A fire point credibility determination method, device and medium

Abstract

The present invention discloses a method, device, and medium for determining the credibility of a fire point. The method includes: acquiring image data including multi-dimensional data information within a preset area; performing a cloud removal operation on the image data using a cloud recognition algorithm; determining whether a preset first judgment condition is satisfied for each pixel of the valid image data based on the 7th band brightness temperature data and the 13th band brightness temperature data, thereby obtaining a first judgment result; determining whether a preset second judgment condition is satisfied for each pixel of the valid image data based on the 7th band brightness temperature data and the 13th band brightness temperature data, thereby obtaining a second judgment result; determining whether a preset third judgment condition is satisfied for each pixel of the valid image data based on angle information data, the 7th band brightness temperature data, the 13th band brightness temperature data, and a 90-meter ground elevation DEM, thereby obtaining a third judgment result; and determining the credibility of the fire point for each pixel of the valid image data based on the first, second, and third judgment results.

Description

Technical Field

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

[0002] Remote sensing allows for large-scale, high-efficiency fire monitoring. The geostationary Fengyun-4B (FY-4B), the first operational satellite in my country's new generation of geostationary meteorological satellites, can monitor fires with high temporal resolution. This payload improves operational efficiency and stability. However, satellite remote sensing fire monitoring typically uses a threshold identification method, which has limited accuracy, particularly in areas with complex natural conditions and large variations in underlying surface areas. Therefore, accurately identifying thermal power plants has become a pressing technical challenge. Summary of the Invention

[0003] In view of the deficiencies of 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 fire point credibility is provided, comprising:

[0005] Acquire image data including multiple dimensional data information within 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 elevation DEM;

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

[0007] determining, pixel by pixel, whether the valid image data satisfies a preset first judgment condition based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a first judgment result;

[0008] Determining whether the valid image data satisfies a preset second determination condition pixel by pixel based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a second determination result;

[0009] Determine whether the valid image data satisfies a preset third judgment condition pixel by pixel 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, and obtain a third judgment result;

[0010] The credibility of the fire point of each pixel of the valid image data is determined based on the first judgment result, the second judgment result and the third judgment result.

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

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

[0013] Radiometric calibration was performed on the Fengyun-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, determining whether the valid image data satisfies a preset first determination condition pixel by pixel based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a first determination 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 effective value 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 effective value mean of the 7th band, the average absolute variance of the 7th band, the effective value mean 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 a 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, 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 Valid pixel set of band 13 is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels from 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, determining whether the valid image data satisfies a preset second determination condition pixel by pixel based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a second determination result, includes:

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

[0031] According to the difference average value, the difference effective value mean value and the difference average absolute square deviation of each pixel, it is judged whether each pixel of the valid 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] Where, ΔS N is the mean value of the difference; ΔM is the mean effective value of the difference; ΔT is the mean 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). 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] The valid image data is judged pixel by pixel 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 elevation DEM to determine whether the preset third judgment condition is met, and a 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 value of the 7th band, the standard deviation of the 7th band, the mean value of the 13th band, and the standard deviation of the 13th band;

[0044] The mean value of the 7th band, the standard deviation of the 7th band, the mean value of the 13th band, the standard deviation of the 13th band, the satellite zenith angle, the satellite azimuth angle, the solar zenith angle, the solar azimuth angle, the brightness temperature data of the 7th band, the brightness temperature data of the 13th band, and the 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: F (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] Wherein, 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 configured to acquire image data within a preset area, including multiple dimensional data information, 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 elevation DEM;

[0051] The 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, configured to judge, pixel by pixel, whether the valid image data satisfies a preset first judgment condition based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtain a first judgment result;

[0053] a second judgment module, configured to judge, pixel by pixel, whether the valid image data satisfies a preset second judgment condition based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtain a second judgment result;

[0054] a third judgment module, configured to determine whether the valid image data satisfies a preset third judgment condition pixel by pixel 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, 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 valid 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 according to 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; and the processor for reading the executable instructions from the memory and executing 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 multi-dimensional data information in a preset area, preset condition judgments are gradually performed. According to the judgment results, the credibility of the fire points in the preset area is determined, and a combination of conditional thresholds and random forest models 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 1 is a flow chart of a method for determining fire point credibility provided by an exemplary embodiment of the present invention;

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

[0062] Figure 3 1 is a schematic structural 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 herein.

