Linear 3-D transformations of Landsat 5 TM satellite images for the enhancement of archaeological signatures during the phenological cycle of crops
File(s)
Journal
International Journal of Remote Sensing,
Date Issued
2015
Abstract
A linear 3-D transformation that can be used for the enhancement of crop marks
related to buried archaeological features is developed and presented in this article. The
methodology is based on three steps: (1) recalculation of the ground narrowband
spectroradiometric measurements to the multispectral Landsat 5 Thematic Mapper
(TM) sensor, based on the relative response filter of the sensor, (2) application of
principal component analysis (PCA) transformation in order to determine the initial
axes used for the orthogonal transformation, followed by (3) a 3-D rotation of the PCA
axes. The linear coefficients of the transformation were retrieved and adjusted to
different phenological stages of the crops. The transformation was successfully evaluated
using both in situ measurements and Landsat 5 TM images in two different
archaeological case studies. The proposed transformation tends to enhance archaeological
signatures better than other established vegetation indices or algorithms, while
the methodology can be expanded to any other multispectral satellite images using
only the visible and very near-infrared part of the spectrum.
related to buried archaeological features is developed and presented in this article. The
methodology is based on three steps: (1) recalculation of the ground narrowband
spectroradiometric measurements to the multispectral Landsat 5 Thematic Mapper
(TM) sensor, based on the relative response filter of the sensor, (2) application of
principal component analysis (PCA) transformation in order to determine the initial
axes used for the orthogonal transformation, followed by (3) a 3-D rotation of the PCA
axes. The linear coefficients of the transformation were retrieved and adjusted to
different phenological stages of the crops. The transformation was successfully evaluated
using both in situ measurements and Landsat 5 TM images in two different
archaeological case studies. The proposed transformation tends to enhance archaeological
signatures better than other established vegetation indices or algorithms, while
the methodology can be expanded to any other multispectral satellite images using
only the visible and very near-infrared part of the spectrum.