Tien Dat Pham
Orcid: 0000-0002-6422-2847Affiliations:
- RIKEN Center for Advanced Intelligence Project (AIP), Tokyo, Japan
- Vietnam National University of Agriculture, Center for Agricultural Research and Ecological Studies, Hanoi, Vietnam (former)
According to our database1,
Tien Dat Pham
authored at least 14 papers
between 2018 and 2022.
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Bibliography
2022
Mapping Multi-Decadal Mangrove Extent in the Northern Coast of Vietnam Using Landsat Time-Series Data on Google Earth Engine Platform.
Remote. Sens., 2022
2021
Detecting Multi-Decadal Changes in Seagrass Cover in Tauranga Harbour, New Zealand, Using Landsat Imagery and Boosting Ensemble Classification Techniques.
ISPRS Int. J. Geo Inf., 2021
2020
Probabilistic Mangrove Species Mapping with Multiple-Source Remote-Sensing Datasets Using Label Distribution Learning in Xuan Thuy National Park, Vietnam.
Remote. Sens., 2020
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.
Remote. Sens., 2020
A New Hybrid Firefly-PSO Optimized Random Subspace Tree Intelligence for Torrential Rainfall-Induced Flash Flood Susceptible Mapping.
Remote. Sens., 2020
A New Modeling Approach for Spatial Prediction of Flash Flood with Biogeography Optimized CHAID Tree Ensemble and Remote Sensing Data.
Remote. Sens., 2020
A Comparative Assessment of Ensemble-Based Machine Learning and Maximum Likelihood Methods for Mapping Seagrass Using Sentinel-2 Imagery in Tauranga Harbor, New Zealand.
Remote. Sens., 2020
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.
Remote. Sens., 2020
2019
A Review of Remote Sensing Approaches for Monitoring Blue Carbon Ecosystems: Mangroves, Seagrassesand Salt Marshes during 2010-2018.
Sensors, 2019
Multi-Hazard Exposure Mapping Using Machine Learning Techniques: A Case Study from Iran.
Remote. Sens., 2019
Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges.
Remote. Sens., 2019
Soil Salinity Mapping Using SAR Sentinel-1 Data and Advanced Machine Learning Algorithms: A Case Study at Ben Tre Province of the Mekong River Delta (Vietnam).
Remote. Sens., 2019
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2018
Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran).
Remote. Sens., 2018