface humidity data of the current day of earthquake
Surface coverage data in seismic regionsLCAnd seismic year microwave radiation image data
。
After the required historical contemporaneous multisource auxiliary data is obtained, firstly, the obtained historical contemporaneous multisource auxiliary data is required to be preprocessed, and the preprocessing comprises unified microwave radiation remote sensing image data
Surface coverage classification dataLCSurface temperature data
Surface moisture data
Seismic current day temperature data
Seismic current day humidity data
And seismic year microwave radiation image data
And the extent of the investigation region.
Subsequently, a single surface covering is constructedIncomplete microwave radiation background field of cover classification i
The method comprises the following specific steps:
1) as shown in fig. 3, taking an MCD12C1 data set as an example of the data of the ground cover type, the ground cover type of the data set includes 17 types of ground cover, including water, evergreen coniferous forest, evergreen broadleaf forest, deciduous coniferous forest, deciduous broadleaf forest, mixed forest, dense shrub, loose shrub, multi-tree wasteland, grassland, permanent wetland, farmland, city and built-up area, intersection of farmland and natural vegetation, ice, snow and barren area, so that the value range of i is 1-17; taking 17 matrixes with the same size as the ground surface coverage data in the research area, assigning the coordinate point corresponding to the same ground surface coverage type to be 1 for each ground surface coverage type i, assigning all the coordinate points corresponding to other ground surface coverage types to be 0, and repeating the operation to obtain the mask matrixes of the 17 ground surface coverage classifications
(i = 1-17) and combining the earth surface temperature data of y year and t date
And surface moisture data
Obtaining all surface temperature matrixes with surface coverage type i
And surface humidity matrix
(ii) a According to the established earth surface coverage mask matrix with the earth surface coverage type i in the seismic research area
(i = 1-17) and combining earth surface temperature data of the same day of the earthquake
And earth surface humidity data of earthquake on day
Obtaining a ground surface temperature matrix of the earthquake on the same day with the ground surface coverage type i,
And earthquake day earth surface humidity matrix
(ii) a Surface temperature matrix
Earth surface humidity matrix
Earth surface temperature matrix of earthquake on day
And earthquake day earth surface humidity matrix
The specific calculation method of (a) is as follows:
2) repeating the operation of the step 1) on the historical contemporaneous multisource auxiliary data, continuously calculating the earth surface covering type i in other historical contemporaneous earth surface humidity matrixes and earth surface temperature matrixes, and constructing the earth surface temperature matrixes of the earth surface covering type in all historical contemporaneous earth surface temperature matrixes into an earth surface temperature matrix set
Constructing a single earth surface coverage type earth surface humidity matrix in all historical period into an earth surface humidity matrix set
Y = Y, Y-1, … Y-m, T = T ± 1, T ± 2 … T ± n (m and n are constants), i =1, 2, 3 … 17.
3) Set of surface temperature matrix of single surface coverage type i
Various land-surface temperature matrixes in
Earth surface temperature matrix of the same day as earthquake
Comparison to calculate the earth's surface temperature matrix
Earth surface temperature matrix of the same day as earthquake
The correlation of (c); integrating earth surface humidity matrix
Earth surface humidity matrix in
The current day of earthquakeSurface humidity matrix
Comparing to calculate the earth's surface humidity matrix
Earth surface humidity matrix of the same day of earthquake
In particular, the surface temperature matrix
Earth surface temperature matrix of the same day as earthquake
The matrix correlation between them is expressed as a temperature correlation value
Surface humidity matrix
Earth surface humidity matrix of the same day of earthquake
The matrix correlation between them is expressed as a humidity correlation value
More specifically:
where j and p are the matrix dimensions,
as a surface temperature matrix
Is calculated as the arithmetic mean of the average of the values,
for seismic day surface temperature matrix
Is calculated as the arithmetic mean of the average of the values,
as a surface humidity matrix
Is calculated as the arithmetic mean of the average of the values,
for earthquake day surface humidity matrix
Is calculated as the arithmetic mean of (1).
