Satellite cloud image live broadcast method

Abstract

This application provides a method for live streaming of satellite cloud images, relating to the field of satellite monitoring technology. The method includes the following steps: acquiring multiple cloud images observed by satellite; pre-setting grids of different sizes for the cloud images and classifying the cloud images to obtain cloud images of different resolutions; cropping the cloud images of corresponding resolutions according to the pre-set grids to obtain corresponding slices; grouping each slice according to time and creating video slices; and loading relevant information from the video slices onto the user terminal to display satellite cloud image animations according to the window size and position. This method can deliver high spatiotemporal resolution meteorological satellite cloud images to the user terminal in a timely manner, providing users with low-latency and high-timeliness cloud image services, thereby achieving live streaming of satellite cloud image animations, meeting weather monitoring needs, and providing technical support for meteorological forecasting services.

Description

Technical Field

[0001] This invention relates to the field of satellite monitoring technology, specifically to a method for live streaming of satellite cloud images. Background Technology

[0002] With the rapid development of satellite remote sensing technology, the temporal and spatial resolution of satellite cloud images are becoming increasingly higher. In particular, my country's new-generation geostationary meteorological satellite, Fengyun-4B, features a newly added rapid imager capable of high-frequency, high-spatial-resolution rapid observation and imaging of a 2000×1800 square kilometer area at a spatial resolution of 250m, once per minute. These high-temporal-resolution cloud images can intuitively reflect real-time weather conditions and are highly effective in observing and monitoring rapidly changing extreme weather events such as typhoons and severe convection. This plays a crucial role in the development of weather forecasting systems and improving meteorological service capabilities. However, the significantly improved temporal and spatial resolution also increases the amount of data acquired by satellite observations, posing a significant challenge to subsequent data processing and the timeliness of satellite cloud image generation. Timeliness is paramount for rapidly changing weather conditions.

[0003] To provide forecasters and other users with a clear and real-time view of the continuous changes in cloud formations and the Earth's surface, conventional satellite cloud image visualization methods include: 1. Transmitting the sequence of cloud images to be displayed to the user's device and showing them frame by frame at a specified playback speed. The larger the size and number of cloud images, the greater the amount of data transmitted, and the greater the computational resources required by the user's device. Therefore, this method is extremely inefficient and provides a poor user experience when applied to satellite cloud images with high temporal and spatial resolutions. 2. Creating a video from the cloud image sequence and transmitting it to the user's device for playback. While this significantly reduces the data volume, it still has significant drawbacks: First, high spatial resolution cloud images have a large overall size, resulting in excessively high video resolution. Decoding and playback on the user's device consumes a large amount of computational resources. For example, the regional cloud image size of the Fengyun-4B satellite's rapid imager at a 250-meter spatial resolution is 7600 pixels × 8000 pixels, which is insufficient for most mainstream personal use. First, user computers struggle to load and play such high-resolution videos smoothly. Second, high temporal resolution cloud images update rapidly; for example, the Fengyun-4B satellite's rapid imager can generate a cloud image every minute. Videos require frequent reloading and replaying to achieve real-time updates, resulting in massive data transmission and playback stuttering, impacting user experience. Furthermore, most conventional video players lack zoom and roaming capabilities, making it inconvenient for users to view local details and changes in cloud images. Third, while dividing each cloud image into hierarchical pyramid tiles and transmitting a series of tiles within the viewport to the user for stitching and frame-by-frame rotation based on user input provides zoom and roaming capabilities for viewing panoramic and local views of high spatial resolution cloud images, during animation playback, the asynchronous loading of tiles at different positions within the same frame due to parallel loading for efficiency can lead to unupdated parts during playback. If preloading and buffering are used to avoid the problem of local non-updates, users will have to wait longer. Moreover, the transmission and buffering of a large number of tiles also puts high demands on bandwidth and computing resources, making it difficult to achieve a good user experience when there are many cloud maps and the playback frame rate is fast.

[0004] Therefore, to address the above issues, it is necessary to study rapid processing and visualization technologies for high spatiotemporal resolution meteorological satellite remote sensing data, so as to provide users with intuitive and real-time displays of continuous changes in cloud formations, meet the needs of weather system monitoring, and provide technical support for meteorological forecasting services. Summary of the Invention

[0005] To address the challenge of providing intuitive and real-time display of high spatiotemporal resolution meteorological satellite remote sensing images, this application offers a method for live streaming of satellite cloud images. This method delivers high spatiotemporal resolution meteorological satellite cloud images to users in a timely manner, providing them with low-latency and high-efficiency cloud image services. It enables live streaming of satellite cloud image animations, meets weather monitoring needs, and provides technical support for meteorological forecasting services.

