Trend Analysis in Satellite Imagery


Temporal sequence processing (TSP) is a research area having applications in diverse fields varying from weather forecasting to time series prediction, speech recognition and remote sensing. TSP is a function approximation task whose goal is to estimate future values of a sequence of observations based on current and past values of the sequence.

In this paper we present the trends in satellite imagery using an algorithm Vector Quantized Temporal Associative Memory (VQTAM )[1].We present a dynamic model to detect the temporal changes in satellite imagery using SOFM in particular we model a time series that can be used for forecasting.

  • Abstract
  • Key Words
  • 1 Introduction
  • 2. Vector Quantized Temporal Associative Memory (VQTAM) Model
  • 3 Methodology
  • 4. Experimental Result
  • 5. Conclusion
  • References

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