4) The obtained temperature correlation value
And temperature factor thresholdK 1Comparing and selecting the temperature correlation value
> K 1Earth surface temperature matrix
As preferred historical auxiliary data and recording selected surface temperature matrix
The corresponding year and date of (a); the obtained humidity-related value
And humidity factor thresholdK 2Comparing and selecting the humidity related value
>K 2Earth surface temperature matrix
As preferred historical auxiliary data and recording selected surface temperature matrix
The corresponding year and date of (a),K 1andK 2as an empirical value, it can be set to 0.7 and 0.6, respectively, in the present embodiment; surface temperature matrix with subsequent classification of surface coverage as i
Corresponding year and date of (1) and a surface temperature matrix with a surface coverage classification of i
The corresponding year and date of (a) are intersected to obtain the preferred historical year y 'and date t' of which the earth surface temperature and the earth surface humidity of the earth surface coverage classification i are similar to the earth surface temperature and the earth surface humidity of the earth surface coverage classification i on the day of the earthquake occurrence.
5) Selecting microwave radiation remote sensing image data with the year y 'and the date t' and classified as i by earth surface coverage
Constituting a collection of preferred microwave radiation remote sensing image data of a surface covering type i
}。
6) According to the preferred single earth surface covering type i microwave radiation remote sensing image data collection
Constructing an incomplete microwave radiation background field with a ground surface covering type i
Specifically, it is derived from the following formula:
wherein the content of the first and second substances,N 1is a said collection
The number of matrices in (1).
7) Repeating the steps 1) to 6) to obtain an incomplete microwave radiation background field set of all surface coverage types in the seismic research area
}，
Then, the incomplete microwave radiation background field is collected
All the matrixes in the array are fused to obtain complete microwave radiation background field data
(the complete microwave radiation background field is shown in fig. 4), the specific fusion method is shown as follows:
wherein q refers to the total classification number in the surface coverage classification data, the value of this embodiment is 17, and n is the union operator number.
Finally, will
And earthquake year microwave radiation image data
Comparing to obtain seismic microwave radiation abnormal data
(the seismic microwave radiation anomaly map is shown in fig. 5), the specific comparison mode is shown as the following formula:
although the embodiments of the present invention have been described in detail with reference to the accompanying drawings, the embodiments of the present invention are not limited to the details of the above embodiments, and various simple modifications can be made to the technical solutions of the embodiments of the present invention within the technical idea of the embodiments of the present invention, and the simple modifications all belong to the protection scope of the embodiments of the present invention.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, the embodiments of the present invention do not describe every possible combination.
In addition, any combination of various different implementation manners of the embodiments of the present invention is also possible, and the embodiments of the present invention should be considered as disclosed in the embodiments of the present invention as long as the combination does not depart from the spirit of the embodiments of the present invention.
Claims (11)
1. A method for extracting seismic microwave radiation anomaly by combining multi-source auxiliary data is characterized by comprising the following steps:
A) acquiring microwave radiation remote sensing image data and historical contemporaneous multisource auxiliary data in an earthquake region according to the year, date and place of earthquake occurrence, wherein the historical contemporaneous multisource auxiliary data comprises earth surface coverage classification data, earth surface temperature data and earth surface humidity data;
B) calculating the correlation between the earth surface temperature data and the earth surface humidity data in the single earth surface coverage area and the earthquake year temperature data and the earthquake year humidity data based on the earth surface coverage classification data, and accordingly selecting a plurality of groups of earth surface temperature data and earth surface humidity data with highest correlation with the earthquake day temperature data and the earthquake day humidity data in the historical contemporaneous multisource auxiliary data of the single earth surface coverage area as preferred historical auxiliary data, selecting the microwave radiation remote sensing image data in a single earth surface coverage classification area on the same day as the preferred historical auxiliary data, synthesizing a plurality of microwave radiation remote sensing image data into incomplete microwave radiation background field data of a single earth surface covering classification area, and repeating the operation to construct complete microwave radiation background field data of all the earth surface covering classification areas;
C) acquiring earthquake year microwave radiation image data, and differentiating the earthquake year microwave radiation image data and the complete microwave radiation background field data to obtain earthquake microwave radiation abnormal data.
