Satellite remote sensing intelligent monitoring device and method

Abstract

The invention provides a satellite remote sensing intelligent monitoring device and method, and belongs to the technical field of satellite remote sensing. Comprising a monitoring management mechanism, the monitoring management mechanism comprises an installation main body, protection installation mechanisms are arranged on the two sides of the installation main body, an installation plate is arranged on the back face of the installation main body, and the monitoring management mechanism is used for monitoring and managing the environment of the coal cleaning plant area. The protective mounting mechanism is used for mounting and protecting the mounting main body, a placement plate is arranged in the mounting main body, a processing assembly is arranged on the upper surface of the placement plate and used for processing and transmitting remote sensing information, and a circulating fan is arranged on the lower surface of the placement plate and used for cooling the mounting main body. And a ventilation plate is arranged below the circulating fan. According to the invention, various feature data of the to-be-detected point can be judged, so that the threshold value of specific ground feature extraction is obtained, and the extraction rate of change pattern spots is improved.

Description

Technical Field

[0001] The present invention relates to the field of satellite remote sensing technology, and in particular to a satellite remote sensing intelligent monitoring device and method. Background Art

[0002] With the widespread application of deep learning in computer vision, deep learning has found many successful application cases in the field of remote sensing. These application cases include land feature classification, ground change detection, and new building detection. In these application cases, the original data being processed is ordinary image data with high resolution. Among them, most ordinary image data has a resolution of less than 10 meters and only has three RGB channels. Therefore, it is easy to migrate deep learning algorithms applied to ordinary image data to these remote sensing fields.

[0003] As a kind of hyperspectral data, satellite remote sensing monitoring data not only has three RGB channels, but also includes channels of multiple bands such as surface temperature, cloud temperature, and atmospheric temperature. It is difficult to migrate the deep learning method of ordinary image processing to this data set for application. How to build a strong deep learning model with stable performance, high versatility and scalability, and use massive satellite remote sensing data as the basic data for model training, so as to achieve efficient extraction of change patches is crucial. Therefore, this application provides a satellite remote sensing intelligent monitoring device and method to meet the needs. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a satellite remote sensing intelligent monitoring device and method to solve the problem that it is difficult to migrate the deep learning method of ordinary image processing to satellite remote sensing monitoring data and the extraction efficiency of change spots is slow.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A satellite remote sensing intelligent monitoring device and method include: a monitoring and management mechanism, the monitoring and management mechanism including an installation body, protective installation mechanisms are provided on both sides of the installation body, and a mounting plate is provided on the back of the installation body. The monitoring and management mechanism is used to monitor and manage the environment of a coal washing plant, and the protective installation mechanism is used for installation and protection of the installation body.

[0007] Furthermore, a placement plate is provided inside the installation body, a processing component is provided on the upper surface of the placement plate, and the processing component is used for processing and transmitting remote sensing information; a circulation fan is provided on the lower surface of the placement plate, and a ventilation plate is provided below the circulation fan, and the ventilation plate is provided in a mesh structure; a fixing block is provided on the side of the installation body.

[0008] Furthermore, a plurality of mounting blocks are provided on the top and bottom of the mounting body, a mounting hole is provided inside each mounting block, a fixing bolt is provided inside each mounting hole, and the mounting blocks are connected to the mounting plate via the fixing bolts.

[0009] Furthermore, the protective mounting mechanism includes a mounting side plate, which is located on one side of the mounting body and is connected to the mounting plate. A spring is provided on the side of the mounting side plate close to the mounting body, and a fixing plate is provided on the end of the spring away from the mounting side plate.

[0010] Furthermore, a fixing groove is provided on one side of the fixing plate close to the installation body, a sealing gasket is provided inside the fixing groove, and the fixing groove is matched and connected with the fixing block.

[0011] Furthermore, protective plates are provided at both ends of the fixing plate, and the protective plates are arranged in an L-shape.

[0012] Furthermore, the processing component includes a data acquisition module, which is used to acquire satellite remote sensing data. The data acquisition module includes a single-point feature acquisition unit, which is used to extract features from at least one data element in the remote sensing monitoring data to obtain single-point feature data of the remote sensing monitoring data;

[0013] a neighboring point feature acquisition unit, configured to extract features from the at least one adjacent data element in the remote sensing monitoring data to obtain neighboring point feature data of the remote sensing monitoring data;

[0014] The feature data obtaining unit is configured to obtain the feature data of the remote sensing monitoring data according to the single-point feature data of the remote sensing monitoring data and the adjacent point feature data of the remote sensing monitoring data.

