Fire point credibility judgment method and device and medium

Abstract

The invention discloses a fire point credibility judgment method and device and a medium. The method comprises the following steps: acquiring image data including multi-dimension data information in a preset area; carrying out cloud removal operation on the image data by adopting a cloud recognition algorithm; judging whether the effective image data meets a preset first judgment condition or not pixel by pixel according to the seventh waveband brightness temperature data and the thirteenth waveband brightness temperature data, and obtaining a first judgment result; judging whether the effective image data meets a preset second judgment condition or not pixel by pixel according to the seventh waveband brightness temperature data and the thirteenth waveband brightness temperature data, and obtaining a second judgment result; according to the angle information data, the seventh wave band brightness temperature data, the thirteenth wave band brightness temperature data and the 90-meter ground altitude DEM, whether the effective image data meets a preset third judgment condition or not is judged pixel by pixel, and a third judgment result is obtained; and determining fire point credibility of each pixel of the effective image data according to the first judgment result, the second judgment result and the third judgment result.

Description

Technical Field

[0001] The present invention relates to the technical field of fire point identification, and more specifically, to a fire point credibility determination method, device and medium. Background Art

[0002] Remote sensing can be used to monitor fires over large areas with high time efficiency. The geostationary Fengyun-4B satellite (FY-4B) is the first operational satellite of my country's new generation of geostationary meteorological satellites, the Fengyun-4 series. It can perform high-temporal resolution business applications on fires. The use of this payload can improve business timeliness and stability. However, the threshold identification method is usually used to monitor fires based on satellite remote sensing. This method has limitations on the accuracy of fire identification, especially in areas with complex natural conditions and large differences in underlying surfaces. It is difficult to select thresholds. How to accurately identify thermal power has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention provides a method, device and medium for determining the credibility of a fire point.

[0004] According to one aspect of the present invention, a method for determining the credibility of a fire point is provided, comprising:

[0005] Acquire image data including multiple dimensional data information in a preset area, wherein the multiple dimensional data information includes: angle information data, 7th band brightness temperature data, 13th band brightness temperature data and 90-meter ground elevation DEM;

[0006] Use cloud recognition algorithm to remove cloud from image data and obtain valid image data;

[0007] Judging whether the effective image data satisfies a preset first judgment condition pixel by pixel according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtaining a first judgment result;

[0008] Judging whether the effective image data satisfies a preset second judgment condition pixel by pixel according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtaining a second judgment result;

[0009] According to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM, the valid image data is judged pixel by pixel whether it meets the preset third judgment condition, and a third judgment result is obtained;

[0010] The credibility of the fire point of each pixel of the effective image data is determined according to the first judgment result, the second judgment result and the third judgment result.

[0011] Optionally, obtaining image data including multiple dimensional data information in a preset area includes:

[0012] Extract the angle information data from the Fengyun-4B satellite image in the preset area;

[0013] Carry out radiometric calibration on the FY-4B image to obtain the brightness temperature data of the 7th and 13th bands;

[0014] Image data including multiple dimensional data information is determined based on the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM in the preset area.

[0015] Optionally, judging pixel by pixel whether the valid image data meets a preset first judgment condition according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtaining a first judgment result includes:

[0016] Get the valid pixel set of band 7 within the preset range of each pixel in the brightness temperature data of band 7;

[0017] Calculate the mean of the effective values ​​of the 7th band and the average absolute variance of the 7th band of the pixels corresponding to the set of effective pixels of the 7th band that meet the preset conditions;

[0018] Get the valid pixel set of band 13 within the preset range of each pixel in the brightness temperature data of band 13;

[0019] Calculate the mean of the effective values ​​of the 13th band and the average absolute variance of the 13th band of the pixels corresponding to the set of effective pixels of the 13th band that meet the preset conditions;

[0020] According to the 7th band effective value mean, the 7th band average absolute variance, the 13th band effective value mean and the 13th band average absolute variance of each pixel, it is judged whether each pixel of the effective image data meets the first judgment condition, and the first judgment result is obtained.

