Mirela G. Tulbure

According to our database, Mirela G. Tulbure authored at least 8 papers between 2015 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

The role of spatial context and multitask learning in the detection of organic and conventional farming systems based on Sentinel-2 time series.

Jan Hemmerling, Marcel Schwieder, Philippe Rufin, Leon-Friedrich Thomas, Mirela G. Tulbure, Patrick Hostert, Stefan Erasmi

CoRR, March, 2026

2025

Leveraging AI multimodal geospatial foundation models for improved near-real-time flood mapping at a global scale.

Mirela G. Tulbure, Julio Caineta, Mark Broich, Mollie D. Gaines, Philippe Rufin, Leon-Friedrich Thomas, Hamed Alemohammad, Jan Hemmerling, Patrick Hostert

CoRR, December, 2025

2024

Creating spatially complete zoning maps using machine learning.

Margaret A. Lawrimore, Georgina M. Sanchez, Cayla Cothron, Mirela G. Tulbure, Todd K. BenDor, Ross K. Meentemeyer

Comput. Environ. Urban Syst., 2024

Taking it further: Leveraging pseudo-labels for field delineation across label-scarce smallholder regions.

Philippe Rufin, Sherrie Wang, Sá Nogueira Lisboa, Jan Hemmerling, Mirela G. Tulbure, Patrick Meyfroidt

Int. J. Appl. Earth Obs. Geoinformation, 2024

2021

Monitoring Small Water Bodies Using High Spatial and Temporal Resolution Analysis Ready Datasets.

Vinicius Perin, Samapriya Roy, Joe D. Kington, Thomas Harris, Mirela G. Tulbure, Noah Stone, Torben Barsballe, Michele Reba, Mary A. Yaeger

Remote. Sens., 2021

2019

The role of GRACE total water storage anomalies, streamflow and rainfall in stream salinity trends across Australia's Murray-Darling Basin during and post the Millennium Drought.

Valentin Heimhuber, Mirela G. Tulbure, Mark Broich, Zunyi Xie, M. Hurriyet

Int. J. Appl. Earth Obs. Geoinformation, 2019

2018

Multi-sensor airborne and satellite data for upscaling tree number information in a structurally complex eucalypt forest.

Iurii Shendryk, Mark Broich, Mirela G. Tulbure

Int. J. Appl. Earth Obs. Geoinformation, 2018

2015

A spatially explicit land surface phenology data product for science, monitoring and natural resources management applications.

Mark Broich, Alfredo R. Huete, Matt Paget, Xuanlong Ma, Mirela G. Tulbure, Natalia Restrepo Coupe, Bradley J. Evans, Jason Beringer, Rakhesh Devedas, Kevin P. Davies, Alex Held

Environ. Model. Softw., 2015