A method for estimating pollutant emission of straw open-air burning based on fire trace area

Abstract

The application discloses a kind of straw open-air burning pollutant emission estimation method based on fire trace area, it is related to atmospheric pollution prevention technical field.The scheme includes: using fire trace identification model, extracting fire trace in satellite image data, the burning area of target crop is calculated by spatial intersection analysis, the pollutant emission of target crop straw open-air burning is calculated, and the accuracy of pollutant emission estimation value is improved by accurately identifying fire trace through fire trace identification model.

Description

Technical Field

[0001] This application relates to the field of air pollution control technology, and in particular to a method for estimating pollutant emissions from open burning of straw based on the area of ​​the fire site. Background Technology

[0002] Open burning of straw is a traditional method of agricultural waste disposal, widely practiced in agricultural areas around the world. However, the pollutants released from open straw burning have a significant impact on air quality and human health. Estimating the emissions of pollutants from open straw burning is a crucial aspect of atmospheric environmental management, but this work is extremely challenging due to the complexities involved in identifying fire points, the emission process, and various environmental factors. Therefore, accurately estimating the emissions of pollutants from open straw burning and clarifying the distribution of pollution is of great significance for atmospheric environmental management.

[0003] In related technologies, traditional methods for estimating pollutant emissions from open burning of straw use fire point data detected by satellite remote sensing. This method is easily limited by spatiotemporal resolution, and the long transit period makes it easy to miss short-duration burning events. The low resolution makes it difficult to accurately identify scattered and small-scale burning areas, resulting in a large number of missed identifications in the identification of fire points and burning areas, which leads to low accuracy in the estimated pollutant emissions. Summary of the Invention

[0004] This specification provides an embodiment of a method for estimating pollutant emissions from open burning of straw based on the area of ​​the fire-affected area, in order to solve the problem of low accuracy in pollutant emission estimation in the prior art.

[0005] To solve the above-mentioned technical problems, the embodiments in this specification are implemented as follows:

[0006] Firstly, the embodiments of this specification provide a method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected area, including:

[0007] Acquire satellite imagery data of the target area within a preset time period;

[0008] Fire traces in the satellite imagery data were identified using a fire trace identification model.

[0009] Acquire distribution data, straw coverage data, and phenological period data of the target crop, and perform spatial intersection analysis with the fire traces to calculate the burned area of ​​the target crop;

[0010] Based on the target crop's yield per unit area, straw-to-grain ratio, drying ratio, pollutant emission factor, and straw coverage ratio coefficient, combined with the burning area, the pollutant emissions from the burning of the target crop's straw are calculated.

[0011] Secondly, the embodiments of this specification provide a device for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected area, comprising:

[0012] The acquisition module is used to acquire satellite imagery data of the target area within a preset time period;

[0013] The identification module is used to identify fire traces in the satellite image data using a fire trace identification model;

[0014] The first calculation module is used to acquire the distribution data, straw coverage data and phenological period data of the target crop, and perform spatial intersection analysis with the fire trace to calculate the burning area of ​​the target crop;

[0015] The second calculation module is used to calculate the pollutant emissions from the burning of the target crop straw based on the target crop's yield per unit area, straw-to-grain ratio, drying ratio, pollutant emission factor, and straw coverage ratio coefficient, combined with the burning area.

[0016] Thirdly, the embodiments of this specification provide a device for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected area, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected area in Scheme 1.

[0017] Fourthly, the embodiments of this specification provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for estimating pollutant emissions from open burning of straw based on the area of ​​the fire-affected area in Scheme 1.

[0018] One embodiment of this specification achieves the following beneficial effects: by using a fire site identification model to extract fire sites from satellite image data, calculating the burning area of ​​the target crop through spatial intersection analysis, calculating the pollutant emissions from open burning of target crop straw, and accurately identifying fire sites through the fire site identification model, the accuracy of pollutant emission estimates is improved. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1A flowchart illustrating a method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire site, provided as an embodiment of this specification.

[0021] Figure 2 A schematic diagram illustrating the classification results of the target area output by the fire trace identification model provided in the embodiments of this specification;

[0022] Figure 3 A schematic diagram illustrating an application scenario of a method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected area, as provided in the embodiments of this specification.

