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Remote Sens. 2009, 1(4), 1171-1189; doi:10.3390/rs1041171
Article

A Class-Oriented Strategy for Features Extraction from Multidate ASTER Imagery

1
 and 2,*
Received: 23 October 2009; in revised form: 20 November 2009 / Accepted: 26 November 2009 / Published: 30 November 2009
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Abstract: In this paper we propose a hybrid classification method, adopting the best features extraction strategy for each land cover class on multidate ASTER data. To enable an effective comparison among images, Multivariate Alteration Detection (MAD) transformation was applied in the pre-processing phase, because of its high level of automation and reliability in the enhancement of change information among different images. Consequently, different features identification procedures, both spectral and object-based, were implemented to overcome problems of misclassification among classes with similar spectral response. Lastly, a post-classification comparison was performed on multidate ASTER-derived land cover (LC) maps to evaluate the effects of change in the study area.
Keywords: class-oriented classification; MAD calibration; TIR ASTER bands; change detection class-oriented classification; MAD calibration; TIR ASTER bands; change detection
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Crocetto, N.; Tarantino, E. A Class-Oriented Strategy for Features Extraction from Multidate ASTER Imagery. Remote Sens. 2009, 1, 1171-1189.

AMA Style

Crocetto N, Tarantino E. A Class-Oriented Strategy for Features Extraction from Multidate ASTER Imagery. Remote Sensing. 2009; 1(4):1171-1189.

Chicago/Turabian Style

Crocetto, Nicola; Tarantino, Eufemia. 2009. "A Class-Oriented Strategy for Features Extraction from Multidate ASTER Imagery." Remote Sens. 1, no. 4: 1171-1189.


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