Multitemporal Spectral Analysis for Cheatgrass (Bromus tectorum) Classification

N. Singh, N. F. Glenn, Nancy Glenn

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

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.
Original languageAmerican English
JournalInternational Journal of Remote Sensing
Volume30
Issue number13
StatePublished - 10 Jul 2009

EGS Disciplines

  • Earth Sciences

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