Review Article Digital change detection techniques using remotely-sensed data
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TLDR
An evaluation of results indicates that various procedures of change detection produce different maps of change even in the same environment.Abstract:
A variety of procedures for change detection based on comparison of multitemporal digital remote sensing data have been developed. An evaluation of results indicates that various procedures of change detection produce different maps of change even in the same environment.read more
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An Unsupervised Technique Based on Morphological Filters for Change Detection in Very High Resolution Images
TL;DR: An unsupervised technique for change detection (CD) in very high geometrical resolution images is proposed, which is based on the use of morphological filters and increases the accuracy of the CD process as compared with the standard CVA approach.
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Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images
TL;DR: Deep Slow Feature Analysis (DSFA) as mentioned in this paper uses two symmetric deep networks for projecting the input data of bi-temporal imagery, then the SFA module is deployed to suppress the unchanged components and highlight the changed components of the transformed features.
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Landsat TM imagery and NDVI differencing to detect vegetation change: assessing natural forest expansion in Basilicata, southern Italy
TL;DR: The NDVI (Normalized Difference Vegetation Index) differencing method using Landsat Thematic Mapping images was implemented to assess natural expansion of forests in the Basilicata region (southern Italy) for the period 1984 through 2010, showing 91.8% accuracy in detection of natural forest expansion.
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A New Multivariate Statistical Model for Change Detection in Images Acquired by Homogeneous and Heterogeneous Sensors
TL;DR: This paper proposes a new approach for similarity measurement between images acquired by heterogeneous sensors that exploits the considered sensor physical properties and specially the associated measurement noise models and local joint distributions.
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Extending post-classification change detection using semantic similarity metrics to overcome class heterogeneity: A study of 1992 and 2001 U.S. National Land Cover Database changes
TL;DR: A fuzzy sets based approach is used to develop attribute based prototype definitions of land cover classes to look at land cover changes as a semantic change evaluated through semantic similarity metrics.
References
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The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat
R. J. Kauth,G. S. Thomas +1 more
TL;DR: In this article, the time trajectories of agricultural data points as seen in Landsat signal space form a pattern suggestive of a tasselled woolly cap, which is used to estimate and correct atmospheric haze and moisture effects.