Drone-based Surface Temperature Measurement Method, Device, Equipment and Storage Medium

Abstract

The present invention relates to the field of remote sensing data analysis, and particularly to a method for measuring surface temperature based on an unmanned aerial vehicle, including: obtaining a thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of a target area through the unmanned aerial vehicle; converting the thermal infrared image into a surface temperature image, extracting a plurality of sample data corresponding to each land type from the surface temperature image, and obtaining temperature data corresponding to the sample data; constructing a surface temperature measurement model according to the temperature data, meteorological data, building height data corresponding to each land type, and building area data; in response to a measurement instruction, the measurement instruction includes a thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of an area to be classified, and obtaining a surface temperature measurement result of the area to be classified according to the thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the area to be classified.

Description

Technical Field

[0001] The present invention relates to the field of remote sensing data analysis, and particularly to a method, device, equipment, and storage medium for measuring surface temperature based on an unmanned aerial vehicle (UAV). Background Art

[0002] The urban thermal environment in a small area has a significant impact on human health and the urban heat island effect. By measuring the surface temperature of a small area, the current thermal environment of the area can be reflected.

[0003] In the current technical solutions, the surface temperature of a small area is measured through in-situ measured data and high-resolution remote sensing information. However, due to limited in-situ measurement stations, the in-situ measured data shows uneven data distribution, making it difficult to accurately measure the surface temperature of a small area. Summary of the Invention

[0004] Based on this, the object of the present invention is to provide a method, device, equipment, and storage medium for measuring surface temperature based on an unmanned aerial vehicle (UAV). By obtaining the temperature data corresponding to each land use type in the thermal infrared image, and constructing a surface temperature measurement model according to the temperature data corresponding to each land use type, meteorological data, building height data corresponding to each land use type, and building area data, accurate measurement of the surface temperature of a small area can be achieved efficiently and quickly.

[0005] In a first aspect, an embodiment of the present application provides a method for measuring surface temperature based on an unmanned aerial vehicle (UAV), including the following steps:

[0006] Obtain, by means of an unmanned aerial vehicle, a thermal infrared image, meteorological data, building height data corresponding to each land use type, and building area data of a target area, where the thermal infrared image includes several land use types, and the meteorological data includes air temperature data and wind speed data;

[0007] Convert the thermal infrared image into a surface temperature image, and extract several sample data corresponding to each land use type from the surface temperature image;

[0008] Construct a surface temperature measurement model according to the temperature data, meteorological data, building height data corresponding to each land use type, and building area data;

[0009] In response to a measurement instruction, the measurement instruction includes a thermal infrared image, meteorological data, building height data corresponding to each land use type, and building area data of an area to be classified. Input the thermal infrared image, meteorological data, building height data corresponding to each land use type, and building area data of the area to be classified into the surface temperature measurement model to obtain a surface temperature measurement result of the area to be classified.

[0010] In a second aspect, an embodiment of the present application provides a device for measuring surface temperature based on an unmanned aerial vehicle (UAV), including:

[0011] An acquisition module, configured to acquire a thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of a target area through a UAV, wherein the thermal infrared image includes several land types, and the meteorological data includes air temperature data and wind speed data;

[0012] A sample extraction module, configured to convert the thermal infrared image into a surface temperature image, and extract several sample data corresponding to each land type from the surface temperature image;

[0013] A construction module, configured to construct a surface temperature measurement model according to the temperature data, meteorological data, building height data corresponding to each land type, and building area data;

[0014] A measurement module, configured to respond to a measurement instruction, where the measurement instruction includes a thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of an area to be classified, and input the thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the area to be classified into the surface temperature measurement model to obtain a surface temperature measurement result of the area to be classified.

[0015] In a third aspect, an embodiment of the present application provides a computer device, including: a processor, a memory, and a computer program stored on the memory and executable on the processor; when the computer program is executed by the processor, the steps of the method for measuring surface temperature based on a UAV as described in the first aspect are implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the method for measuring surface temperature based on a UAV as described in the first aspect are implemented.

[0017] In an embodiment of the present application, a method, device, equipment, and storage medium for measuring surface temperature based on a UAV are provided. By acquiring temperature data corresponding to each land type in a thermal infrared image, and constructing a surface temperature measurement model according to the temperature data corresponding to each land type, meteorological data, building height data corresponding to each land type, and building area data, accurate measurement of the surface temperature of a small area is realized, which is efficient and fast.

