Integrated processing method and system for satellite data

Abstract

The invention relates to the technical field of satellite remote sensing data processing, and discloses an integrated processing method and system for satellite data, and the method comprises the steps: obtaining a selection instruction; wherein the selection instruction is an instruction for processing L1-level data in an HDF format or an instruction for processing product data in an NC format; if the selection instruction is the instruction for processing the NC format product data, executing an NC product data processing flow; and if the selection instruction is the instruction for processing the L1-level data in the HDF format, executing an HDFL1-level data processing flow. According to the method, a plurality of dispersed processing steps are integrated into a unified tool, and through an automatic process, the operation is greatly simplified, and the data processing period from original data to available products is shortened.

Description

Technical Field

[0001] This invention relates to the field of satellite remote sensing data processing technology, and in particular to an integrated processing method and system for satellite data. Background Technology

[0002] With the rapid development of remote sensing technology, new-generation geostationary meteorological satellites such as Fengyun-4B (FY-4B) have provided massive amounts of observational data and products in multiple formats and resolutions. However, in practical applications, processing this data still presents many challenges:

[0003] 1. Cumbersome and fragmented processing flow: For different data products provided by the FY-4B satellite, such as L1-level data in HDF format and CLM and CLT data in NC format, users typically need to use different software or write separate scripts for processing. This results in a fragmented processing flow, complex operations, and low efficiency.

[0004] 2. High technical threshold: Data processing involves multiple professional steps such as radiometric calibration, geographic correction, format conversion, and data cropping. These operations require users to have strong programming skills and knowledge of remote sensing data processing, making it unfriendly to non-professional users.

[0005] 3. Lack of unified and automated tools: The market lacks an integrated, menu-driven processing tool that can encapsulate the entire process of FY-4B satellite data from raw data to standardized geographic raster data (such as GeoTIFF). Users often need to manually set a large number of parameters, resulting in repetitive work and making it difficult to achieve batch and automated business processes.

[0006] 4. Lack of data collaboration mechanism: Existing workflows typically treat L1-level raw data and advanced product data (such as CLM products) as independent information sources and process them separately. When users need to combine the two for comprehensive analysis (for example, using CLM products to extract cloud areas from L1 images), they must manually perform complex spatiotemporal matching and data overlay, lacking an automated mechanism that can efficiently link and collaboratively process the two. Summary of the Invention

[0007] The purpose of this invention is to provide an integrated processing method and system for satellite data, addressing the problems of cumbersome processing procedures, high technical barriers, lack of automation tools, and lack of collaborative processing mechanisms in existing technologies. The core of the method is to provide an integrated processing framework, which is launched through a unified menu-driven user interface. Users can choose to process HDF format L1-level data and NC format product data according to their needs. The system guides users to input the raw data path, geographic lookup table file, and output directory. Users can flexibly select various preset areas, including China and custom areas, for data cropping and can specify the bands to be processed. This method integrates core functions such as radiometric calibration, rapid geometric correction based on geographic lookup tables, cloud mask creation, cloud extraction, multi-band data synthesis, and GeoTIFF format conversion. Ultimately, the system can automatically process raw, complex satellite data into TIFF format imagery with standard geographic coordinates (WGS84) that can be directly used for subsequent analysis. It also supports packaging the entire application into a standalone EXE executable file, enabling installation-free and cross-platform use.

[0008] To achieve the above objectives, the following technical solution is adopted:

[0009] In a first aspect, the present invention provides an integrated processing method for satellite data, comprising:

[0010] Obtain a selection instruction; wherein the selection instruction is an instruction for processing HDF format L1 level data or an instruction for processing NC format product data;

[0011] If the selection instruction is an instruction for processing NC format product data, then the NC product data processing flow is executed, which includes:

[0012] Receive user input including the folder path of the NC file, the path of the geographic lookup table file, the output directory, and the data type;

[0013] The system receives the cropping range and output file prefix selected by the user. If the data type is cloud detection data, it also receives the user's selection instruction on whether to create a cloud mask.

[0014] Based on the geographic lookup table, the NC data is geographically corrected and cropped. If a selection instruction to create a cloud mask is received, a cloud mask is created, and the processed data is output as a GeoTIFF format file with WGS84 standard geographic coordinates.

