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Ha Nam Thang

Expert in GIS, Remote Sensing and Machine Learning for:

  • Mapping and change assessment for blue carbon ecosystem

  • Environmental modeling and impact assessment

  • Marine spatial planning for sustainable aquaculture and resource conservation

  • Environmental Science and Pollution Research

  • Geocarto International

  • September 2003 - September 2007: University of Agriculture and Forestry (Hue University, Viet Nam) in the Field of Aquaculture

  • August 2011 - August 2013: University of Tsukuba (Japan) in the Field of Environmental Science (Msc)

  • February 2018 - September 2021: The University of Waikato (New Zealand) in the Field of Earth Science (PhD)

  • GIS spatial analysis

  • Interpolation with IDW, Kriging techniques

  • Spatial planning using Multi-Criteria Evaluation (MCE)

  • GIS mapping and analysis

  • Atmospheric correction for coarse/ medium/ high/ very high spatial resolution using the apps of ACOLITE, Sen2Cor, MAYA, iCOR

  • Water column correction using DII, BRI and bio-optical methods

  • Time series satellite image analysis

  • Raster image analysis

  • Remote sensing-based mapping/ change assessment of blue carbon ecosystem

  • GIS & Remote sensing-based valuation of blue carbon ecosystem

  • Employment of the state-of-the-art machine learning algorithms for regression/ classification works

  • Apply meta-heuristic algorithms for feature selection

  • Apply meta-heuristic algorithms and Bayesian model for the optimization of machine learning model's hyper-parameters

  • Develop Web-GIS application for data visualization, query and exporting desired thematic map

  • Deployment of Web-GIS application to GIS server






















Random forest and nature-inspired algorithms for mapping groundwater nitrate concentration in a coastal multi-layer aquifer system

Zoning Seagrass Protection in Lap An Lagoon, Vietnam Using a Novel Integrated Framework for Sustainable Coastal Management

DOI: http://dx.doi.org/10.1007/s13157-021-01504-8

Comparing the performance of machine learning algorithms for remote and in situ estimations of chlorophyll-a content: A case study in the Tri An Reservoir, Vietnam

DOI: https://doi.org/10.1002/wer.1643

Learning from Multimodal and Multisensor Earth Observation Dataset for Improving Estimates of Mangrove Soil Organic Carbon in Vietnam

Detecting Multi-Decadal Changes in Seagrass Cover in Tauranga Harbour, New Zealand, Using Landsat Imagery and Boosting Ensemble Classification Techniques

DOI: https://doi.org/10.3390/ijgi10060371

Evaluating the predictive power of different machine learning algorithms for groundwater salinity prediction of multi-layer coastal aquifers in the Mekong Delta, Vietnam

A Review of Remote Sensing Approaches for Monitoring Blue Carbon Ecosystems: Mangroves, Seagrassesand Salt Marshes during 2010–2018

A Comparative Assessment of Ensemble-Based Machine Learning and Maximum Likelihood Methods for Mapping Seagrass Using Sentinel-2 Imagery in Tauranga Harbor, New Zealand

Estimating Mangrove Above-Ground Biomass Using Extreme Gradient Boosting Decision Trees Algorithm with Fused Sentinel-2 and ALOS-2 PALSAR-2 Data in Can Gio Biosphere Reserve, Vietnam

Comparison of Machine Learning Methods for Estimating Mangrove Above-Ground Biomass Using Multiple Source Remote Sensing Data in the Red River Delta Biosphere Reserve, Vietnam

Inland harmful cyanobacterial bloom prediction in the eutrophic Tri An Reservoir using satellite band ratio and machine learning approaches

Estimation of nitrogen and phosphorus concentrations from water quality surrogates using machine learning in the Tri An Reservoir, Vietnam

Improvement of Mangrove Soil Carbon Stocks Estimation in North Vietnam Using Sentinel-2 Data and Machine Learning Approach