[0023] Figure 4 A schematic diagram of a device for estimating pollutant emissions from open burning of straw based on the area of ​​a fire site, provided as an embodiment of this specification;

[0024] Figure 5 This is a schematic diagram of a device for estimating pollutant emissions from open burning of straw based on the area of ​​a fire site, provided as an embodiment of this specification. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of one or more embodiments of this specification clearer, the technical solutions of one or more embodiments of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of one or more embodiments of this specification.

[0026] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0027] The method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected site, as provided in the embodiments of the specification, will be described in detail with reference to the accompanying drawings.

[0028] Figure 1 This is a flowchart illustrating a method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected area, as provided in this embodiment. From a programming perspective, the entity executing the process can be a program hosted on an application server or an application client. From a hardware perspective, the entity executing the process can be a terminal device; this embodiment does not impose any particular limitation on this.

[0029] like Figure 1 As shown, the process may include the following steps:

[0030] Step 110: Acquire satellite imagery data of the target area within a preset time period.

[0031] In the embodiments described in this specification, logging into the relevant satellite data service platform allows downloading satellite imagery data of a target area within a preset time period. For example, logging into the official website of the European Space Agency's Copernicus Data Space Ecosystem (https: / / dataspace.copernicus.eu) allows downloading a Sentinel-2 satellite imagery dataset for a specific district in a specific city of a specific province on June 12, 2024. This satellite product has a global revisit frequency of 5 days, and the Sentinel-2 Multispectral Instrument (MSI) samples 13 spectral bands, acquiring data including detailed time, latitude, longitude, and band information.

[0032] In practice, to ensure the quality of satellite imagery data, satellite impact data is preprocessed. Specifically, remote sensing processing platforms (such as Google Earth Engine) are used to remove clouds from downloaded satellite images, crop the images to the study area, and remove irrelevant areas.

[0033] Step 120: Use the fire trace identification model to identify fire traces in the satellite image data.

[0034] In the embodiments of this specification, a fire trace identification model is constructed based on algorithms such as random forest and support vector machine to extract fire trace features from satellite image data and identify fire traces.

[0035] Step 130: Obtain the distribution data, straw coverage data, and phenological period data of the target crop, and perform spatial intersection analysis with the fire traces to calculate the burned area of ​​the target crop.

[0036] In the embodiments of this specification, the distribution data is obtained by downloading the raster data of the distribution of major grain-producing land from a relevant data platform (such as Figshare platform) to obtain basic crop distribution data such as geographical location, range, crop type, and planting pattern.

[0037] Straw mulch data: Obtain geographic coordinates of the mulch area, plot boundary data, and straw status information to understand the distribution of straw in the target area.

[0038] Phenological data: Collect phenological data of various crops in each province, process them into ten-day grid crop rotation vector data, and clarify the growth stages of crops at different times.

[0039] Spatial intersection analysis was performed between the distribution data of the target crop, straw mulch data, and phenological period data and the disaster-affected areas to calculate the burning area of ​​the target crop under different straw mulch scenarios within the target area.

[0040] In practice, by obtaining distribution data, straw coverage data, and phenological data of different crops, the burning area of ​​different crops can be calculated.

[0041] Step 140: Based on the target crop's yield per unit area, straw-to-grain ratio, drying ratio, pollutant emission factor, and straw coverage ratio coefficient, and in conjunction with the burning area, calculate the pollutant emissions from the burning of the target crop's straw.

[0042] In the embodiments of this specification, the yield per unit area of ​​the target crop in the target region is obtained from the statistical yearbook published by the National Bureau of Statistics. Data on the straw-to-grain ratio and dry matter ratio of the target crop in different provinces and cities are obtained through literature review. Proportion coefficients for different straw mulching scenarios (stubble and residue, straw mulch, etc.) are obtained through literature review. Multiple pollutants (such as SO2 and NO) from the target crop are obtained through literature review and the "Technical Guidelines for Compiling Air Pollutant Emission Inventories of Biomass Incineration Sources," etc. x PM 10 PM 2.5 For emission factors (e.g., local measured emission factors are collected first. If multiple measured values ​​exist, outliers are removed and the average value is taken as the final emission factor).

