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• W2777184823 abstract "The rapid growth of golf course has constituted a nonnegligible threat to conservation of cropland and water resource in China. To monitor golf course at a large scale with low cost, a practical bottom-up golf course detection approach using multispectral remote sensing imagery is proposed. First of all, turfgrass, water-body and bunker are determined as the basic elements based on analyzing golf course land-use characteristics. Secondly, turfgrass and water-body are extracted using spectral indexes and these two basic elements are combined as region-of-interest under guidance of prior-knowledge. Afterwards, bunker is extracted by spectral mixture analysis restricted to region-of-interest. Finally, fuzzy C-means is adopted to recognize golf course using landscape metrics. A SPOT-5 HRG multispectral image of Beijing is used to validate the proposed method, and detection rate and false alarm rate are 86.67% and 38.10% respectively." @default.
• W2777184823 created "2018-01-05" @default.
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• W2777184823 date "2017-01-01" @default.
• W2777184823 modified "2023-09-24" @default.
• W2777184823 title "Practical Bottom-up Golf Course Detection Using Multispectral Remote Sensing Imagery" @default.
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• W2777184823 doi "https://doi.org/10.1007/978-3-319-71589-6_48" @default.
• W2777184823 hasPublicationYear "2017" @default.
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