CN115391579A - Remote sensing image space-time aggregation instant computing image service method - Google Patents

Abstract

The invention relates to the field of remote sensing image calculation service, in particular to a remote sensing image space-time aggregation instant calculation image service method. The invention specifically adopts a space-time polymerization-based instant calculation method to perform multi-scale dynamic image tile service of the multi-source satellite remote sensing image. The invention establishes a data transmission mode of a space-time image database and a standard service interface, can realize the effective connection of a user customized tile service request and the instant dynamic tile calculation, meets the requirements of different types of customization, simultaneously enables a user side to participate in the interaction of the image service pair by the instant dynamic tile calculation service, breaks through the traditional service mode that only a static tile pair service mode is passively received, and constructs a space-time image model with coexisting time and space by the space-time aggregation remote sensing image service model which is adopted by the invention so as to better provide services from different dimensions of time and space.

Description

A real-time calculation image service method for remote sensing image spatio-temporal aggregation

technical field

The invention relates to the field of remote sensing image computing services, and the IPC classification number is: G06F16/51, which relates to a remote sensing image spatio-temporal aggregation real-time computing image service method.

Background technique

At this stage, with the development of social economy and the progress of urbanization, ecological environment monitoring and the development of land resources have gradually become one of the key research issues. Remote sensing satellite images can collect a wide range of geographic information and land use data, so as to This is for regional land resource monitoring and data analysis. Traditional remote sensing satellite image service platforms include Google Maps, Gaode Maps, Baidu Maps, Tiandi Maps, etc. However, in the process of remote sensing image service data processing, static slices are usually used to provide image tile services. The image service content has been solidified and can only provide fixed information content. It cannot better integrate satellite remote sensing images with high revisit frequency, high-frequency coverage, and all-weather data acquisition capabilities, and cannot meet the current needs of different types of high-level data. The timely service capability of different types of remote sensing data of the satellite remote sensing image platform at a lower resolution cannot meet the new demand for remote sensing satellite image services for natural resource investigation and monitoring.

Patent CN202011600442 provides a method for quickly loading remote sensing images on the Android system (compatible with BS and CS service models), by establishing a thread pool in the Android system that can obtain tile data to collect tile data, and at the same time by optimizing The system parameters in the process of loading data are used to increase the speed of asynchronous task execution. Therefore, the core technical point of this patent is to optimize and improve the data read and write speed of the Android system.

Patent CN201811004785 provides a geographic grid-based remote sensing image segmentation method and equipment, by separately processing remote sensing images and remote sensing data based on geographic grid segmentation through load balancing servers, thereby relieving the server from processing remote sensing images. Due to the data pressure in the data process, the metadata is segmented separately to improve the efficiency of data segmentation.

However, the above patents have not fully processed the data information fusion, access frequency and acquisition capabilities of the sending end based on satellite remote sensing data. At the same time, the solidified image data is still processed by static slicing, which cannot better improve the timely service of remote sensing data. Therefore, it is urgent to introduce a real-time computing image service method for spatial-temporal aggregation of remote sensing images

Contents of the invention

Aiming at the existing problems, the present invention provides a remote sensing image time-space aggregation real-time calculation image service method, which specifically adopts the real-time calculation method based on time-space aggregation to perform multi-scale dynamic image tile service of multi-source satellite remote sensing images.

Preferably, the multi-source satellite remote sensing images specifically include panorama satellites and orthophoto images of other satellites.

Preferably, the orthophoto is stored online as image data, and metadata based on multi-source satellite remote sensing images is established to construct a spatio-temporal data structure model.

Preferably, the spatio-temporal data structure model is based on the spatial image model with a time series added; the time series includes changes in land cover in the same space at different times.

Preferably, the spatio-temporal data structure model includes spatio-temporal image databases with online, near-line and offline generalized distributed storage.

Preferably, the spatio-temporal image database classifies the collected metadata, and outputs the classified metadata for real-time calculation based on spatio-temporal aggregation.

Preferably, the real-time calculation based on spatio-temporal aggregation divides the classified metadata according to different time frames, and adaptively registers the metadata divided by time frames with the high spatial resolution data.

Preferably, the real-time calculation based on spatio-temporal aggregation is based on a spatio-temporal image database to build a computing service system platform.

Preferably, the computing service system platform includes a storage network, a computing platform, and a real-time computing distributed parallel service system; wherein the computing distributed parallel service system uses multiple servers to process real-time computing dynamic tiles in parallel.

Preferably, the computing service system platform communicates with the client by establishing a standardized unified service interface; the standardized unified service interface connects user-customized tile service requests with real-time dynamic tile computing.

Compared with prior art, the beneficial effect of the present invention is:

(1) The present invention establishes a data transmission mode of a spatio-temporal image database and a standard service interface. Compared with the traditional image service, which only targets individual data results, and the service content is single, or the service can only be performed according to the data version, the database is relatively large. Many, different types of data are often unable to be centrally and effectively managed. It can realize the effective connection between user-customized tile service requests and real-time dynamic tile calculations, and then complete the entire image service process to meet different types of customization needs.

(2) The real-time computing dynamic tile service of the present invention enables the client to participate in the interaction of image service pairs, breaking through the traditional service mode of only passively accepting static tile pair service mode.

(3) The spatio-temporal aggregation remote sensing image service model adopted in the present invention constructs a spatio-temporal image model with coexistence of time and space, which can provide services from different dimensions of time and space, and simultaneously access the surface coverage of the area at a certain spatial location at any time, which This service capability optimizes the existing image service system.

Description of drawings

Fig. 1 is a flowchart of a real-time computing image service method for spatial-temporal aggregation of remote sensing images.

Detailed ways

A real-time computing image service method based on spatio-temporal aggregation of remote sensing images. Specifically, a real-time computing method based on spatio-temporal aggregation is used to provide multi-scale dynamic image tile services for multi-source satellite remote sensing images. Specifically, satellite remote sensing image data is performed in units of scenes Segment storage, processing and distribution, the underlying data storage and organization logic of the present invention aims at the limitations of this technology, adopts a new data organization storage model, and combines the new development direction of high-performance computing to build a service for Natural resource investigation, monitoring, supervision and other satellite remote sensing image service methods with higher timeliness, more complex demands, and more intelligent services, and provide the maximum time management accuracy of satellite remote sensing image results, so that the time resolution of the results can reach days, Even hours, minutes, seconds level.

Specifically, the real-time calculation image service method of remote sensing image spatio-temporal aggregation described in the present invention includes:

S1. Based on the whole-scene satellite remote sensing image results and their metadata, build a generalized distributed storage spatio-temporal remote sensing image database based on online, near-line and offline. The system manages information including time, space, scale, source, sensor, etc. The real-time calculation of the database provides support;

S2. Build a high-performance computing service system platform, including high-performance storage network, high-performance computing platform and real-time computing distributed parallel service system;

S3. Standardize and unify the service interface, realize the effective connection between the user's customized tile service request and the real-time dynamic tile calculation, and then complete the entire image service process.

In a preferred embodiment, in the data storage, management and scheduling method based on the whole-scene satellite remote sensing image results, the method mainly solves the efficient database management based on the whole-scene satellite image results, and is also compatible with other ways to organize and store the images As a result, this method can also solve the needs of high-performance parallel computing cluster interfaces, ensure the efficiency, security and consistency of data access to different computing nodes, and be responsible for the maintenance of image databases, including data storage management and removal, to maintain Dynamic growth and healthy development of remote sensing image databases.

In a preferred implementation, the high-performance computing-based dynamic slice computing method described in the present invention. This method first aims at the spatio-temporal image data model, and solves the logic problem of dynamic tile calculation in a series of demand customization modes related to scale, time, space, and data source through real-time calculation; secondly, by constructing spatiotemporal and massive and multi-scaled remote sensing image color base maps to achieve dynamic tile color balance; moreover, through time and space optimization analysis, the tile calculation process is optimized to reduce unnecessary remote sensing image IO processes and improve tile calculation efficiency. It has greatly improved the service capability and social and economic benefits of satellite remote sensing images.

In one embodiment, the multi-source satellite remote sensing image specifically includes panorama satellites and orthophoto images of other satellites. Specifically, the orthophotos collected by the full-view satellite retain all the information of each remote sensing image, all the overlapping in space and the continuous coverage in time, and then construct a three-dimensional space-time where time and space coexist The image model makes it possible for image services to provide services from different dimensions of time and space.

In a preferred embodiment, the traditional remote sensing data production mode adopts the method of framing to store and manage the results, which requires a lot of manpower, time, and money to mosaic and cut the data, resulting in a large amount of information in the image data. The most serious problem is that the spatial and temporal dimensions of the image are compressed, and the spatially overlapping and temporally continuous data information is solidified into two-dimensional image data, which greatly reduces the data service capability and quality. In the spatio-temporal aggregation service technology, the whole-view satellite remote sensing orthoimage is used as the data source, which can greatly save manpower, energy and materials for data processing, and more importantly, it can greatly provide remote sensing image data applications. The timeliness of service provides the efficiency from image data acquisition to image service, which is of great significance to the social and economic benefits of multi-source satellite remote sensing imagery.

In one embodiment, the orthophoto is stored online as image data, and metadata based on multi-source satellite remote sensing images is established to construct a spatio-temporal data structure model.

In one embodiment, the spatio-temporal data structure model is based on a spatial image model with a time series added; the time series includes changes in land cover in the same space at different times.

In one embodiment, the spatio-temporal data structure model includes spatio-temporal image databases with online, near-line and offline generalized distributed storage.

In one embodiment, the spatio-temporal image database classifies the collected metadata, and outputs the classified metadata for real-time calculation based on spatio-temporal aggregation. Specifically, the real-time computing method based on spatio-temporal aggregation , to better solve the problem of spatio-temporal data organization model in data spatio-temporal aggregation services, specifically, the classification categories include time, space, scale, source, sensor, etc., the categories described in the present invention include but are not limited to the present invention said content.

In one embodiment, the real-time calculation based on spatio-temporal aggregation divides the classified metadata according to different time frames, and adaptively matches the metadata divided by time frames with high spatial resolution data. allow.

In one embodiment, the real-time calculation based on spatio-temporal aggregation is based on a spatio-temporal image database to build a computing service system platform.

In one embodiment, the computing service system platform includes a storage network, a computing platform, and a real-time computing distributed parallel service system; wherein the computing distributed parallel service system uses multiple servers to process real-time computing dynamic tiles in parallel .

In a preferred embodiment, how to provide standardized image tile services according to client requests has always been a key technical difficulty in satellite remote sensing image data transmission. Traditional static tiles are no longer feasible for this model. The three-dimensional spatio-temporal image data is statically transferred to the two-dimensional tile service, and the dynamic tile service technology described in the present invention is combined with real-time computing, using high-performance computing and adopting dynamic tile production technology to meet the client's request , real-time dynamic production request space and time image tiles, and then real-time image map tile service.

In one embodiment, the computing service system platform communicates with the client by establishing a standardized unified service interface; the standardized unified service interface connects user-customized tile service requests with real-time dynamic tile calculations .

In a preferred embodiment, the underlying logic of the present invention lies in that the present invention stores and serves data by using the results of satellite remote sensing images to maximize the preservation of the original space and time attributes of remote sensing images and maximize the The space-time information of the image data is retained, and data and framework support are provided for the follow-up to provide more complex, intelligent and diversified services; secondly, the method of the present invention fully combines the current high-performance computing technology for the development prospect, and adopts the method of real-time calculation and dynamic slicing to It solves the problem that static image slice services cannot be provided under the condition of spatio-temporal image data model. While meeting the needs of traditional image services, it also solves the problem of intelligent, automated and customized services under the framework of spatio-temporal image database, which can meet different data sources and different The scale, different standards, and distributed storage of dynamic aggregation services for remote sensing image results have truly solved the need for an image library and a standard service interface to provide all the information of remote sensing images to the outside world at the logical level.

Claims (10)

1. A real-time image computing service method for remote sensing image space-time aggregation is characterized in that a real-time computing method based on space-time aggregation is specifically adopted to perform multi-scale dynamic image tile service of multi-source satellite remote sensing images.

2. The method as claimed in claim 1, wherein the multi-source satellite remote sensing image includes panoramic and other framing satellite ortho images.

3. The remote-sensing image space-time polymerization real-time calculation image service method according to claim 2, characterized in that the orthoimage is subjected to image data online storage, and a remote-sensing image space-time image database based on a space-time data structure model is constructed by combining multi-source satellite remote-sensing image metadata.

4. The remote-sensing image space-time polymerization real-time computation image service method according to claim 3, characterized in that the space-time data structure model is added with a time sequence on the basis of a space image model; the time sequence carries out the earth surface coverage change of the same space in different time.

5. The method for serving remote-sensing image spatio-temporal aggregation real-time computation images according to claim 3 or 4, characterized in that the spatio-temporal data structure model comprises online, near-line and offline generalized distributed storage libraries.

6. The method as claimed in claim 3, wherein the spatiotemporal image database dynamically manages and schedules the remote-sensing images based on metadata, and outputs the image tile service of spatiotemporal aggregation real-time computation in combination with the real-time request of the user.

7. The remote-sensing image space-time aggregation instant computation image service method according to claim 6, characterized in that the instant computation service interface performs dynamic planning and intelligent matching on requirements of remote-sensing image time, space, scale and the like aiming at input requests, so as to realize dynamic space-time aggregation.

8. The remote-sensing image spatiotemporal aggregation instant computation image service method as claimed in claim 6 or 7, wherein the instant computation is based on a spatiotemporal image database to build a computation service system platform.

9. The remote-sensing image space-time aggregation instant computation image service method according to claim 8, wherein the computation service system platform comprises a storage network, a computation platform and an instant computation distributed parallel service system; the computing distributed parallel service system adopts a plurality of servers to process real-time computing dynamic tiles in parallel.

10. The remote-sensing image space-time polymerization instant computation image service method according to claim 8, characterized in that, the computation service system platform is communicated with the user side by establishing a standardized uniform service interface; and the standardized unified service interface is used for connecting the user customized tile service request with the instant dynamic tile calculation.

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