[0015] If the selection instruction is an instruction for processing HDF format L1 level data, then the HDFL1 level data processing flow is executed, which includes:

[0016] Receive user input for the folder path where the HDF file is located, the geographic lookup table file path, and the output folder path;

[0017] The system receives the user's selected resolution, cropping range, range of bands to be processed, and output file prefix. If the resolution is a set resolution, it also receives the user's selection instruction on whether to apply cloud extraction.

[0018] Read the calibration coefficients in the HDF file and convert the raw DN values ​​in the HDF data into radiance or reflectance;

[0019] Based on the geographic lookup table, the radiometrically calibrated HDF data is geographically corrected and cropped. If a selection instruction for application cloud extraction is received, masking processing is performed based on the geographic information cloud mask file. The processed data is then synthesized into a multi-band GeoTIFF format file and output. The GeoTIFF format file contains WGS84 standard geographic coordinates.

[0020] Preferably, the data type includes cloud detection data or cloud top temperature data.

[0021] Preferably, the cutting range includes a preset cutting range and a custom cutting range. The preset cutting range includes [45°E, 170°E, 0°N, 58°N], [73°E, 135°E, 4°N, 54°N], or [110°E, 117°E, 25°N, 29°N].

[0022] Preferably, the specific formula for converting the raw DN values ​​in the HDF data into radiance or reflectance is as follows:

[0023] target_channel[valid_mask]=cal_channel[cal_mask][nom_channel[valid_mask]]

[0024] Wherein, target_channel is the converted target channel data, valid_mask is the valid data mask, cal_channel is the scaling coefficient channel data, cal_mask is the scaling coefficient mask, and nom_channel is the original DN value channel data.

[0025] Preferably, the specific formula for masking based on the geographic information cloud mask file is as follows:

[0026] mask_band[mask_data==1]=clipped_band[mask_data==1]

[0027] Wherein, mask_band is the band data after masking, mask_data is the cloud mask data, and clipped_band is the clipped HDF band data.

[0028] Secondly, the present invention also provides an integrated processing system for satellite data, the system comprising:

[0029] The function selection module is configured to acquire selection instructions; wherein the selection instructions are instructions for processing HDF format L1 level data or instructions for processing NC format product data.

[0030] The NC product data processing module is configured to execute an NC product data processing flow when the selected instruction is an instruction for processing NC format product data. The NC product data processing flow includes:

[0031] Receive user input including the folder path of the NC file, the path of the geographic lookup table file, the output directory, and the data type;

[0032] The system receives the cropping range and output file prefix selected by the user. If the data type is cloud detection data, it also receives the user's selection instruction on whether to create a cloud mask.

[0033] Based on the geographic lookup table, the NC data is geographically corrected and cropped. If a selection instruction to create a cloud mask is received, a cloud mask is created, and the processed data is output as a GeoTIFF format file with WGS84 standard geographic coordinates.

[0034] The HDFL Level 1 data processing module is configured to execute an HDFL Level 1 data processing flow when the selected instruction is for processing HDF format L1 level data. The HDFL Level 1 data processing flow includes:

[0035] Receive user input for the folder path where the HDF file is located, the geographic lookup table file path, and the output folder path;

[0036] The system receives the user's selected resolution, cropping range, range of bands to be processed, and output file prefix. If the resolution is a set resolution, it also receives the user's selection instruction on whether to apply cloud extraction.

[0037] Read the calibration coefficients in the HDF file and convert the raw DN values ​​in the HDF data into radiance or reflectance;

[0038] Based on the geographic lookup table, the radiometrically calibrated HDF data is geographically corrected and cropped. If a selection instruction for application cloud extraction is received, masking processing is performed based on the geographic information cloud mask file. The processed data is then synthesized into a multi-band GeoTIFF format file and output. The GeoTIFF format file contains WGS84 standard geographic coordinates.

[0039] Preferably, the data type includes cloud detection data or cloud top temperature data.

[0040] Preferably, the cutting range includes a preset cutting range and a custom cutting range. The preset cutting range includes [45°E, 170°E, 0°N, 58°N], [73°E, 135°E, 4°N, 54°N], or [110°E, 117°E, 25°N, 29°N].

