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http://dx.doi.org/10.11108/kagis.2013.16.2.088

Detection of Small Green Space in an Urban Area Using Airborne Hyperspectral Imagery and Spectral Angle Mapper  

Kim, Tae-Woo (Dept. of Spatial Information Engineering, Pukyong National University)
Choi, Don-Jeong (Dept. of Spatial Information Engineering, Pukyong National University)
We, Gwang-Jae (Geostory Inc.)
Suh, Yong-Cheol (Dept. of Spatial Information Engineering, Pukyong National University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.16, no.2, 2013 , pp. 88-100 More about this Journal
Abstract
Urban green space is one of most important aspects of urban infrastructure for improving the quality of life of city dwellers as it reduces the heat island effect and is used for recreation and relaxation. However, no systematic management of urban green space has been introduced in Korea as past practices focused on efficient development. A way to calculate the amount of green space needed to complement an urban area must be developed to preserve urban green space and to determine 'regulations determining the total amount of greenery'. In recent years, various studies have quantified urban green space and infrastructure using remotely sensed data. However, it is difficult to detect a myriad small green spaces in a city effectively when considering the spatial resolution of the data used in existing research. In this paper, we quantified small urban green spaces using CASI-1500 hyperspectral imagery. We calculated MCARI, a vegetation index for hyperspectral imagery, to evaluate the greenness of small green spaces. In addition, we applied image-classification methods, including the ISODATA algorithm and Spectral Angle Mapper, to detect small green spaces using supervised and unsupervised classifications. This could be used to categorize land-cover into four classes: unclassified, impervious, suspected green, and vegetation green.
Keywords
Airborne Hyperspectral Imagery; Urban Small Green Space; Spectral Angle Mapper; Vegetation Index;
Citations & Related Records
Times Cited By KSCI : 13  (Citation Analysis)
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