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Explore the spatial resolution differences among MODIS, Landsat, Planet, and Maxar imagery. Analyze impacts on urban planning, agriculture monitoring, and environmental management. Includes datasets, analysis scripts, and visualizations.

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Data-In-Action-IMPACT

Comparative Analysis of Spatial Resolution in Commercial Data and NASA Mission Products Overview

Welcome to the GitHub repository for "Comparative Analysis of Spatial Resolution in Commercial Data and NASA Mission Products." This project explores how spatial resolution influences the precision and applicability of satellite imagery in Earth observation. We delve into the capabilities of MODIS, Landsat, Planet, and Maxar, comparing their strengths in various applications.

Introduction

Spatial resolution is a critical factor in Earth observation, shaping the precision and richness of satellite imagery. Higher spatial resolution allows for more detailed analysis and is essential for applications requiring fine-scale observations, such as urban planning and precision agriculture. Conversely, moderate resolution is more suited for broader-scale environmental monitoring and land use changes. This project aims to compare the spatial resolution of commercial satellite data with standard NASA mission products, focusing on MODIS, Landsat, Planet, and Maxar.

Comparison of Platforms

  • MODIS: With its moderate resolution, MODIS excels in monitoring large-scale phenomena over broad areas. It is invaluable for tracking macro-level environmental changes and trends.

  • Landsat: Striking a balance between moderate and high resolution, Landsat is versatile, supporting a wide range of applications from land cover analysis to environmental monitoring.

  • Planet: Known for its high-frequency data collection, Planet provides detailed information over smaller areas, making it ideal for applications requiring frequent updates.

  • Maxar: Offering exceptionally high-resolution imagery, Maxar is unmatched in applications needing the utmost precision, such as detailed urban planning and infrastructure monitoring.


Case Studie

Urban to Agriculture Transition in Omaha, NE: In Omaha, NE, urban sprawl is encroaching on fertile farmland, presenting challenges for farmers.

  • MODIS tracks macro-level shifts in land use.

  • Landsat delineates urban boundaries and land cover changes.

  • Planet provides high-frequency, detailed insights into specific crop types and land parcels.

  • Maxar monitors changes at the building level, offering a detailed view of urban encroachment impacts.


Conclusion

The choice of satellite data for monitoring urban to agriculture transitions and natural water/land features depends on the required scale and precision. While NASA mission products like MODIS and Landsat provide valuable insights at moderate to high resolutions, commercial providers such as Planet and Maxar offer the flexibility to choose resolutions tailored to specific needs, from broad-scale monitoring to detailed, high-precision analysis. This diversity in spatial resolution options enhances our ability to understand and manage dynamic changes in urban and natural landscapes. Repository Contents


Repository Contents

Datasets: Sample datasets from MODIS, Landsat, Planet, and Maxar.

Analysis Scripts: Python scripts for comparing spatial resolutions and analyzing case studies.

Documentation: Detailed documentation explaining the methodology and findings.

Results: Visualizations and results of the comparative analysis.

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Explore the spatial resolution differences among MODIS, Landsat, Planet, and Maxar imagery. Analyze impacts on urban planning, agriculture monitoring, and environmental management. Includes datasets, analysis scripts, and visualizations.

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