[0041] Preferably, the specific formula for converting the raw DN values ​​in the HDF data into radiance or reflectance is as follows:

[0042] target_channel[valid_mask]=cal_channel[cal_mask][nom_channel[valid_mask]]

[0043] Wherein, target_channel is the converted target channel data, valid_mask is the valid data mask, cal_channel is the scaling coefficient channel data, cal_mask is the scaling coefficient mask, and nom_channel is the original DN value channel data.

[0044] Preferably, the specific formula for masking based on the geographic information cloud mask file is as follows:

[0045] mask_band[mask_data==1]=clipped_band[mask_data==1]

[0046] Wherein, mask_band is the band data after masking, mask_data is the cloud mask data, and clipped_band is the clipped HDF band data.

[0047] The beneficial effects of this invention are reflected in:

[0048] 1. Improve processing efficiency: Integrate multiple scattered processing steps into a unified tool, greatly simplifying operations and shortening the data processing cycle from raw data to usable products through automated processes.

[0049] 2. Lowering the barrier to entry: The menu-driven interface and clear operation instructions enable users without a professional programming background to easily complete complex satellite data preprocessing tasks.

[0050] 3. Enhanced application flexibility: Supports multiple resolutions from 500m to 4km, covering the two mainstream formats HDF and NC, and provides flexible region cropping and band selection functions to meet the personalized needs of different scientific research and business applications.

[0051] 4. Convenient deployment: By packaging the application and all dependent libraries into a single executable file (.exe), users can run it directly on mainstream operating systems such as Windows without complex environment configuration (such as installing GDAL, Python, etc.), which greatly improves the portability and ease of use of the software. Attached Figure Description

[0052] Figure 1 A flowchart of an integrated processing method for satellite data according to an embodiment of the present invention is shown;

[0053] Figure 2 A flowchart of NC product data processing according to an embodiment of the present invention is shown;

[0054] Figure 3 A flowchart of HDFL Level 1 data processing according to an embodiment of the present invention is shown;

[0055] Figure 4 This diagram illustrates the system startup command-line menu interface displayed when executing an NC product data processing flow according to an embodiment of the present invention;

[0056] Figure 5 This diagram illustrates the input parameters during the execution of an NC product data processing flow according to an embodiment of the present invention.

[0057] Figure 6 A schematic diagram of the processing procedure when executing the NC product data processing flow according to an embodiment of the present invention is shown;

[0058] Figure 7 This diagram illustrates the cloud mask extraction results obtained by executing the NC product data processing flow according to an embodiment of the present invention.

[0059] Figure 8 This diagram illustrates the input parameters when executing an HDFL Level 1 data processing flow according to an embodiment of the present invention.

[0060] Figure 9 This diagram illustrates the input parameters when executing an HDFL Level 1 data processing flow according to an embodiment of the present invention.

[0061] Figure 10 A schematic diagram of the processing procedure when executing HDFL Level 1 data processing flow according to an embodiment of the present invention is shown;

[0062] Figure 11 This diagram illustrates the cloud mask extraction results obtained by executing the HDFL Level 1 data processing flow according to an embodiment of the present invention.

[0063] Figure 12 A structural diagram of an integrated satellite data processing system according to an embodiment of the present invention is shown. Detailed Implementation

[0064] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0065] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples.

[0066] This invention provides an integrated processing method for satellite data, such as... Figure 1 The diagram shown is an overall flowchart of the integrated processing method and system for satellite data. The integrated processing method and system for satellite data includes the following steps S10 to S30.

[0067] S10: Obtain selection instructions; where the selection instructions are instructions for processing HDF format L1 level data or instructions for processing NC format product data.

[0068] For example, upon launching the main program, the system displays a text menu interface. The user selects either "1. HDFL Level 1 Data Processing" or "2. NC Product Data Processing" based on the data type to be processed. The system then invokes the corresponding processing module based on the user's selection. This processing module includes a first module and a second module. The first module is configured to execute the NC product data processing flow described in step S20 below, and the second module is configured to execute the HDFL Level 1 data processing flow described in step S30 below.

[0069] S20: If the selected instruction is to process NC format product data, then the NC product data processing flow will be executed.

[0070] like Figure 2 As shown, the NC product data processing flow includes the following steps S201-S203.

[0071] S201: Receives user input of the folder path where the NC file is located, the path of the geographic lookup table file, the output directory, and the data type.

