New approach for spectral change detection assessment using multistrip airborne hyperspectral data

S. Adar*, Y. Shkolnisky, E. Ben Dor

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

6 Scopus citations

Abstract

Change detection of imaging spectroscopy data is widely used in many applications. Among them, environmental monitoring is of great importance. In this paper, we introduce a new automated method, termed spectral overlapping threshold (SOT), to derive a threshold to distinguish between 'change' and 'no change' areas. The method exploits the overlapping regions in multi-strip mosaic images, which are regarded as 'no change' areas because they are acquired only a few minutes apart. The method consists of two steps. First, similarity measures are applied to the overlapping areas. Then, the histogram of the similarity values are computed and the thresholds for each land use land cover (LULC) category are determined. The method is independent of the underlying SM used to detect changes, and is demonstrated here for the spectral angle measure (SAM), spectral information divergence (SID), Euclidean distance (ED) and spectral correlation measure (SCM). This process is demonstrated for a mosaic of HyMap sensor data acquired in 2009 and 2010 over Sokolov mining area, Czech Republic.

Original languageEnglish
Pages4966-4969
Number of pages4
DOIs
StatePublished - 2012
Event2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany
Duration: 22 Jul 201227 Jul 2012

Conference

Conference2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
Country/TerritoryGermany
CityMunich
Period22/07/1227/07/12

Keywords

  • change detection
  • similarity measure
  • spectral overlapping threshold (SOT)

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