diff --git a/Sentinal-project.html b/Sentinal-project.html index 2851f95..e8c6576 100644 --- a/Sentinal-project.html +++ b/Sentinal-project.html @@ -5,7 +5,7 @@ - Data Processing System + Copernicus Programme @@ -93,7 +93,7 @@

Arun

-

Data Processing System

+

Copernicus Programme

  1. Remote sensing Content
  2. Home
    3. @@ -132,7 +132,7 @@

    Data Processing System

    -

    Data Processing System

    +

    Europe’s eyes on Earth: the EU’s Copernicus Programme

    @@ -140,310 +140,178 @@

    Data Processing System

    -
    - Image Description -
    -

    Introduction to remote sensing

    -

    Remote sensing is the process of gathering information about the Earth's surface and atmosphere from a distance, typically using sensors mounted on - satellites, aircraft, drones, or other platforms. This technology allows us to collect data and images without making direct physical contact with - the target area.

    + +
    +

    Introduction

    +
      +
    • Copernicus is the most ambitious Earth observation programme to date.
      • +
    • To meet the operational needs of the Copernicus programme, ESA developed the family of Sentinel satellites.
      • +
    • At present, three complete two-satellite constellations are in orbit, along with two additional single satellites—Sentinel-5P.
      • +
    • Copernicus provides a unified system through which huge amounts of data are fed into a range of thematic + information services, designed to benefit the environment and humanitarian needs while supporting effective policy-making for a more sustainable future. +
    + +

    Applications of Copernicus space missions

    + Copernicus covers wide number of applications. For use cases please check the Success Stories on Sentinel Online. +

    The main applications are in environmental science, climate change and disaster management.

    +
      +
    • Climate change
      • +
    • Land Overview
      • +
    • Marine monitoring overview
      • +
    • Atmospheric monitoring overview
      • +
    • Greenhouse gases
      • +
    • Reactive gases
      • +
    • Ozone and solar UV Radiation
      • +
    • Floods
      • +
    • Forest Fires
      • +
    • Landslides
      • +
    • Earthquakes and Volcanic eruption
      • +
    • Humanitarian crises
      • +
    • Oil spills
      • +
    • Border Surveillance
      • +
    • Maritime surveillance
      • +
    + +

    Sentinel missions

    + The Copernicus program, led by the European Union and the European Space Agency (ESA), is a comprehensive Earth observation program + that aims to provide accurate and timely environmental information to support a wide range of applications. The Sentinel missions are + a key component of the Copernicus program, consisting of a constellation of Earth observation satellites designed to monitor different + aspects of the Earth's environment. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Mission NameObjectiveApplicationsOnboard SensorsYear of LaunchOrbitPrimary Function
    Sentinel-1ATo provide all-weather, day-and-night Earth observation data for land and ocean monitoring.Land use mapping, ice cover monitoring, maritime safety, flood mapping, and disaster response.C-band synthetic aperture radar (SAR)April 3, 2014Sun-synchronous, near-polar orbitRadar imagery for land use, ice cover, and maritime safety
    Sentinel-1BTo provide all-weather, day-and-night Earth observation data for land and ocean monitoring, complementing Sentinel-1A.Land use mapping, ice cover monitoring, maritime safety, flood mapping, and disaster response.C-band synthetic aperture radar (SAR)April 25, 2016Sun-synchronous, near-polar orbitRadar imagery for land use, ice cover, and maritime safety
    Sentinel-2ATo provide high-resolution multispectral imagery for land cover mapping, vegetation monitoring, and water resource management.Land cover mapping, vegetation monitoring, water resource management, agricultural monitoring, and forestry management.Multispectral instrument (MSI)June 23, 2015Sun-synchronous, near-polar orbitMultispectral imagery for land cover, vegetation, and water resources
    Sentinel-2BTo provide high-resolution multispectral imagery for land cover mapping, vegetation monitoring, and water resource management, complementing Sentinel-2A.Land cover mapping, vegetation monitoring, water resource management, agricultural monitoring, and forestry management.Multispectral instrument (MSI)March 7, 2017Sun-synchronous, near-polar orbitMultispectral imagery for land cover, vegetation, and water resources
    Sentinel-3ATo provide continuous and accurate measurements of sea surface temperature, ocean color, and land surface temperature.Ocean monitoring, climate change research, marine meteorology, and fisheries management.Sea and Land Surface Temperature Radiometer (SLSTR), Ocean and Land Colour Instrument (OLCI), and Synthetic Aperture Radar Altimeter (SRAL)February 16, 2016Sun-synchronous, near-polar orbitSea surface temperature, ocean currents, and sea ice
    Sentinel-3BTo provide continuous and accurate measurements of sea surface temperature, ocean color, and land surface temperature, complementing Sentinel-3A.Ocean monitoring, climate change research, marine meteorology, and fisheries management.Sea and Land Surface Temperature Radiometer (SLSTR), Ocean and Land Colour Instrument (OLCI), and Synthetic Aperture Radar Altimeter (SRAL)April 25, 2018Sun-synchronous, near-polar orbitSea surface temperature, ocean currents, and sea ice
    Sentinel-4To provide continuous monitoring of atmospheric composition, including ozone, nitrogen dioxide, sulfur dioxide, and formaldehyde.Air quality monitoring, climate change research, and atmospheric modeling.Total Ozone Parcel Instrument (TROPOMI)October 21, 2017Geostationary orbitAtmospheric composition, including ozone, nitrogen dioxide, and sulfur dioxide
    Sentinel-5PTo provide atmospheric composition measurements, including greenhouse gases, aerosols, and trace gases.Air quality monitoring, climate change research, and atmospheric modeling.Total Ozone Parcel Instrument (TROPOMI)October 13, 2017Sun-synchronous, near-polar orbitAtmospheric composition, including greenhouse gases and aerosols
    Sentinel-5ATo provide atmospheric composition measurements, including ozone, nitrogen dioxide, sulfur dioxide, and formaldehyde.Air quality monitoring, climate change research, and atmospheric modeling.Total Ozone Parcel Instrument (TROPOMI)August 22, 2020Sun-synchronous, near-polar orbitAtmospheric composition, including ozone, nitrogen dioxide, and sulfur dioxide
    Sentinel-6To provide high-precision measurements of sea surface topography, significant wave height, and wind speed.Ocean monitoring, climate change research, maritime safety, and coastal zone management.Poseidon-3 radar altimeter, microwave radiometer (MWR), and synthetic aperture radar (SAR)November 21, 2020Sun-synchronous, near-polar orbitSea surface topography and wave heights
    + + + + + + + + + Image Description