[0018] For better understanding and implementation, the present invention will be described in detail below with reference to the accompanying drawings. Description of the Drawings

[0019] Figure 1 Schematic flowchart of the surface temperature measurement method based on an unmanned aerial vehicle provided by the first embodiment of the present application;

[0020] Figure 2 Schematic flowchart of the surface temperature measurement method based on an unmanned aerial vehicle provided by the second embodiment of the present application;

[0021] Figure 3 Schematic flowchart of S2 in the surface temperature measurement method based on an unmanned aerial vehicle provided by the first embodiment of the present application;

[0022] Figure 4 Schematic structural diagram of the ANN model of the surface temperature measurement method based on an unmanned aerial vehicle provided by the first embodiment of the present application;

[0023] Figure 5 Schematic flowchart of the surface temperature measurement method based on an unmanned aerial vehicle provided by the third embodiment of the present application;

[0024] Figure 6 Schematic structural diagram of the surface temperature measurement device based on an unmanned aerial vehicle provided by an embodiment of the present application;

[0025] Figure 7 Schematic structural diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0026] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0027] The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. The singular forms "a", "the", and "said" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0028] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" / "when" as used herein may be interpreted as "when...", "when...", or "in response to determining".

[0029] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of the method for measuring surface temperature based on an unmanned aerial vehicle provided in the first embodiment of this application. The method includes the following steps:

[0030] S1: Obtain the thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the target area through an unmanned aerial vehicle. Among them, the thermal infrared image includes several land types, and the meteorological data includes air temperature data and wind speed data.

[0031] The execution subject of the method for measuring surface temperature based on an unmanned aerial vehicle is the measuring device of the method for measuring surface temperature based on an unmanned aerial vehicle (hereinafter referred to as the measuring device). In an optional embodiment, the measuring device may be a computer device, which may be a server, or a server cluster formed by combining multiple computer devices.

[0032] The target area includes several surface types. The thermal infrared image is used to record the thermal infrared radiation information invisible to the human eye radiated by ground objects, and can be used to identify ground objects and invert surface parameters. Among them, the inverted surface parameters include temperature, emissivity, humidity, thermal inertia, etc.

[0033] The meteorological data is a set of data reflecting the weather, including air temperature data and wind speed data, and is used to reflect the weather conditions of each land type.

[0034] The measuring device can obtain the thermal infrared image of the target area through an unmanned aerial vehicle, or can also obtain it by downloading from a database. The measuring device can obtain the building height data and building area data corresponding to each land type of the target area by downloading from a database.

[0035] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of the method for measuring surface temperature based on an unmanned aerial vehicle provided in the second embodiment of this application, including step S5. The step S5 is before step S2, and is specifically as follows:

[0036] S5: Preprocess the thermal infrared image to obtain the preprocessed thermal infrared image, where the preprocessing steps include radiometric correction, geometric correction, and geometric registration.

[0037] In this embodiment, the measuring device performs radiometric correction, geometric correction, and geometric registration processing on the thermal infrared image to obtain the processed thermal infrared image, which is used to correct the thermal infrared image of the target area collected by the UAV and improve the accuracy of temperature measurement.

[0038] S2: Convert the thermal infrared image into a land surface temperature image, extract several sample data corresponding to each land cover type from the land surface temperature image, and obtain the temperature data corresponding to the sample data.

[0039] The land surface temperature image is a regional temperature map drawn for the land surface, recording the land surface temperature in each area within the image. The temperature data can be obtained through the sensors on the UAV. In this embodiment, the classification device obtains the temperature data corresponding to the sample data through the UAV, where the temperature data includes the temperature parameters of the sample data corresponding to each land cover type at different time periods.

[0040] In this embodiment, the measuring device converts the thermal infrared image into a land surface temperature image, extracts several sample data corresponding to each land cover type from the land surface temperature image, and obtains the temperature data corresponding to each land cover type according to the sample data.

[0041] Please refer to Figure 3 , Figure 3 which is a schematic flowchart of S2 in the method for measuring land surface temperature based on UAV provided in the first embodiment of this application, including steps S201 to S203, specifically as follows:

[0042] S201: Convert the thermal infrared image into a land surface temperature image according to the thermal infrared image and the land surface temperature algorithm.

