Spectral unmixing for fire smoke detection and removal

No abstract is available for this paper.

• Publication year

  2016

• Venue

  IEEE International Geoscience and Remote Sensing Symposium

• Publication date

  2016-07-10

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.1109/IGARSS.2016.7729203
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Forest Fire Smoke Detection Using Back-Propagation Neural Network Based on MODIS Data

  2015cited by this paper
• A new algorithm for forest fire smoke detection based on MODIS data in Heilongjiang province

  2011cited by this paper
• A fast iterative algorithm for implementation of pixel purity index

  2006cited by this paper
• The Impact of Boreal Forest Fire on Climate Warming

  2006cited by this paper
• Vertex component analysis: a fast algorithm to unmix hyperspectral data

  2005cited by this paper
• Automatic Detection of Fire Smoke Using Artificial Neural Networks and Threshold Approaches Applied to AVHRR Imagery

  2001cited by this paper
• N-FINDR: an algorithm for fast autonomous spectral end-member determination in hyperspectral data

  1999cited by this paper
• SPIE's International Symposium on Optical Science, Engineering, and Instrumentation報告

  1998cited by this paper
• The effect of smoke particles on clouds and climate forcing

  1997cited by this paper

• Video smoke removal based on low‐rank tensor completion via spatial‐temporal continuity constraint

  2021cites this paper