    Project Overview:

    -

    The Sentinel-6 mission aims to monitor sea level changes with high precision. - Planning a real-time data processing system for data collected from a satellite like Sentinel-6 involves several key steps and requirements. - A successful ground segment data processing system for satellite missions requires careful consideration of various factors to ensure its - effectiveness and reliability. This project aims to improve the data processing ground segments, particularly focusing on level 0, level 1, - and level 2 data processing.

    +

    Project description

    Image Description -

    Here's an overview of the main considerations for planning such a system:

    -
      -
    • Data Requirements: -
        -
      • Understand the type of data collected by the satellite and its volume.
        • -
      • Define the data format, resolution, and frequency of acquisition.
        • -
      • Ensure compatibility with data standards and formats used in the industry.
        • -
      -
      • -
    • Data Ingestion: -
        -
      • Establish a reliable and efficient data ingestion process from the satellite.
        • -
      • Ensure data reception and storage with minimal latency.
        • -
      • Implement mechanisms for data recovery in case of interruptions.
        • -
      -
      • -
    • Data Quality Assurance: -
        -
      • Develop quality control procedures to validate and clean incoming data.
        • -
      • Detect and handle anomalies, missing data, or outliers.
        • -
      • Maintain data integrity and accuracy throughout processing.
        • -
      -
      • -
    • Data Processing Pipeline: -
        -
      • Create a well-defined data processing pipeline, including preprocessing, analysis, and post-processing stages.
        • -
      • Select appropriate algorithms and models for data processing.
        • -
      • Optimize processing workflows for efficiency and accuracy.
        • -
      -
      • -
    • System Architecture: -
        -
      • Design a scalable and flexible system architecture that can adapt to changing mission requirements.
        • -
      • Select hardware and software components that meet processing and storage needs.
        • -
      • Implement redundancy and failover mechanisms for reliability.
        • -
      -
      • -
    • Scalability and Performance: -
        -
      • Plan for future scalability to accommodate data growth.
        • -
      • Monitor and optimize system performance to meet real-time processing requirements.
        • -
      -
      • -
    • Data Storage: -
        -
      • Choose a suitable data storage solution that balances performance and cost.
        • -
      • Implement data archiving and retrieval mechanisms.
        • -
      • Ensure data security and access controls.
        • -
      -
      • -
    • Data Distribution: -
        -
      • Design efficient data distribution mechanisms for end-users and other systems.
        • -
      • Provide secure and authenticated access to processed data.
        • -
      • Consider data visualization tools for easy data exploration.
        • -
      -
      • -
    • Monitoring and Alerting: -
        -
      • Implement real-time monitoring to track system health, data processing status, and data quality.
        • -
      • Set up alerting systems to notify relevant personnel of anomalies or performance issues.
        • -
      -
      • -
    • Security and Compliance: -
        -
      • Prioritize data security and compliance with relevant regulations.
        • -
      • Implement encryption for data in transit and at rest.
        • -
      • Ensure access controls and user authentication.
        • -
      -
      • -
    • Documentation and Reporting: -
        -
      • Maintain comprehensive documentation of system configurations, processes, and procedures.
        • -
      • Generate regular reports on system performance and data quality for stakeholders.
        • -
      -
      • -
    • Disaster Recovery and Redundancy: -
        -
      • Develop and test disaster recovery plans to ensure data integrity and system availability in case of failures.
        • -
      • Implement redundancy for critical system components, such as satellite ground stations.
        • -
      -
      • -
    • Software and Algorithm Maintenance: -
        -
      • Regularly update and maintain the software used for data processing.
        • -
      • Keep algorithms and models up to date for accurate results.
        • -
      -
      • -
    • Collaboration and Coordination: -
        -
      • Collaborate with mission partners and external providers for data processing and support services.
        • -
      • Coordinate software releases and system changes effectively.
        • -
      -
      • -
    • Training and Skill Development: -
        -
      • Provide training to team members to ensure they are equipped to handle data processing challenges.
        • -
      • Promote skill development and knowledge sharing within the team.
        • -
      -
      • -
    • Budget and Cost Management: -
        -
      • Develop and manage a budget for the ground segment data processing system.
        • -
      • Optimize costs while maintaining system efficiency and reliability.
        • -
      -
      • -
    + + + -

