Two strategies for remote sensing classification accuracy improvement of salt marsh vegetation: A case study in Chongming Dongtan

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3 Scopus citations

Abstract

Remote sensing technology has become the primary tool for salt marsh vegetation classification at large scales. However, there is still a major problem in differentiating between different spectra for the same vegetation and the same spectrum for different vegetation, when classifying salt marsh vegetation in remotely sensed images. In this paper, two strategies for this problem were proposed. One was through the integration and application of multi-seasonal images based on decision tree method, and another was through the integration of auxiliary data with remote sensing based on fuzzy mathematical theory. It was proved that the two strategies can improve the classification accuracy of salt marsh vegetation to some extent and have a good popularization value.

Original languageEnglish
Title of host publicationProceedings of the 2009 2nd International Congress on Image and Signal Processing, CISP'09
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 2nd International Congress on Image and Signal Processing, CISP'09 - Tianjin, China
Duration: 17 Oct 200919 Oct 2009

Publication series

NameProceedings of the 2009 2nd International Congress on Image and Signal Processing, CISP'09

Conference

Conference2009 2nd International Congress on Image and Signal Processing, CISP'09
Country/TerritoryChina
CityTianjin
Period17/10/0919/10/09

Keywords

  • Auxiliary information
  • Decision tree method
  • Fuzzy mathematics
  • Multi-temporal images
  • Remote sensing

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