Mapping Lorey's height over Hyrcanian forests of Iran using synergy of ICESat/GLAS and optical images

Lorey's height, representative of mean height in uneven-aged forest stands, is a valuable parameter for forest ecosystem management. While in situ measures provide the most precise information, remote-sensing techniques may provide less expensive but denser and more operational alternative of L...

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Bibliographic Details
Published in:	European journal of remote sensing Vol. 51; no. 1; pp. 100 - 115
Main Authors:	Rajab Pourrahmati, Manizheh, Baghdadi, Nicolas, Darvishsefat, Ali A, Namiranian, Manouchehr, Gond, Valery, Bailly, Jean-Stéphane, Zargham, Nosratollah
Format:	Journal Article
Language:	English
Published:	Cagiari Taylor & Francis 01-01-2018 Taylor & Francis Ltd Taylor & Francis Group
Subjects:	Applications artificial neural network (ANN) Artificial neural networks Computer Science Data mining Digital Elevation Models Ecosystem management Elevation Engineering Sciences Environmental Engineering Environmental Sciences Forest ecosystems Forest management Forests Global Changes ICESat/GLAS Image Processing In situ measurement Iran Laser altimeters Lorey's height Machine Learning Mapping Mountainous areas Neural networks optical images Optics Photonic Principal components analysis random forest (RF) Regression analysis Regression models Remote sensing Satellites Sensing techniques Statistics Waveforms Iran LOREY'S HEIGHT OPTICAL IMAGES ARTIFICIAL NEURAL NETWORK (ANN) IRAN RANDOM FOREST (RF) ICESAT/GLAS
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