Remote sensing-based determination of deciduous and understory phenology over boreal forest

Date
2011
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Abstract
Phenology of the deciduous trees and understory grasses are the vegetation developmental stages influenced by the climatic variables. The study of the deciduous and understory phenology is important in understanding plant growth, net ecosystem CO2 exchange, forest flammability, forest hydrology, risk of insect infestation, etc. The objective of the study was to determine the phenological stages of deciduous [i.e., deciduous leaf out (DLO), deciduous leaf fall (DLF)] and understory grass green-up [i.e., green grass stage (GGS)] over the boreal forested region in the Canadian province of Alberta. In this study, the MODIS-based 8-day: (i) surface temperature (Ts)-images to derive the equivalent air temperature (T O ; used to determine DLF), (ii) surface reflectances for calculation of normalized difference water index (NDWI: used to determine DLO and GGS) and (iii) accumulated growing degree days (AGDD: a favourable temperature regime for plant growth: used to determine DLO and GGS). The temporal dynamics of AGDD, T O and NDWI was analysed, in conjunction with in-situ DLO, DLF and GGS observations in determining the optimal thresholds for DLO in 2006 (i.e., 80 degree-days and NDWI 0.325), DLF in 2006-2007 (i.e., 4 °C) and GGS in 2006 (i.e., 90 degree-days and NDWI 0.45). The implementation of these thresholds revealed reasonable agreements [i.e. , on an average (91.9% of the DLO and 94.2% of the GGS for AGDD) and (65% of both DLO and GGS for NDWI) within ±2 periods or ±16 days of deviations during 2007-2008; and 77.4% of the DLF for Ta within same deviations during 2008)] with compare to the in-situ observed data.
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Bibliography: p. 90-105
A few pages are in colour.
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Citation
Rahman, K. M. (2011). Remote sensing-based determination of deciduous and understory phenology over boreal forest (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/4478
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