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Mollie D. Gaines
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Can we detect more ephemeral floods with higher density harmonized Landsat Sentinel 2 data compared to Landsat 8 alone?
MG Tulbure, M Broich, V Perin, M Gaines, J Ju, SV Stehman, T Pavelsky, ...
ISPRS Journal of Photogrammetry and Remote Sensing 185, 232-246, 2022
302022
A multi-sensor satellite imagery approach to monitor on-farm reservoirs
V Perin, MG Tulbure, MD Gaines, ML Reba, MA Yaeger
Remote Sensing of Environment 270, 112796, 2022
122022
On-farm reservoir monitoring using Landsat inundation datasets
V Perin, MG Tulbure, MD Gaines, ML Reba, MA Yaeger
Agricultural Water Management 246, 106694, 2021
112021
Effects of Climate and Anthropogenic Drivers on Surface Water Area in the Southeastern United States
MD Gaines, MG Tulbure, V Perin
Water Resources Research 58 (3), e2021WR031484, 2022
102022
A review of geospatial content in IEEE visualization publications
A Yoshizumi, MM Coffer, EL Collins, MD Gaines, X Gao, K Jones, ...
2020 IEEE Visualization Conference (VIS), 51-55, 2020
92020
Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh
V Tiwari, MG Tulbure, J Caineta, MD Gaines, V Perin, M Kamal, ...
Journal of Environmental Management 351, 119615, 2024
22024
Preliminary comparison and evaluation of soil moisture simulated in GFSv15 and GFSv16
Y Xia, H Wei, J Meng, G Gayno, H Lei, R Yang, Y Wu, F Yang, MJ Barlage, ...
101st American Meteorological Society Annual Meeting, 2021
12021
Quantifying Urban Flood Extent Using Satellite Imagery and Random Forest: A Case Study in Southeastern Pennsylvania
R Composto, MG Tulbure, V Tiwari, MD Gaines, J Caineta
2024
Comparing Remotely Sensed Surface Water Areas Between Moderate-and High-Resolution Data Products to Assess Uncertainty in Machine Machine Learning-Projected Surface Water Area
M Gaines, MG Tulbure, V Perin, J Caineta, V Tiwari, R Composto
AGU23, 2023
2023
Quantifying and Downscaling Methane Concentration from Winter Rice Fields in Bangladesh using Satellite Data and Machine Learning approach
V Tiwari, MG Tulbure, J Caineta, M Gaines, R Composto
AGU23, 2023
2023
Quantifying Flood Extent Using Satellite Imagery and Machine Learning after Hurricane Ida in Pennsylvania
R Composto, MG Tulbure, V Tiwari, M Gaines, J Caineta
AGU23, 2023
2023
Multi-sensor fusion for global flood mapping
MG Tulbure, M Broich, J Caineta, M Gaines, V Perin, SV Stehman, ...
AGU23, 2023
2023
Rice area mapping in Bangladesh: Harnessing the power of time-series of Sentinel data and Google Earth Engine
V Tiwari, MG Tulbure, MD Gaines, V Perin
Fall Meeting 2022, 2022
2022
Projecting surface water area in the southeastern US under multiple emissions and development scenarios
M Gaines, MG Tulbure, V Perin, V Tiwari
AGU Fall Meeting Abstracts 2022, H13C-04, 2022
2022
Global Flood Mapping with High-Resolution Optical-Radar Data Fusion
MG Tulbure, M Gaines, V Perin, T Pavelsky, SV Stehman, M Broich, ...
AGU Fall Meeting Abstracts 2022, H33E-04, 2022
2022
Projecting surface water in the Southeastern US under three climate and development scenarios
MD Gaines, MG Tulbure, V Perin
AGU Fall Meeting 2021, 2021
2021
Towards global flood mapping with machine learning based on the Harmonized Landsat-Sentinel 2 data
M Tulbure, M Broich, M Gaines, S Stehman, T Pavelsky, V Perin, J Ju, ...
AGU Fall Meeting Abstracts 2021, H44E-03, 2021
2021
The Effects of Climate and Human Drivers on Changes in Surface Water in the Southeastern United States
M Gaines, MG Tulbure
AGU Fall Meeting Abstracts 2020, H083-0012, 2020
2020
Can we detect more ephemeral floods with higher density harmonized Landsat 8/Sentinel 2 data compared to just one sensor?
MG Tulbure, M Broich, J Ju, V Perin, M Gaines, S Yin, SV Stehman, ...
AGU Fall Meeting Abstracts 2020, H016-08, 2020
2020
Calculating a Drought Vulnerability Index for South Africa based on Social and Biophysical Characteristics
M Gaines
2019
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