2018 International Conference on Advanced Science and Engineering (ICOASE) 2018
DOI: 10.1109/icoase.2018.8548859
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Estimating and Mapping Aboveground Biomass of Natural Quercus Aegilops Using WorldView-3 Imagery

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Cited by 6 publications
(4 citation statements)
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“…Remote sensing involves data gathering 'at a distance' from aircrafts, or computerized sensors on the earth, in water, or from space (Hoffmann et al 2014). Remote sensing can be applied to predicate both ocean and terrestrial initial production which means that production of yields, wood, feed, and biofuel, and regulation of climate through variations in carbon stock can be calculated (Al-Quraishi et al 2022, Hassanpour & YT Mustafa 2018, Obeyed et al 2018.…”
Section: Remote Sensingmentioning
confidence: 99%
“…Remote sensing involves data gathering 'at a distance' from aircrafts, or computerized sensors on the earth, in water, or from space (Hoffmann et al 2014). Remote sensing can be applied to predicate both ocean and terrestrial initial production which means that production of yields, wood, feed, and biofuel, and regulation of climate through variations in carbon stock can be calculated (Al-Quraishi et al 2022, Hassanpour & YT Mustafa 2018, Obeyed et al 2018.…”
Section: Remote Sensingmentioning
confidence: 99%
“…Randomlyone kg. of these leaves were taken and transferred to the laboratory for drying purposes.The total FW of each individual tree AGB was calculated as the sum of the weights of each tree component (17). Dryweight (DW): Sub-samples of each component of a tree dried at 105 ○ C ±2.…”
Section: Estimating Agb and Its Componentsmentioning
confidence: 99%
“…The impact of changes in vegetation biomass is highly relevant to estimate current conditions and probable future scenarios of ecosystem evolution. Above-ground biomass (AGB) influences environmental processes, such as the hydrological cycle, soil erosion and degradation, especially in semi-arid areas [7,8]. Remotely sensed satellite data are wellknown and effective in vegetation monitoring.…”
Section: Introductionmentioning
confidence: 99%
“…Other traditional vegetation indexes, such as NDVI, may perform less successfully, although they are often considered "a priori" better predictors in AGB modelling. Saturation effects and the high canopy cover of meadows and pastures may explain the low performance of vegetation indices [11,12]. For the current paper, we pursued two linked goals: to select the most suitable algorithms for mountain pasture capacity estimation and to apply algorithms chosen for practical usage, i.e.…”
Section: Introductionmentioning
confidence: 99%