2. The method for extracting seismic microwave radiation anomaly through united multisource auxiliary data according to claim 1, wherein the year of earthquake occurrence is Y and the date is T, the year Y of the microwave radiation remote sensing image data and the historical contemporaneous multisource auxiliary data comprises Y and years before Y, and the date T of the microwave radiation remote sensing image data and the historical contemporaneous multisource auxiliary data comprises days before or days after the date T.
3. The method for extracting seismic microwave radiation anomalies through combined multi-source auxiliary data as claimed in claim 2, wherein the step of synthesizing the complete microwave radiation background field data in the step B) comprises:
a) preprocessing the surface temperature data and the surface humidity data in the microwave radiation remote sensing image data and the historical contemporaneous multi-source auxiliary data and the surface coverage classification data of the earthquake occurrence area;
b) according to the ground surface coverage classification data, combining the ground surface temperature data and the ground surface humidity data to construct an incomplete microwave radiation background field of a single ground surface coverage classification area;
c) and constructing the incomplete microwave radiation background fields of all the earth surface covering and classifying areas, and fusing and constructing the incomplete microwave radiation background fields of all the earth surface covering and classifying areas into complete microwave radiation background field data with the year of Y and the date of T.
4. The method for extracting seismic microwave radiation anomalies from combined multi-source auxiliary data as claimed in claim 3, characterized in that the preprocessing in step a) includes unifying the resolution of the data and unifying the study areas.
5. The method for extracting seismic microwave radiation anomalies through the joint multi-source auxiliary data according to claim 4, characterized in that the construction step of the incomplete microwave radiation background field in the step b) comprises the following steps:
b1) establishing a ground surface coverage mask matrix with the ground surface coverage type i in the research area according to the ground surface coverage classification data
Combining all the surface temperature data and the surface humidity data with the surface coverage type i, the year y and the date t to obtain a set of surface temperature matrix with the surface coverage type i
Collection of matrix of surface humidity
}; combining the earth surface temperature data and the earth surface humidity data of the current earthquake day to obtain an earth surface temperature matrix of the current earthquake day
And earthquake day earth surface humidity matrix
；
b2) Calculating the surface temperature matrix set (a) with the surface coverage type i one by one
Every earth surface temperature matrix in the earth surface temperature matrix and the earth surface temperature matrix of the earthquake day
Matrix correlation between the two and the surface humidity matrix set
And each earth surface humidity matrix in the earth surface humidity matrix and the earth surface humidity matrix of the earthquake day
Matrix correlation between;
b3) selecting the surface temperature matrix set according with the correlation requirement according to the correlation of the matrix
Great face and the surface humidity matrix set
And according to the earth surface temperature matrix set conforming to the correlation requirement
Great face and the surface humidity matrix set
Is corresponding toThe collection of year and date { (y ', t') }, and the collection of the microwave radiation remote sensing image data for which all the earth surface covering types are i year, y 'and date, t', are obtained
}；
b4) Subjecting said set to a mapping
Calculating all the microwave radiation remote sensing image data in the previous step to obtain the incomplete microwave radiation background field of the single earth surface coverage classification area
。
6. The method for extracting seismic microwave radiation anomalies through combination of multi-source auxiliary data as claimed in claim 5, wherein the surface temperature matrix in step b 2)
And the earth surface temperature matrix of the earthquake on the day
The matrix correlation between them is expressed as a temperature correlation value
：
Where j and p are the matrix dimensions,
is the surface temperature matrix
Is calculated as the arithmetic mean of the average of the values,
for the earth surface temperature matrix of the earthquake day
Is calculated as the arithmetic mean of (1).
