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Delineation of Built-Up Areas from Very High-Resolution Satellite Imagery Using Multi-Scale Textures and Spatial Dependence

by Yixiang Chen 1,*, Zhiyong Lv 2, Bo Huang 3,* and Yan Jia 1
1
Department of Surveying and Geoinformatics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
2
School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China
3
Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China
*
Authors to whom correspondence should be addressed.
Remote Sens. 2018, 10(10), 1596; https://doi.org/10.3390/rs10101596
Received: 16 August 2018 / Revised: 20 September 2018 / Accepted: 3 October 2018 / Published: 8 October 2018
(This article belongs to the Section Remote Sensing Image Processing)
Very high spatial resolution (VHR) satellite images possess several advantages in terms of describing the details of ground targets. Extracting built-up areas from VHR images has received increasing attention in practical applications, such as land use planning, urbanization monitoring, geographic information database update. In this study, a novel method is proposed for built-up area detection and delineation on VHR satellite images, using multi-resolution space-frequency analysis, spatial dependence modelling and cross-scale feature fusion. First, the image is decomposed by multi-resolution wavelet transformation, and then the high-frequency information at different levels is employed to represent the multi-scale texture and structural characteristics of built-up areas. Subsequently, the local Getis-Ord statistic is introduced to model the spatial patterns of built-up area textures and structures by measuring the spatial dependence among frequency responses at different spatial positions. Finally, the saliency map of built-up areas is produced using a cross-scale feature fusion algorithm, followed by adaptive threshold segmentation to obtain the detection results. The experiments on ZY-3 and Quickbird datasets demonstrate the effectiveness and superiority of the proposed method through comparisons with existing algorithms. View Full-Text
Keywords: high-resolution; built-up area detection; multi-resolution wavelet; spatial dependence; cross-scale high-resolution; built-up area detection; multi-resolution wavelet; spatial dependence; cross-scale
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MDPI and ACS Style

Chen, Y.; Lv, Z.; Huang, B.; Jia, Y. Delineation of Built-Up Areas from Very High-Resolution Satellite Imagery Using Multi-Scale Textures and Spatial Dependence. Remote Sens. 2018, 10, 1596.

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