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Multitemporal spectral analysis for cheatgrass (Bromus tectorum) classification

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Abstract:

Operational satellite remote sensing data can provide the temporal repeatability necessary to capture phenological differences among species. This study develops a multitemporal stacking method coupled with spectral analysis for extracting information from Landsat imagery to provide species-level information. Temporal stacking can, in an approximate mathematical sense, effectively increase the 'spectral' resolution of the system by adding spectral bands of several multitemporal images. As a demonstration, multitemporal linear spectral unmixing is used to successfully delineate cheatgrass (Bromus tectorum) from soil and surrounding vegetation (77% overall accuracy). This invasive plant is an ideal target for exploring multitemporal methods because of its phenological differences with other vegetation in early spring and, to a lesser degree, in late summer. The techniques developed in this work are directly applicable for other targets with temporally unique spectral differences.

Document Type: Research Article

DOI: https://doi.org/10.1080/01431160802562222

Affiliations: 1: Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, TN, USA 2: Department of Geosciences, Idaho State University-Boise, Boise, ID 83702, USA

Publication date: 2009-01-01

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