Remote sensing techniques in the analysis of change detection

Mouat, D. A.; Mahin, Glenda G.; Lancaster, Judith

doi:10.1080/10106049309354407

Cited by 102 publications

(34 citation statements)

References 28 publications

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“…Di erence or ratio images are very suitable for change detection (Mouat et al 1993 ). 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.…”

Section: Erence and Ratio Imagesmentioning

confidence: 99%

“…It is nearly impossible to acquire multisensor data simultaneously so that fusion of data from di erent sensors mostly includes a temporal factor. An overview on image enhancement techniques for change detection from multisensor data including image di erencing, ratioing and PCA is given in Mouat et al ( 1993). The techniques are described in § 4.…”

Section: T Emporal Aspects For Change Detectionmentioning

confidence: 99%

See 1 more Smart Citation

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

Pohl¹,

Genderen

1998

International Journal of Remote Sensing

1,980

1,025

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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 ® eld 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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Section: Erence and Ratio Imagesmentioning

confidence: 99%

Section: T Emporal Aspects For Change Detectionmentioning

confidence: 99%

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

Pohl¹,

Genderen

1998

International Journal of Remote Sensing

1,980

1,025

View full text Add to dashboard Cite

show abstract

“…Many of the world's wetland systems are being converted to agricultural or urban use and this change can be monitored using remotely sensed data (Ringrose et al 1988, Williams 1990, Mackey 1993, Markham et al 1993, Jensen et al 1995, Haack 1996 recorded at different times (Singh 1989). Each change detection method has its own merits and no method is optimal in all cases (Singh 1989, Mouat et al 1993, Deer 1995, Coppin and Bauer 1996, Serpico and Bruzzone 1999. Examples include band differencing (Weismiller et al 1977, Wink andKing 2006), transformed band differencing (Nelson 1983), ratioing (Howarth and Wickware 1981), regression (Singh 1986), principal components analysis (PCA) (Byrne et al 1980, Liu et al 2004) and change vector analysis (CVA) (Malila 1980, Nackaerts et al 2005.…”

Section: Introductionmentioning

confidence: 99%

Utilizing image texture to detect land-cover change in Mediterranean coastal wetlands

Berberoğlu

Akin

Atkinson

et al. 2010

International Journal of Remote Sensing

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Land-use/cover change dynamics were investigated in a Mediterranean coastal wetland. Change Vector Analysis (CVA) without and with image texture derived from the co-occurrence matrix and variogram were evaluated for detecting landuse/cover change. Three Landsat Thematic Mapper (TM) scenes recorded on July 1985, 1993 and 2005 were used, minimizing change detection error caused by seasonal differences. Images were geometrically, atmospherically and radiometrically corrected. CVA without and with texture measures were implemented and assessed using reference images generated by object-based supervised classification. These outputs were used for cross-classification to determine the 'from-to' change used to compare between techniques. The Landsat TM image bands together with the variogram yielded the most accurate change detection results, with Kappa statistics of 0.7619 and 0.7637 for the 1985-1993 and 1993-2005 image pairs, respectively.

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“…Change detection is the procedure of discovering and observing the difference in a body or phenomenon by visualising at difference times (Singh, 1989;Mouat et al, 1993).…”

Section: Change Detection In Land Use and Land Covermentioning

confidence: 99%

Change Detection of Land-use and Land-cover of Dehradun City: A Spatio-Temporal Analysis

Patidar¹,

Sankhla²

2015

IJARSG

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An attempt has been made in this research paper to detect the land-use and land-cover changes of Dehradun city of India during the period of May 2004 to May 2013. In addition, change detection in land use and land cover and the extent of inter-class changes have also been emphasized. Unsupervised classification has been adopted in LISS-III (2004) and Landsat-8 (MSS) images of the study area. The study has revealed that the built-up area in Dehradun city expanded by more than fifty percent during the study period. On the other hand, areas under vegetation, agricultural land and open fields have decreased about thirty eight and thirteen per cent respectively. Continuous assessments of land use/land cover changes in this city and the execution of proper land use planning is required for optimum and systematic development.

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Remote sensing techniques in the analysis of change detection

Cited by 102 publications

References 28 publications

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

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

Utilizing image texture to detect land-cover change in Mediterranean coastal wetlands

Change Detection of Land-use and Land-cover of Dehradun City: A Spatio-Temporal Analysis

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