[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 will understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, 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, “a plurality of” 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 this invention merely describes an association relationship between related objects, indicating that three possible relationships exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Furthermore, the character " / " in this invention generally indicates that the related objects 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 with each other. 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, they 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 therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0075] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate in conjunction with numerous other general-purpose or specialized computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with terminal devices, computer systems, servers, and other electronic devices 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.

[0076] Electronic devices such as terminal devices, computer systems, and servers 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, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked via 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 FIG. 1 is a flow chart of a method for determining the credibility of a fire point provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as Figure 1 As shown, the fire point credibility determination method 100 includes the following steps:

[0079] Step 101: Acquire image data including multiple dimensional data information within 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 elevation DEM;

[0080] Step 102: Using a cloud recognition algorithm to perform a cloud removal operation on the image data to obtain valid image data;

[0081] Step 103: determining whether the valid image data satisfies a preset first determination condition pixel by pixel based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a first determination result;

[0082] Step 104: determining whether the valid image data satisfies a preset second determination condition pixel by pixel based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a second determination result;

[0083] Step 105 , determining whether the valid image data satisfies a preset third judgment condition pixel by pixel 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 elevation DEM, and obtaining a third judgment result;

[0084] Step 106: Determine the credibility of the fire point of each pixel of the valid image data based on 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 The specific steps are as follows:

[0086] Step 1) Radiometric calibration was performed on the FY4B band data from the Fengyun-4B satellite, converting the band values ​​into reflectance or brightness temperature. Gridded data for brightness temperature data for bands B7 and B13, as well as four angles (satellite zenith angle VZA, satellite azimuth angle VAA, solar zenith angle SZA, and solar azimuth angle SAA) were obtained for the study area. The gridded data were generated by resampling the 90-meter ground elevation DEM to the same resolution as the FY4B band data.

[0087] Step 2) Use the cloud identification product produced by the China Meteorological Administration to remove clouds; the cloud and invalid values ​​are set to X = 65535; obtain 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).

[0088] Step 3) Determine the fire point in the cloudless area:

[0089] Judgment condition P1 (P11∧P12∧P13∧P14): Use two bands B7 (3.75μm) B 13 (10.80μm) to make the first judgment of 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 elements in the set, which is different from the absolute value), then retain N and calculate the mean of all valid values ​​of band B7 around pixel (i, j) Mean absolute variance T7 = Similarly, we get band B13 The mean of all valid values ​​around pixel (i, j) mean absolute variance ε0 takes the value of 0.25.

[0090] Condition P11:

[0091] Condition P12:

[0092] Condition P13:

[0093] Condition P14:

[0094] Where, and Respectively represent band B7 (3.75μm) B 13 The brightness temperature value at the effective pixel (i, j) of (10.80μm), ε1, ε2, ε3 and ε4 are the judgment thresholds, and the values ​​are 320K, 15K, 4K and 4K.

[0095] Judgment condition P2 (P21∧P22∧P23∧P24): using two bands B7 (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] Where ε5, ε6, ε7 and ε8 are the decision thresholds, which 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), to calculate B7 and B 13 The mean and standard deviation of the 3*3 sliding window are denoted as MB7 and MB 13 and SB7, SB 13 , where all valid results are found within the 3*3 range before calculation. Get the final 11 elements B7, B13 、MB7、MB 13 ,SB7,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 the 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, or 3.

