Environment monitoring and early warning system based on remote sensing data

Abstract

The utility model relates to an environment monitoring and early warning system based on remote sensing data, which is characterized in that a data preprocessing module executes operations such as radiometric calibration, geometric correction and atmospheric correction, and space-time alignment and feature level fusion processing of data are realized through a multi-source data fusion unit; and the data analysis module applies a machine learning algorithm sub-module and a spatial analysis unit to perform feature extraction and environment abnormal change identification on the preprocessed data. The early-warning decision-making module generates an early-warning decision-making instruction based on comparison of an analysis result and an environment quality standard threshold value, and trend analysis aided decision-making is realized through a historical data comparison unit. And the early warning issuing module issues early warning information to a target user group through a multi-mode communication channel, and supports personalized setting of a user-defined early warning receiving mode and a grade threshold value. And the data storage module adopts a distributed cloud storage architecture, so that high-reliability storage and elastic expansion of mass remote sensing data are realized.

Description

TECHNICAL FIELD

[0001] The utility model provides a kind of early warning system belongs to remote sensing technical field, especially based on environmental monitoring early warning system of remote sensing data. BACKGROUND

[0002] Environmental monitoring and early warning is a comprehensive environmental management tool, which relies on advanced monitoring technology and equipment, through the layout of various monitoring points in the environment, real-time or periodic continuous monitoring of various environmental factors such as air, water, soil, noise and key indicators such as pollutant concentration, collecting a large amount of environmental data, then using scientific data analysis methods and models to process, analyze and evaluate these data, when the monitoring data changes abnormally, such as the pollutant concentration is about to exceed the set environmental quality standard threshold, or through data analysis to predict that the environmental quality may deteriorate sharply within a certain period of time in the future, potential threats to the ecological system, public health or social and economic activities, timely warning signal is sent to notify relevant environmental management departments, enterprises and the public to take appropriate preventive and response measures, so as to effectively reduce environmental risks, protect the ecological environment and human well-being, and ensure the sustainable development of the environment.

[0003] The existing environmental monitoring and early warning system is usually composed of multiple levels, and its basic structure generally includes data acquisition layer, data transmission layer, data storage layer, data analysis layer and early warning release layer. The data acquisition layer collects environmental data such as temperature, humidity, pollutant concentration through various sensors and monitoring equipment; the data transmission layer is responsible for transmitting the collected data to the center server or cloud platform through wired or wireless means; the data storage layer stores the transmitted data and establishes a reasonable data structure and database management system; the data analysis layer uses various and models to analyze and process the stored data to find the rules and trends in the data; the early warning release layer releases warning information through SMS, email, APP push and other means according to the analysis results.

[0004] However, this structure has some inaccuracies. First, in the data acquisition process, the accuracy and stability of the sensor may be affected, resulting in errors in the collected data. Second, signal interference, data loss and other problems may occur during data transmission, affecting the integrity and accuracy of the data. In addition, the establishment and parameter setting of the data analysis model may have certain subjectivity and limitations, resulting in deviations between the analysis results and the actual situation.

[0005] At the same time, the instability of the data source is also an important problem. The service life of the sensor, the change of the environmental conditions and human factors can cause the instability of data acquisition. For example, the sensor may be aged, damaged and the like due to long-term use, which affects the data acquisition quality. In addition, the data transmission depends on network communication, and the instability of the network, the interference of the signal and the like can cause the interruption or delay of the data transmission. These inaccuracies and the instability of the data source can affect the overall performance and reliability of the environmental monitoring and early warning system, thereby adversely affecting the environmental management and decision-making. Utility model content

[0006] In order to make up for the deficiency of the prior art, the present application provides an environmental monitoring and early warning system based on remote sensing data, which solves the problems of inaccurate structure and unstable data source of the existing environmental monitoring and early warning system.

[0007] In order to solve the above technical problems, the utility model provides the following technical scheme: an environmental monitoring and early warning system based on remote sensing data, comprising a remote sensing data acquisition module, the remote sensing data acquisition module is communicated and is connected with data transmission module, the data transmission module is used for collecting environmental remote sensing data, and the data is transmitted to the data processing center through wired or wireless network, integrated multi-protocol transmission interface and adopts data encryption technology;

[0008] The data preprocessing module is communicated and connected with the data transmission module, performs preprocessing operation, and integrates a multi-source data fusion unit;

[0009] The data analysis module is communicated and connected with the data preprocessing module, applies a model to perform feature extraction and environmental abnormal change identification, and is configured with a spatial analysis unit and a machine learning submodule;

[0010] The early warning decision module is communicated and connected with the data analysis module, generates early warning decision instructions based on the comparison between the analysis results and the environmental quality standard threshold, and is configured with a historical data comparison unit;

[0011] The early warning release module is communicated and connected with the early warning decision module, releases early warning information to a target user group through a multi-modal communication channel, and contains a customizable user interface;

[0012] The data storage module is electrically connected with the data preprocessing module and the data analysis module respectively, establishes a storage system of remote sensing data and its processing results, and adopts a distributed cloud storage architecture;

[0013] The system control module is connected with all the function modules, performs system coordination control of task scheduling, communication management and running state monitoring, and integrates a real-time fault diagnosis unit.