[0072] In practice, after the user selects this function, the system prompts the user to enter the folder path where the NC file is located, the path of the geographic lookup table file, the output directory, and the data type (such as CLM, CLT, etc.).

[0073] S202: Receives the cropping range and output file prefix selected by the user. If the data type is cloud detection data, it also receives the user's selection instruction on whether to create a cloud mask.

[0074] In practice, users select the cropping range and output file prefix. For CLM (Cloud Inspection) data, an option to "create a cloud mask" is provided.

[0075] S203: Performs geographic correction and cropping on NC data based on a geographic lookup table. If a selection instruction to create a cloud mask is received, a cloud mask is created, and the processed data is output as a GeoTIFF format file with WGS84 standard geographic coordinates.

[0076] In practice, the system uses a geographic lookup table to perform geographic correction and cropping on the NC data, and names it according to the rule {prefix}_{timestamp}_{data type}_{cropping range}.tif, outputting it as a GeoTIFF file.

[0077] S30: If the selected instruction is to process HDF format L1 level data, then the HDF L1 level data processing flow will be executed.

[0078] like Figure 3 As shown, the HDFL Level 1 data processing flow includes the following steps S301-S304.

[0079] S301: Receives user input of the folder path where the HDF file is located, the geographic lookup table file path, and the output folder path.

[0080] In practice, after the user selects this function, the system will prompt the user to enter the folder path where the HDF file is located, the path of the geographic lookup table (.raw format) file, and the path of the output folder in sequence.

[0081] S302: Receives the resolution, cropping range, band range to be processed, and output file prefix selected by the user. If the resolution is the set resolution, it also receives the user's selection instruction on whether to apply cloud extraction.

[0082] In practice, users select the data resolution (500m, 1km, 2km, or 4km), cropping range (e.g., China [73,135,4,54] or a custom latitude and longitude range), the band range to be processed, and the prefix of the output file based on the prompts. For 4km resolution data, the system additionally provides an option to "apply cloud extraction".

[0083] S303: Reads the calibration coefficients in the HDF file and converts the original DN values ​​in the HDF data into radiance or reflectance.

[0084] In practice, the system reads the calibration coefficients from the HDF file and applies the following calibration formula to the original DN (Digital Number) value to convert it into radiance or reflectance: target_channel[valid_mask]=cal_channel[cal_mask][nom_channel[valid_mask]

[0085] Wherein, target_channel is the converted target channel data, valid_mask is the valid data mask, cal_channel is the scaling coefficient channel data, cal_mask is the scaling coefficient mask, and nom_channel is the original DN value channel data.

[0086] S304: Based on the geographic lookup table, perform geographic correction and cropping on the radiometrically calibrated HDF data. If a selection instruction for application cloud extraction is received, perform masking processing based on the geographic information cloud mask file, synthesize the processed data into a multi-band GeoTIFF format file and output it. The GeoTIFF format file contains WGS84 standard geographic coordinates.

[0087] In practice, the system reads the geographic lookup table provided by the user to obtain a table of latitude and longitude ranges. Simultaneously, the data is cropped based on the latitude and longitude range selected by the user.

[0088] The user inputs the path to the GeoTIFF (Geographic Information Cloud Mask) file. The system iterates through the mask files, matching HDFL Level 1 data with the same date for masking. The formula is as follows:

[0089] mask_band[mask_data==1]=clipped_band[mask_data==1]

[0090] Wherein, mask_band is the band data after masking, mask_data is the cloud mask data, and clipped_band is the clipped HDF band data.

[0091] Combine one or more processed bands into a single multi-band GeoTIFF file, and name and save it according to the rule {prefix}{timestamp}_{band range}-{cropping range}.tif.

[0092] In one specific embodiment, the above process steps can be packaged into a software script (build_exe.py) using the PyInstaller tool. Executing this script automatically analyzes project dependencies (such as numpy, gdal, h5py, etc.) and packages the Python interpreter, all code, and dependent libraries into a single executable file (FY4B_Integration_Tool.exe) located in the dist / directory. This file can be run directly on computers without Python or related libraries installed, enabling convenient distribution and use of the method.

[0093] In summary, the method provided by the embodiments of the present invention has at least the following beneficial effects:

[0094] 1) This method highly integrates various data processing functions for Fengyun-4B (FY-4B) satellite into a unified tool. It simultaneously supports the processing of HDF format L1-level data and NC format product data within a single application, and integrates a series of core steps such as radiometric calibration, geographic correction, multi-region cropping, cloud mask creation, cloud extraction, multi-band output, and format conversion. This changes the previously cumbersome process of using different tools and writing multiple scripts, forming a one-stop solution.

[0095] 2) This method provides a menu-driven user interface. Users do not need to write any code; they can simply follow the clear command-line prompts, select functions sequentially, and enter parameters such as paths to automatically complete complex processing flows. This greatly lowers the technical barrier to satellite data processing, making it easy for users who are not remote sensing or programming professionals to use.

[0096] 3) This method supports all four L1 data resolutions from 500m, 1km, 2km to 4km, and covers multiple products such as CLM and CLT. It also includes multiple preset cropping regions such as China and Zhuzhou, and supports user-defined latitude and longitude ranges, flexibly meeting the personalized data needs of different scientific research or business scenarios.

[0097] 4) This method includes a packaging script (build_exe.py) that packages the entire Python application and all its complex dependencies (such as GDAL, NumPy, and H5py) into a single .exe executable file. This is a significant innovation in solving the problem of difficult environment configuration in traditional remote sensing tools. Users do not need to install Python or configure a complex GDAL environment on their computers to run and use the tool directly, greatly improving its portability, distribution efficiency, and user adoption.

[0098] To further illustrate the feasibility and advancement of the method proposed in this invention, this embodiment uses FY-4B full-disk data passing over the area at 04:00 UTC and 16:00 UTC on October 29, 2024 as an example, with the target region being the Northern Hemisphere (latitude and longitude range: [45°E, 170°E, 0°N, 58°N]). It fully demonstrates the entire process from raw observation data to multi-band GeoTIFF products that can be directly used for scientific research. The case study runs in parallel across three typical business scenarios, highlighting the comprehensive advantages of this system in batch processing, cross-format collaboration, cloud mask linkage, and one-click packaging and distribution.

[0099] Data source description:

[0100] Level 1 data:

[0101] FY4B-_AGRI--_N_DISK_1050E_L1-_FDI-_MULT_NOM_20241029040000_20241029041459_4000M_V0001.HDF (4Km resolution).

[0102] NC Product Data:

[0103] FY4B-_AGRI--_N_DISK_1050E_L2-_CLM-_MULT_NOM_20241029040000_20241029041459_4000M_V0001.NC (Cloud Detection Product).

[0104] RAW file:

[0105] FY4B-_DISK_1050E_GEO_NOM_LUT_20240227000000_4000M_V0001.raw (Geographic Lookup Table).

[0106] NC product data processing is used to create cloud mask files. Running the executable file "FY4B_Integration_Tool.exe" will bring up the system startup command-line menu interface as follows: Figure 4As shown. The user enters "2" to select processing NC product data. In this processing flow, the input parameters are as follows. Figure 5 As shown, the processing procedure is as follows: Figure 6 As shown, the final cloud mask extraction result is as follows: Figure 7 As shown.

[0107] HDF L1 level data processing is used to extract cloud areas. Running the executable file "FY4B_Integration_Tool.exe" will bring up the system's command-line menu interface as follows: Figure 8 As shown. The user inputs "1" to select processing HDF_L1 level data. In this processing flow, the input parameters are as follows: Figure 9 As shown, the processing procedure is as follows: Figure 10 As shown, the final cloud mask extraction result is as follows: Figure 11 As shown. The cloud area extraction results are as follows. Figure 12 As shown.

[0108] This invention also provides an integrated satellite data processing system, such as... Figure 12 As shown, the system includes:

[0109] The function selection module 1201 is configured to obtain a selection instruction; wherein the selection instruction is an instruction for processing HDF format L1 level data or an instruction for processing NC format product data.

[0110] NC product data processing module 1202 is configured to execute an NC product data processing flow when the selected instruction is an instruction to process NC format product data, the NC product data processing flow including:

[0111] Receive user input including the folder path of the NC file, the path of the geographic lookup table file, the output directory, and the data type;

[0112] The system receives the cropping range and output file prefix selected by the user. If the data type is cloud detection data, it also receives the user's selection instruction on whether to create a cloud mask.