[0006] The technical solution adopted by this application embodiment to solve its technical problem is: a method for live broadcasting of satellite cloud images, characterized by including the following steps:

[0007] S1. Obtain multiple cloud images from satellite observations;

[0008] S2. Preset different grid sizes for the cloud map and classify the cloud map to obtain cloud maps of different resolutions;

[0009] S3. Crop the cloud map of the corresponding resolution according to the preset grid to obtain the corresponding slice;

[0010] S4. Group the slices according to time and create video slices;

[0011] S5. The user client loads relevant information about the video slice to display satellite cloud image animations based on the window size and position.

[0012] In one specific implementation, in step S3, when cropping the cloud map according to a preset grid, an overlapping area is set between adjacent grids so that the user can seamlessly switch between adjacent grids when browsing.

[0013] In one specific implementation, the size of the grid is G = (W + A) / R, where W is the larger of the horizontal and vertical pixel values ​​of the satellite cloud image animation display window, R is the grid scaling factor, and A is the pixel distance that allows the grid to be dragged and roamed.

[0014] In one specific implementation, in step S2, when the cloud map is classified according to resolution, the spatial resolution relationship between adjacent classifications is P. n =kP n+1 ;where P n P represents the spatial resolution of the nth level of the hierarchy. n+1 Let k be the spatial resolution of the (n+1)th level of the classification; k > 1; n is a natural number.

[0015] In one specific implementation, after classifying the cloud imagery according to resolution, the spatial resolution for switching between adjacent classifications during satellite cloud imagery animation display is P. m , where P m The value is between P n and Pn+1 Between these parameters, so that when satellite cloud image animations are displayed in the user's view, the spatial resolution of the cloud image is adjusted by zooming in and out of the grid. m The boundary is in the adjacent level P n and P n+1 Switching between them; the grid allows scaling factor R = P n+1 / P m .

[0016] In one specific implementation, in step S4, the latest video slice is selected to construct a video index file and a cloud map time list file, wherein the cloud map time list file contains the time information corresponding to each frame of the cloud map in the video slice.

[0017] In one specific implementation, step S1 involves real-time monitoring of the cloud imagery observed by the satellite and timely acquisition of updated cloud images.

[0018] In one specific implementation, in step S4, video slices are created from the acquired updated cloud map, and the original related video slices, video index files, and cloud map time list files are updated accordingly.

[0019] In one specific implementation, in step S4, information parameters are set for the video slices created from the updated cloud map to distinguish them, and an update notification is sent to the user terminal.

[0020] In one specific implementation, in step S5, after receiving the update notification, the user terminal re-acquires the updated video index file and cloud map time list file, and loads the relevant video slices that need to be updated.

[0021] The advantages of the embodiments of this application are:

[0022] 1. The live satellite cloud image broadcasting method encodes cloud images into video format, groups them into video slices according to time, transmits them as video streams, and updates each video slice individually. After receiving a message notification, the user only needs to reload the last video slice, which reduces the amount of data transmission and enables fast transmission and fast updates, thereby solving the problem of transmission and updating of high spatiotemporal resolution meteorological satellite remote sensing data.

[0023] 2. The live satellite cloud image streaming method uses a grid-based approach to create videos. This allows for the appropriate reduction and resolution of cloud images in the generated videos to provide panoramic animation displays. Alternatively, cloud images in the videos can be cropped into multiple grids according to the user's view size to provide detailed displays of local cloud images, thus meeting diverse user needs.

[0024] 3. The live satellite cloud image streaming method has overlapping areas between multiple adjacent grids in the cloud image file, which can make each position in the cloud image as close as possible to the center of the user's screen, so that the user can switch seamlessly when browsing between adjacent grids.

[0025] 4. The live satellite cloud image streaming method can further improve the user experience. Users can pan and zoom the satellite cloud image animation window to display animated videos of areas of interest. When the user operates the window position at the corresponding resolution and it exceeds the edge of the video's visible range, the corresponding grid slice can be rematched according to the current window position to obtain and play the video slice of the corresponding resolution. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the hierarchical grid and user window for a satellite cloud image live streaming method according to the present invention. Detailed Implementation

[0027] This application provides a method for live streaming of satellite cloud images, addressing the issue of intuitive real-time display of high spatiotemporal resolution meteorological satellite remote sensing images. The overall approach is as follows:

[0028] This invention provides a method for live streaming of satellite cloud images, comprising the following steps: acquiring multiple cloud images observed by satellite; pre-setting grids of different sizes for the cloud images and classifying the cloud images into different resolutions; cropping the cloud images of corresponding resolutions according to the pre-set grids to obtain corresponding slices; grouping each slice according to time and creating video slices; and loading relevant information of the video slices onto the user terminal to display satellite cloud image animations according to the window size and position. This method can deliver high spatiotemporal resolution meteorological satellite cloud images to the user terminal in a timely manner, providing users with low-latency and high-timeliness cloud image services, thereby realizing live streaming of satellite cloud image animations, meeting weather monitoring needs, and providing technical support for meteorological forecasting services.

