Mapping, remote sensing, signature physics and terrain state

Abstract

Investigates compact mathematical representations of terrain data, explores automated learning of built elemental features unique to location, formulates new techniques for automatically retrieving Earth surface features, properties and patterns, explores sensing phenomenology and surface state as affected by terrain and weather, studies optimizing and adapting decision making based on changing geospatial conditions.

Document Details

Document Type
Accomplishment
Publication Date
Oct 01, 2022
Source ID
953d4349439e69f5717bf652ef58a802

Tags

Readers

  • Atmospheric Remote Sensing.
  • Neural Network Machine Learning.
  • Sensor Fusion and Tracking Systems.

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