[0014] Preferably, the remote sensing data acquisition module comprises a data quality control submodule for quality evaluation and screening of the acquired remote sensing data.

[0015] Preferably, the data transmission module transmits data to the data processing center through wired or wireless network, integrates multi-protocol transmission interface and adopts data encryption technology.

[0016] Preferably, the data analysis module integrates a machine learning submodule to improve the accuracy and timeliness of abnormal identification by training an environmental change prediction model.

[0017] Preferably, the early warning release module contains a customizable user interface to support user-defined early warning receiving methods and personalized settings of level thresholds.

[0018] Preferably, the data storage module adopts a distributed cloud storage architecture to achieve high-reliability storage and elastic expansion of massive remote sensing data.

[0019] Preferably, the system control module integrates a real-time fault diagnosis unit configured to dynamically monitor the running state of each module and execute abnormal handling strategies.

[0020] Preferably, the early warning decision module is configured with a historical data comparison unit to realize trend analysis assisted decision-making by constructing a time-series environmental database.

[0021] Preferably, the data preprocessing module integrates a multi-source data fusion unit to realize spatio-temporal alignment and feature-level fusion processing of heterogeneous remote sensing data.

[0022] Preferably, the data analysis module is configured with a spatial analysis unit to perform geographic spatial data processing functions including spatial interpolation and clustering analysis.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0024] The utility model discloses a remote sensing data based environmental monitoring and early warning system, which comprises a remote sensing data acquisition module, a data quality control submodule, a data transmission module, a data preprocessing module, a data analysis module, an early warning decision module, an early warning release module and a data storage module.

[0025] Other advantages, objects, and features of the present utility model will be apparent to those skilled in the art from the following specification, and will be learned from the practice of the present utility model. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 The utility model discloses an environmental monitoring and early warning system based on remote sensing data's architecture diagram;

[0027] Figure 2 The utility model discloses an environmental monitoring and early warning system based on remote sensing data's use flow chart. DETAILED DESCRIPTION

[0028] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all the other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0029] It should be noted that the terms "vertical", "horizontal", "upper", "lower", "left", "right", and similar expressions used herein are for illustrative purposes only and do not represent the only embodiments.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs; the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application; the term "and / or" used herein includes any and all combinations of one or more related listed items.

[0031] As shown in Figure 1 The environment monitoring and early warning system based on remote sensing data includes a plurality of interconnected modules. The remote sensing data acquisition module is in communication connection with the data transmission module, responsible for transmitting the collected environmental remote sensing data to the data processing center through wired or wireless network. The data preprocessing module is in communication connection with the data transmission module, and performs preprocessing operation. The data analysis module is in communication connection with the data preprocessing module, and applies a model to perform feature extraction and environmental abnormal change identification. The early warning decision module is in communication connection with the data analysis module, and generates early warning decision instructions. The early warning release module is in communication connection with the early warning decision module, and releases early warning information. The data storage module is in electrical connection with the data preprocessing module and the data analysis module, respectively, and establishes a storage system. The system control module is in global connection with each functional module, and performs system coordination control.

[0032] In this embodiment, each module is connected by communication and electrical connection to form a complete system, realizing the full-process automation and intelligentization from data acquisition, transmission, preprocessing, analysis, decision-making to publishing and storage. The communication connection between the remote sensing data acquisition module and the data transmission module ensures the real-time and integrity of the data, and the connection between the data preprocessing module and the data analysis module guarantees the accuracy and availability of the data. The connection between the early warning decision-making module and the early warning publishing module realizes the rapid generation and publishing of the early warning information, and the connection between the data storage module and each module ensures the safe storage and efficient management of the data. The global connection of the system control module realizes the unified coordination and control of each module, improving the stability and reliability of the system. This modular design and connection method not only improves the flexibility and scalability of the system, but also realizes the efficient processing of environmental monitoring data and the timely publishing of early warning information, providing strong technical support for environmental monitoring and early warning.

[0033] As shown in Figure 2 A remote sensing data-based environmental monitoring and early warning system includes a plurality of interconnected modules. The remote sensing data acquisition module is communicatively connected to the data transmission module, which is responsible for transmitting the collected environmental remote sensing data to the data processing center through wired or wireless networks. The data preprocessing module is communicatively connected to the data transmission module and performs preprocessing operations. The data analysis module is communicatively connected to the data preprocessing module and applies models for feature extraction and environmental abnormal change identification. The early warning decision-making module is communicatively connected to the data analysis module to generate early warning decision-making instructions. The early warning publishing module is communicatively connected to the early warning decision-making module to publish early warning information. The data storage module is electrically connected to the data preprocessing module and the data analysis module to establish a storage system. The system control module is globally connected to each functional module to perform system coordination and control.

[0034] In this embodiment, each module is connected by communication and electrical connection to form a complete system, realizing the full-process automation and intelligentization from data acquisition, transmission, preprocessing, analysis, decision-making to publishing and storage. The communication connection between the remote sensing data acquisition module and the data transmission module ensures the real-time and integrity of the data, and the connection between the data preprocessing module and the data analysis module guarantees the accuracy and availability of the data. The connection between the early warning decision-making module and the early warning publishing module realizes the rapid generation and publishing of the early warning information, and the connection between the data storage module and each module ensures the safe storage and efficient management of the data. The global connection of the system control module realizes the unified coordination and control of each module, improving the stability and reliability of the system. This modular design and connection method not only improves the flexibility and scalability of the system, but also realizes the efficient processing of environmental monitoring data and the timely publishing of early warning information, providing strong technical support for environmental monitoring and early warning.

[0035] Although the utility model has disclosed as above with preferable embodiments, it is not used to limit the utility model, anyone familiar with this technology can make various changes and modifications without departing from the spirit and scope of the utility model, therefore the protection scope of the utility model should be limited by the claims.

Claims

1. An environmental monitoring and early warning system based on remote sensing data, comprising a remote sensing data acquisition module, characterized in that: the remote sensing data acquisition module is communicatively connected with a data transmission module, the data transmission module is used for collecting environmental remote sensing data, transmitting the data to a data processing center through wired or wireless network, integrating a multi-protocol transmission interface and adopting data encryption technology; a data preprocessing module is communicatively connected with the data transmission module, performs preprocessing operations, and integrates a multi-source data fusion unit; a data analysis module is communicatively connected with the data preprocessing module, applies a model to perform feature extraction and environmental abnormal change recognition, and is configured with a spatial analysis unit and a machine learning submodule; an early warning decision module is communicatively connected with the data analysis module, generates early warning decision instructions based on a comparison between the analysis results and environmental quality standard thresholds, and is configured with a historical data comparison unit; an early warning release module is communicatively connected with the early warning decision module, releases early warning information to a target user group through multi-modal communication channels, and includes a customizable user interface; a data storage module is electrically connected with the data preprocessing module and the data analysis module, respectively, establishes a storage system for remote sensing data and its processing results, and adopts a distributed cloud storage architecture; a system control module is globally connected with each functional module, performs system coordination control of task scheduling, communication management and running state monitoring, and integrates a real-time fault diagnosis unit.

2. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The remote sensing data acquisition module includes a data quality control submodule for quality evaluation and screening of collected remote sensing data.

3. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The data transmission module transmits data to the data processing center through wired or wireless network, integrates a multi-protocol transmission interface and adopts data encryption technology.

4. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The data analysis module integrates a machine learning submodule to improve the accuracy and timeliness of abnormal recognition by training an environmental change prediction model.

5. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The early warning release module includes a customizable user interface, which supports user-defined personalized settings of early warning receiving methods and level thresholds.

6. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The data storage module adopts a distributed cloud storage architecture to realize high-reliability storage and elastic expansion of massive remote sensing data.

7. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The system control module integrates a real-time fault diagnosis unit configured to dynamically monitor the running state of each module and execute abnormal handling strategies.

8. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The early warning decision module is configured with a historical data comparison unit to realize trend analysis assisted decision-making by constructing a time-series environmental database.

9. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The data preprocessing module integrates a multi-source data fusion unit to realize spatio-temporal alignment and feature-level fusion processing of heterogeneous remote sensing data.

10. The environment monitoring and early warning system based on remote sensing data according to claim 1, characterized in that: The data analysis module is configured with a spatial analysis unit to perform geographic spatial data processing functions including spatial interpolation and clustering analysis.

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