[0021] Optionally, the first judgment condition P1 is P11∧P12∧P13∧P14, wherein:

[0022] P11:

[0023] P12:

[0024] P13:

[0025] P14:

[0026] in,

[0027]

[0028] Where M 7 is the mean effective value of the 7th band; T7 is the mean absolute variance of the 7th band; M 13 is the mean effective value of the 13th band; T 13 is the mean absolute variance of the 13th band, the set of valid pixels of the 7th band The set of valid pixels in band 13 is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels of the pixel (i, j), It is the brightness temperature value of the 13th band of the pixel (a, b) within N pixels from the pixel (i, j).

[0029] Optionally, judging pixel by pixel whether the valid image data meets a preset second judgment condition according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtaining a second judgment result includes:

[0030] Calculate the average value of the difference between the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, the mean value of the effective value of the difference, and the average absolute variance of the difference for each pixel;

[0031] According to the difference average value, difference effective value mean value and difference average absolute variance of each pixel, it is judged whether each pixel of the effective image data meets the second judgment condition, and a second judgment result is obtained.

[0032] Optionally, the second judgment condition P2 is P21∧P22∧P23∧P24, wherein:

[0033] P21:

[0034] P22:

[0035] P23:

[0036] P24:

[0037] in,

[0038]

[0039]

[0040] In the formula, ΔS N is the average value of the difference; ΔM is the mean of the effective value of the difference; ΔT is the average absolute variance of the difference, is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels of the pixel (i, j), It is the brightness temperature value of the 13th band of the pixel (a, b) within N pixels from the pixel (i, j).

[0041] Optionally, the angle information data includes satellite zenith angle, satellite azimuth angle, solar zenith angle and solar azimuth angle, and,

[0042] According to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM, the valid image data is pixel by pixel determined to determine whether it meets the preset third judgment condition, and the third judgment result is obtained, including:

[0043] Calculate the mean and standard deviation of the brightness temperature data of the 7th band and the 13th band in the 3*3 sliding window respectively, and obtain the mean of the 7th band, the standard deviation of the 7th band, the mean of the 13th band, and the standard deviation of the 13th band;

[0044] The 7th band mean, 7th band standard deviation, 13th band mean, 13th band standard deviation, satellite zenith angle, satellite azimuth angle, solar zenith angle, solar azimuth angle, 7th band brightness temperature data, 13th band brightness temperature data and 90-meter ground elevation DEM of each pixel are input into the pre-trained thermal power detection model, and the fire point identification result of each pixel in the effective image data is output;

[0045] According to the fire point recognition result of each pixel, it is judged whether each pixel of the effective image data meets the third judgment condition, and the third judgment result is obtained, wherein the third judgment condition P3 is: (i,j) =1, where F (i,j) is the fire point identification result of pixel (i, j).

[0046] Optionally, the judgment formula of the fire point credibility Q is:

[0047]

[0048] In the formula, P1 is the first judgment condition, P2 is the second judgment condition, and P3 is the third judgment condition.

[0049] According to another aspect of the present invention, there is provided a fire point credibility determination device, comprising:

[0050] An acquisition module is used to acquire image data including multiple dimensional data information in a preset area, wherein the multiple dimensional data information includes: angle information data, 7th band brightness temperature data, 13th band brightness temperature data and 90-meter ground altitude DEM;

[0051] A cloud removal module is used to remove the cloud from the image data using a cloud recognition algorithm to obtain valid image data;

[0052] A first judgment module is used to judge whether the valid image data satisfies a preset first judgment condition pixel by pixel according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtain a first judgment result;

[0053] A second judgment module is used to judge whether the valid image data satisfies a preset second judgment condition pixel by pixel according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtain a second judgment result;

[0054] A third judgment module is used to judge whether the valid image data satisfies a preset third judgment condition pixel by pixel according to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM, and obtain a third judgment result;

[0055] The determination module is used to determine the credibility of the fire point of each pixel of the effective image data according to the first judgment result, the second judgment result and the third judgment result.

[0056] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute the method described in any one of the above aspects of the present invention.

[0057] According to another aspect of the present invention, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of the above aspects of the present invention.

