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Sensors 2012, 12(3), 3528-3561; doi:10.3390/s120303528

Evaluation of a Change Detection Methodology by Means of Binary Thresholding Algorithms and Informational Fusion Processes

ETSITGC, Universidad Politécnica de Madrid, Campus SUR, Ctra. de Valencia, km.7, 28031 Madrid, Spain
Faculty of Computer Sciences, Universidad Politécnica de Madrid, Campus de Montegancedo, 28660 Boadilla del Monte Madrid, Spain
Faculty of Computer Sciences, Universidad Complutense Madrid, 28040 Madrid, Spain
Author to whom correspondence should be addressed.
Received: 7 December 2011 / Revised: 14 February 2012 / Accepted: 7 March 2012 / Published: 13 March 2012
(This article belongs to the Section Remote Sensors)
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Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth’s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.
Keywords: optical sensors; change detection; thresholding; information fusion; ROC space optical sensors; change detection; thresholding; information fusion; ROC space
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Molina, I.; Martinez, E.; Arquero, A.; Pajares, G.; Sanchez, J. Evaluation of a Change Detection Methodology by Means of Binary Thresholding Algorithms and Informational Fusion Processes. Sensors 2012, 12, 3528-3561.

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