Geospatial analysis of land use change in the Savannah River Basin using Google Earth Engine. - Hamdi A. Zurqani; Christopher J. Post; Elena Mikhailova; Mark Schlautman; Julia L. Sharp (Int. J. Appl. Earth Obs. Geoinformation, 2018)

Evaluation of Riparian Tree Cover and Shading in the Chauga River Watershed Using LiDAR and Deep Learning Land Cover Classification. - Madeleine M. Bolick; Christopher J. Post; Elena Mikhaylova; Hamdi A. Zurqani; Andrew P. Grunwald; Elizabeth A. Saldo (Remote. Sens., 2021)

Development of Digital Terrain Model Under High Dense Forest Cover Using USGS and Drone Lidar Data. - Segun M. Adedapo; Hamdi A. Zurqani (IGARSS, 2023)

Mapping and Monitoring the Spatial and Temporal Variation of Drought and Its Impact on Vegetation Cover in Arkansas, USA. - Shadia A Alzurqani; Hamdi A. Zurqani; Don White; Kathleen Bridges; Shawn Jackson (IGARSS, 2023)

Using Machine Learning and Google Earth Engine to Develop a High-Resolution Forest Canopy Cover Dataset: A Case Study in Arkansas, USA. - Hamdi A. Zurqani (IGARSS, 2023)

Evaluating the performance of various interpolation techniques on digital elevation models in highly dense forest vegetation environment. - Segun M. Adedapo; Hamdi A. Zurqani (Ecol. Informatics, 2024)

An automated approach for developing a regional-scale 1-m forest canopy cover dataset using machine learning and Google Earth Engine cloud computing platform. - Hamdi A. Zurqani (Softw. Impacts, 2024)

A multi-source approach combining GEDI LiDAR, satellite data, and machine learning algorithms for estimating forest aboveground biomass on Google Earth Engine platform. - Hamdi A. Zurqani (Ecol. Informatics, 2025)