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Hadi Fadaei

Researcher at Kyoto University

Publications -  18
Citations -  285

Hadi Fadaei is an academic researcher from Kyoto University. The author has contributed to research in topics: Normalized Difference Vegetation Index & Vegetation. The author has an hindex of 5, co-authored 18 publications receiving 211 citations. Previous affiliations of Hadi Fadaei include University of Tehran & Japan Agency for Marine-Earth Science and Technology.

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Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran)

TL;DR: The results showed that the AGB models derived from the combination of the Sentinel-2A and the ALOS-2 PALSAR-2 data had the highest accuracy, followed by models using the Sentinel -2A dataset and the AlOS- 2 PALSar-2 dataset.
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Unmanned aerial survey of fallen trees in a deciduous broadleaved forest in eastern Japan.

TL;DR: High-spatial-resolution aerial photographs taken from an unmanned aerial vehicle (UAV) are used to survey fallen trees in a deciduous broadleaved forest in eastern Japan and suggest that UAV surveys will make it possible to monitor the spatial and temporal variations in forest structure and function at lower cost.
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Mechanical behavior of pistachio nut and its kernel under compression loading

TL;DR: In this article, some mechanical properties of five varieties of Iranian pistachio nut and its kernel (namely; Akbari, Badami, Kalle-Ghuchi, Momtaz and O'hadi) were determined.
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Moisture Dependent Geometric and Mechanical Properties of Wild Pistachio (Pistacia vera L.) Nut and Kernel

TL;DR: In this article, wild pistachio (Pistacia vera L.) nuts and kernels were analyzed for selected geometric properties and mechanical behavior under compression loading, and the results revealed that wild pistachio nut required higher rupture force and energy to crack wild pithio nuts for compression along the L-axis as compared to other two axes.

Estimation of tree density with high-resolution imagery in the zarbin forest of north iran (cupressus sempervirence var. horzontalis)

TL;DR: In this article, a pixel-based classification has been used for tree density per hectare, which is useful for estimation of biomass, enabling better decision making for natural resource managers in environmental fields.