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

Adar, Simon; Shkolnisky, Yoel; Dor, Eyal Ben

doi:10.1109/igarss.2012.6352497

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…The PCA is a linear transformation that used widely among analysis remote sensing imagery. The main purpose of PCA maintains bands have the most effects on variance (Adar et al, 2012;Eismann and Meola, 2008;Hasanlou and Seydi, 2018).…”

Section: Pcamentioning

confidence: 99%

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Transformation Based Algorithms for Change Detection in Full Polarimetric Remote Sensing Images

Seydi

Shahhoseini

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Thanks to the recent advances in the development of polarimetric synthetic aperture radar (SAR) sensors, this remote sensing field attracts many applications. Among the different applications of these data, change detection is one of the most important applications. PolSAR images, due to interactions between electromagnetic waves and the target, could be used to study changes in the Earth's surface. This paper is a type of transformation-based method for polarimetric change detection (CD) purpose. For this purpose, we use full polarimetry imaging radar and extracted 138 features based on decomposition. The CD methods are the principal component analysis (PCA), the Multivariate Alteration Detection (MAD), the Iteratively Reweighted Multivariate Alteration Detection (IR-MAD), the Covariance Equalization (CE), and the Cross-Covariance (CRC). Assessment of the incorporated methods performed using most common criteria as quantity and quality assessment, such as overall accuracy (OA), kappa coefficient, and as visual analysis. The results of the experiments show that CC has better performance compared with other algorithms.

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Section: Pcamentioning

confidence: 99%

“…This method tries to estimate the second time image as a linear transformation from the first time image. Finally, the change extracted by calculation residuals (Adar et al, 2012;Eismann and Meola, 2008;Pieper et al, 2015).…”

Section: Crcmentioning

confidence: 99%

Transformation Based Algorithms for Change Detection in Full Polarimetric Remote Sensing Images

Seydi

Shahhoseini

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…These methods are further divided into two more groups: similarity based (SB) and distance based (DB) (Choi, Cha, & Tappert, 2010). These methods aim at measuring the difference between data in all bands using a math operator (Adar, Shkolnisky, & Dor, 2012). These CD methods are simple, fast and less sensitive to atmospheric conditions (Hussain et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

A new land-cover match-based change detection for hyperspectral imagery

Seydi

Hasanlou

2017

European Journal of Remote Sensing

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The presence of phenomena such as earthquakes, floods and artificial human activities causes changes on the Earth's surface. Change detection (CD) is an essential tool for the monitoring and managing of resources on local and global scales. Hyperspectral imagery can provide more detailed results for detecting changes in land-cover types. The main objective of this paper is to present a new, supervised CD method by combining similarity-based and distance-based methods to increase the efficiency of already existing CD approaches. The proposed method applies in two phases and uses three different algorithms, including image differencing, modified Z-score analysis and spectral angle mapper. The efficiency of the presented method is evaluated using Hyperion multi-temporal hyperspectral imagery. The receiver-operating characteristic curve index is used for assessing and comparing the results. The results clearly demonstrate the superiority of the proposed method for the detection and production of more accurate change maps. Furthermore, the proposed method is also able to detect changes with an accuracy of more than 96%, a false alarm rate lower than 0.03 and an area under the curve of about 0.986 in overall comparison to other conventional CD techniques. In addition, this method achieved an optimal threshold value with more rapid convergence.

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Use of Multispectral and Hyperspectral Satellite Imagery for Monitoring Waterbodies and Wetlands

Hasanlou

Seydi

2021

Coastal Research Library

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

Cited by 4 publications

References 11 publications

Transformation Based Algorithms for Change Detection in Full Polarimetric Remote Sensing Images

Transformation Based Algorithms for Change Detection in Full Polarimetric Remote Sensing Images

A new land-cover match-based change detection for hyperspectral imagery

Use of Multispectral and Hyperspectral Satellite Imagery for Monitoring Waterbodies and Wetlands

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