Classification Endmember Selection with Multi-Temporal Hyperspectral Data
Open Access
- 14 May 2020
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 12 (10), 1575
- https://doi.org/10.3390/rs12101575
Abstract
In hyperspectral image classification, so-called spectral endmembers are used as reference data. These endmembers are either extracted from an image or taken from another source. Research has shown that endmembers extracted from an image usually perform best when classifying a single image. However, it is unclear if this also holds when classifying multi-temporal hyperspectral datasets. In this paper, we use spectral angle mapper, which is a frequently used classifier for hyperspectral datasets to classify multi-temporal airborne visible/infrared imaging spectrometer (AVIRIS) hyperspectral imagery. Three classifications are done on each of the images with endmembers being extracted from the corresponding image, and three more classifications are done on the three images while using averaged endmembers. We apply image-to-image registration and change detection to analyze the consistency of the classification results. We show that the consistency of classification accuracy using the averaged endmembers (around 65%) outperforms the classification results generated using endmembers that are extracted from each image separately (around 40%). We conclude that, for multi-temporal datasets, it is better to have an endmember collection that is not directly from the image, but is processed to a representative average.Keywords
This publication has 30 references indexed in Scilit:
- Mapping Advanced Argillic Alteration at Cuprite, Nevada, Using Imaging SpectroscopyEconomic Geology, 2014
- Good practices for estimating area and assessing accuracy of land changeRemote Sensing of Environment, 2014
- Quantitative and comparative examination of the spectral features characteristics of the surface reflectance information retrieved from the atmospherically corrected images of HyperionJournal of Applied Remote Sensing, 2013
- Multi- and hyperspectral geologic remote sensing: A reviewInternational Journal of Applied Earth Observation and Geoinformation, 2011
- Integration of spatial–spectral information for the improved extraction of endmembersRemote Sensing of Environment, 2007
- A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapperRemote Sensing of Environment, 2004
- Thematic Map ComparisonPhotogrammetric Engineering & Remote Sensing, 2004
- Automatic analysis of the difference image for unsupervised change detectionIEEE Transactions on Geoscience and Remote Sensing, 2000
- Simulated Aster data for geologic studiesIEEE Transactions on Geoscience and Remote Sensing, 1995
- The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer dataRemote Sensing of Environment, 1993