[0058] Therefore, the present invention proposes a method for determining the credibility of fire points. By acquiring image data including multiple dimensional data information in a preset area, preset condition judgments are gradually performed, and the credibility of fire points in the preset area is determined based on the judgment results. A combination of conditional threshold and random forest model is used to identify fire points, thereby improving the accuracy of fire point detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0060] Figure 1 It is a flow chart of a method for determining the credibility of a fire point provided by an exemplary embodiment of the present invention;

[0061] Figure 2 is another flow chart of a method for determining the credibility of a fire point provided by an exemplary embodiment of the present invention;

[0062] Figure 3 It is a structural schematic diagram of a fire point credibility determination device provided by an exemplary embodiment of the present invention;

[0063] Figure 4 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0064] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described here.

[0065] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0066] Those skilled in the art can understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0067] It should also be understood that, in the embodiments of the present invention, “plurality” may refer to two or more than two, and “at least one” may refer to one, two or more than two.

[0068] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0069] In addition, the term "and / or" in the present invention is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects before and after are in an "or" relationship.

[0070] It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced to each other, and for the sake of brevity, they will not be described one by one.

[0071] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0072] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0073] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0074] It should be noted that like reference numerals and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof will not be necessary in subsequent figures.

[0075] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate together with numerous other general-purpose or special-purpose computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, servers, etc. include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, minicomputer systems, mainframe computer systems, and distributed cloud computing technology environments including any of the above systems, and so on.

[0076] Terminal devices, computer systems, servers and other electronic devices can be described in the general context of computer system-executable instructions (such as program modules) executed by a computer system. Generally, program modules can include routines, programs, object programs, components, logics, data structures, etc., which perform specific tasks or implement specific abstract data types. The computer system / server can be implemented in a distributed cloud computing environment where tasks are executed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0077] Exemplary Methods

[0078] Figure 1 It is a schematic flowchart of a fire point credibility determination method provided by an exemplary embodiment of the present invention. This embodiment can be applied to an electronic device, such as Figure 1 As shown, the fire point credibility determination method 100 includes the following steps:

[0079] Step 101, obtain image data including multi-dimensional data information within a preset area, where the multi-dimensional data information includes: angle information data, brightness temperature data of the 7th band, brightness temperature data of the 13th band, and 90-meter ground elevation DEM;

[0080] Step 102, perform cloud removal operation on the image data using a cloud recognition algorithm to obtain effective image data;

[0081] Step 103, based on the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, determine for each pixel of the effective image data whether it meets a preset first judgment condition, and obtain a first judgment result;

[0082] Step 104, judging whether the effective image data satisfies a preset second judgment condition pixel by pixel according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtaining a second judgment result;

[0083] Step 105, judging whether the valid image data satisfies a preset third judgment condition pixel by pixel according to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM, and obtaining a third judgment result;

[0084] Step 106, determining the credibility of the fire point of each pixel of the effective image data according to the first judgment result, the second judgment result and the third judgment result.

[0085] Specifically, in order to solve the technical problems existing in the background technology, the present invention adopts a combination method of conditional threshold and random forest model to identify fire points. Figure 2 As shown, the specific steps are as follows:

[0086] Step 1) Radiometric calibration was performed on the FY4B band data of the Fengyun-4B satellite, and the band values ​​were converted into reflectivity or brightness temperature. The brightness temperature data of the two bands B7 and B13 in the study area and the grid data of four angle information (satellite zenith angle VZA, satellite azimuth angle VAA, solar zenith angle SZA, and solar azimuth angle SAA) were obtained. The 90-meter ground elevation data DEM was resampled to the same resolution as the FY4B band data to produce grid data.

[0087] Step 2) Use the cloud identification product produced by the China Meteorological Administration to remove clouds; the cloud and invalid values ​​are taken as X=65535; and the grid data of the two valid bands B7 and B13 and four angle information (satellite zenith angle VZA, satellite azimuth angle VAA, solar zenith angle SZA, solar azimuth angle SAA) are obtained.

[0088] Step 3) Determine the fire point in the cloud-free area:

[0089] Judgment condition P1 (P11∧P12∧P13∧P14): Use two bands B 7 (3.75μm)B 13 (10.80μm) is used to make the first judgment on the fire point. The set of all valid pixels within N pixels around the pixel (i, j) is taken. Where N∈{1,2,3,4,5,6}, N is within the value range, satisfying (|S N | represents the number of set elements, which is different from the absolute value), then keep N and calculate band B 7 The mean of all valid values ​​around pixel (i, j) Mean absolute variance T7 = Similarly, we get band B 13 The mean of all valid values ​​around pixel (i, j) Mean absolute variance ε 0 The value is 0.25.

