Extract Rainfall data Using Random Sample Points from CHIRPS Data in Google Earth Engine

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  • čas přidán 22. 07. 2024
  • In this tutorial, we dive into the powerful capabilities of Google Earth Engine (GEE) to extract rainfall data using random sample points from CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) dataset. Whether you're a researcher, student, or enthusiast exploring environmental studies, this guide provides a step-by-step walkthrough to leverage GEE for your study area.
    CHIRPS dataset offers high-resolution precipitation data globally, making it a valuable resource for various applications such as hydrology, agriculture, and climate studies. By utilizing random sample points, we ensure representative data collection across the study area, enhancing the accuracy and reliability of our analysis.
    Throughout the tutorial, we cover essential concepts including:
    - Introduction to Google Earth Engine and CHIRPS dataset
    - Setting up the GEE code editor environment
    - Defining the study area and selecting random sample points
    - Accessing and visualizing CHIRPS precipitation data
    - Extracting rainfall values for sample points
    - Analyzing and interpreting the extracted data
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    📚 Useful Links:
    Code link: code.earthengine.google.com/f...
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    CHIRPS Daily data: developers.google.com/earth-e...
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    Whether you're new to GEE or looking to enhance your skills, this tutorial offers valuable insights and practical knowledge to effectively utilize Earth observation data for rainfall analysis. Join us on this journey to unlock the potential of GEE for your research endeavors.
    Don't forget to like, share, and subscribe for more tutorials on geospatial analysis, remote sensing, and environmental science! Let's empower ourselves with data-driven insights to understand and protect our planet better. Happy mapping! 🌍🛰️
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    #extract #rainfalldata #googleearthengine #chirps #RainfallAnalysis #remotesensing #environmentalscience #geospatialanalysis #tutorial #datascience #earthobservation

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