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PYTAF: A Python Tool for Spatially Resampling Earth Observation Data.

Guangyu Zhao1, Muqun Yang2, Yizhao Gao1

  • 1Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, IL USA.

Earth Science Informatics
|August 25, 2022
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Summary
This summary is machine-generated.

A new software tool, pytaf, efficiently resamples Earth observation data from various formats (swath, grid, point). This enables better fusion of data from multiple instruments for enhanced Earth science research.

Keywords:
GridNearest NeighborPytafPythonResampleSwath

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Area of Science:

  • Earth Science
  • Geophysics
  • Climate Science

Background:

  • Earth observation data are crucial for weather, climate, and natural hazard forecasting.
  • Data are stored in swath, grid, or point structures, necessitating resampling for multi-instrument studies.
  • Increasing data volumes demand computationally efficient tools for data fusion.

Purpose of the Study:

  • To introduce pytaf, a software tool for efficient resampling of Earth observation data.
  • To address the need for high computational efficiency in processing large-scale datasets.
  • To facilitate the combination of measurements from multiple instruments.

Main Methods:

  • Developed pytaf using a novel block indexing algorithm for resampling.
  • Implemented core functions in C with OpenMP for parallel computation.
  • Created a user-friendly Python interface for accessibility.

Main Results:

  • pytaf successfully resamples Earth observation data across swath, grid, and point structures.
  • The tool is designed for processing large-scale datasets efficiently.
  • Demonstrated successful mission-wide data resampling for five EOS-Terra instruments.

Conclusions:

  • pytaf provides a computationally efficient solution for resampling diverse Earth observation data formats.
  • The tool enhances the ability to fuse multi-instrument data for deeper geophysical insights.
  • pytaf supports large-scale Earth science research and data integration.