[0043] The crop straw yield per unit area is calculated based on crop yield per unit area, straw-to-grain ratio, and dryness ratio. The pollutant emissions from the burning of target crop straw are then calculated by combining the crop burning area, crop straw yield per unit area, pollutant emission factors, and straw coverage ratio coefficient.

[0044] By obtaining the unit area yield, straw-to-grain ratio, drying ratio, pollutant emission factors, and straw coverage ratio coefficient of different crops, the emissions of various pollutants generated by the burning of crop straw can be calculated, providing data support for atmospheric environmental management.

[0045] It should be understood that the order of some steps in the methods described in one or more embodiments of this specification may be interchanged according to actual needs, or some steps may be omitted or deleted.

[0046] In the embodiments of this specification, a fire site identification model is used to extract fire sites from satellite image data. The burning area of ​​the target crop is calculated through spatial intersection analysis, and the pollutant emissions from open burning of target crop straw are calculated. The fire site identification model accurately identifies fire sites, thereby improving the accuracy of pollutant emission estimates.

[0047] based on Figure 1 In addition to the method described in the embodiments of this specification, some specific implementation schemes of the method are also provided, which will be described below.

[0048] Optionally, the acquisition of distribution data, straw mulch data, and phenological period data of the target crop, and the spatial intersection analysis of these data with the fire-affected area to calculate the burned area of ​​the target crop, as described in the embodiments of this specification, may specifically include:

[0049] Based on the geographic information system, the fire traces are converted into vector data to obtain fire trace vector data;

[0050] Based on a geographic information system, the distribution data, straw cover data, and phenological period data of the target crop are converted into vector data to obtain the distribution vector data, straw cover vector data, and crop rotation vector data of the target crop.

[0051] Spatial intersection analysis is performed on the fire site vector data, the distribution vector data, the straw cover vector data, and the crop rotation vector data. Computational geometry tools are then used to calculate the burning area of ​​the target crop.

[0052] In this embodiment of the specification, raster data of the distribution of major grain-producing land is downloaded from the Figshare platform and converted into vector data based on the Geographic Information System (ArcGIS); straw cover data is obtained and converted into vector data based on ArcGIS; phenological period data of various crops in each province are obtained and processed into crop rotation vector data in ten-day grids based on ArcGIS.

[0053] Fire site vector data, distribution vector data, straw cover vector data, and crop rotation vector data were imported into a Geographic Information System (ArcGIS). Using the geoprocessing module, the fire site vector data was overlaid with the distribution vector data, straw cover vector data, and crop rotation vector data to generate a crop distribution map within the fire's impact area. Computational geometry tools were then used in the attribute table to calculate the burning area of ​​each crop type under different straw cover scenarios within the target area.

[0054] Optionally, the formula for calculating pollutant emissions in the embodiments of this specification can be:

[0055] E j,k =A j ×Q i,j,y ×EF×η;Q i,j,y =P i,j,y ×N i,j ×D j

[0056] Among them, E j,k The emission of pollutant k from open burning of target crop j straw; A j The area of ​​open burning of target crop j straw; Q i,j,yLet P be the annual yield per unit area of ​​straw for target crop j, i be the province, and y be the year; i,j,y N represents the annual yield per unit area of ​​the target crop j; i,j The straw-to-grain ratio of the target crop j; D j denoted as the drying ratio of target crop j straw; EF is the pollutant emission factor generated by burning target crop j straw; η is the proportional coefficient of target crop straw coverage, with a value ranging from 0 to 1.

[0057] To facilitate understanding, let's take Shandong Province's wheat harvest in 2020 as an example. The area A of open-air burning of wheat straw... j The yield per unit area of ​​wheat straw in Shandong Province in 2020 was 1.28 hectares, Q. i,j,y The yield per unit area of ​​wheat in Shandong Province in 2020 was 7786.72 kg / ha. i,j,y The straw-to-grain ratio of wheat straw in Shandong Province was 6529.20 kg / ha. i,j The drying ratio of wheat straw is 1.34, D. j The coefficient for straw coverage is 0.89, and the proportionality coefficient η is 0.15. The pollutant emissions from open burning of wheat straw are shown in Table 1.

