Title
Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images.
Abstract
Urban functional zones, such as commercial, residential, and industrial zones, are basic units of urban planning, and play an important role in monitoring urbanization. However, historical functional-zone maps are rarely available for cities in developing countries, as traditional urban investigations focus on geographic objects rather than functional zones. Recent studies have sought to extract functional zones automatically from very-high-resolution (VHR) satellite images, and they mainly concentrate on classification techniques, but ignore zone segmentation which delineates functional-zone boundaries and is fundamental to functional-zone analysis. To resolve the issue, this study presents a novel segmentation method, geoscene segmentation, which can identify functional zones at multiple scales by aggregating diverse urban objects considering their features and spatial patterns. In experiments, we applied this method to three Chinese citiesBeijing, Putian, and Zhuhaiand generated detailed functional-zone maps with diverse functional categories. These experimental results indicate our method effectively delineates urban functional zones with VHR imagery; different categories of functional zones extracted by using different scale parameters; and spatial patterns that are more important than the features of individual objects in extracting functional zones. Accordingly, the presented multiscale geoscene segmentation method is important for urban-functional-zone analysis, and can provide valuable data for city planners.
Year
DOI
Venue
2018
10.3390/rs10020281
REMOTE SENSING
Keywords
Field
DocType
urban landscape,functional zone,object-based image analysis,multiscale image segmentation,VHR images
Urbanization,Satellite,Segmentation,Remote sensing,Urban planning,Geology,Spatial ecology,Cartography
Journal
Volume
Issue
ISSN
10
2
2072-4292
Citations 
PageRank 
References 
1
0.37
24
Authors
4
Name
Order
Citations
PageRank
Zhang, X.1203.18
Shihong Du219219.39
Qiao Wang39721.94
Weiqi Zhou45213.42