[0043] The land surface temperature algorithm is:

[0044]

[0045] where T s is the land surface temperature; C is the brightness temperature value; C' is the equivalent average atmospheric temperature; a and b are regression coefficients; α and β are intermediate coefficients, where α = e·r, β = (1 - e)[1 + e(1 - r)], e is the atmospheric transmittance, and r is the land surface emissivity;

[0046] The brightness temperature value can be measured by the sensor of the drone. In this embodiment, the classification device obtains the land surface emissivity and atmospheric transmittance of each pixel in the thermal infrared image, inputs them into a preset land surface temperature algorithm, and calculates the land surface temperature corresponding to each pixel according to the preset equivalent atmospheric average temperature and brightness temperature value, so as to obtain a land surface temperature image, thereby converting the thermal infrared image into a land surface temperature image.

[0047] S202: Obtain the area proportion data corresponding to each of the land type categories.

[0048] The land type category refers to the surface coverage type of the ground objects in the target area, including white tiles, white steel plate roofs, white road cement, brown steel plate roofs, red roof tiles, red steel plate roofs, off-white roof cement, gray roof cement, blue steel plate roofs, off-white steel plate roofs, light blue steel plate roofs, dark brown steel plate roofs, dark gray road cement, dark blue steel plate roofs, asbestos tiles, brown roof tiles.

[0049] The area proportion data is the proportion of the area of each land type category in the area of all land type categories in the land surface temperature image.

[0050] In this embodiment, the measurement device analyzes the land surface temperature image to obtain the area proportion data corresponding to each of the land type categories in the land surface temperature image.

[0051] S203: Extract a number of sample data corresponding to each of the land type categories from the land surface temperature image according to the area proportion data.

[0052] In this embodiment, the measurement device extracts a number of sample data corresponding to each of the land type categories from the land surface temperature image according to the area proportion data.

[0053] S3: Construct a land surface temperature measurement model according to the temperature data, meteorological data, building height data corresponding to each of the land type categories, and building area data.

[0054] The land surface temperature measurement model is an ANN (Artificial Neural Network), that is, an artificial neural network model, a complex network structure formed by a large number of processing units (neurons) connected to each other. Through repeated learning and training of known information, by gradually adjusting and changing the connection weights of neurons, the purpose of processing information and simulating the relationship between input and output is achieved. Please refer to Figure 4 , Figure 4 which is a schematic structural diagram of the ANN model of the method for measuring land surface temperature based on drones provided in the first embodiment of this application. The ANN model consists of an input layer, an output layer, and a hidden layer. Among them, the input layer is:

[0055] {X = X1, …, X n-1 , X n}

[0056] Wherein, X n is the input vector of the input layer;

[0057] The output layer is:

[0058] {Y = Y1, …, Y n-1 , Y n}

[0059] Wherein, Y n is the output vector of the output layer;

[0060] The input layer is used to obtain information, and the hidden layer is used for information processing and processing. Its weight determines the performance of the neural network model. In this embodiment, the measurement device uses the temperature data as the output layer of the ANN model, and the meteorological data, the building height data corresponding to each land type, and the building area data as the input layer. According to the weight vectors ω ih and ω hj , training is performed to construct a surface temperature measurement model, where the weight vector ω ih is the weight vector from the i to h direction; ω hj is the weight vector from the h to j direction.

[0061] S4: In response to the measurement instruction, the measurement instruction includes the thermal infrared image of the area to be classified, meteorological data, the building height data corresponding to each land type, and the building area data. According to the thermal infrared image of the area to be classified, meteorological data, the building height data corresponding to each land type, and the building area data, input them into the surface temperature measurement model to obtain the surface temperature measurement result of the area to be classified.

[0062] The measurement instruction is issued by the user and received by the measurement device.

[0063] In this embodiment, the measurement device obtains the measurement instruction sent by the user and responds. The measurement device inputs the thermal infrared image of the area to be classified, meteorological data, the building height data corresponding to each land type, and the building area data into the surface temperature measurement model to obtain the surface temperature measurement result of the area to be classified.

[0064] Please refer to Figure 5 , Figure 5 which is the schematic flowchart of the method for measuring surface temperature based on an unmanned aerial vehicle provided in the third embodiment of the present application, and further includes step S6. The step S6 is after step S4, and specifically as follows:

[0065] S6: In response to a display instruction, which includes the measured surface temperature results of the area to be classified, obtain electronic map data. According to the surface temperature data in the measured surface temperature results and the temperature identifier corresponding to the surface temperature data, obtain the temperature identifiers of each area of the electronic map data, and perform the display and annotation of the temperature identifiers on the electronic map data.

[0066] The display instruction is issued by the user and received by the measuring device.

[0067] In this embodiment, the measuring device obtains the display instruction sent by the user and responds to it, obtaining electronic map data. The measuring device obtains the temperature identifier corresponding to the surface temperature data according to the surface temperature data in the measured surface temperature results. Specifically, the temperature identifier can be a color identifier, and different colors represent different ranges of surface temperature intervals. And it is returned to the display interface of the measuring device, and the display and annotation of the temperature identifier are performed on the electronic map.

[0068] Please refer to Figure 6 , Figure 6 FIG. is a schematic structural diagram of a surface temperature measurement device based on an unmanned aerial vehicle provided in an embodiment of the present application. This device can implement all or part of the surface temperature measurement device based on an unmanned aerial vehicle through software, hardware, or a combination of both. The device 6 includes:

[0069] An acquisition module 61, configured to obtain a thermal infrared image, meteorological data, building height data and building area data corresponding to each land type of a target area through an unmanned aerial vehicle, wherein the thermal infrared image includes several land types, and the meteorological data includes air temperature data and wind speed data;

[0070] A sample extraction module 62, configured to convert the thermal infrared image into a surface temperature image, and extract several sample data corresponding to each land type from the surface temperature image;

[0071] A construction module 63, configured to construct a surface temperature measurement model according to the temperature data, meteorological data, building height data and building area data corresponding to each land type;

[0072] A measurement module 64, configured to respond to a measurement instruction, which includes a thermal infrared image, meteorological data, building height data and building area data corresponding to each land type of the area to be classified. According to the thermal infrared image, meteorological data, building height data and building area data corresponding to each land type of the area to be classified, input them into the surface temperature measurement model to obtain the measured surface temperature results of the area to be classified.

[0073] In the embodiments of the present application, through an acquisition module, a thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of a target area are acquired by a drone. Among them, the thermal infrared image includes several land types, and the meteorological data includes air temperature data and wind speed data; through a sample extraction module, the thermal infrared image is converted into a surface temperature image, and several sample data corresponding to each land type are extracted from the surface temperature image; through a construction module, according to the temperature data, meteorological data, building height data corresponding to each land type, and building area data, a surface temperature measurement model is constructed; through a measurement module, in response to a measurement instruction, the measurement instruction includes a thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the area to be classified. According to the thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the area to be classified, they are input into the surface temperature measurement model to obtain the surface temperature measurement result of the area to be classified. The present application realizes the accurate measurement of the surface temperature of a small area, which is efficient and fast by acquiring the temperature data corresponding to each land type in the thermal infrared image and constructing a surface temperature measurement model according to the temperature data corresponding to each land type, meteorological data, building height data corresponding to each land type, and building area data.

[0074] Please refer to Figure 7 , Figure 7 which is a schematic structural diagram of a computer device provided by an embodiment of the present application. The computer device 7 includes: a processor 71, a memory 72, and a computer program 73 stored in the memory 72 and executable on the processor 71; the computer device can store multiple instructions, and the instructions are suitable for being loaded and executed by the processor 71 to perform the method steps of the above Figures 1 to 4 shown embodiment. The specific execution process can be referred to the specific description of the Figures 1 to 4 shown embodiment, and details are not described herein.

[0075] Among them, the processor 71 may include one or more processing cores. The processor 71 uses various interfaces and circuits to connect various parts within the server. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 72, and by calling the data stored in the memory 72, it executes various functions of the drone-based surface temperature measurement device 6 and processes data. Optionally, the processor 71 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 71 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the touch display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 71 and may be implemented separately by a single chip.

[0076] Among them, the memory 72 may include a random access memory (RAM) and may also include a read-only memory (ROM). Optionally, the memory 72 includes a non-transitory computer-readable storage medium. The memory 72 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 72 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch instructions, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store the data involved in the above-mentioned method embodiments. Optionally, the memory 72 may also be at least one storage device located far from the aforementioned processor 71.

[0077] The embodiment of the present application also provides a storage medium, which can store multiple instructions. The instructions are suitable for being loaded and executed by a processor to perform the method steps of the above Figures 1 to 4 shown embodiments. The specific execution process can be referred to Figures 1 to 4 the specific description of the shown embodiments and will not be elaborated here.

[0078] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiments can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of the functional units and modules are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working processes of the units and modules in the above system can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated here.

[0079] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0080] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in the form of hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0081] In the embodiments provided by the present invention, it should be understood that the disclosed device / terminal device and method can be implemented in other ways. For example, the device / terminal device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0082] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0083] In addition, in each embodiment of the present invention, each functional unit may be integrated into one processing unit, may exist physically alone for each unit, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0084] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above method embodiments of the present invention, it may also be completed by instructing relevant hardware through a computer program. The computer program may be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above method embodiments may be implemented. Among them, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form, etc.

[0085] The present invention is not limited to the above embodiments. If various changes or deformations to the present invention do not depart from the spirit and scope of the present invention, and if these changes and deformations are within the scope of the claims of the present invention and equivalent technical scope, then the present invention also intends to include these changes and deformations.

Claims

1. A method for measuring surface temperature based on an unmanned aerial vehicle, characterized in that, Including the following steps: Obtain the thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the target area through a drone. Among them, the thermal infrared image includes several land types, and the meteorological data includes temperature data and wind speed data; According to the thermal infrared image and the land surface temperature algorithm, convert the thermal infrared image into a land surface temperature image, where the land surface temperature algorithm is: where, T s is the surface temperature; C is the brightness temperature value; C’ is the equivalent average atmospheric temperature; a and b are regression coefficients; α and β are intermediate coefficients, where α = e·r, β = (1 - e)[1 + e(1 - r)], e is the atmospheric transmittance, and r is the surface emissivity; Extract several sample data corresponding to each land type from the land surface temperature image, and obtain the temperature data corresponding to the sample data; Construct a land surface temperature measurement model according to the temperature data, meteorological data, building height data corresponding to each land type, and building area data; In response to a measurement instruction, the measurement instruction includes the thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the area to be classified. According to the thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the area to be classified, input them into the land surface temperature measurement model to obtain the land surface temperature measurement result of the area to be classified.

2. The method for measuring surface temperature based on an unmanned aerial vehicle according to claim 1, wherein Before converting the thermal infrared image into a land surface temperature image, it includes the steps of: Preprocess the thermal infrared image to obtain a preprocessed thermal infrared image, where the preprocessing steps include radiometric correction, geometric correction, and geometric registration.

3. The method for measuring the surface temperature based on an unmanned aerial vehicle according to claim 1, wherein The step of extracting several sample data corresponding to each land type from the land surface temperature image includes the steps of: Obtain the area proportion data corresponding to each land type; According to the area proportion data, extract several sample data corresponding to each land type from the land surface temperature image.

4. The method for measuring surface temperature based on an unmanned aerial vehicle according to claim 1, wherein It also includes the steps of: In response to a display instruction, the display instruction includes the land surface temperature measurement result of the area to be classified. Obtain electronic map data, and according to the land surface temperature data in the land surface temperature measurement result and the temperature identifier corresponding to the land surface temperature data, obtain the temperature identifiers of each area of the electronic map data, and display and mark the temperature identifiers on the electronic map data.

5. An unmanned aerial vehicle-based surface temperature measurement device, characterized in that, Including: An acquisition module for obtaining the thermal infrared image, meteorological data, building height data corresponding to each land type, and building area data of the target area through a drone. Among them, the thermal infrared image includes several land types, and the meteorological data includes temperature data and wind speed data; A sample extraction module for converting the thermal infrared image into a land surface temperature image according to the thermal infrared image and the land surface temperature algorithm, where the land surface temperature algorithm is: where, T s is the surface temperature; C is the brightness temperature value; C’ is the equivalent average atmospheric temperature; a and b are regression coefficients; α and β are intermediate coefficients, where α = e·r, β = (1 - e)[1 + e(1 - r)], e is the atmospheric transmittance, and r is the surface emissivity; Extract several sample data corresponding to each land type from the land surface temperature image, and obtain the temperature data corresponding to the sample data; A construction module for constructing a land surface temperature measurement model according to the temperature data, meteorological data, building height data corresponding to each land type, and building area data; A measurement module, configured to respond to a measurement instruction, where the measurement instruction includes a thermal infrared image of the area to be classified, meteorological data, building height data corresponding to each of the land type categories, and building area data, and input the thermal infrared image of the area to be classified, meteorological data, building height data corresponding to each of the land type categories, and building area data into the surface temperature measurement model to obtain a surface temperature measurement result of the area to be classified.

6. A computer device, characterized in that, Comprising: A processor, a memory, and a computer program stored on the memory and executable on the processor; when the computer program is executed by the processor, it implements the steps of the unmanned aerial vehicle-based surface temperature measurement method according to any one of claims 1 to 4.

7. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the unmanned aerial vehicle-based surface temperature measurement method according to any one of claims 1 to 4.

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