[PDF][PDF] Development of a new allometric equation correlated WTH RS variables for the assessment of date palm biomass

S Issa, B Dahy, T Ksiksi, N Saleous - Conference paper. UAE …, 2018 - researchgate.net
Conference paper. UAE University, College of Science: United Arab …, 2018researchgate.net
The United Arab Emirates (UAE) has the largest number of date palms for any single country
in the world with an estimated number of about 42 million palms. Date palm, Phoenix
dactylifera, is considered as the most important fruit crop in arid regions. In addition to its
ability to tolerate harsh weather, high temperature, drought and high levels of salinity, date
palm is a good source for carbon sequestration in such ecosystems. The main objectives of
the actual study were to develop new allometric equations for aboveground biomass …
Abstract
The United Arab Emirates (UAE) has the largest number of date palms for any single country in the world with an estimated number of about 42 million palms. Date palm, Phoenix dactylifera, is considered as the most important fruit crop in arid regions. In addition to its ability to tolerate harsh weather, high temperature, drought and high levels of salinity, date palm is a good source for carbon sequestration in such ecosystems. The main objectives of the actual study were to develop new allometric equations for aboveground biomass assessment of date palm in the arid lands of the UAE and to determine the best remote sensing (RS) predictors to develop a RS-based biomass assessment model. Testing plots from Al Ain area (UAE) were used to estimate the above ground biomass (AGB) of date palm using standard sampling techniques. It was found that crown area (CA) and trunk height (Ht) of the date palm were the best field measured variables for the prediction of AGB. In each plot, crown area (CA) and trunk height (Ht) of date palms were measured to estimate the biomass at plot level. These findings were tested for their correlation with remote sensing (RS) variables (derived from Landsat 8 bands) to determine the best predictors and develop a RS based biomass assessment model. The relationships between the AGB and RS variables (eg, single bands and various vegetation indices) were investigated using multiple linear regression analysis. Preliminary results were promising, and final model is being built and will be published soon.
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