[0015] Furthermore, the processing component further includes an information processing module, which is used for information processing of feature data;

[0016] A data construction module, wherein the data construction module is used to construct a deep learning model;

[0017] A data correction module, wherein the data correction module is used to perform data correction of feature data;

[0018] The error calculation module is used to calculate the error of each feature data.

[0019] A satellite remote sensing intelligent monitoring method comprises the following steps:

[0020] S1. Obtain remote sensing monitoring data of the area to be detected;

[0021] S2. Extracting features from at least one data element in the detected remote sensing monitoring data to obtain single-point feature data of the remote sensing monitoring data;

[0022] S3, performing feature extraction on the at least one adjacent data element to be detected in the remote sensing monitoring data to obtain adjacent point feature data of the remote sensing monitoring data;

[0023] S4. Obtaining feature data of the remote sensing monitoring data based on the single-point feature data of the remote sensing monitoring data and the adjacent point feature data of the remote sensing monitoring data;

[0024] S5. Determine relevant information of the area to be detected based on the characteristic data of the remote sensing monitoring data.

[0025] Furthermore, the method further comprises:

[0026] S401. Build a deep learning model;

[0027] S402: Correct the feature data and perform error calculation.

[0028] Specifically, after the calibration is completed, accuracy verification is required to determine the accuracy of the characteristic information after calibration, and the determination coefficient R is calculated according to the formula 2 And the root mean square error RMSE, when R 2 The closer it is to 1, the smaller the RMSE is, and the higher the accuracy of the feature data obtained by remote sensing is. 2 The range is from 0 to 1. When R 2 The closer it is to 1, the higher the correlation between the two series, and the better the corrected correlation. Generally, an R2 greater than 0.6 is considered to be highly consistent.

[0029]

[0030] In the formula, Xi is the characteristic information, Yi is the characteristic information, is the average value of the corrected characteristic information data, is the average value of the feature information of the detection points, and n is the number of detection points.

[0031] Compared with the prior art, the present invention has at least the following beneficial effects:

[0032] In the above scheme,

[0033] 1. By matching and connecting the fixing blocks on the side of the mounting body with the fixing grooves on the side of the fixing plate and squeezing the spring, the fixing plate can fix mounting bodies of different sizes. When the side wall of the device is hit, the spring can reduce the impact force, avoiding affecting the circuit components inside the mounting body and increasing the practicality of the device.

[0034] 2. Acquire remote sensing monitoring data of the point to be detected; perform feature extraction on at least one data element in the remote sensing monitoring data to obtain single-point feature data of the remote sensing monitoring data; perform feature extraction on at least one adjacent data element in the remote sensing monitoring data to obtain neighboring point feature data of the remote sensing monitoring data; obtain feature data of the remote sensing monitoring data based on the single-point feature data of the remote sensing monitoring data and the neighboring point feature data of the remote sensing monitoring data; judge various feature data of the point to be detected based on the feature data of the remote sensing monitoring data, thereby obtaining a threshold for extracting specific objects and improving the extraction rate of change patches. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which are incorporated herein and constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the description, further serve to explain the principles of the present disclosure and to enable one skilled in the relevant art to make and use the present disclosure.

[0036] Figure 1 This is a schematic diagram of the overall structure of the satellite remote sensing intelligent monitoring device;

[0037] Figure 2 This is a schematic diagram of the internal structure of the satellite remote sensing intelligent monitoring device;

[0038] Figure 3 For the present invention Figure 2 Enlarged view of point A in the middle;

[0039] Figure 4 This is a module structure diagram of the satellite remote sensing intelligent monitoring device;

[0040] Figure 5 The present invention is a flow chart of a method for satellite remote sensing intelligent monitoring method.

[0041] [reference numerals]

[0042] 1. Monitoring and management mechanism; 11. Installation body; 12. Installation block; 13. Data acquisition module; 14. Placement plate; 15. Ventilation plate; 16. Data construction module; 17. Information processing module; 18. Circulation fan; 2. Protection installation mechanism; 21. Installation side panel; 22. Protection plate; 23. Fixing plate; 24. Spring; 25. Fixing block; 3. Installation plate; 4. Data correction module; 5. Error calculation module.

