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Article

Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images

1
School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China
2
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
3
Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik IS 107, Iceland
4
Department of Surveying and Geoinformatics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 901; https://doi.org/10.3390/rs10060901
Received: 28 April 2018 / Revised: 2 June 2018 / Accepted: 5 June 2018 / Published: 8 June 2018
Land cover change detection (LCCD) based on bi-temporal remote sensing images plays an important role in the inventory of land cover change. Due to the benefit of having spatial dependency properties within the image space while using remote sensing images for detecting land cover change, many contextual information-based change detection methods have been proposed in past decades. However, there is still a space for improvement in accuracies and usability of LCCD. In this paper, a LCCD method based on adaptive contextual information is proposed. First, an adaptive region is constructed by gradually detecting the spectral similarity surrounding a central pixel. Second, the Euclidean distance between pairwise extended regions is calculated to measure the change magnitude between the pairwise central pixels of bi-temporal images. All the bi-temporal images are scanned pixel by pixel so the change magnitude image (CMI) can be generated. Then, the Otsu or a manual threshold is employed to acquire the binary change detection map (BCDM). The detection accuracies of the proposed approach are investigated by three land cover change cases with Landsat bi-temporal remote sensing images and aerial images with very high spatial resolution (0.5 m/pixel). In comparison to several widely used change detection methods, the proposed approach can produce a land cover change inventory map with a competitive accuracy. View Full-Text
Keywords: land cover change detection; adaptive contextual information; bi-temporal remote sensing images land cover change detection; adaptive contextual information; bi-temporal remote sensing images
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MDPI and ACS Style

Lv, Z.; Liu, T.; Zhang, P.; Atli Benediktsson, J.; Chen, Y. Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images. Remote Sens. 2018, 10, 901. https://doi.org/10.3390/rs10060901

AMA Style

Lv Z, Liu T, Zhang P, Atli Benediktsson J, Chen Y. Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images. Remote Sensing. 2018; 10(6):901. https://doi.org/10.3390/rs10060901

Chicago/Turabian Style

Lv, Zhiyong, Tongfei Liu, Penglin Zhang, Jón Atli Benediktsson, and Yixiang Chen. 2018. "Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images" Remote Sensing 10, no. 6: 901. https://doi.org/10.3390/rs10060901

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