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Current situation and needs of change detection techniques

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TLDR
The major steps involved in a change detection are overviewed, a summary of major change detection methods is summarised, the impacts of scales and complexity of study areas on the selection of remote-sensing data and change detection algorithms are discussed and the needs of developing newchange detection methods are discussed.
Abstract
Research on change detection techniques has long been an active topic and many techniques have been developed. In reality, change detection is a comprehensive procedure that requires careful consideration of many factors such as the nature of change detection problems, image preprocessing, selection of suitable variables and algorithms. This paper briefly overviews the major steps involved in a change detection, summarises major change detection methods, discusses the impacts of scales and complexity of study areas on the selection of remote-sensing data and change detection algorithms and finally discusses the needs of developing new change detection methods. As high spatial resolution images are easily available in the past decade, texture- and object-based methods become valuable to improve change detection performance. At national and global scales, coarse spatial resolution satellite images such as MODIS become important data sources for rapidly detecting land-cover change, but results have high unce...

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Citations
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Journal ArticleDOI

A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges

TL;DR: To fully exploit the available multitemporal HS images and their rich information content in change detection (CD), it is necessary to develop advanced automatic techniques that can address the complexity of the extraction of change information in an HS space.
Journal ArticleDOI

Fusing Landsat and SAR time series to detect deforestation in the tropics

TL;DR: In this article, a pixel-based multi-sensor correlation and fusion approach (MulTiFuse) was proposed to exploit the full observation density of optical and SAR time series.
Journal ArticleDOI

Unsupervised change detection in VHR remote sensing imagery – an object-based clustering approach in a dynamic urban environment

TL;DR: This paper presents a novel object-based approach for unsupervised change detection with focus on individual buildings with a unique procedure for determination of the number of relevant principal components and k-means clustering is applied for discrimination of changed and unchanged buildings.
Journal ArticleDOI

Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia

TL;DR: In this article, a generic structural break detection framework (BFAST) was used to improve the monitoring of forest cover loss by combining multiple data streams, such as Landsat data in combination with MODIS or rainfall data.
References
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Journal ArticleDOI

Textural Features for Image Classification

TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
Book

Introductory Digital Image Processing: A Remote Sensing Perspective

TL;DR: Introductory Digital Image Processing: A Remote Sensing Perspective focuses on digital image processing of aircraft- and satellite-derived, remotely sensed data for Earth resource management applications.
Journal ArticleDOI

Global Change and the Ecology of Cities

TL;DR: Urban ecology integrates natural and social sciences to study these radically altered local environments and their regional and global effects of an increasingly urbanized world.
BookDOI

Assessing the accuracy of remotely sensed data : principles and practices

TL;DR: This chapter discusses Accuracy Assessment, which examines the impact of sample design on cost, statistical Validity, and measuring Variability in the context of data collection and analysis.
Journal ArticleDOI

Object based image analysis for remote sensing

TL;DR: This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way.
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