Saah, D.[David]
* 2017: Self-Calibrating Runoff and Streamflow Remote Sensing Model for Ungauged Basins Using Open-Access Earth Observation Data, A
* 2018: Operational Before-After-Control-Impact (BACI) Designed Platform for Vegetation Monitoring at Planetary Scale, An
* 2019: Mapping Plantations in Myanmar by Fusing Landsat-8, Sentinel-2 and Sentinel-1 Data along with Systematic Error Quantification
* 2020: Comparing Sentinel-1 Surface Water Mapping Algorithms and Radiometric Terrain Correction Processing in Southeast Asia Utilizing Google Earth Engine
* 2020: Comparison of Three Temporal Smoothing Algorithms to Improve Land Cover Classification: A Case Study from NEPAL, A
* 2020: Predictive Analytics for Identifying Land Cover Change Hotspots in the Mekong Region
* 2020: ST-CORAbico: A Spatiotemporal Object-Based Bias Correction Method for Storm Prediction Detected by Satellite
* 2021: Automatic Detection of Impervious Surfaces from Remotely Sensed Data Using Deep Learning
* 2021: Lessons Learned While Implementing a Time-Series Approach to Forest Canopy Disturbance Detection in Nepal
* 2023: Evaluating SAR Radiometric Terrain Correction Products: Analysis-Ready Data for Users
* 2023: Near Real-Time Mapping of Tropical Forest Disturbance Using SAR and Semantic Segmentation in Google Earth Engine, A
* 2023: Uncovering Dynamics of Global Mangrove Gains and Losses
12 for Saah, D.
Saah, D.S.[David S.]
* 2018: Historical and Operational Monitoring of Surface Sediments in the Lower Mekong Basin Using Landsat and Google Earth Engine Cloud Computing