7. The method for extracting seismic microwave radiation anomalies through combination of multi-source auxiliary data as claimed in claim 5, wherein the surface humidity matrix in step b 2)
And the earth surface humidity matrix of the earthquake on the day
The matrix correlation between them is expressed as a humidity correlation value
：
Where j and p are the matrix dimensions,
is the ground surface humidity matrix
Is calculated as the arithmetic mean of the average of the values,
for the earth surface humidity matrix of the earthquake on the day
Is calculated as the arithmetic mean of (1).
8. The method for extracting seismic microwave radiation anomalies through combination of multi-source auxiliary data as claimed in claim 5, characterized in that in step b4) the incomplete microwave radiation background field
Is derived from the following formula:
wherein the content of the first and second substances,N 1is a said collection
The number of matrices in (1).
9. The method for extracting seismic microwave radiation anomalies through the joint multi-source auxiliary data as claimed in claim 5, wherein the step of constructing the complete microwave radiation background field in the step c) comprises the following steps:
c1) repeating the operations from step b1) to step b4) to obtain a set of incomplete microwave radiation background fields for all terrain coverage classification areas
}；
c2) According to the ground surface covering classification data, the set of the incomplete microwave radiation background fields of all the ground surface covering classification areas is ready
Combine into a complete microwave radiation background field
。
10. The method for extracting seismic microwave radiation anomalies through combination of multi-source auxiliary data as claimed in claim 9, characterized in that the complete microwave radiation background field data in the step c2)
Is derived from the following formula:
wherein q is the total classification number in the land cover classification data, and n is the union operation sign.
11. The method for extracting seismic microwave radiation anomaly combined with multi-source auxiliary data according to claim 10, wherein the seismic microwave radiation anomaly data in the step C) are
Is derived from the following formula:
wherein the content of the first and second substances,
and the microwave radiation image data of the earthquake year is referred to.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110787048.1A CN113238282B (en) | 2021-07-13 | 2021-07-13 | Method for extracting seismic microwave radiation abnormity by combining multi-source auxiliary data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110787048.1A CN113238282B (en) | 2021-07-13 | 2021-07-13 | Method for extracting seismic microwave radiation abnormity by combining multi-source auxiliary data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113238282A CN113238282A (en) | 2021-08-10 |
| CN113238282B true CN113238282B (en) | 2021-09-28 |
Family
ID=77135308
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110787048.1A Active CN113238282B (en) | 2021-07-13 | 2021-07-13 | Method for extracting seismic microwave radiation abnormity by combining multi-source auxiliary data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113238282B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113762275B (en) * | 2021-11-10 | 2022-02-08 | 中南大学 | Method for extracting seismic microwave radiation anomaly based on moon mean background field |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101793972A (en) * | 2010-03-25 | 2010-08-04 | 强祖基 | Technology for predicting satellite thermal infrared luminance temperature abnormality in short term for strong earthquake |
| CN110632599A (en) * | 2019-09-03 | 2019-12-31 | 华中科技大学 | Atmospheric temperature profile direct inversion method and system |
| CN110673206A (en) * | 2019-08-26 | 2020-01-10 | 吉林大学 | Satellite magnetic field data earthquake abnormity detection method based on non-negative matrix factorization |
| CN112801924A (en) * | 2021-04-15 | 2021-05-14 | 中南大学 | Method for constructing surface pure microwave radiation background field |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015116873A2 (en) * | 2014-02-02 | 2015-08-06 | Ertha Space Technologies | Earthquake forecaster |
