Work

Machine Learning-Based Forest Canopy Height Modeling with Multi-Sensor and GEDI Data

Year: 2024

Type: conference-paper

DOI: 10.1109/edis63605.2024.10783293

Authors: Benhalima Noureddine, Ouarzeddine Mounira, Souissi Boularbah, Bengusmia Djamal

Institutions: University of Sciences and Technology Houari Boumediene, Bureau National d’Études pour le Développement Rural

Language: English

Topic: Remote Sensing and LiDAR Applications

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Life on land

Open Access status: closed

OpenAlex ID: W4405361531

FWCI: 1.058

Cites: 14

Cited by: 1

Related to: 10