    Example Scenario: Sentinel-6 Real-Time Data Processing System

    -

    Sentinel-6, also known as the Copernicus Sentinel-6, is a series of Earth observation satellites designed to monitor sea-level rise and ocean - circulation. These satellites are part of the European Space Agency's (ESA) Copernicus program, which is a joint initiative with the European - Commission. The Sentinel-6 mission contributes to global climate and environmental monitoring by providing crucial data related to sea-level changes.

    - -

    For a succesfull ground segment data processing system for the Senitnal-6 sattelite:

    -
      -
    • Data Requirements: -
        -
      • Sentinel-6 collects ocean surface height and sea-level data.
        • -
      • Data arrives in NetCDF format with a frequency of one measurement per second.
        • -
      -
      • -
    • Data Ingestion: -
        -
      • Use satellite ground stations for real-time data reception.
        • -
      • Implement a data buffer for temporary storage before processing.
        • -
      -
      • -
    • Quality Control: -
        -
      • Validate data for outliers and data gaps.
        • -
      • Implement automated data cleaning procedures.
        • -
      -
      • -
    • Data Processing Pipeline: -
        -
      • Develop a pipeline that includes algorithms for sea-level measurement and trend analysis.
        • -
      • Incorporate real-time data visualization for quick assessment.
        • -
      -
      • -
    • System Architecture: -
        -
      • Choose cloud-based architecture for scalability.
        • -
      • Use parallel processing and distributed computing resources.
        • -
      -
      • -
    • Scalability and Performance: -
        -
      • Plan for a 20% data volume increase annually.
        • -
      • Monitor system performance to ensure real-time processing.
        • -
      -
      • -
    • Data Storage: -
        -
      • Utilize a cloud-based storage solution with data redundancy.
        • -
      • Implement data partitioning for efficient retrieval.
        • -
      -
      • -
    • Data Distribution: -
        -
      • Share processed data through a web portal for researchers and institutions.
        • -
      • Implement access controls and authentication.
        • -
      -
      • -
    • Monitoring and Alerting: -
        -
      • Set up real-time monitoring for system health and data quality.
        • -
      • Receive alerts for anomalies or performance issues.
        • -
      -
      • -
    • Security and Compliance: -
        -
      • Ensure data encryption in transit and at rest.
        • -
      • Comply with data protection regulations.
        • -
      -
      • -
    • Documentation: -
        -
      • Maintain detailed documentation for system configuration and data processing procedures.
        • -
      -
      • -
    • Disaster Recovery and Redundancy: -
        -
      • Develop a disaster recovery plan for data and system components.
        • -
      • Implement redundant satellite ground stations for data reception.
        • -
      -
      • -
    - -

    Steps to creating a succesful ground segment data processing system:

    -
      -
    • Requirements Gathering: -
        -
      • Description: Requirements Gathering is the initial phase of planning the data processing system for - Sentinel-6. In this phase, you collect and document the specific needs and expectations for the system. This step is - essential to understand what the system should achieve and how it should operate.
        • -
      • Key Activities: -
          -
        • Identify the type of data collected by Sentinel-6, such as ocean surface height and sea-level data.
          • -
        • Define data attributes, including format (e.g., NetCDF) and acquisition frequency (one measurement per second).
          • -
        • Gather input from stakeholders, including scientists, data users, and mission objectives.
          • -
        • Document the compliance requirements, data quality standards, and performance criteria.
          • -
        -
      • Outcome: A comprehensive set of requirements that serve as the foundation for system design and development.
        • - -
      -
      • -
    • System Blueprint: -
        -
      • Description: The System Blueprint phase involves designing the high-level architecture of the data processing system. - It outlines the structure, components, and workflows necessary to meet the requirements gathered in the previous phase.
        • -
      • Key Activities: -
          -
        • Define the architecture, specifying cloud-based infrastructure for scalability and parallel processing.
          • -
        • Create a detailed plan for the data processing pipeline, including algorithms for sea-level measurement and trend analysis.
          • -
        • Specify real-time data visualization tools for quick assessment.
          • -
        • Identify data storage solutions with redundancy and partitioning for efficient retrieval.
          • -
        -
        • -
      • Outcome:A comprehensive system design document that serves as a roadmap for system development and implementation.
        • -
      -
      • - -
    • System Development: -
        -
      • Description: System Development is the phase where the designed architecture and components are implemented. It involves coding, - configuring, and building the system based on the System Blueprint.
        • -
      • Key Activities: -
          -
        • Develop and configure the data processing pipeline, incorporating algorithms for sea-level measurement and trend analysis.
          • -
        • Set up cloud-based infrastructure, including distributed computing resources.
          • -
        • Implement a real-time monitoring system to track system health, data quality, and anomalies.
          • -
        • Ensure data encryption in transit and at rest, complying with data protection regulations.
          • -
        -
        • -
      • Outcome: A functioning data processing system that processes Sentinel-6 data in real time, meets the requirements, - and aligns with the designed architecture.
        • -
      -
      • - -
    • Integrate (Seamless Operation): -
        -
      • In the context of Sentinel-6, "Integrate (Seamless Operation)" refers to the process of ensuring that all components of the data - processing system work together harmoniously. This includes both new and existing components.
        • -
      • The goal is to create a smooth, interconnected system where data flows seamlessly from ingestion to processing to distribution.
        • -
      • It involves configuring and testing various software and hardware components to minimize disruptions and bottlenecks in data processing.
        • -
      -
      • -
    • Maintenance and Evolution: -
        -
      • "Maintenance and Evolution" involves the ongoing care and improvement of the data processing system used for Sentinel-6.
        • -
      • Maintenance includes routine tasks such as monitoring, troubleshooting, and fixing issues as they arise. It ensures that the system - runs smoothly and efficiently.
        • -
      • Evolution, on the other hand, focuses on making planned improvements to the system to meet changing mission requirements and accommodate - technological advancements.
        • -
      • It encompasses software updates, hardware upgrades, and enhancements to algorithms and processing workflows.
        • -
      -
      • -
    • Anomaly Processing: -
        -
      • Anomaly processing refers to the identification and handling of unexpected or abnormal situations in the data processing system.
        • -
      • In the context of Sentinel-6, this could involve recognizing data outliers, missing data, or errors in real-time data streams.
        • -
      • Anomaly processing includes developing algorithms and procedures to address these anomalies, ensuring data quality and system reliability.
        • -
      • -
      -
      • -
    • Test Suite Setup: -
        -
      • "Test Suite Setup" is the creation of a comprehensive set of test cases and environments to evaluate the performance and functionality of the data processing system.
        • -
      • It involves designing tests to simulate various scenarios, data conditions, and processing conditions to validate the system's reliability.
        • -
      • The test suite ensures that the system performs consistently and accurately under different circumstances.
        • -
      • It includes unit testing, integration testing, and end-to-end testing to verify the entire data processing pipeline.
        • -
      -
      • -

      These aspects collectively contribute to the robust and reliable operation of the data processing system for Sentinel-6, allowing for seamless data processing, ongoing maintenance and - improvement, handling of anomalies, and rigorous testing to ensure the system's effectiveness and accuracy in processing oceanographic data.

      -
    +

    Reference:

    • Visit the "EUMESAT training website".
      • diff --git a/assets/css/style.css b/assets/css/style.css index 1ca5648..60b0615 100644 --- a/assets/css/style.css +++ b/assets/css/style.css @@ -1221,6 +1221,12 @@ th { background-color: #f2f2f2; } +@media (max-width: 600px) { + table { + width: 100%; + } +} + /*-------------------------------------------------------------- # Creating a image box --------------------------------------------------------------*/