-
2021
- 2021-07-13 CN CN202110787048.1A patent/CN113238282B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101793972A (en) * | 2010-03-25 | 2010-08-04 | 强祖基 | Technology for predicting satellite thermal infrared luminance temperature abnormality in short term for strong earthquake |
| CN110673206A (en) * | 2019-08-26 | 2020-01-10 | 吉林大学 | Satellite magnetic field data earthquake abnormity detection method based on non-negative matrix factorization |
| CN110632599A (en) * | 2019-09-03 | 2019-12-31 | 华中科技大学 | Atmospheric temperature profile direct inversion method and system |
| CN112801924A (en) * | 2021-04-15 | 2021-05-14 | 中南大学 | Method for constructing surface pure microwave radiation background field |
Non-Patent Citations (2)
| Title |
|---|
| 断裂活动及孕震过程遥感热异常分析的研究进展;吴立新 等;《测绘学报》;20171031;第46卷(第10期);第1470-1481页 * |
| 汶川地震前多圈层短—临遥感异常回顾及其时空关联性;何苗 等;《遥感学报》;20201231;地681-700页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113238282A (en) | 2021-08-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Mucher et al. | Land cover characterization and change detection for environmental monitoring of pan-Europe | |
| Gao | A comparative study on spatial and spectral resolutions of satellite data in mapping mangrove forests | |
| Rozenstein et al. | Comparison of methods for land-use classification incorporating remote sensing and GIS inputs | |
| Rashid et al. | Geospatial tools for assessing land degradation in Budgam district, Kashmir Himalaya, India | |
| Chen et al. | Mapping forest and their spatial–temporal changes from 2007 to 2015 in tropical hainan island by integrating ALOS/ALOS-2 L-Band SAR and landsat optical images | |
| CN104008552B (en) | Time sequence SAR image cultivated land extraction method based on dynamic time warp | |
| CN109063553A (en) | Field-crop growth defect area's remote sensing fast diagnosis method after a kind of land control | |
| CN111445011A (en) | Mountain fire early warning method based on meteorological and remote sensing data | |
| Chen et al. | Rice crop mapping using Sentinel-1A phenological metrics | |
| CN115236655B (en) | Landslide identification method, system, equipment and medium based on fully-polarized SAR | |
| Mustafa | Spatiotemporal analysis of vegetation cover in Kurdistan region-Iraq using MODIS image data | |
| AU2021102192A4 (en) | Remote sensing classification and identification method, device, equipment and storage medium for soil types | |
| CN112434663B (en) | Power transmission line forest fire detection method, system and medium based on deep learning | |
| CN113238282B (en) | Method for extracting seismic microwave radiation abnormity by combining multi-source auxiliary data | |
| Konda et al. | Vegetation damage assessment due to Hudhud cyclone based on NDVI using Landsat-8 satellite imagery | |
| Yang et al. | Mapping forest in the southern Great Plains with ALOS-2 PALSAR-2 and Landsat 7/8 data | |
| CN111062267A (en) | Time series remote sensing image dimension reduction method | |
| Fu et al. | Forest cover classification with MODIS images in Northeastern Asia | |
| Liu et al. | Environment monitoring of Shanghai Nanhui intertidal zone with dual-polarimetric SAR data based on deep learning | |
| Xue et al. | Flood monitoring by integrating normalized difference flood index and probability distribution of water bodies | |
| Wu et al. | Improving the accuracy of fractional evergreen forest cover estimation at subpixel scale in cloudy and rainy areas by harmonizing landsat-8 and sentinel-2 time-series data | |
| Gaber et al. | Mapping the surface changes in the area of East Port-Said, Egypt using multi-temporal and multi-sensors remote sensing data | |
| Saleem | Using CORONA and Landsat data for evaluating and mapping long-term LULC changes in Iraqi Kurdistan | |
| Adugna et al. | Comparison of FY-3C VIRR and MODIS Time-Series Composite Data for Regional Land Cover Mapping of a Part of Africa | |
| Bitelli et al. | A land in its setting: remote sensing satellite imagery for the characterization of the Eblaite Chora |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |