Review Article Digital change detection techniques using remotely-sensed data

doi:10.1080/01431168908903939

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Review Article Digital change detection techniques using remotely-sensed data

Journal Article•DOI•

Review Article Digital change detection techniques using remotely-sensed data

Ashbindu Singh¹•Institutions (1)

Indian Ministry of Environment and Forests¹

01 Jun 1989-International Journal of Remote Sensing (Taylor & Francis Group)-Vol. 10, Iss: 6, pp 989-1003

TL;DR: An evaluation of results indicates that various procedures of change detection produce different maps of change even in the same environment.

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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.

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Journal Article•DOI•

Change detection techniques

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Dengsheng Lu¹, Paul Mausel², Emilio F. Moran¹•Institutions (2)

Indiana University¹, Indiana State University²

20 Jun 2004-International Journal of Remote Sensing

TL;DR: This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature and summarizes and reviews these techniques.

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Abstract: Timely and accurate change detection of Earth's surface features is extremely important for understanding relationships and interactions between human and natural phenomena in order to promote better decision making. Remote sensing data are primary sources extensively used for change detection in recent decades. Many change detection techniques have been developed. This paper summarizes and reviews these techniques. Previous literature has shown that image differencing, principal component analysis and post-classification comparison are the most common methods used for change detection. In recent years, spectral mixture analysis, artificial neural networks and integration of geographical information system and remote sensing data have become important techniques for change detection applications. Different change detection algorithms have their own merits and no single approach is optimal and applicable to all cases. In practice, different algorithms are often compared to find the best change detection results for a specific application. Research of change detection techniques is still an active topic and new techniques are needed to effectively use the increasingly diverse and complex remotely sensed data available or projected to be soon available from satellite and airborne sensors. This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature.

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2,785 citations

Cites background or methods from "Review Article Digital change detec..."

...Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different times (Singh 1989)....
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...A low-pass filtered variant of the original image is used to approximate the Easy to implement Low accuracy Tropical forest change (Singh 1989)....
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...Two methods are often used for selection of thresholds (Singh 1989, Deer 1995, Yool et al. 1997): (1) interactive procedure or manual trial-and-error procedure—an analyst interactively adjusts the thresholds and evaluates the resulting image until satisfied; and (2) statistical measures— selection…...
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...Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different times (Singh 1989 )....
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...A variety of change detection techniques have been developed, and many have been summarized and reviewed (Singh 1989, Mouat et al. 1993, Deer 1995, Coppin and Bauer 1996, Jensen 1996, Jensen et al. 1997, Yuan et al. 1998, Serpico and Bruzzone 1999)....
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Journal Article•DOI•

Multisensor image fusion in remote sensing: Concepts, methods and applications

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Christine Pohl, J.L. van Genderen¹•Institutions (1)

International Institute of Minnesota¹

01 Jan 1998-International Journal of Remote Sensing

TL;DR: This review paper describes and explains mainly pixel based image fusion of Earth observation satellite data as a contribution to multisensor integration oriented data processing.

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Abstract: With the availability of multisensor, multitemporal, multiresolution and multifrequency image data from operational Earth observation satellites the fusion of digital image data has become a valuable tool in remote sensing image evaluation. Digital image fusion is a relatively new research field at the leading edge of available technology. It forms a rapidly developing area of research in remote sensing. This review paper describes and explains mainly pixel based image fusion of Earth observation satellite data as a contribution to multisensor integration oriented data processing.

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2,284 citations

Cites methods from "Review Article Digital change detec..."

...The ratio method is even more useful because of its capability to emphasise more on the slight signature variations (Zobrist et al. 1979, Singh 1989)....
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...Using the predicted value obtained from the leastsquare regression, the di erence image is the regression value-pixel of time one (Singh 1989, Shettigara 1992 )....
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...The combinations of IHS/RGB and PCA/RGB found recognition especially in geology (Haydn et al. 1982, Singh 1989, Koopmans and Richetti 1993, YeÂ sou et al. 1993 a, 1993 b)....
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Good Practice Guidance for Land Use, Land-Use Change and Forestry

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J. Penman, M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, R. Pipatti, L Buendia, K Miwa, T. Ngara, K Tanabe, Fabian Wagner - Show less +7 more

01 Jan 2003

2,059 citations

Journal Article•DOI•

Digital change detection methods in ecosystem monitoring: a review

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Pol Coppin¹, Inge Jonckheere¹, Kristiaan Nackaerts¹, Bart Muys¹, Eric F. Lambin² - Show less +1 more•Institutions (2)

Katholieke Universiteit Leuven¹, Université catholique de Louvain²

01 May 2004-International Journal of Remote Sensing

TL;DR: This review paper, which summarizes the methods and the results of digital change detection in the optical/infrared domain, has as its primary objective a synthesis of the state of the art today.