[0043] As shown in the figure, in order to clearly implement the structure of the embodiment of the present invention, specific structures and devices are marked in the figure, but this is only for illustrative purposes and is not intended to limit the present invention to the specific structure, device and environment. According to specific needs, ordinary technicians in this field can adjust or modify these devices and environments, and the adjustments or modifications made are still included in the scope of the appended claims. DETAILED DESCRIPTION

[0044] The following describes in detail a satellite remote sensing intelligent monitoring device and method provided by the present invention, with reference to the accompanying drawings and specific embodiments. It is also noted that, for the sake of completeness, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative implementations for known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0045] It should be noted that references in the specification to "one embodiment," "an embodiment," "an exemplary embodiment," "some embodiments," etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not every embodiment necessarily includes such specific features, structures, or characteristics. In addition, when specific features, structures, or characteristics are described in conjunction with an embodiment, it is within the knowledge of persons skilled in the relevant art to implement such features, structures, or characteristics in conjunction with other embodiments (whether or not explicitly described).

[0046] In general, terms can be understood, at least in part, from their use in context. For example, depending at least in part on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0047] It will be understood that the meanings of “on,” “over,” and “above” in this disclosure should be interpreted in the broadest manner, such that “on” means not only “directly on” something, but also includes being “on” something with intervening features or layers, and “on” or “over” means not only “on” or “above” something, but also includes being “on” or “above” something with no intervening features or layers.

[0048] Additionally, spatially relative terms such as "below," "beneath," "lower," "above," and "upper" may be used herein for descriptive convenience to describe the relationship of one element or feature to another element or features, as illustrated in the accompanying drawings. Spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the accompanying drawings. The device may be oriented in other ways, and the spatially relative descriptors used herein should be similarly interpreted accordingly.

[0049] Example 1

[0050] like Figures 1-4 As shown, an embodiment of the present invention provides a satellite remote sensing intelligent monitoring device and method, including: a monitoring and management mechanism 1, the monitoring and management mechanism 1 includes an installation body 11, and protective installation mechanisms 2 are provided on both sides of the installation body 11. A mounting plate 3 is provided on the back of the installation body 11. The monitoring and management mechanism 1 is used to monitor and manage the environment of the coal washing plant, and the protective installation mechanism 2 is used for installation and protection of the installation body 11.

[0051] In one possible implementation, a placement plate 14 is provided inside the installation body 11, and a processing component is provided on the upper surface of the placement plate 14, and the processing component is used for processing and transmitting remote sensing information. A circulation fan 18 is provided on the lower surface of the placement plate 14, and a ventilation plate 15 is provided below the circulation fan 18. The ventilation plate 15 is arranged in a mesh structure, and a fixing block 25 is provided on the side of the installation body 11.

[0052] In one possible implementation, a plurality of mounting blocks 12 are provided at the top and bottom of the mounting body 11, each of the mounting blocks 12 has a mounting hole therein, each of the mounting holes has a fixing bolt therein, and the mounting blocks 12 are connected to the mounting plate 3 via the fixing bolts.

[0053] In one possible implementation, the protective mounting mechanism 2 includes a mounting side plate 21, which is located on one side of the mounting body 11 and is connected to the mounting plate 3. A spring 24 is provided on the side of the mounting side plate 21 close to the mounting body 11, and a fixing plate 23 is provided on the end of the spring 24 away from the mounting side plate 21. A fixing groove is provided on the side of the fixing plate 23 close to the mounting body 11, and a sealing gasket is provided inside the fixing groove. The fixing groove is matched and connected with the fixing block 25, and a protective plate 22 is provided at both ends of the fixing plate 23. The protective plate 22 is L-shaped. By matching and connecting the fixing block 25 on the side of the mounting body 11 with the fixing groove on the side of the fixing plate 23 and squeezing the spring 24, the fixing plate 23 can fix mounting bodies 11 of different sizes. When the side wall of the device is hit, the spring 24 can reduce the impact force to avoid affecting the circuit components inside the mounting body 11, thereby increasing the practicality of the device.

[0054] In one possible implementation, the processing component includes a data acquisition module 13, which is used to acquire satellite remote sensing data. The data acquisition module 13 includes a single-point feature acquisition unit, which is used to extract features from at least one data element in the remote sensing monitoring data to obtain single-point feature data of the remote sensing monitoring data.

