Alexandra Hurduc

 
 

Profile

Research Group: RG1 – Climate variability processes and extremes
Position at IDL: PhD Student
Job: PhD Student 
Email: ahurduc@fc.ul.pt 
Room: 8.03.04 
Academic Degree and field of specialization: 

MSc in Marine Sciences

Scientific Informations

ORCID: https://orcid.org/ 0000-0003-2828-8766

Research Gate: https://www.researchgate.net/profile/Alexandra-Hurduc

Google Scholar: https://scholar.google.com/citations?user=oY6fTwsAAAAJ&hl=pt-PT&oi=ao


Scientific Interests

Main Interests: 

Remote sensing, land surface temperature, temporal and spatial variability of urban heat islands.

Top 10 Publications: 

Lima, M. M., Hurduc, A., Ramos, A. M., & Trigo, R. M. (2021). The Increasing Frequency of Tropical Cyclones in the Northeastern Atlantic sector. Frontiers in Earth Science, 1040.

Pinto, M. M., DaCamara, C. C., Hurduc, A., Trigo, R. M., & Trigo, I. F. (2020). Enhancing the fire weather index with atmospheric instability information. Environmental Research Letters15(9), 0940b7.

 

Books & Chapters (up to 10): 

DaCamara, C. C., Libonati, R., Pinto, M. M., & Hurduc, A. (2019). Near-and Middle-Infrared Monitoring of Burned Areas from Space. In Satellite Information Classification and Interpretation. IntechOpen.

Pinto, M. M., Hurduc, A., Trigo, R. M., Trigo, I. F., & DaCamara, C. C. (2018). The extreme weather conditions behind the destructive fires of June and October 2017 in Portugal. Parte: http://hdl. handle. net/10316.2/44517.

Conferences (last 15 presentations): 

Hurduc, A., Ermida, S. L., DaCamara, C., & Trigo, I. (2019, September). Link between Several Land Surface Variables Disseminated By the LSA SAF. In 2019 Joint Satellite Conference. AMS.

Hurduc, A., Ermida, S., Trigo, I., & DaCamara, C. (2019, January). Assessing consistency among Land Surface Temperature and other land surface parameters disseminated by the LSA SAF. In Geophysical Research Abstracts (Vol. 21).

Pinto, M. M., Hurduc, A., DaCamara, C. C., Trigo, I. F., & Trigo, R. M. (2019, January). Burned Areas Segmentation with Convolutional Neural Networks. In Geophysical Research Abstracts (Vol. 21).