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Journal of Applied Remote Sensing

Remote sensing-based determination of understory grass greening stage over boreal forest
Author(s): Quazi K. Hassan; K. Mahmud Rahman
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Paper Abstract

Our objective was the determination of understory grass greening stage (GGS: defined as the date when 75% of the grass in the surrounding area of a particular location would be green) using remote sensing data over the boreal-dominant forested regions in the Canadian province of Alberta. We used moderate resolution imaging spectroradiometer (MODIS)-derived accumulated growing degree days (AGDD) and normalized difference water index (NDWI) with ground-based understory GGS observations at approximately 120 lookout tower sites during the period 2006 to 2008. During 2006, we extracted the temporal dynamics of AGDD/NDWI at the lookout tower sites and determined the best thresholds (i.e., 90 degree-days for AGDD and 0.45 for NDWI). These AGDD/NDWI thresholds were then implemented during 2007 and 2008; and observed that AGDD had better prediction capabilities in comparison to NDWI (i.e., ∼94% and ∼65% of the incidents fall within ±2  periods or ±16 days of deviations with the ground-based understory GGS observations using AGDD and NDWI thresholds, respectively). The outcomes would potentially be useful in understanding availability of food and habitat for wildlife species/animals; microclimatic environment, composition, and diversity of plant community; and forest fire danger and fire behavior in case of fire occurrences.

Paper Details

Date Published: 8 April 2013
PDF: 11 pages
J. Appl. Remote Sens. 7(1) 073578 doi: 10.1117/1.JRS.7.073578
Published in: Journal of Applied Remote Sensing Volume 7, Issue 1
Show Author Affiliations
Quazi K. Hassan, Univ. of Calgary (Canada)
K. Mahmud Rahman, Univ. of Calgary (Canada)

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