[0055] a neighboring point feature acquisition unit, configured to extract features from the at least one adjacent data element in the remote sensing monitoring data to obtain neighboring point feature data of the remote sensing monitoring data;

[0056] The feature data obtaining unit is configured to obtain the feature data of the remote sensing monitoring data according to the single-point feature data of the remote sensing monitoring data and the adjacent point feature data of the remote sensing monitoring data.

[0057] Furthermore, the processing component further includes an information processing module 17, which is used for information processing of feature data;

[0058] A data construction module 16, wherein the data construction module 16 is used to construct a deep learning model;

[0059] A data correction module 4, wherein the data correction module 4 is used to perform data correction of feature data;

[0060] The error calculation module 5 is used to calculate the error of each feature data.

[0061] The technical solution provided by the present invention matches and connects the fixing block 25 on the side of the installation body 11 with the fixing groove on the side of the fixing plate 23, and compresses the spring 24 so that the fixing plate 23 can fix installation bodies 11 of different sizes. When the side wall of the device is hit, the spring 24 can reduce the impact force to avoid affecting the circuit components inside the installation body 11. Then, the remote sensing monitoring data of the point to be detected is acquired by the data acquisition module 13; and a single-point feature acquisition unit is used to extract features of at least one data element in the remote sensing monitoring data, and a neighboring point feature acquisition unit is used to obtain single-point feature data of the remote sensing monitoring data; feature extraction is performed on the at least one adjacent data element in the remote sensing monitoring data, and a feature data acquisition unit is used to obtain neighboring point feature data of the remote sensing monitoring data; feature data of the remote sensing monitoring data is obtained based on the single-point feature data of the remote sensing monitoring data and the neighboring point feature data of the remote sensing monitoring data; based on the feature data of the remote sensing monitoring data, each feature data of the point to be detected is judged, thereby obtaining a threshold for extracting specific ground objects and improving the extraction rate of change patterns.

[0062] Example 2

[0063] like Figure 5 As shown, a satellite remote sensing intelligent monitoring method includes the following steps:

[0064] S1. Obtain remote sensing monitoring data of the area to be detected;

[0065] S2. Extracting features from at least one data element in the detected remote sensing monitoring data to obtain single-point feature data of the remote sensing monitoring data;

[0066] S3, performing feature extraction on the at least one adjacent data element to be detected in the remote sensing monitoring data to obtain adjacent point feature data of the remote sensing monitoring data;

[0067] S4. Obtaining feature data of the remote sensing monitoring data based on the single-point feature data of the remote sensing monitoring data and the adjacent point feature data of the remote sensing monitoring data;

[0068] S401. Build a deep learning model;

[0069] S402: Correct the feature data and perform error calculation.

[0070] Specifically, after the calibration is completed, accuracy verification is required to determine the accuracy of the characteristic information after calibration, and the determination coefficient R is calculated according to the formula 2 And the root mean square error RMSE, when R 2 The closer it is to 1, the smaller the RMSE is, and the higher the accuracy of the feature data obtained by remote sensing is.2 The range is from 0 to 1. When R 2 The closer it is to 1, the higher the correlation between the two series, and the better the corrected correlation. Generally, an R2 greater than 0.6 is considered to be highly consistent.

[0071]

[0072] In the formula, Xi is the characteristic information, Yi is the characteristic information, is the average value of the corrected characteristic information data, is the average value of the feature information of the detection points, and n is the number of detection points.

[0073] S5. Determine relevant information of the area to be detected based on the characteristic data of the remote sensing monitoring data.

[0074] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0075] Those skilled in the art will understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc.

[0076] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A satellite remote sensing intelligent monitoring device and method, characterized in that: include: A monitoring and management mechanism (1) is characterized in that: the monitoring and management mechanism (1) includes an installation body (11), both sides of the installation body (11) are provided with protective installation mechanisms (2), the back of the installation body (11) is provided with a mounting plate (3), the monitoring and management mechanism (1) is used to monitor and manage the environment of the coal washing plant, and the protective installation mechanism (2) is used for installation and protection of the installation body (11).