[0104] For a certain pixel, comprehensively judge the fire point credibility 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 multi-dimensional data information in a preset area, preset condition judgments are gradually performed. According to the judgment results, the credibility of the fire points in the preset area is determined, and a combination of conditional thresholds and random forest models 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 a fire point credibility determination device provided by an exemplary embodiment of the present invention. Figure 3 As shown, the apparatus 300 includes:

[0110] An acquisition module 310 is configured to acquire image data within a preset area, including multiple dimensional data information, 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 elevation DEM;

[0111] The cloud removal module 320 is used to perform cloud removal operations on the image data using a cloud recognition algorithm to obtain valid image data;

[0112] The first judgment module 330 is configured to judge whether the valid image data satisfies a preset first judgment condition pixel by pixel based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtain a first judgment result;

[0113] The second judgment module 340 is configured to judge whether the valid image data satisfies a preset second judgment condition pixel by pixel based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtain a second judgment result;

[0114] A third determination module 350 is configured to determine, pixel by pixel, whether the valid image data satisfies a preset third determination condition based on the angle information data, the brightness temperature data of the 7th and 13th bands, and the 90-meter ground elevation DEM, and obtain a third determination result.

[0115] The determination module 360 ​​is used to determine the credibility of the fire point of each pixel of the valid 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] The extraction submodule is used to extract the angle information data from the Fengyun-4B satellite image in the preset area;

[0118] The radiometric calibration submodule is used to perform radiometric calibration on the Fengyun-4B satellite image and obtain the brightness temperature data of the 7th and 13th bands.

[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 judgment 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 based on the mean effective value of the 7th band, the average absolute variance of the 7th band, the mean effective value of the 13th band, and the average absolute variance of the 13th band of each pixel, and obtain a 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, 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 Valid pixel set of band 13 is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels from 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 judgment module 340 includes:

[0135] The third calculation submodule is used to calculate the difference average value, difference effective value mean and difference average absolute square error 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, difference effective value mean and difference average absolute square deviation of each pixel, and obtain a second judgment result.

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

[0138] P21:

[0139] P22:

[0140] P23:

[0141] P24:

[0142] in,

[0143]

[0144] Where, ΔS N is the mean value of the difference; ΔM is the mean effective value of the difference; ΔT is the mean 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). It 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 satellite zenith angle, satellite azimuth angle, solar zenith angle and solar azimuth angle, and,

[0146] The third judgment module 350 includes:

[0147] The fourth calculation submodule is used to 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 the 3*3 sliding window respectively, and obtain the mean value of the 7th band, the standard deviation of the 7th band, the mean value of the 13th band, and the standard deviation of the 13th band;

[0148] The detection submodule is used to 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, 7th band brightness temperature data, 13th band brightness temperature data, and 90-meter ground elevation DEM of each pixel into the pre-trained thermal power detection model, and output the fire point identification result of each pixel in the effective image data;

[0149] The third judgment submodule is used to judge whether each pixel of the valid image data meets the third judgment condition based on the fire point recognition result of each pixel, and obtain the third judgment result, wherein the third judgment condition P3 is: F (i,j) =1, where F (i,j) is the fire point identification result of pixel (i, j).

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

[0151]

[0152] Wherein, 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 4This is the 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, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 41 may execute 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 further 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, and the like.

[0158] The output device 44 can output various information to the outside. The output device 44 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-mentioned methods and devices, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to perform the steps of the method according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0162] The computer program product may be written in any combination of one or more programming languages ​​to implement the operations of embodiments of the present invention, including object-oriented programming languages ​​such as Java, C++, and conventional procedural programming languages ​​such as C or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, 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] In addition, an embodiment of the present invention may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0164] The computer-readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to a system, system or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with 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 thereof.

[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, strengths, and effects mentioned in the present invention are merely illustrative and non-limiting, and should not be construed as necessarily possessed by each embodiment of the present invention. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, and are not intended to be limiting. These details do not necessarily limit the present invention to being implemented using these specific details.

[0166] Each embodiment in this specification is described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. References to the same or similar parts between the various embodiments are sufficient. For system embodiments, since they largely correspond to method embodiments, their description is relatively simple. For relevant parts, references to the description of the method embodiments are sufficient.

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

[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, and firmware. The above sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above, unless otherwise specified. 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 recording media that store programs 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 this field to make or use the present invention. Various modifications to these aspects will be 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 according to the widest scope consistent with the principles disclosed here and novel features.

