Spatial Dynamics and Analysis of Crops Using Super Resolution and Radar Fusion

Abstract

Researchers at the University of Alabama in Huntsville's Information Technology and Information Center (UAH/ITSC) conducted research using deep learning technologies with satellite imagery to develop an improved method of pan-sharpening multispectral imagery (MSI) and then fusing the resulting fine resolution (< .5 m/pixel) MSI product with a fine resolution (< 10 m/pixel) synthetic aperture radar (SAR) data. Results are used to produce an enriched Geospatial Intelligence (GEOINT) product for spatial analysis of crops. Results showed that our PanColorGAN produced the best results followed by the basic GAN (generative adversarial network), and then the supervised CNN (convolution neural networks).

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Document Details

Document Type
Technical Report
Publication Date
Apr 11, 2022
Accession Number
AD1166649

Entities

People

  • John M Beck

Organizations

  • University of Alabama in Huntsville

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computer Vision
  • Computers
  • Convolutional Neural Networks
  • Data Fusion
  • Data Processing
  • Deep Learning
  • Dimensionality Reduction
  • Information Processing
  • Information Science
  • Information Systems
  • Low Resolution
  • Machine Learning
  • Neural Networks
  • Pattern Recognition
  • Remote Sensing
  • Supervised Machine Learning
  • Synthetic Aperture Radar

Readers

  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Image Processing and Computer Vision.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Space
  • Space - Space Objects