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Title: Multitemporal spectral analysis for cheatgrass (Bromus tectorum) classification.

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.
Authors:
 [1] ;  [2]
  1. ORNL
  2. Idaho State University
Publication Date:
OSTI Identifier:
1003775
DOE Contract Number:
DE-AC05-00OR22725
Resource Type:
Journal Article
Resource Relation:
Journal Name: International Journal of Remote Sensing; Journal Volume: 30; Journal Issue: 13
Research Org:
Oak Ridge National Laboratory (ORNL)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; ACCURACY; CLASSIFICATION; PLANTS; REMOTE SENSING; RESOLUTION; SATELLITES; SOILS; TARGETS