[0058] Table 1

[0059] pollutants Emission factors Emissions / Kg <![CDATA[SO2]]> 0.85 1271.58 <![CDATA[NO X ]]> 2.15 3216.35 <![CDATA[PM 10 ]]> 10.86 16246.33 <![CDATA[PM 2.5 ]]> 10.39 15543.22 NMVOCs 4.48 6701.98 <![CDATA[NH3]]> 0.37 553.51 CO 60 89758.77 Hg 0.000011 0.016

[0060] Optionally, before identifying fire traces in the satellite image data using the fire trace identification model as described in the embodiments of this specification, the method may include:

[0061] A training sample dataset was constructed based on historical satellite imagery data containing fire traces.

[0062] The fire site identification model is trained based on the training sample dataset to obtain the trained fire site identification model.

[0063] In the embodiments described in this specification, historical satellite imagery data (such as Sentinel-2) containing fire traces are used, selecting multi-temporal and multi-regional satellite imagery data to ensure that the samples cover different land cover types (vegetation, water bodies, buildings, roads, straw, fire traces, etc.). Each category of samples is color-coded (e.g., fire traces are marked in red) and its attributes are defined (e.g., category name, coverage area). The labeled samples are then divided into training and testing sets in a ratio (e.g., 7:3) for model training and validation.

[0064] Multiple remote sensing indices (such as NDVI, NDWI, EVI, and BAI) are extracted from satellite imagery data to enhance the ability to distinguish ground features. Texture features (such as mean and variance) in the near-infrared band are calculated and slope data (such as SRTM DEM) is introduced to combine them into multi-band imagery as input features to train the fire trace identification model.

[0065] Taking a fire trail identification model built using the random forest algorithm as an example, hyperparameters are set (e.g., number of trees = 200, sampling ratio = 0.8), and the model is trained using the training set data. Cross-validation is then used to optimize the model parameters and avoid overfitting.

[0066] In practice, a confusion matrix is ​​generated based on the test set data, and indicators such as overall accuracy, Kappa coefficient, and user accuracy are calculated. An evaluation threshold is set (e.g., Kappa coefficient ≥ 0.8). If the threshold is not met, the model parameters are adjusted (e.g., increasing the number of trees or optimizing the kernel function) and the model is retrained.

[0067] Figure 2 This is a schematic diagram of the classification results of the target area output by the fire trace identification model provided in the embodiments of this specification.

[0068] like Figure 2 As shown, different colors represent different land cover types, which can be classified as vegetation, water bodies, buildings, roads, straw, and fire traces.

[0069] Optionally, after identifying fire traces in the satellite image data using the fire trace identification model described in the embodiments of this specification, the method includes:

[0070] Based on the geographic information system, the area of ​​the fire-affected area is calculated.

[0071] Based on the ground observation data of the target area collected by the UAV, calculate the ground observation area of ​​the fire within the target area;

[0072] Determine whether the error between the observed ground area and the fire-affected area is less than or equal to a preset threshold;

[0073] If so, the trained fire site identification model will be used as the target fire site identification model.

[0074] In this embodiment of the specification, based on ArcGIS, the fire-affected area raster data is converted into vector polygons, and the total area of ​​the vector polygons is calculated using ArcGIS's computational geometry tools. Ground observation data collected by the UAV includes the fire's occurrence time, latitude and longitude, location, imagery, and actual fire area.

[0075] Calculate the absolute and relative errors between the ground observation area and the fire scar area, where the absolute error = |fire scar area - UAV observation area|;

[0076] The preset threshold can be 20%. If the relative error is less than or equal to the threshold, it means that the accuracy of the fire trace identification model meets the standard and can be used as the target fire trace identification model.

[0077] If the relative error exceeds the threshold, the model needs to be optimized (e.g., by adjusting feature parameters or increasing training samples) and retrained to ensure it is suitable for accurately estimating pollutant emissions from open burning of straw.

[0078] Figure 3 This diagram illustrates an application scenario of a method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected site, as provided in the embodiments of this specification.

[0079] like Figure 3 As shown, step 301: acquire satellite image data of the target area within a preset time period and perform preprocessing;

[0080] Step 302: Use the fire site identification model to identify fire sites in satellite imagery data and evaluate the accuracy of the fire site identification model;

[0081] Step 303: Obtain ground observation data and calculate the relative error between the ground observation area and the fire-affected area;

[0082] Step 304: Determine whether the relative error is less than or equal to a preset threshold;

[0083] If yes, step 305: Obtain the distribution data, straw cover data, and phenological period data of the target crop, and perform spatial intersection analysis with the fire traces to calculate the burned area of ​​the target crop; if no, optimize the model and return to step 302.

