Detecting invasive plant species using hyperspectral satellite imagery

Fuan Tsai, En Kai Lin, Hsiang Hua Wang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

3 引文 斯高帕斯(Scopus)

摘要

Hyperspectral remote sensing images provide more complete and detailed spectral information about ground coverage and have a great potential to identify specific plant species in vegetation covered areas. The high data dimensionality of hyperspectral data can cause substantial impact to its applications. Principal component analysis is a common technique used for feature reduction in remote sensing image analysis. However, it may also overlook subtle but useful information. This research developed a segmented principal component analysis scheme that can be used to reduce the dimensionality of a hyperspectral image but also retain critical spectral features helpful in discriminating different vegetation types. The developed methodology was applied to the analysis of a Hyperion hyperspectal image to determine the status of an invasive plant species (Leucaena leucocephala) in southern Taiwan.

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主出版物標題25th Anniversary IGARSS 2005
主出版物子標題IEEE International Geoscience and Remote Sensing Symposium
頁面3002-3005
頁數4
DOIs
出版狀態已出版 - 2005
事件2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005 - Seoul, Korea, Republic of
持續時間: 25 7月 200529 7月 2005

出版系列

名字International Geoscience and Remote Sensing Symposium (IGARSS)
4

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???event.eventtypes.event.conference???2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005
國家/地區Korea, Republic of
城市Seoul
期間25/07/0529/07/05

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