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Abstract: Techniques based on multi-temporal, multi-spectral, satellite-sensor-acquired data have demonstrated potential as a means to detect, identify, map and monitor ecosystem changes, irrespective of their causal agents. This review paper, which summarizes the methods and the results of digital change detection in the optical/infrared domain, has as its primary objective a synthesis of the state of the art today. It approaches digital change detection from three angles. First, the different perspectives from which the variability in ecosystems and the change events have been dealt with are summarized. Change detection between pairs of images (bi-temporal) as well as between time profiles of imagery derived indicators (temporal trajectories), and, where relevant, the appropriate choices for digital imagery acquisition timing and change interval length definition, are discussed. Second, pre-processing routines either to establish a more direct linkage between remote sensing data and biophysical phenomena, or to temporally mosaic imagery and extract time profiles, are reviewed. Third, the actual change detection methods themselves are categorized in an analytical framework and critically evaluated. Ultimately, the paper highlights how some of these methodological aspects are being fine-tuned as this review is being written, and we summarize the new developments that can be expected in the near future. The review highlights the high complementarity between different change detection methods.

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2,043 citations

Cites background or methods from "Review Article Digital change detec..."

...For tropical deforestation assessment, Singh ( 1989 ) tried both image smoothing and edge enhancements, but did not detect any increase in the final change detection accuracy with either method....
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...A couple of years later (Singh 1989), he reviewed that statement and concluded that the regression method performed only marginally better than univariate image differencing techniques in detecting tropical forest cover changes....
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...For tropical deforestation assessment, Singh (1989) tried both image smoothing and edge enhancements, but did not detect any increase in the final change detection accuracy with either method....
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...Singh (1986, 1989) used the technique in tropical deforestation monitoring with only modest results....
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...Singh (1989) changed the focus slightly by centering the definitions more on a temporal scale: simultaneous analysis of multi-temporal data versus comparative analysis of independently produced classifications for different dates....
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Image change detectio algorithms : A systematic survey

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R. J. Radke

01 Jan 2005

TL;DR: A systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling is presented.

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1,750 citations

Cites background or methods from "Review Article Digital change detec..."

...images [ 19 ]. DiStefano et al. [73] performed simple differencing on subsampled gradient images....
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...Singh in 1989 [ 19 ] and Coppin and Bauer in 1996 [20]....
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...1 Such methods were shown to have generally poor performance [ 19 ], [20]....
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References

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Journal Article•DOI•

Red and photographic infrared linear combinations for monitoring vegetation

[...]

Compton J. Tucker¹•Institutions (1)

Goddard Space Flight Center¹

01 May 1979-Remote Sensing of Environment

TL;DR: In this article, the relationship between various linear combinations of red and photographic infrared radiances and vegetation parameters is investigated, showing that red-IR combinations to be more significant than green-red combinations.

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8,537 citations

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Remote sensing and image interpretation

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Thomas Martin Lillesand¹•Institutions (1)

University of Minnesota¹

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Abstract: A textbook prepared primarily for use in introductory courses in remote sensing is presented. Topics covered include concepts and foundations of remote sensing; elements of photographic systems; introduction to airphoto interpretation; airphoto interpretation for terrain evaluation; photogrammetry; radiometric characteristics of aerial photographs; aerial thermography; multispectral scanning and spectral pattern recognition; microwave sensing; and remote sensing from space.

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6,790 citations

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Statistical and structural approaches to texture

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Robert M. Haralick¹•Institutions (1)

Virginia Tech¹

01 Jan 1979

TL;DR: This survey reviews the image processing literature on the various approaches and models investigators have used for texture, including statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models.

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Abstract: In this survey we review the image processing literature on the various approaches and models investigators have used for texture. These include statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models. We discuss and generalize some structural approaches to texture based on more complex primitives than gray tone. We conclude with some structural-statistical generalizations which apply the statistical techniques to the structural primitives.

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The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat

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R. J. Kauth¹, G. S. Thomas•Institutions (1)

Environmental Research Institute of Michigan¹

01 Jan 1976

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.

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Abstract: The time trajectories of agricultural data points as seen in Landsat signal space form a pattern suggestive of a tasselled woolly cap. Most of the important crop phenomena can be described using this three dimensional construct: the distribution of signals from bare soil, the processes of green development, yellow development, and shadowing and harvesting. A linear preprocessing transformation which isolates green development, yellow development and soil brightness is used to reduce the dimension of the signal space. Specific measurable pattern elements of the tasselled cap are used to estimate and correct atmospheric haze and moisture effects.

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1,558 citations