[0084] Step 306: Based on the target crop's yield per unit area, straw-to-grain ratio, drying ratio, pollutant emission factor, and straw coverage ratio coefficient, and combined with the burning area, calculate the pollutant emissions from the burning of target crop straw.

[0085] Figure 4 This is a schematic diagram of a device for estimating pollutant emissions from open burning of straw based on the area of ​​a fire site, provided as an embodiment of this specification.

[0086] Corresponding to the method embodiment, this embodiment also provides a device for estimating pollutant emissions from open burning of straw based on the area of ​​the fire-affected area, which may include:

[0087] The acquisition module 402 is used to acquire satellite image data of the target area within a preset time period;

[0088] The identification module 404 is used to identify fire traces in the satellite image data using a fire trace identification model;

[0089] The first calculation module 406 is used to acquire the distribution data, straw coverage data and phenological period data of the target crop, and perform spatial intersection analysis with the fire trace to calculate the burning area of ​​the target crop;

[0090] The second calculation module 408 is used to calculate the pollutant emissions from the burning of the target crop straw based on the target crop's yield per unit area, straw-to-grain ratio, drying ratio, pollutant emission factor, and straw coverage ratio coefficient, combined with the burning area.

[0091] Optionally, the acquisition of distribution data, straw mulch data, and phenological period data of the target crop, and the spatial intersection analysis of these data with the fire-affected area to calculate the burned area of ​​the target crop, as described in the embodiments of this specification, may specifically include:

[0092] Based on the geographic information system, the fire traces are converted into vector data to obtain fire trace vector data;

[0093] Based on a geographic information system, the distribution data, straw cover data, and phenological period data of the target crop are converted into vector data to obtain the distribution vector data, straw cover vector data, and crop rotation vector data of the target crop.

[0094] Spatial intersection analysis is performed on the fire site vector data, the distribution vector data, the straw cover vector data, and the crop rotation vector data. Computational geometry tools are then used to calculate the burning area of ​​the target crop.

[0095] Optionally, the formula for calculating pollutant emissions in the embodiments of this specification can be:

[0096] E j,k =A j ×Q i,j,y ×EF×η;Q i,j,y =P i,j,y ×N i,j ×D j

[0097] Among them, E j,k The emission of pollutant k from open burning of target crop j straw; A j The area of ​​open burning of target crop j straw; Q i,j,y Let P be the annual yield per unit area of ​​straw for target crop j, i be the province, and y be the year;i,j,y N represents the annual yield per unit area of ​​the target crop j; i,j The straw-to-grain ratio of the target crop j; D j denoted as the drying ratio of target crop j straw; EF is the pollutant emission factor generated by burning target crop j straw; η is the proportional coefficient of target crop straw coverage, with a value ranging from 0 to 1.

[0098] Based on the same idea, this specification also provides devices corresponding to the above methods in its embodiments.

[0099] Figure 5 This is a schematic diagram of a device for estimating pollutant emissions from open-air straw burning based on the area of ​​a fire-affected area, provided as an embodiment of this specification. Figure 5 As shown in the embodiments of this specification, an apparatus 500 for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected site is provided. The apparatus includes a memory 530, a processor 510, and a computer program 520 stored in the memory. The processor 510 executes the computer program 520 to implement the method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected site as described in any of the above embodiments.

[0100] The embodiments of this specification provide an apparatus for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected site. This apparatus may include a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the method for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected site as described in any of the above embodiments.

[0101] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the method for estimating pollutant emissions from open burning of straw based on the area of ​​the fire-affected area described in any of the above embodiments.

