Parth Naik successfully defended his PhD Thesis on “Advanced Techniques For Prediction of Forest Above Ground Biomass Using Satellite Remote Sensing Data.” The thesis, co-supervised by Michele Dalponte and Lorenzo Bruzzone, was the results of a collaboration between the Fondazione Edmund Mach and the University of Trento.
Congratulations to Parth!
Announced the departure of the ESA’s spacecraft JUICE (Jupiter for ICy moon Explorer) from the Toulouse facilities to the Kourou base in French Guiana for launch in the second half of April.
RSLab achieved important research results in 2022 on both Earth Observation and Planetary Exploration and the related topics. Some relevant numbers are as follows:
The figure reports the cloud of words built with the titles of the 2022 journal papers. More details are available on this website.
We wish you a Happy 2023!
After the inclusion in the Highly Cited Researcher (HCR) by Clarivate Analytics for 2022, Lorenzo Bruzzone is at the top also of the Highly Cited Reasearchers ranking of the University of Stanford.
An analysis carried out by the University of Trento points out the very good results achieved by the university in this rankig and identifies prof. Bruzzone as the researcher at the University of Trento with the highest performance.
See here for more details.
Lorenzo Bruzzone has been recognized as a Highly Cited Researcher (HCR) by Clarivate Analytics for 2022.
Each year, Clarivate™ identifies the world’s most influential researchers ─ the select few who have been most frequently cited by their peers over the last decade. In 2022, fewer than 7,000, or about 0.1%, of the world’s researchers, in 21 research fields and across multiple fields, have earned this exclusive distinction.
Highly Cited Researchers have demonstrated significant and broad influence reflected in their publication of multiple highly cited papers over the last decade. These highly cited papers rank in the top 1% by citations for a field or fields and publication year in the Web of Science™. Of the world’s population of scientists and social scientists, Highly Cited Researchers™ are 1 in 1,000.
The full list of highly cited Reserachers is available here
See also the news of the Department of Information Engineering and Computer Science.
Congratulations to Giulio Weikmann (PhD student at RSLab) who got theMaster Thesis Award at the Consiglio Nazionale delle Ricerche – Istituto per il Rilevamento Elettromagnetico dell’Ambiente (CNR-IREA) and Associazione Italiana Telerilevamento (AIT) held in Bologna (Italy) for the thesis “A Recurrent Deep Learning Model for Large Scale Crop Type Mapping using Time Series of Sentinel-2 Images”.
More info: Vincitori del premio tesi di laurea “Eugenio Zilioli”, 17° Edizione (cnr.it)
In July, August, and September 2022 hyperspectral, multispectral and thermal data were acquired in the two vineyards in region of Riva del Garda. These data will be used to investigate the usefulness of the MCAPEFA camera in the early detection of Flavescence dorée. Flavescence dorée is a grapevine trunk disease, which rate of spreading across vineyards in the Trentino region is increasing.
ESA Envision mission (in which RSLab has the leadership of the Subsurface Radar Sounder) is currently in B1 study phase. Among the different activities in progress, specific attention is focused on the aerobreaking phase around Venus, in which the spacecraft will need to lower its orbit with thousand of passages through the planet’s atmosphere for up to two years. More details on the aerobreaking are given in the articles below.
Image credit: ESA
Elisa Sbalchiero was awarded with the second place (out of more than 220 candidates) at the 2022 Student Prize Paper Comeptition at the very prestigious 2022 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) held in Kuala Lumpur (Malesia) for the paper “A method for focusing raw simulated radar sounder data”, co-authored with Dr. Sanchari Thakur and Prof. Lorenzo Bruzzone.
Congratulations!
The H2020 ExtremeEarth project has concluded successfully, developing artificial intelligence techniques for the automatic analysis of remote sensing images. In the project RSLab had the leadership in the design and development of deep learning architectures for the Food Security use case.