[0090] Condition P11:

[0091] Condition P12:

[0092] Condition P13:

[0093] Condition P14:

[0094] In the formula, and Respectively represent band B 7 (3.75μm)B 13 Brightness temperature at effective pixel (i,j) (10.80μm), ε 1 , ε 2 , ε 3 and ε 4 For the determination threshold, the values ​​are 320K, 15K, 4K and 4K.

[0095] Judgment condition P2 (P21∧P22∧P23∧P24): Use two bands B 7 (3.75μm)B 13 (10.80μm) for the second judgment of the fire point. The average value of the difference between the two channels The mean of the effective value of the difference between the two channels The mean absolute square error of the difference between the two channels

[0096] Condition P21:

[0097] Condition P22:

[0098] Condition P23:

[0099] Condition P24:

[0100] In the formula, ε 5 , ε 6 , ε 7 and ε 8 For the determination threshold, the values ​​are 3.5, 6K, 3, and -4K respectively.

[0101] Judgment condition P3: Use the random forest algorithm to make the third judgment on the fire point, combined with the effective value grid data in step 2), calculate B 7 , B 13 The mean and standard deviation of the 3*3 sliding window are denoted as MB 7 、MB 13 and SB 7 , SB 13 , where all valid results are found in the 3*3 range before calculation. Get the final 11 elements B 7 , B 13 、MB 7 、MB 13 , SB 7 , SB 13 , VZA, VAA, SZA, SAA and DEM data, according to the forest fire information data of the forestry department, extract sample points and set the fire points to 1 and non-fire points to 0, use the random forest algorithm to learn the model, and use the model to predict the fire points in grid F. For pixel (i, j):

[0102] Condition P3: F (i,j) =1

[0103] Step 4) Confirm the fire point credibility according to step 3) and set the credibility to 1, 2, 3.

[0104] For a certain pixel, comprehensively judge the credibility of the fire point Q, where:

[0105]

[0106] Among them, 0 is a non-fire point, and the credibility of 1-2-3 fire points gradually increases.

[0107] Therefore, the present invention proposes a method for determining the credibility of fire points. By acquiring image data including multiple dimensional data information in a preset area, preset condition judgments are gradually performed, and the credibility of fire points in the preset area is determined based on the judgment results. A combination of conditional threshold and random forest model is used to identify fire points, thereby improving the accuracy of fire point detection.

[0108] Exemplary Devices

[0109] Figure 3 FIG. 1 is a schematic diagram of the structure of a fire point credibility determination device provided by an exemplary embodiment of the present invention. Figure 3 As shown, the device 300 includes:

[0110] An acquisition module 310 is used to acquire image data including multiple dimensional data information in a preset area, wherein the multiple dimensional data information includes: angle information data, brightness temperature data of the 7th band, brightness temperature data of the 13th band, and a 90-meter ground altitude DEM;

[0111] A cloud removal module 320 is used to remove the cloud from the image data using a cloud recognition algorithm to obtain valid image data;

[0112] The first judgment module 330 is used to judge whether the valid image data satisfies a preset first judgment condition pixel by pixel according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtain a first judgment result;

[0113] The second judgment module 340 is used to judge whether the effective image data satisfies a preset second judgment condition pixel by pixel according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtain a second judgment result;

[0114] The third judgment module 350 is used to judge whether the valid image data satisfies a preset third judgment condition pixel by pixel according to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM, and obtain a third judgment result;

[0115] The determination module 360 ​​is used to determine the credibility of the fire point of each pixel of the effective image data according to the first judgment result, the second judgment result and the third judgment result.

[0116] Optionally, the acquisition module 310 includes:

[0117] An extraction submodule is used to extract angle information data from the FY-4B satellite image in a preset area;

[0118] The radiation calibration submodule is used to perform radiation calibration on the FY-4B satellite image and obtain the brightness temperature data of the 7th band and the 13th band;

[0119] The determination submodule is used to determine image data including multiple dimensional data information based on the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM in the preset area.