[0102] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, for... Figure 5 As the device shown is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0103] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0104] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, ASICs, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0105] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0106] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0107] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0109] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0110] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0111] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0112] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0113] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, 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, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0114] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0115] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0116] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0117] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for estimating pollutant emissions from open burning of straw based on the area of ​​the burned area, characterized in that, include: Acquire satellite imagery data of the target area within a preset time period; A training sample dataset was constructed based on historical satellite imagery data containing fire traces. The fire site identification model is trained based on the training sample dataset to obtain the trained fire site identification model. In the training sample dataset, various remote sensing indices of satellite image data are extracted to enhance the ability to distinguish ground features. Texture features of the near-infrared band are calculated and slope data is introduced to combine them into multi-band images as input features to train the fire trace identification model. Fire traces in the satellite imagery data were identified using a fire trace identification model. Acquire distribution data, straw mulch data, and phenological period data of the target crop, and perform spatial intersection analysis with the fire-affected areas to calculate the burned area of ​​the target crop, including: Based on a geographic information system (GIS), the fire-affected areas are converted into vector data to obtain fire-affected area vector data. Also based on the GIS, the distribution data, straw cover data, and phenological period data of the target crop are converted into vector data to obtain distribution vector data, straw cover vector data, and crop rotation vector data for the target crop. Spatial intersection analysis is performed between the fire-affected area vector data and the distribution vector data, straw cover vector data, and crop rotation vector data, and computational geometry tools are used to calculate the burned area of ​​the target crop. Based on the target crop's yield per unit area, straw-to-grain ratio, drying ratio, pollutant emission factor, and straw coverage ratio coefficient, combined with the burning area, the pollutant emissions from the burning of the target crop's straw are calculated. The formula for calculating the pollutant emissions is as follows: ； ； in, The emission of pollutant k from open burning of target crop j straw; The area of ​​open burning of target crop straw; Let i be the annual yield per unit area of ​​straw for the target crop j, i be the province, and y be the year; Let be the annual yield per unit area of ​​the target crop j; The straw-to-grain ratio of the target crop j; The drying ratio of the target crop j's straw; Pollutant emission factors generated from the burning of target crop straw; The proportionality coefficient for the straw coverage of the target crop ranges from 0 to 1.

2. The method according to claim 1, characterized in that, After identifying fire traces in the satellite imagery data using a fire trace identification model, the method includes: Based on the geographic information system, the area of ​​the fire-affected area is calculated. Based on the ground observation data of the target area collected by the UAV, calculate the ground observation area of ​​the fire within the target area; Determine whether the error between the observed ground area and the fire-affected area is less than or equal to a preset threshold; If so, the trained fire site identification model will be used as the target fire site identification model.

3. A device for estimating pollutant emissions from open burning of straw based on the area of ​​the burned area, characterized in that, include: The acquisition module is used to acquire satellite imagery data of the target area within a preset time period; The identification module is used to identify fire traces in the satellite image data using a fire trace identification model; The first calculation module is used to acquire the distribution data, straw coverage data and phenological period data of the target crop, and perform spatial intersection analysis with the fire trace to calculate the burned area of ​​the target crop; The second calculation module is used to calculate the pollutant emissions from the burning of the target crop straw based on the target crop's yield per unit area, straw-to-grain ratio, drying ratio, pollutant emission factor, and straw coverage ratio coefficient, combined with the burning area.

4. The apparatus according to claim 3, characterized in that, The process of acquiring distribution data, straw mulch data, and phenological period data of the target crop, and performing spatial intersection analysis with the fire-affected areas to calculate the burned area of ​​the target crop specifically includes: Based on the geographic information system, the fire traces are converted into vector data to obtain fire trace vector data; Based on a geographic information system, the distribution data, straw cover data, and phenological period data of the target crop are converted into vector data to obtain the distribution vector data, straw cover vector data, and crop rotation vector data of the target crop. Spatial intersection analysis is performed on the fire site vector data, the distribution vector data, the straw cover vector data, and the crop rotation vector data. Computational geometry tools are then used to calculate the burning area of ​​the target crop.

5. The apparatus according to claim 3, characterized in that, The formula for calculating the pollutant emissions is as follows: ； ； in, The emission of pollutant k from open burning of target crop j straw; The area of ​​open burning of target crop straw; Let i be the annual yield per unit area of ​​straw for the target crop j, i be the province, and y be the year; Let be the annual yield per unit area of ​​the target crop j; The straw-to-grain ratio of the target crop j; The drying ratio of the target crop j's straw; Pollutant emission factors generated from the burning of target crop straw; The proportionality coefficient for the straw coverage of the target crop ranges from 0 to 1.

6. A device for estimating pollutant emissions from open burning of straw based on the area of ​​a fire-affected area, comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 2.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 2.

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