H. Tamiminia

发表

Clustering of Multi-Temporal Fully Polarimetric L-Band SAR Data for Agricultural Land Cover Mapping

Saeid Homayouni, A. Safari, H. Tamiminia, 2015 .

Mapping Two Decades of New York State Forest Aboveground Biomass Change Using Remote Sensing

M. Mahdianpari, B. Salehi, C. Beier, 2022, Remote. Sens..

A COMPARATIVE ANALYSIS OF PIXEL-BASED AND OBJECT-BASED APPROACHES FOR FOREST ABOVE-GROUND BIOMASS ESTIMATION USING RANDOM FOREST MODEL

M. Mahdianpari, B. Salehi, C. Beier, 2022, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

Comparison of Machine and Deep Learning Methods to Estimate Shrub Willow Biomass from UAS Imagery

Daniel J. Klimkowski, T. Volk, M. Mahdianpari, 2021 .

Google Earth Engine for geo-big data applications: A meta-analysis and systematic review

Masoud Mahdianpari, Lindi J. Quackenbush, Brian Brisco, 2020 .

Wetland Monitoring Using SAR Data: A Meta-Analysis and Comprehensive Review

Masoud MahdianPari, Brian Brisco, Bahram Salehi, 2020, Remote. Sens..

A COMPARISON OF DECISION TREE-BASED MODELS FOR FOREST ABOVE-GROUND BIOMASS ESTIMATION USING A COMBINATION OF AIRBORNE LIDAR AND LANDSAT DATA

M. Mahdianpari, B. Salehi, C. Beier, 2021, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis

M. Mahdianpari, B. Salehi, H. Tamiminia, 2022 .

Random Forest Outperformed Convolutional Neural Networks for Shrub Willow Above Ground Biomass Estimation Using Multi-Spectral UAS Imagery

Bahram Salehi, Timothy A. Volk, Masoud MahdianPari, 2021, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS.

EVALUATING PIXEL-BASED AND OBJECT-BASED APPROACHES FOR FOREST ABOVE-GROUND BIOMASS ESTIMATION USING A COMBINATION OF OPTICAL, SAR, AND AN EXTREME GRADIENT BOOSTING MODEL

M. Mahdianpari, B. Salehi, C. Beier, 2022, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

A particle swarm optimized kernel-based clustering method for crop mapping from multi-temporal polarimetric L-band SAR observations

Heather McNairn, Saeid Homayouni, Abdolreza Safari, 2017, Int. J. Appl. Earth Obs. Geoinformation.

State-wide forest canopy height and aboveground biomass map for New York with 10 m resolution, integrating GEDI, Sentinel-1, and Sentinel-2 data

M. Mahdianpari, B. Salehi, H. Tamiminia, 2023, Ecol. Informatics.

Generating A 10 M Resolution Canopy Height Model Of New York State Using Gedi And Sentinel-2 Data

M. Mahdianpari, B. Salehi, H. Tamiminia, 2023, IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium.