Method, device and equipment for estimating straw burning proportion and medium

Abstract

The invention relates to a method, device, equipment and medium for estimating the straw burning proportion, and belongs to the technical field of environmental protection, and the method comprises the steps: obtaining thermal abnormal point remote sensing data and land coverage data of a to-be-estimated region; identifying a straw burning fire point based on the thermal abnormal point remote sensing data and the land coverage data, and calculating the straw burning area of the straw burning fire point; acquiring reference data of the reference year, wherein the reference data comprises a reference straw burning area, a reference crop area and a reference straw burning proportion; and calculating the straw burning proportion of the to-be-estimated area according to the reference data and the straw burning area and the crop planting area of the to-be-estimated area. According to the method, the estimation precision of the straw incineration proportion time sequence data is improved, and reliable support is provided for pollution emission quantitative evaluation, incineration risk zoning control and differentiated treatment strategy making.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of environmental protection, and specifically relates to a method, device, equipment and medium for estimating the proportion of straw burning. BACKGROUND

[0002] The substances released by open burning of crop straw not only have a significant impact on air quality and human health, but also change atmospheric radiation at different levels and affect global climate. Accurate understanding of the open burning of straw in each region, estimation and construction of the burning proportion data over time are crucial for scientific assessment of pollution emissions, accurate delineation of burning risk control areas and development of differentiated management strategies, and constitute a key data support foundation.

[0003] Current straw burning monitoring mainly relies on human investigation and satellite monitoring. Human investigation can achieve accurate verification, but the cost is high, the efficiency is low, and the update frequency is extremely low, making it difficult to expand to large-scale applications. Satellites can carry out large-scale and high-frequency monitoring, but there are problems such as interference by clouds and confusion of straw burning fire points with other heat anomaly points (such as forest / grassland fires, industrial heat sources, and high-temperature ground objects). Traditional satellite monitoring techniques usually rely on static land cover classification data to directly screen heat anomaly points in farmland areas as straw burning fire points. In actual business applications, a large amount of manual correction is still required. There are technical problems such as low accuracy of straw burning identification and straw burning proportion estimation results, and low update frequency of straw burning proportion data. SUMMARY

[0004] In view of the above analysis, the embodiments of the present application aim to provide a method, device, equipment and medium for estimating the proportion of straw burning, to solve the technical problem of low accuracy of straw burning proportion estimation results in the prior art.

[0005] The purpose of the present application is achieved as follows: The first aspect of the present application provides a method for estimating the proportion of straw burning, comprising: obtaining heat anomaly point remote sensing data and land cover data of a region to be estimated; identifying straw burning fire points based on the heat anomaly point remote sensing data and land cover data, and calculating the straw burning area of the straw burning fire points; wherein the identification of the straw burning fire points based on the heat anomaly point remote sensing data and land cover data comprises: removing interference data in the heat anomaly point remote sensing data based on a space-time coupling criterion; and performing spatial matching on the processed heat anomaly point remote sensing data and the land cover data based on a confidence function of thermal emissivity and land cover to identify the straw burning fire points; obtaining reference data of a reference year, the reference data including a reference straw burning area, a reference crop area and a reference straw burning proportion; The straw burning ratio of the area to be estimated is calculated based on the benchmark data and the straw burning area and crop planting area of ​​the area to be estimated.

[0006] Furthermore, the remote sensing data of the thermal anomaly point at least includes the latitude and longitude coordinates of the thermal anomaly point, the thermal radiation power and the spatial resolution of the satellite.

[0007] Furthermore, the method of eliminating interference data in the thermal anomaly point remote sensing data based on the spatiotemporal coupling criterion includes: obtaining thermal anomaly point clustering areas based on the thermal anomaly point remote sensing data using a spatial clustering method; and calculating the number of thermal anomaly events in each clustering area within a preset time period and the standard deviation of the time intervals between thermal anomaly events, expressed as: , in, N Indicates the number of thermal abnormal events, Indicates the n The occurrence time of the secondary thermal anomaly event, in days; Identify non-straw burning clusters based on the number of thermal anomaly events and the standard deviation of the time intervals between thermal anomaly events; and eliminate data corresponding to the non-straw burning clusters in the remote sensing data of the thermal anomaly points.

[0008] Furthermore, the confidence function based on the fusion of thermal emissivity and land cover performs spatial matching on the processed thermal anomaly remote sensing data and the land cover data to identify straw burning fire spots, including: mapping the coordinates of each thermal anomaly point retained in the thermal anomaly remote sensing data after processing to the position of the corresponding pixel in the land cover data; extracting a land cover matrix within a pixel neighborhood window of a specific size from the land cover data with the corresponding pixel as the center; calculating the farmland coverage rate within the pixel neighborhood window according to the land cover matrix; and calculating the confidence that the current thermal anomaly point is a straw burning fire spot according to the thermal radiation power of each thermal anomaly point and the corresponding farmland coverage rate, which is expressed as: Among them, P represents the farmland coverage rate, and They represent the minimum and maximum thresholds of farmland coverage, respectively, and can be set flexibly according to actual conditions. frp Indicates the thermal emissivity of the thermal anomaly point, , and represent the standard deviation and mean of the thermal emissivity distribution of straw burning fire points, and represent the standard deviation and mean of the thermal emissivity distribution except for the straw burning fire point; Screening the straw burning fire point from the hot anomaly points according to the confidence.

[0009] Further, the straw burning area of the straw burning fire point is calculated, including: the to-be-estimated area is grid partitioned, the coordinates of the straw burning fire point are mapped as grid indexes, the straw burning area is calculated according to the grid indexes of all the straw burning fire points, and is expressed as: Wherein, to and te indicates the start and end time of the straw concentrated burning period, wl indicates the grid side length, lon,lat indicates the coordinates of the straw burning fire point, indicates the conversion of the coordinates into the grid indexes, k indicates the crop type.

[0010] Further, the straw burning ratio of the to-be-estimated area is calculated according to the reference data and the straw burning area and the crop planting area of the to-be-estimated area, and is expressed as: Wherein, indicates the to-be-estimated area i in the target year j of the crop k straw burning area, indicates the to-be-estimated area i in the reference year o of the crop k reference straw burning area, indicates the to-be-estimated area i in the reference year o of the crop k reference planting area, indicates the to-be-estimated area i in the target year j of the crop k planting area, indicates the to-be-estimated area i in the reference year o of the crop k reference straw burning ratio.

[0011] The second aspect embodiment of the present application provides a device for estimating the straw burning ratio, including: a data acquisition module, configured to acquire remote sensing data and land cover data of hot anomaly points in a to-be-estimated area; The straw burning area calculation module is configured to identify a straw burning fire point based on the thermal anomaly point remote sensing data and the land cover data, and calculate a straw burning area of the straw burning fire point; wherein the identification of the straw burning fire point based on the thermal anomaly point remote sensing data and the land cover data comprises: removing interference data in the thermal anomaly point remote sensing data based on a space-time coupling criterion; and performing spatial matching on the processed thermal anomaly point remote sensing data and the land cover data based on a confidence function of thermal radiation rate and land cover fusion, so as to identify the straw burning fire point. The reference data acquisition module is configured to acquire reference data of a reference year, the reference data comprising a reference straw burning area, a reference crop area and a reference straw burning ratio. The straw burning ratio estimation module is configured to calculate a straw burning ratio of a region to be estimated according to the reference data and the straw burning area and the crop planting area of the region to be estimated.

[0012] The third aspect of the present application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to implement the method for estimating the straw burning ratio according to any one of the embodiments.

[0013] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method for estimating the straw burning ratio according to any one of the embodiments.

[0014] Compared with the prior art, the present application can achieve at least one of the following beneficial effects: The method for estimating the straw burning ratio provided by the present application can accurately identify the straw burning fire point in the thermal anomaly point by comprehensively analyzing the thermal anomaly point remote sensing data and the land cover data, calculate the straw burning area of the straw burning fire point, and then calculate the straw burning ratio of the region to be estimated in combination with the reference data, thereby improving the accuracy of the straw burning ratio estimation result and providing reliable support for subsequent management work. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0016] figure 1 The flowchart of the method for estimating the straw burning ratio provided by the first embodiment of the present application is shown in the figure. figure 2A device schematic diagram for estimating the straw burning ratio provided for the embodiment 2 of the present application is shown in the figure; figure 3 An electronic device architecture schematic diagram provided for the embodiment 3 of the present application is shown in the figure; figure 4 A thermal anomaly point processing effect schematic diagram provided for the embodiment 1 of the present application is shown in the figure; figure 5 A thermal emissivity distribution schematic diagram provided for the embodiment 1 of the present application is shown in the figure; figure 6 A straw burning fire point identification result schematic diagram provided for the embodiment 1 of the present application is shown in the figure; figure 7 A straw burning ratio estimation result schematic diagram provided for the embodiment 1 of the present application is shown in the figure. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. It should be noted that the embodiments in the present disclosure and the features in the embodiments can be combined, separated, interchanged and / or rearranged without conflict. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present application.

[0018] Embodiment 1 One specific embodiment of the present application, as shown in the figure, figure 1 , 4 A method for estimating the straw burning ratio is disclosed, which comprises the following steps: It should be noted that the straw burning ratio estimated by the present application refers to the open-air straw burning ratio.

[0019] S1, obtaining thermal anomaly point remote sensing data and land cover data of a region to be estimated.

[0020] In the present embodiment, the thermal anomaly point remote sensing data at least comprises the longitude and latitude coordinates of the thermal anomaly point, the thermal radiation power and the spatial resolution of the satellite.

[0021] For example, the thermal anomaly point remote sensing data is obtained based on the VIIRS satellite spectral data inversion of the thermal anomaly point or direct download of the FIRMS thermal anomaly point product of NASA, and the land cover data can be selected as the GLC30 data.

[0022] S2, identifying the straw burning fire point based on the thermal anomaly point remote sensing data and the land cover data, and calculating the straw burning area of the straw burning fire point.

[0023] In this embodiment, step S2 specifically comprises: S201, removing interference data in the thermal anomaly point remote sensing data based on a space-time coupling criterion, comprising the following steps: (1) Using a spatial clustering method to obtain a thermal anomaly point aggregation area according to the thermal anomaly point remote sensing data; (2) Calculating the number of thermal anomaly events in each aggregation area within a preset time period and the time interval standard deviation of the thermal anomaly events; Specifically, a thermal anomaly event refers to the occurrence of at least one thermal anomaly point in the same aggregation area on the same day, which is determined as a thermal anomaly event. The time interval standard deviation of the thermal anomaly event is calculated as follows: Wherein, N represents the number of thermal anomaly events, represents the occurrence time of the n th thermal anomaly event, which can be represented by Julian day, and the unit is day. .

[0024] (3) Identifying non-straw burning aggregation areas according to the number of thermal anomaly events and the time interval standard deviation of the thermal anomaly events; Specifically, for any thermal anomaly point aggregation area, if the number of thermal anomaly events and the time interval standard deviation of the thermal anomaly events both satisfy and , it is determined that the thermal anomaly point aggregation area is a non-straw burning aggregation area, and the thermal anomaly point is interference data. represents the minimum threshold of the thermal anomaly event, represents the minimum threshold of the time interval standard deviation of the thermal anomaly event, both of which are set by humans.

[0025] (4) Removing the data corresponding to the non-straw burning aggregation area in the thermal anomaly point remote sensing data.

[0026] Specifically, after identifying all non-straw burning aggregation areas, the thermal anomaly point interference data corresponding to the non-straw burning aggregation area is removed from the thermal anomaly point remote sensing data.

[0027] For example, as shown in the figure, the gray part of the figure is farmland, the black part is other land cover types, the black frame in the figure is a thermal anomaly point caused by straw burning, and the white frame in the figure is a thermal anomaly point caused by non-straw burning. figure 4

[0028] S202, based on the confidence function of the fusion of thermal radiation and land cover, the processed thermal anomaly point remote sensing data and the land cover data are spatially matched to identify straw burning fire points, comprising: ​(1) mapping the coordinates of each thermal anomaly point reserved in the thermal anomaly point remote sensing data after processing to the position of the corresponding pixel in the land cover data; For example, assuming that the coordinates of a thermal anomaly point are , the land cover data is a grid map, and the coordinates of the upper left corner are , the coordinates of the thermal anomaly point are mapped to the pixel as follows: , b , and the resolution of the land cover data is

[0029] (2) extracting a land cover matrix in a pixel neighborhood window of a specific size in the land cover data centered on the corresponding pixel; For example, extracting the land cover matrix in a window centered on the pixel .

[0030] (3) calculating the farmland coverage rate in the pixel neighborhood window according to the land cover matrix; Specifically, the calculation formula of the farmland coverage rate is as follows: , wherein , crop indicates that the land cover type is farmland.

[0031] (4) calculating the confidence degree of the current thermal anomaly point being a straw burning fire point according to the thermal radiation power of each thermal anomaly point and the corresponding farmland coverage rate; Specifically, the confidence degree calculation formula of the straw burning fire point is as follows: , wherein and respectively represent the minimum threshold and the maximum threshold of the farmland coverage rate, which can be flexibly set according to the actual situation, frp represents the thermal radiation rate of the thermal anomaly point, , and respectively represent the standard deviation and the mean value of the thermal radiation rate distribution of the straw burning fire point, and respectively represent the standard deviation and the mean value of the thermal radiation rate distribution except for the straw burning fire point, as shown in the distribution diagram of the thermal radiation rate frp of the straw burning fire point and other thermal anomaly points. figure 5

[0032] (5) screening the straw burning fire points from the thermal anomaly points according to the confidence degree.

[0033] Specifically, the thermal anomaly points with a confidence degree greater than a preset threshold are set as the straw burning fire points. ​​

[0034] In some embodiments, after identifying the straw burning fire points, the method further comprises eliminating the fire points caused by urban expansion, factory construction and oil and gas well development by combining with the night light index data, specifically: performing logarithmic transformation on the night light index of the current year, performing Gaussian filtering for signal enhancement, then calculating the spatial gradient field by Sobel operator, combining with double threshold segmentation and direction consistency verification, extracting the expanded urban area and industrial factory area, and eliminating the fire points within the range.

[0035] For example, as shown in FIG. 2, the left graph is the data of the thermal anomaly points (blue points) in a certain region in a certain year, and the right graph is the straw burning fire points (red points) identified by step S202. figure 6

[0036] S203, calculating the straw burning area of the straw burning fire point, comprising: grid partitioning the to-be-estimated region, mapping the coordinates of the straw burning fire points to grid indexes, and calculating the straw burning area according to the grid indexes of all the straw burning fire points, which is represented as: wherein, to and te represent the start and end time of the straw burning period, wl represents the grid side length, lon,lat represents the coordinates of the straw burning fire point, represents the conversion of the coordinates to the grid indexes, k represents the crop type.

[0037] In some embodiments, considering the influence of cloud coverage on the straw burning area, cloud coverage data correction is introduced, specifically: when grid partitioning the to-be-estimated region, the grid side length is determined in combination with the range of the study area, the fire point density and the cloud distribution characteristics, to ensure the effectiveness of the cloud coverage area statistics within a single grid and the requirement of representing the spatial variation of the burning event; based on the historical fire point monitoring data and the straw burning concentration period within a year, the peak period of burning is further selected, usually the change of the fire points within the concentration period conforms to the normal distribution rule or the characteristics of the quadratic function, and the peak period window can be determined in combination with the curve characteristics; the relationship among the straw burning area, the year and the cloud coverage rate within the peak period of the crops year by year is statistically analyzed, and a corresponding correction function is established, which is not limited to the form of the correction function.

[0038] S3, obtaining reference data of a reference year, the reference data comprising a reference straw burning area, a reference crop area and a reference straw burning ratio.

[0039] S4, calculating the straw burning ratio of the to-be-estimated region according to the reference data and the straw burning area and the crop planting area of the to-be-estimated region. ​

[0040] Specifically, the straw burning ratio of the area to be estimated is calculated based on the benchmark data and the straw burning area and crop planting area of ​​the area to be estimated, and is expressed as: in, Indicates the area to be estimated i In the target year j crops k of straw burning area, Indicates the area to be estimated i In the base year o crops k The benchmark straw burning area, Indicates the area to be estimated i In the base year o crops k The base planting area, Indicates the area to be estimated i In the target year j crops k of planted area, Indicates the area to be estimated i In the base year o crops k The benchmark straw burning ratio.

[0041] In some embodiments, the area to be estimated i Where it is difficult to obtain baseline data or field surveys are not possible, geographically adjacent areas with similar crop planting structures can be used. Perform similar calculations, expressed as: .

[0042] like figure 7 As shown, taking 2012 as the base year for a certain province, the method provided in this embodiment is used to estimate the straw burning ratio in the subsequent 11 years.

[0043] Compared with the existing technology, the method for estimating the straw burning ratio provided in this embodiment comprehensively analyzes the spatiotemporal distribution and thermal radiation characteristics of straw burning, combines remote sensing data of thermal anomaly points and land cover data, accurately identifies straw burning fire points in thermal anomaly points, and then calculates the straw burning area of ​​the straw burning fire points. It then calculates the straw burning ratio of the area to be estimated in combination with the baseline data, thereby improving the accuracy and update frequency of the straw burning ratio estimation results, and providing reliable support for subsequent governance work.

[0044] Example 2 This embodiment provides a device for estimating the straw burning ratio, such as figure 2 Shown, including: The data acquisition module is configured to acquire thermal anomaly point remote sensing data and land cover data of the region to be estimated. The straw burning area calculation module is configured to identify a straw burning fire point based on the thermal anomaly point remote sensing data and the land cover data, and calculate a straw burning area of the straw burning fire point. The identification of the straw burning fire point based on the thermal anomaly point remote sensing data and the land cover data includes: removing interference data in the thermal anomaly point remote sensing data based on a space-time coupling criterion; and performing spatial matching on the processed thermal anomaly point remote sensing data and the land cover data based on a confidence function of thermal radiation and land cover fusion to identify the straw burning fire point. The reference data acquisition module is configured to acquire reference data of a reference year, the reference data including a reference straw burning area, a reference crop area, and a reference straw burning ratio. The straw burning ratio estimation module is configured to calculate a straw burning ratio of the region to be estimated according to the reference data and the straw burning area and the crop planting area of the region to be estimated.

[0045] Embodiment 3 The embodiment provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to implement the method for estimating a straw burning ratio according to any one of the preceding embodiments. figure 3 As shown in the figure, the electronic device comprises a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to implement the method for estimating a straw burning ratio according to any one of the preceding embodiments.

[0046] Embodiment 4 The embodiment provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the method for estimating a straw burning ratio according to any one of the preceding embodiments.

[0047] The computer readable storage medium includes permanent and non-permanent, removable and non-removable media, which can be realized by any method or technology to store information. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device. According to the definition herein, computer readable media does not include transitory computer readable media, such as modulated data signals and carriers.

[0048] Those skilled in the art should further understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in the above description in a general manner. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0049] The steps of the method or algorithm described in combination with the embodiments disclosed herein can be implemented in hardware, software executed by a processor, or a combination of both. The software module can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0050] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for estimating the proportion of straw burning, characterized in that: include: Obtain remote sensing data of thermal anomalies and land cover data of the area to be estimated; Identifying straw burning fire spots based on the thermal anomaly remote sensing data and the land cover data, and calculating the straw burning area of ​​the straw burning fire spots; wherein the identifying straw burning fire spots based on the thermal anomaly remote sensing data and the land cover data includes: eliminating interference data in the thermal anomaly remote sensing data based on a spatiotemporal coupling criterion; and spatially matching the processed thermal anomaly remote sensing data and the land cover data based on a confidence function fused with thermal emissivity and land cover to identify the straw burning fire spots; Obtaining baseline data for a baseline year, the baseline data including a baseline straw burning area, a baseline crop area, and a baseline straw burning ratio; The straw burning ratio of the area to be estimated is calculated based on the benchmark data and the straw burning area and crop planting area of ​​the area to be estimated.

2. The method for estimating the straw burning ratio according to claim 1, characterized in that: The thermal anomaly point remote sensing data at least includes the latitude and longitude coordinates of the thermal anomaly point, thermal radiation power and spatial resolution of the satellite.

3. The method for estimating the straw burning ratio according to claim 1, characterized in that: The method of eliminating interference data in the remote sensing data of the thermal anomaly point based on the spatiotemporal coupling criterion includes: Using a spatial clustering method to obtain a thermal anomaly point clustering area based on the thermal anomaly point remote sensing data; The number of thermal anomaly events within the preset time period and the standard deviation of the time intervals between thermal anomaly events are calculated for each cluster area and expressed as: ， in, N Indicates the number of thermal abnormal events, Indicates the n The occurrence time of the secondary thermal anomaly event, in days; Identify non-straw burning clusters based on the number of thermal anomaly events and the standard deviation of the time intervals between thermal anomaly events; Eliminate the data corresponding to the non-straw burning cluster areas in the remote sensing data of the thermal anomaly points.

4. The method for estimating the straw burning ratio according to claim 1, characterized in that: The confidence function based on the fusion of thermal emissivity and land cover is used to spatially match the processed thermal anomaly point remote sensing data and the land cover data to identify straw burning fire points, including: Mapping the coordinates of each thermal anomaly point retained in the thermal anomaly point remote sensing data after processing to the position of a corresponding pixel in the land cover data; Extract the land cover matrix within the pixel neighborhood window of a specific size from the land cover data with the corresponding pixel as the center; Calculating the farmland coverage within the pixel neighborhood window according to the land cover matrix; The confidence level of the current thermal anomaly point being a straw burning fire point is calculated based on the thermal radiation power of each thermal anomaly point and the corresponding farmland coverage rate, and is expressed as: Among them, P represents the farmland coverage rate, and Represent the minimum and maximum thresholds of farmland coverage, frp Indicates the thermal emissivity of the thermal anomaly point, , and represent the standard deviation and mean of the thermal emissivity distribution of straw burning fire points, and represent the standard deviation and mean of the thermal emissivity distribution except for the straw burning fire point; The straw burning fire spots among the thermal anomaly spots are screened according to the confidence level.

5. The method for estimating the straw burning ratio according to claim 4, characterized in that: The calculation of the straw burning area of ​​the straw burning fire point includes: The area to be estimated is divided into grids, the coordinates of the straw burning fire points are mapped to grid indexes, and the straw burning area is calculated according to the grid indexes of all straw burning fire points, which is expressed as: in, to and te Indicates the start and end time of the concentrated straw burning period, wl represents the grid side length, ( lon,lat ) represents the coordinates of the straw burning fire point, Indicates converting coordinates into grid indices. k Indicates the type of crop.

6. The method for estimating the straw burning ratio according to claim 5, characterized in that: The straw burning ratio of the area to be estimated is calculated based on the benchmark data and the straw burning area and crop planting area of ​​the area to be estimated, and is expressed as: in, Indicates the area to be estimated i In the target year j crops k of straw burning area, Indicates the area to be estimated i In the base year o crops k The benchmark straw burning area, Indicates the area to be estimated i In the base year o crops k The base planting area, Indicates the area to be estimated i In the target year j crops k of planted area, Indicates the area to be estimated i In the base year o crops k The benchmark straw burning ratio.

7. A device for estimating the proportion of straw burning, characterized in that: The device comprises: A data acquisition module is used to obtain remote sensing data of thermal anomalies and land cover data of the area to be estimated; a straw burning area calculation module, configured to identify straw burning fire spots based on the thermal anomaly remote sensing data and the land cover data, and calculate the straw burning area of ​​the straw burning fire spots; wherein the identifying of straw burning fire spots based on the thermal anomaly remote sensing data and the land cover data comprises: removing interference data from the thermal anomaly remote sensing data based on a spatiotemporal coupling criterion; and spatially matching the processed thermal anomaly remote sensing data and the land cover data based on a confidence function fused with thermal emissivity and land cover to identify the straw burning fire spots; A benchmark data acquisition module is used to obtain benchmark data of a benchmark year, wherein the benchmark data includes a benchmark straw burning area, a benchmark crop area, and a benchmark straw burning ratio; The straw burning ratio estimation module is used to calculate the straw burning ratio of the area to be estimated based on the benchmark data and the straw burning area and crop planting area of ​​the area to be estimated.

8. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for estimating the straw burning ratio according to any one of claims 1 to 6 is implemented.

9. A storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the method for estimating the straw burning ratio according to any one of claims 1 to 6 is implemented.

Images