[0120] Optionally, the first determination module 330 includes:

[0121] The first acquisition submodule is used to obtain a set of valid pixels in the 7th band within a preset range of each pixel in the brightness temperature data of the 7th band;

[0122] The first calculation submodule is used to calculate the 7th band effective value mean and the 7th band average absolute variance of the pixels corresponding to the 7th band effective pixel set that meets the preset conditions;

[0123] The second acquisition submodule is used to obtain a set of valid pixels in the 13th band within a preset range of each pixel in the brightness temperature data of the 13th band;

[0124] The second calculation submodule is used to calculate the 13th band effective value mean and the 13th band average absolute variance of the pixels corresponding to the 13th band effective pixel set that meets the preset conditions;

[0125] The first judgment submodule is used to judge whether each pixel of the valid image data meets the first judgment condition according to the mean of the effective value of the 7th band of each pixel, the average absolute variance of the 7th band, the mean of the effective value of the 13th band and the average absolute variance of the 13th band, and obtain the first judgment result.

[0126] Optionally, the first judgment condition P1 is P11∧P12∧P13∧P14, wherein:

[0127] P11:

[0128] P12:

[0129] P13:

[0130] P14:

[0131] in,

[0132]

[0133] Where M 7 is the mean effective value of the 7th band; T 7 is the mean absolute variance of the 7th band; M 13 is the mean effective value of the 13th band; T 13 is the mean absolute variance of the 13th band, the set of valid pixels of the 7th band The set of valid pixels in band 13 is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels of the pixel (i, j), It is the brightness temperature value of the 13th band of the pixel (a, b) within N pixels from the pixel (i, j).

[0134] Optionally, the second determination module 340 includes:

[0135] The third calculation submodule is used to calculate the difference average value, difference effective value mean value and difference average absolute variance between the brightness temperature data of the 7th band and the brightness temperature data of the 13th band pixel by pixel;

[0136] The second judgment submodule is used to judge whether each pixel of the valid image data meets the second judgment condition according to the difference average value, the difference effective value mean value and the difference average absolute variance of each pixel, and obtain the second judgment result.

[0137] Optionally, the second judgment condition P2 is P21 ∧ P22 ∧ P23 ∧ P24, where,

[0138] P21:

[0139] P22:

[0140] P23:

[0141] P24:

[0142] where,

[0143]

[0144] In the formula, ΔS N is the average value of the difference; ΔM is the mean value of the effective value of the difference; ΔT is the average absolute variance of the difference, is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels from the pixel (i, j), is the brightness temperature value of the 13th band of the pixel (a, b) within N pixels from the pixel (i, j).

[0145] Optionally, the angle information data includes the satellite zenith angle, the satellite azimuth angle, the solar zenith angle, and the solar azimuth angle, and,

[0146] The third judgment module 350 includes:

[0147] The fourth calculation sub-module is used to calculate the mean and standard deviation of the brightness temperature data of the 7th band and the 13th band in a 3*3 sliding window respectively, and obtain the 7th band mean, the 7th band standard deviation, the 13th band mean, and the 13th band standard deviation;

[0148] The detection sub-module is used to input the 7th band mean, the 7th band standard deviation, the 13th band mean, the 13th band standard deviation, the satellite zenith angle, the satellite azimuth angle, the solar zenith angle, the solar azimuth angle, the 7th band brightness temperature data, the 13th band brightness temperature data, and the 90-meter ground elevation DEM of each pixel into a pre-trained thermal power detection model, and output the fire point recognition result of each pixel in the effective image data;

[0149] The third judgment sub-module is used to judge whether each pixel of the effective image data meets the third judgment condition according to the fire point recognition result of each pixel, and obtain the third judgment result, where the third judgment condition P3 is: F (i,j) = 1, where F (i,j) is the fire point recognition result of the pixel (i, j).

[0150] Optionally, the judgment formula of the fire point credibility Q is:

[0151]

[0152] In the formula, P1 is the first judgment condition, P2 is the second judgment condition, and P3 is the third judgment condition.

[0153] Exemplary Electronic Devices

[0154] Figure 4 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. Figure 4 As shown, the electronic device 40 includes one or more processors 41 and a memory 42 .