[0029] In this embodiment, the acquired cloud map is encoded into a video format and grouped into video slices by time. This is transmitted as a video stream, and each video slice is updated individually. After receiving a notification from the server, the user only needs to reload the last video slice, thus reducing the amount of data transmitted and achieving fast transmission and updates. Simultaneously, the cloud map is hierarchically classified to obtain cloud maps of different resolutions. Videos are created using a hierarchical grid approach, with different resolution levels to meet different animation display needs: lower-level videos reduce the cloud map's size and resolution to provide panoramic animation; higher-level videos break down the cloud map into multiple slices cropped from a preset grid, suitable for the user's screen resolution, to provide high-definition animation of specific cloud map details. Specifically, various grid sizes are pre-set based on common monitor resolutions. When loading video on the user's end, video slices of the appropriate grid size that cover the entire viewport are loaded as needed. Preferably, when cropping the cloud map according to the preset grid, adjacent grids of the same level overlap to allow for seamless switching during user navigation.

[0030] In this embodiment, the preset grid size G = (W + A) / R, where W is the larger of the horizontal and vertical pixel values ​​in the satellite cloud image animation display window, R is the grid scaling factor (when the scaling factor exceeds R, it switches to an adjacent grid level), and A is the pixel distance allowed for dragging the grid (when the user drags it beyond the range, it switches to another adjacent grid). When the cloud image is classified according to resolution, the spatial resolution relationship between adjacent levels is P. n =kP n+1 ;where P n P represents the spatial resolution of the nth level of the hierarchy. n+1 Let P be the spatial resolution of the (n+1)th level of the classification; k>1, representing a multiple of the spatial resolution between adjacent levels; n is a natural number. After classifying the cloud image according to resolution, the spatial resolution used to switch between adjacent levels during satellite cloud image animation display is P. m , where P m The value is between P n and P n+1 Between these parameters, so that when satellite cloud image animations are displayed in the user's view, the spatial resolution of the cloud image is adjusted by zooming in and out of the grid. m The boundary is in the adjacent level P n and P n+1 Switch between modes; grid allows scaling factor R = P n+1 / P m .

[0031] For example, the spatial resolution between adjacent levels typically increases by a factor of 2, i.e., k = 2, P n =2Pn+1 Simultaneously, it can be applied to adjacent grade P. n and P n+1 Switching to the median of the spatial resolution, i.e., P m =(P n +P n+1 Therefore, the grid allows a scaling factor R = P / 2. n+1 / P m =2 / 3. Furthermore, based on extensive practical experience and considering common screen resolutions, the pixel distance allowing users to drag and roam the grid is set to the standard definition horizontal pixel distance, i.e., A = 720. Therefore, the grid size is: G = (W + 720) * 1.5. According to this formula, the preset grid sizes for common screen types are shown in the table below:

[0032]

[0033] In this example, we take the original satellite cloud images of China (original image size 21984×8735 pixels, size after cropping invalid data 15360×8640 pixels) with a spatial resolution of 500 meters as an example. The corresponding classifications and resolutions are shown in the table below:

[0034]

[0035]

[0036] Further, please refer to Figure 1 A half-redundant overlapping area is set between adjacent grids (e.g., grids U1U2U3U4 and grids V1V2V3V4). When the user window is displayed, the corresponding video slice of the corresponding grid is loaded according to the position of the user window T1T2T3T4. As mentioned above, the existence of the redundant overlapping area also facilitates seamless switching when the user is roaming.

[0037] In this example, satellite-observed cloud images are monitored in real time to obtain updated cloud images promptly. Furthermore, video slices from the latest times are selected to construct a video index file and a cloud image time list file. The cloud image time list file contains the time information corresponding to each frame of the cloud image in the video slice. Video slices are created from the acquired updated cloud images, and the existing related video slices, video index file, and cloud image time list file are updated accordingly. Information parameters are set for the video slices created from the acquired updated cloud images to distinguish them, and an update notification is sent to the user terminal. After receiving the update notification, the user terminal re-obtains the updated video index file and cloud image time list file, and loads the relevant video slices that need to be updated.

[0038] In practice, the steps are as follows:

[0039] I. Cloud Image Processing

[0040] Source file monitoring: Monitors the satellite cloud image source directory in real time, and triggers the cloud image processing flow when a new cloud image is delivered.

[0041] Cloud image preprocessing: cropping and removing areas without data, performing image enhancement, etc.

[0042] Hierarchical grid processing: The cloud map is scaled according to different resolution levels and cropped into slices of fixed size with overlapping areas between adjacent slices according to a preset grid. Unlike the pyramid slices used in website map frames, the slices here need to have overlapping areas between adjacent slices so that each location in the cloud map can be displayed in the center of the user's screen as much as possible, allowing users to slice and switch seamlessly while roaming.

[0043] Taking a 500-meter resolution cloud image of the FY4AAGRI satellite over China and a slice suitable for a 2K screen (2560×1440 pixels) as an example, the input is a 500-meter resolution FY4AAGRI satellite cloud image over China at any time, with an image pixel of 15360×8640, and the output is a slice of the corresponding level, with each slice having a pixel of 4920×4920.

[0044] II. Video Slicing Production

[0045] Based on the cloud map file time, video slices are created by encoding cloud map slices in groups of half an hour. For video slices that have already been created and have been updated with cloud map data, the old file is recreated and overwritten. For example, a video slice file Doc1 for 08:00 to 08:05 is created at 8:05. At 8:29, a video slice file Doc2 for 08:00 to 08:29 is created, and Doc2 overwrites Doc1. Therefore, in this step, the input is a continuous 3-hour slice image cropped from the corresponding grid at the corresponding level, and the output is a group of video slices corresponding to the corresponding grid at the corresponding level. Each level can have multiple grids, and each grid creates a group of video slices. Each group of video slices can contain multiple video slice files, for example, in .ts format. Each video slice file has a playback duration of 1 second and contains half an hour of cloud map slice content.

[0046] III. Publish Live Video Index

[0047] Select video slices from the most recent time period (usually set to the last 3 hours based on business experience), construct a video index file and a cloud map time list file, and add a version number parameter to the video slices that need to be updated for differentiation. In this step, the input is the video slice group at each level of the grid and the relevant cloud map time information, and the output is the video index file and the cloud map time list file. For example, the video index file can be in m3u8 format, and the cloud map time list file can be in JSON format, saving the time information corresponding to each frame.

[0048] IV. Video Update Notification

[0049] The service interface is invoked to send an update notification. In this step, the input is the completion information for the corresponding cloud map animation video, and the output is the background process calling the website service interface, with the website service sending a message to the user client via WebSocket.

[0050] V. Video loading and playback updates

[0051] The client retrieves the latest video list based on the cloud animation product name, resolution, and user window size, and loads the video index file and cloud animation time list file. The client can play the cloud animation by loading video slices, pausing for 2 seconds after playback ends before resuming. When the client receives an update notification, it re-retrieves the corresponding video index file and cloud animation time list file, and reloads the video slices that need updating. In this step, the inputs are the user opening the page, user selection, and roaming operations; the outputs are the corresponding video index file, cloud animation time list file, and video slice file.

[0052] VI. Animation Interaction

[0053] Users can switch between cloud map animation products and change product name parameters by clicking with the mouse, and then proceed to step five. When users drag the mouse or scroll with the mouse wheel, the relevant cloud map animation window is panned and scaled to display the animation of the area of ​​interest to the user. When the user selects the original resolution, the slice row and column numbers of the corresponding grid are calculated based on the current window position, and step five is performed to obtain and play the original resolution video slice at the specified location. When the user drags the mouse at the original resolution and the window position exceeds the edge of the visible video range, the slice row and column numbers of the corresponding grid are recalculated based on the current window position, and step five is performed to obtain and play the original resolution video slice at the specified location, achieving seamless roaming.

[0054] This embodiment also provides an apparatus based on a live satellite cloud imagery method, including one or more processors and a storage device. The storage device is used to store one or more programs, which, when executed by one or more processors, enable the one or more processors to implement the live satellite cloud imagery method.

[0055] The components of the device may include, but are not limited to: one or more processors or processing units, memory, and buses connecting different system components (including memory and processing units).

[0056] A bus refers to one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0057] Devices based on satellite cloud imagery live streaming methods typically include a variety of computer system-readable media. These media can be any available media that can be accessed by devices based on satellite cloud imagery live streaming methods, including volatile and non-volatile media, and portable and non-portable media.

[0058] The memory may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory. Devices based on the satellite cloud imagery live streaming method may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system may be used to read and write non-removable, non-volatile magnetic media (commonly referred to as "hard disk drives"), and may provide disk drives for reading and writing to removable non-volatile disks (e.g., "floppy disks"), and optical disk drives for reading and writing to removable non-volatile optical discs (e.g., CD-ROMs, DVD-ROMs, or other optical media). In these cases, each drive may be connected to a bus via one or more data media interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0059] A program / utility having a set (at least one) of program modules can be stored, for example, in memory. Such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules typically perform the functions and / or methods described in the embodiments of this invention.

[0060] Devices based on the satellite cloud imagery live streaming method can also communicate with one or more external devices (e.g., keyboards, pointing devices, displays, etc.), one or more devices that enable users to interact with the device, and / or any device that enables the device to communicate with one or more other computing devices (e.g., network interface cards, modems, etc.). This communication can be performed via input / output (I / O) interfaces. Furthermore, the device can communicate with one or more networks (e.g., local area networks, wide area networks, and / or public networks, such as the Internet) via a network adapter. The network adapter communicates with other modules of the device via a bus and can be used in conjunction with other hardware and / or software modules, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems. The processing unit executes various functional applications and data processing by running programs stored in memory.

[0061] Additionally, this embodiment may also include a computer-readable storage medium storing a program that, when executed by a processor, implements a method for live streaming satellite cloud images.

[0062] The computer storage medium of this embodiment can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0063] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0064] The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof. The computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0065] In summary, this invention provides a method for live streaming of satellite cloud images, which can deliver high spatiotemporal resolution meteorological satellite cloud images to users in a timely manner, providing users with low-latency and high-timeliness cloud image services. This enables live streaming of satellite cloud image animations, meets weather monitoring needs, provides technical support for weather forecasting services, and thus solves the problem of intuitive and real-time display of high spatiotemporal resolution meteorological satellite remote sensing data.

[0066] Finally, it should be noted that the above embodiments are merely examples for clearly illustrating the present invention and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for live streaming of satellite cloud images, characterized in that, Including the following steps: S1. Obtain multiple cloud images from satellite observations; S2. Preset different grid sizes for the cloud map and classify the cloud map to obtain cloud maps of different resolutions; S3. Crop the cloud map of the corresponding resolution according to the preset grid to obtain the corresponding slice; S4. Group the slices according to time and create video slices; S5. The user client loads relevant information about the video slice to display satellite cloud image animations based on the window size and position; In step S3, when cropping the cloud map according to a preset grid, an overlapping area is set between adjacent grids so that users can seamlessly switch between adjacent grids when browsing. Wherein, the size of the grid is G = (W + A) / R, where W is the larger of the horizontal and vertical pixel values ​​in the satellite cloud image animation display window, R is the grid scaling factor, and A is the pixel distance that allows dragging and roaming the grid; and In step S2, when the cloud map is classified according to resolution, the spatial resolution relationship between adjacent levels is Pn=kPn+1; where Pn is the spatial resolution of the nth level of the classification; Pn+1 is the spatial resolution of the (n+1)th level of the classification; k>1; and n is a natural number.

2. The method for live satellite cloud image broadcasting as described in claim 1, characterized in that, After classifying the cloud image according to resolution, the spatial resolution for switching between adjacent levels during satellite cloud image animation display is Pm, where the value of Pm is between Pn and Pn+1. This ensures that when the satellite cloud image animation is displayed in the user's window, the spatial resolution of the cloud image switches between adjacent levels Pn and Pn+1 with Pm as the boundary when the grid is zoomed in or out. The grid allows a scaling factor R = Pn+1 / Pm.

3. A method for live streaming satellite cloud images as described in any one of claims 1-2, characterized in that, In step S4, the latest video slice is selected to construct a video index file and a cloud map time list file. The cloud map time list file contains the time information corresponding to each frame of the cloud map in the video slice.

4. The method for live satellite cloud image broadcasting as described in claim 3, characterized in that, In step S1, the cloud images observed by the satellite are monitored in real time and updated cloud images are obtained in a timely manner.

5. The method for live satellite cloud image broadcasting as described in claim 4, characterized in that, In step S4, video slices are created from the obtained updated cloud map, and the original related video slices, video index files, and cloud map time list files are updated accordingly.

6. The method for live satellite cloud image broadcasting as described in claim 5, characterized in that, In step S4, information parameters are set for the video slices created from the updated cloud map to distinguish them, and an update notification is sent to the user terminal.

7. The method for live satellite cloud image broadcasting as described in claim 6, characterized in that, In step S5, after receiving the update notification, the user terminal re-acquires the updated video index file and cloud map time list file, and loads the relevant video slices that need to be updated.

Images