[0113] Based on the geographic lookup table, the NC data is geographically corrected and cropped. If a selection instruction to create a cloud mask is received, a cloud mask is created, and the processed data is output as a GeoTIFF format file with WGS84 standard geographic coordinates.

[0114] The HDFL Level 1 data processing module 1203 is configured to execute an HDFL Level 1 data processing flow when the selected instruction is an instruction for processing HDF format L1 level data. The HDFL Level 1 data processing flow includes:

[0115] Receive user input for the folder path where the HDF file is located, the geographic lookup table file path, and the output folder path;

[0116] The system receives the user's selected resolution, cropping range, range of bands to be processed, and output file prefix. If the resolution is a set resolution, it also receives the user's selection instruction on whether to apply cloud extraction.

[0117] Read the calibration coefficients in the HDF file and convert the raw DN values ​​in the HDF data into radiance or reflectance;

[0118] Based on the geographic lookup table, the radiometrically calibrated HDF data is geographically corrected and cropped. If a selection instruction for application cloud extraction is received, masking processing is performed based on the geographic information cloud mask file. The processed data is then synthesized into a multi-band GeoTIFF format file and output. The GeoTIFF format file contains WGS84 standard geographic coordinates.

[0119] In some embodiments, the data type includes cloud detection data or cloud top temperature data.

[0120] In some embodiments, the cutting range includes a preset cutting range and a custom cutting range. The preset cutting range includes [45°E, 170°E, 0°N, 58°N], [73°E, 135°E, 4°N, 54°N], or [110°E, 117°E, 25°N, 29°N].

[0121] In some embodiments, the specific formula for converting the raw DN values ​​in the HDF data into radiance or reflectance is as follows:

[0122] target_channel[valid_mask]=cal_channel[cal_mask][nom_channel[valid_mask]]

[0123] Wherein, target_channel is the converted target channel data, valid_mask is the valid data mask, cal_channel is the scaling coefficient channel data, cal_mask is the scaling coefficient mask, and nom_channel is the original DN value channel data.

[0124] In some embodiments, the specific formula for masking based on the geographic information cloud mask file is as follows:

[0125] mask_band[mask_data==1]=clipped_band[mask_data==1]

[0126] Wherein, mask_band is the band data after masking, mask_data is the cloud mask data, and clipped_band is the clipped HDF band data.

[0127] It should be noted that the integrated satellite data processing system described in the above embodiments and the prior integrated satellite data processing method are based on the same technical concept, have the same technical principles and beneficial effects, and therefore will not be elaborated here.

[0128] The above embodiments are only used to illustrate the present invention and are not intended to limit the present invention. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, all equivalent technical solutions also fall within the scope of the present invention, and the patent protection scope of the present invention should be defined by the claims.

Claims

1. An integrated processing method for satellite data, characterized in that, include: Obtain a selection instruction; wherein the selection instruction is an instruction for processing HDF format L1 level data or an instruction for processing NC format product data; If the selection instruction is an instruction for processing NC format product data, then the NC product data processing flow is executed, which includes: Receive user input including the folder path of the NC file, the path of the geographic lookup table file, the output directory, and the data type; The system receives the cropping range and output file prefix selected by the user. If the data type is cloud detection data, it also receives the user's selection instruction on whether to create a cloud mask. Based on the geographic lookup table, the NC data is geographically corrected and cropped. If a selection instruction to create a cloud mask is received, a cloud mask is created, and the processed data is output as a GeoTIFF format file with WGS84 standard geographic coordinates. If the selection instruction is an instruction for processing HDF format L1 level data, then the HDFL1 level data processing flow is executed, which includes: Receive user input for the folder path where the HDF file is located, the geographic lookup table file path, and the output folder path; The system receives the user's selected resolution, cropping range, range of bands to be processed, and output file prefix. If the resolution is a set resolution, it also receives the user's selection instruction on whether to apply cloud extraction. Read the calibration coefficients in the HDF file and convert the raw DN values ​​in the HDF data into radiance or reflectance; Based on the geographic lookup table, the radiometrically calibrated HDF data is geographically corrected and cropped. If a selection instruction for application cloud extraction is received, masking processing is performed based on the geographic information cloud mask file. The processed data is then synthesized into a multi-band GeoTIFF format file and output. The GeoTIFF format file contains WGS84 standard geographic coordinates.

2. The integrated processing method for satellite data according to claim 1, characterized in that, The data types include cloud detection data or cloud top temperature data.

3. The integrated processing method for satellite data according to claim 1, characterized in that, The cutting range includes a preset cutting range and a custom cutting range. The preset cutting range includes [45°E, 170°E, 0°N, 58°N], [73°E, 135°E, 4°N, 54°N] or [110°E, 117°E, 25°N, 29°N].

4. The integrated processing method for satellite data according to claim 1, characterized in that, The specific formula for converting the raw DN values ​​in HDF data into radiance or reflectance is: target_channel[valid_mask] = cal_channel[cal_mask][nom_channel[valid_mask]] Wherein, target_channel is the converted target channel data, valid_mask is the valid data mask, cal_channel is the scaling coefficient channel data, cal_mask is the scaling coefficient mask, and nom_channel is the original DN value channel data.

5. The integrated processing method for satellite data according to claim 1, characterized in that, The specific formula for masking based on geographic information cloud mask files is as follows: mask_band[mask_data==1]=clipped_band[mask_data==1] Wherein, mask_band is the band data after masking, mask_data is the cloud mask data, and clipped_band is the clipped HDF band data.

6. An integrated satellite data processing system, characterized in that, The system includes: The function selection module is configured to acquire selection instructions; wherein the selection instructions are instructions for processing HDF format L1 level data or instructions for processing NC format product data. The NC product data processing module is configured to execute an NC product data processing flow when the selected instruction is an instruction for processing NC format product data. The NC product data processing flow includes: Receive user input including the folder path of the NC file, the path of the geographic lookup table file, the output directory, and the data type; The system receives the cropping range and output file prefix selected by the user. If the data type is cloud detection data, it also receives the user's selection instruction on whether to create a cloud mask. Based on the geographic lookup table, the NC data is geographically corrected and cropped. If a selection instruction to create a cloud mask is received, a cloud mask is created, and the processed data is output as a GeoTIFF format file with WGS84 standard geographic coordinates. The HDFL Level 1 data processing module is configured to execute an HDFL Level 1 data processing flow when the selected instruction is for processing HDF format L1 level data. The HDFL Level 1 data processing flow includes: Receive user input for the folder path where the HDF file is located, the geographic lookup table file path, and the output folder path; The system receives the user's selected resolution, cropping range, range of bands to be processed, and output file prefix. If the resolution is a set resolution, it also receives the user's selection instruction on whether to apply cloud extraction. Read the calibration coefficients in the HDF file and convert the raw DN values ​​in the HDF data into radiance or reflectance; Based on the geographic lookup table, the radiometrically calibrated HDF data is geographically corrected and cropped. If a selection instruction for application cloud extraction is received, masking processing is performed based on the geographic information cloud mask file. The processed data is then synthesized into a multi-band GeoTIFF format file and output. The GeoTIFF format file contains WGS84 standard geographic coordinates.

7. The integrated satellite data processing system according to claim 6, characterized in that, The data types include cloud detection data or cloud top temperature data.

8. The integrated satellite data processing system according to claim 6, characterized in that, The cutting range includes a preset cutting range and a custom cutting range. The preset cutting range includes [45°E, 170°E, 0°N, 58°N], [73°E, 135°E, 4°N, 54°N] or [110°E, 117°E, 25°N, 29°N].

9. The integrated satellite data processing system according to claim 6, characterized in that, The specific formula for converting the raw DN values ​​in HDF data into radiance or reflectance is: target_channel[valid_mask] = cal_channel[cal_mask][nom_channel[valid_mask]] Wherein, target_channel is the converted target channel data, valid_mask is the valid data mask, cal_channel is the scaling coefficient channel data, cal_mask is the scaling coefficient mask, and nom_channel is the original DN value channel data.

10. The integrated satellite data processing system according to claim 6, characterized in that, The specific formula for masking based on geographic information cloud mask files is as follows: mask_band[mask_data==1]=clipped_band[mask_data==1] Wherein, mask_band is the band data after masking, mask_data is the cloud mask data, and clipped_band is the clipped HDF band data.

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