2. The satellite remote sensing intelligent monitoring device according to claim 1, characterized in that: A placement plate (14) is provided inside the installation body (11), a processing component is provided on the upper surface of the placement plate (14), and the processing component is used for processing and transmitting remote sensing information; a circulation fan (18) is provided on the lower surface of the placement plate (14), and a ventilation plate (15) is provided below the circulation fan (18), and the ventilation plate (15) is provided in a mesh structure; a fixing block (25) is provided on the side of the installation body (11).

3. The satellite remote sensing intelligent monitoring device according to claim 2, characterized in that: A plurality of mounting blocks (12) are provided at the top and bottom of the mounting body (11), a mounting hole is provided inside each mounting block (12), a fixing bolt is provided inside each mounting hole, and the mounting blocks (12) are connected to the mounting plate (3) via the fixing bolts.

4. The satellite remote sensing intelligent monitoring device according to claim 1, characterized in that: The protective mounting mechanism (2) includes a mounting side plate (21), the mounting side plate (21) is located on one side of the mounting body (11), the mounting side plate (21) is connected to the mounting plate (3), a spring (24) is provided on the side of the mounting side plate (21) close to the mounting body (11), and a fixing plate (23) is provided on the end of the spring (24) away from the mounting side plate (21).

5. The satellite remote sensing intelligent monitoring device according to claim 4, characterized in that: A fixing groove is provided on one side of the fixing plate (23) close to the installation body (11), a sealing gasket is provided inside the fixing groove, and the fixing groove is matched and connected with the fixing block (25).

6. The satellite remote sensing intelligent monitoring device according to claim 4, characterized in that: Both ends of the fixing plate (23) are provided with protective plates (22), and the protective plates (22) are arranged in an L-shape.

7. The satellite remote sensing intelligent monitoring device according to claim 2, characterized in that: The processing component includes a data acquisition module (13), the data acquisition module (13) is used to acquire satellite remote sensing data, and the data acquisition module (13) includes a single point feature acquisition unit, which is used to extract features from at least one data element in the remote sensing monitoring data to obtain single point feature data of the remote sensing monitoring data; a neighboring point feature acquisition unit, configured to extract features from the at least one adjacent data element in the remote sensing monitoring data to obtain neighboring point feature data of the remote sensing monitoring data; The feature data obtaining unit is configured to obtain the feature data of the remote sensing monitoring data according to the single-point feature data of the remote sensing monitoring data and the adjacent point feature data of the remote sensing monitoring data.

8. The satellite remote sensing intelligent monitoring device according to claim 1, characterized in that: The processing component further includes an information processing module (17), and the information processing module (17) is used for information processing of feature data; A data construction module (16), wherein the data construction module (16) is used to construct a deep learning model; A data correction module (4), wherein the data correction module (4) is used to perform data correction on the characteristic data; The error calculation module (5) is used to calculate the error of each feature data.

9. A satellite remote sensing intelligent monitoring method, characterized in that: A satellite remote sensing intelligent detection device applied to any one of claims 1-8, comprising the following steps: S1. Obtain remote sensing monitoring data of the area to be detected; S2. Extracting features from at least one data element in the detected remote sensing monitoring data to obtain single-point feature data of the remote sensing monitoring data; S3, performing feature extraction on the at least one adjacent data element to be detected in the remote sensing monitoring data to obtain adjacent point feature data of the remote sensing monitoring data; S4. Obtaining feature data of the remote sensing monitoring data based on the single-point feature data of the remote sensing monitoring data and the adjacent point feature data of the remote sensing monitoring data; S5. Determine relevant information of the area to be detected based on the characteristic data of the remote sensing monitoring data.

10. The satellite remote sensing intelligent monitoring method according to claim 9, characterized in that: The method further comprises: S401, build a deep learning model; S402: Correct the feature data and perform error calculation. Specifically, after the calibration is completed, accuracy verification is required to determine the accuracy of the characteristic information after calibration, and the determination coefficient R is calculated according to the formula 2 And the root mean square error RMSE, when R 2 The closer it is to 1, the smaller the RMSE is, and the higher the accuracy of the feature data obtained by remote sensing is. 2 The range is from 0 to 1. When R 2 The closer it is to 1, the higher the correlation between the two series, and the better the corrected correlation. Generally, an R2 greater than 0.6 is considered to have good consistency. In the formula, Xi is the characteristic information, Yi is the characteristic information, is the average value of the corrected characteristic information data, is the average value of the feature information of the detection points, and n is the number of detection points.

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