[0170] The above description has been presented for purposes of illustration and description. Furthermore, 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, alterations, 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 within 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 elevation DEM; Performing a cloud removal operation on the image data using a cloud recognition algorithm to obtain valid image data; determining, pixel by pixel, whether the valid image data satisfies a preset first judgment condition based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a first judgment result; determining, pixel by pixel, whether the valid image data satisfies a preset second judgment condition based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a second judgment result; Determining whether a preset third judgment condition is satisfied pixel by pixel for the valid image data 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; Determine the credibility of the fire point of each pixel of the valid image data according to the first judgment result, the second judgment result and the third judgment result; The first judgment condition P1 is P11∧P12∧P13∧P14, wherein, P11： P12： P13： P14： in, Where, and Respectively represent bands B7 and B 13 The brightness temperature value at the effective pixel (i, j); ε1, ε2, ε3 and ε4 are the judgment thresholds; M7 is the mean of the effective values ​​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 Valid pixel set of band 13 is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels from 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).

2. The method according to claim 1, characterized in that Acquire image data containing multiple dimensional data information within a preset area, including: Extract the angle information data from the Fengyun-4B satellite image in the preset area; Perform radiometric calibration on the Fengyun-4B image to obtain brightness temperature data in the 7th and 13th bands; The 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.

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 based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a first determination result, including: Obtaining a set of valid pixels in the seventh band within a preset range of each pixel in the brightness temperature data of the seventh 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; Obtaining 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 effective value 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 effective value of the 7th band, the average absolute variance of the 7th band, the mean effective value of the 13th band and the average absolute variance of the 13th band of each pixel, determine whether each pixel of the valid image data meets the first judgment condition and obtain the first judgment result.

4. The method according to claim 1, wherein The method further comprises determining, pixel by pixel, whether the valid image data satisfies a preset second determination condition based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtaining a second determination result, including: Calculating the difference average, difference effective value mean, and difference average absolute square error 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.

5. The method according to claim 4, characterized in that The second judgment condition P2 is P21∧P22∧P23∧P24, where: P21： P22： P23： P24： in, Where ε5, ε6, ε7 and ε8 are the decision thresholds; ΔS N is the mean value of the difference; ΔM is the mean effective value of the difference; ΔT is the mean absolute variance of the difference; is the brightness temperature value of the 7th band within N pixels from 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).

6. 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, Determining whether a preset third judgment condition is satisfied pixel by pixel for the valid image data according to the angle information data, the brightness temperature data of the seventh band, the brightness temperature data of the thirteenth 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 value of the 7th band, the standard deviation of the 7th band, the mean value of the 13th band, and the standard deviation of the 13th band; Inputting 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 elevation DEM of each pixel into a pre-trained thermal power detection model, and outputting the fire point identification 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: F (i,j) =1, where F (i,j) is the fire point identification result of pixel (i, j).

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

8. A fire point credibility determination device, characterized in that: include: An acquisition module is configured to acquire image data within a preset area, including multiple dimensional data information, 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 elevation DEM; a cloud removal module, configured to perform a cloud removal operation on the image data using a cloud recognition algorithm to obtain valid image data; a first judgment module, configured to judge, pixel by pixel, whether the valid image data satisfies a preset first judgment condition based on 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, configured to judge, pixel by pixel, whether the valid image data satisfies a preset second judgment condition based on the brightness temperature data of the seventh band and the brightness temperature data of the thirteenth band, and obtain a second judgment result; a third judgment module, configured to judge, pixel by pixel, whether the valid image data satisfies a preset third judgment condition 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, and obtain a third judgment result; A determination module is used to determine the credibility of the fire point of each pixel of the valid image data according to the first judgment result, the second judgment result and the third judgment result; The first judgment condition P1 is P11∧P12∧P13∧P14, wherein, P11： P12： P13： P14： in, Where, and Respectively represent bands B7 and B 13 The brightness temperature value at the effective pixel (i, j); ε1, ε2, ε3 and ε4 are the judgment thresholds; M7 is the mean of the effective values ​​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 Valid pixel set of band 13 is the brightness temperature value of the 7th band of the pixel (a, b) within N pixels from 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).

9. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 7.

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