[0155] The processor 41 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0156] The memory 42 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 41 may run the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device may also include: an input device 43 and an output device 44, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0157] In addition, the input device 43 may also include, for example, a keyboard, a mouse, etc.

[0158] The output device 44 can output various information to the outside, and can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto.

[0159] Of course, to simplify, Figure 4 Only some of the components related to the present invention in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0160] Exemplary computer program products and computer-readable storage media

[0161] In addition to the above methods and devices, embodiments of the present invention may also be computer program products, which include computer program instructions that, when run on a processor, cause the processor to execute the steps in the methods according to various embodiments of the present invention described in the above "Exemplary Methods" section of this specification.

[0162] The computer program product may be written in any combination of one or more programming languages for programming code to perform the operations of the embodiments of the present invention. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The programming code may be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0163] Furthermore, embodiments of the present invention may also be computer-readable storage media having computer program instructions stored thereon that, when run on a processor, cause the processor to execute the steps in the methods according to various embodiments of the present invention described in the above "Exemplary Methods" section of this specification.

[0164] The computer-readable storage media may employ any combination of one or more readable media. The readable media may be a readable signal media or a readable storage media. The readable storage media may, for example, include but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or combinations thereof. More specific examples (a non-exhaustive list) of the readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0165] The basic principles of the present invention have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present invention are only examples and not limitations, and it cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present invention. In addition, the above-disclosed specific details are only for the purposes of illustration and facilitating understanding, and are not limitations. The above details do not limit the present invention to necessarily adopt the above specific details for implementation.

[0166] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0167] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, systems, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The word "such as" used here refers to the phrase "such as but not limited to", and can be used interchangeably with it.

[0168] The method and system of the present invention may be implemented in many ways. For example, the method and system of the present invention may be implemented by software, hardware, firmware or any combination of software, hardware, firmware. The above order of steps for the method is only for illustration, and the steps of the method of the present invention are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present invention may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.

[0169] It should also be noted that in the system, device and method of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. The above description of the disclosed aspects is provided to enable any technician in the field to make or use the present invention. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined here can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown here, but in accordance with the widest range consistent with the principles and novel features disclosed here.

[0170] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for determining the credibility of a fire point, characterized in that: include: Acquire image data including multiple dimensional data information in a preset area, wherein the multiple dimensional data information includes: angle information data, 7th band brightness temperature data, 13th band brightness temperature data and 90-meter ground elevation DEM; Using a cloud recognition algorithm to perform a cloud removal operation on the image data to obtain valid image data; According to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, judging pixel by pixel whether the valid image data meets a preset first judgment condition, and obtaining a first judgment result; According to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, judging pixel by pixel whether the valid image data meets a preset second judgment condition, and obtaining a second judgment result; According to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM, pixel by pixel of the valid image data is judged whether a preset third judgment condition is met, and a third judgment result is obtained; The credibility of the fire points of each pixel of the valid image data is determined according to the first judgment result, the second judgment result and the third judgment result.

2. The method according to claim 1, characterized in that Obtaining image data including multiple dimensional data information within a preset area, including: Extract the angle information data from the Fengyun-4B satellite image in the preset area; Performing radiometric calibration on the FY-4B image to obtain the brightness temperature data of the 7th band and the brightness temperature data of the 13th band; The image data including multiple dimensional data information is determined according to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM in the preset area.

3. The method according to claim 1, characterized in that The method further comprises: determining pixel by pixel whether the valid image data satisfies a preset first determination condition according to the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a first determination result, including: Obtain a set of valid pixels in the 7th band within a preset range of each pixel in the brightness temperature data of the 7th band; Calculate the mean of the effective values ​​of the 7th band and the average absolute variance of the 7th band of the pixels corresponding to the set of effective pixels of the 7th band that meet the preset conditions; Obtain a set of valid pixels in the 13th band within a preset range of each pixel in the brightness temperature data of the 13th band; Calculate the mean of the effective values ​​of the 13th band and the average absolute variance of the 13th band of the pixels corresponding to the set of effective pixels of the 13th band that meet the preset conditions; According to the mean of the effective values ​​of the 7th band, the average absolute variance of the 7th band, the mean of the effective values ​​of the 13th band and the average absolute variance of the 13th band of each pixel, it is judged whether each pixel of the effective image data meets the first judgment condition, and the first judgment result is obtained.

