Thumbnail
Access Restriction
Subscribed

Author Saleh, A. M. ♦ Belal, A. B. ♦ Arafat, S. M.
Source SpringerLink
Content type Text
Publisher Springer-Verlag
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Natural sciences & mathematics ♦ Earth sciences
Subject Keyword Soil mapping ♦ Field spectrometry ♦ Spectral mixture analyses ♦ North Sinai Egypt ♦ Earth Sciences
Abstract This study examines linear spectral unmixing technique for mapping the surface soil types using field spectroscopy data as the reference spectra. The investigated area is located in North Sinai, Egypt. The study employed data from the Landsat 7 ETM+ satellite sensor with improved spatial and spectral resolution. Mixed remotely sensed image pixels may lead to inaccurate classification results in most conventional image classification algorithms. Spectral unmixing may solve this problem by resolving those into separate components. Four soil type end-members were identified with minimum noise fraction and pixel purity index analyses. The identified soil types are calcareous soils, dry sabkhas, wet sabkhas, and sand dunes. Soil end-member reference spectra were collected in the field using an ASD FieldSpec Pro spectrometer. Constrained sum-to-one and non-negativity linear spectral unmixing model was applied and the soil types map was produced. The results showed that linear spectral unmixing model can be a useful tool for mapping soil types from ETM+ images.
ISSN 18667511
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-12-22
Publisher Place Berlin, Heidelberg
e-ISSN 18667538
Journal Arabian Journal of Geosciences
Volume Number 6
Issue Number 6
Page Count 8
Starting Page 1799
Ending Page 1806


Open content in new tab

   Open content in new tab
Source: SpringerLink