4. The method according to claim 3, characterized in that The first judgment condition P1 is P11∧P12∧P13∧P14, where: P11： P12： P13： P14： in, Where, M7 is the mean of the effective value of the 7th band; T7 is the average absolute variance of the 7th band; M 13 is the mean effective value of the 13th band; T 13 is the mean absolute variance of the 13th band, the set of valid pixels of the 7th band The set of valid pixels in band 13 N∈{1,2,3,4,5,6}, is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels of the pixel (i, j), It is the brightness temperature value of the 13th band of the pixel (a, b) within N pixels from the pixel (i, j).

5. The method according to claim 1, characterized in that The method further comprises: determining pixel by pixel whether the valid image data satisfies a preset second judgment condition according to the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a second judgment result, including: Calculate the difference average value, difference effective value mean value and difference average absolute variance between the brightness temperature data of the 7th band and the brightness temperature data of the 13th band pixel by pixel; According to the difference average value, the difference effective value mean value and the difference average absolute variance of each pixel, it is judged whether each pixel of the valid image data meets the second judgment condition, and the second judgment result is obtained.

6. The method according to claim 5, characterized in that The second judgment condition P2 is P21∧P22∧P23∧P24, where: P21： P22： P23： P24： in, In the formula, ΔS N is the average value of the difference; ΔM is the mean of the effective value of the difference; ΔT is the average absolute variance of the difference, N∈{1,2,3,4,5,6}, is the brightness temperature value of the 7th band within N pixels of pixel (i,j) of pixel (a,b), It is the brightness temperature value of the 13th band of the pixel (a, b) within N pixels from the pixel (i, j).

7. The method according to claim 1, characterized in that The angle information data includes satellite zenith angle, satellite azimuth angle, solar zenith angle and solar azimuth angle, and, The method further comprises: determining pixel by pixel whether the valid image data satisfies a preset third judgment condition according to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM, and obtaining a third judgment result, including: Calculate the mean and standard deviation of the brightness temperature data of the 7th band and the brightness temperature data of the 13th band in a 3*3 sliding window respectively, and obtain the mean of the 7th band, the standard deviation of the 7th band, the mean of the 13th band, and the standard deviation of the 13th band; Input the 7th band mean, 7th band standard deviation, 13th band mean, 13th band standard deviation, satellite zenith angle, satellite azimuth angle, solar zenith angle, solar azimuth angle, the 7th band brightness temperature data, the 13th band brightness temperature data and the 90-meter ground altitude DEM of each pixel into the pre-trained thermal power detection model, and output the fire point recognition result of each pixel in the effective image data; According to the fire point recognition result of each pixel, it is judged whether each pixel of the effective image data meets the third judgment condition, and the third judgment result is obtained, wherein the third judgment condition P3 is: (i,j) =1, where F (i,j) is the fire point identification result of pixel (i, j).

8. The method according to claim 1, characterized in that: The judgment formula of the fire point credibility Q is: In the formula, P1 is the first judgment condition, P2 is the second judgment condition, and P3 is the third judgment condition.

9. A fire point credibility determination device, characterized in that: include: An acquisition module is used to acquire image data including multiple dimensional data information in a preset area, wherein the multiple dimensional data information includes: angle information data, 7th band brightness temperature data, 13th band brightness temperature data and 90-meter ground altitude DEM; A cloud removal module, used to perform a cloud removal operation on the image data using a cloud recognition algorithm to obtain valid image data; A first judgment module is used to judge whether the valid image data satisfies a preset first judgment condition pixel by pixel according to the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtain a first judgment result; A second judgment module is used to judge whether the valid image data satisfies a preset second judgment condition pixel by pixel according to the brightness temperature data of the 7th band and the brightness temperature data of the 13th band, and obtain a second judgment result; A third judgment module is used to judge whether the valid image data satisfies a preset third judgment condition pixel by pixel according to the angle information data, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 90-meter ground altitude DEM, and obtain a third judgment result; A determination module is used to determine the credibility of the fire points of each pixel of the valid image data according to the first judgment result, the second judgment result and the third judgment result.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute any method according to claim 8.

Images