In the early 2000s, the German Aerospace Agency (DLR) was developing innovative hyperspectral optical sensors in preparation for future space missions. To this end, it involved the scientific community by launching an "idea contest" for researchers (see this heritage publication). The object of the competition was the identification of sites on which to carry out "test" acquisitions with prototypes of sensors mounted on an aerial platform. The request obviously had to be justified with the intended use of the data, and with the characteristics of the observed area in relation to the applications of the future space mission.

Prof. Paolo Gamba, coordinator of the Remote Sensing Group at our university, prepared a proposal entitled "Hyperspectral data exploitation for urban land cover analysis”. The proposal was one of the 8 selected out of the 22 received by the German Agency. On 8th July, 2002, a DLR aircraft equipped with two hyperspectral sensor prototypes flew over the city of Pavia and over the Cravino Campus carrying out the acquisition of data on two different urban environments, namely the city center and university facilities. Over the years, these data sets have become a reference point for the international satellite remote sensing community; see the “GRSS Data and Algorithm Standard Evaluation website” portal of the IEEE.

Recently, however, the “Cravino” hyperspectral dataset has taken an extra step: Mathworks, the company that maintains and distributes the famous scientific computation software MATLAB, has decided to use them in their tutorials on the new "hyperspectral toolbox"!

If you wish to see the Cravino Campus as it appeared in 2002 to a hyperspectral sensor, you can look at the MATLAB tutorial pages:

Once again the city of Pavia rises to the chronicles of international remote sensing scientific arena, after appearing in the communication of the European Space Agency regarding the "take-off" of the European satellite Sentinel-2.

The LoRa technology was developed to enable low-power, high-range wireless sensor transmission. Two recent papers from the research group at the TLC&RS lab [1,2] have shown that a simple RSSI-based method can be used for localizing LoRa IoT sensors. Article [1] has been one of the most read paper of the Wiley Internet Technology Letters in 2018-2019, and recently the dataset used in this work has been included in the 2020 GitHub Archive Program. Details of the two papers follow. 

[1] E. Goldoni, L. Prando, A. Vizziello, P. Savazzi, P. Gamba, “Experimental data set analysis of RSSI‐based indoor and outdoor localization in LoRa networks,” Wiley Internet Technology Letters, 24 September 2018,
[2] Pietro Savazzi, Emanuele Goldoni, Anna Vizziello, Lorenzo Favalli, Paolo Gamba, “A Wiener-based RSSI localization algorithm exploiting modulation diversity in LoRa networks,” IEEE Sensors Journal, August 2019, DOI: 10.1109/JSEN.2019.2936764
GitHub Archive Program link:

Prof. Paolo Gamba attends the IEEE MTT-S Administrative Committee (AdCom) meeting in Bruges (Belgium) to sign the Sister Agreement between MTT-S and GRSS. As GRSS President, he fostered the connection among GRSS and other IEEE Societies, and GRSS is going to sign another Agreement with the Antenna and Propagation Society (AP-S) before the end of the year. GRSS is very keen to work together with other communities within and outside IEEE to develop common initiatives.

On Wed. 22nd July 2020 a webinar will take place to present Leonardo Company and the opportunities of masters thesis offered to masters students of Electronics Engineering.


This is the planned agenda:

10:45 - 11:00: Presentation of the company Leonardo s.p.a.

11:00 - 11:30: Presentation of avionic/space products

11:30 - 11:45: Presentation of available thesis topics (Nerviano site, near Milan)

11:45 - 12:00: Q&A


The link to connect to the webinar is reported below:

TEAMS room

Prof. Paolo Gamba is going to deliver an invited lecture at the Istituto di Fisica Applicata of CNR in Florence on this coming Thursday, Oct. 26. The seminar is devoted to explain why the use of multiple sensors is mandatory in urban areas, at multiple spatial and geographical scales. It will also provide a few results or urban area extent characterization at the regional/national level for different urban areas in the world, considering fusion of Sentinel-1 (SAR) and Sentinel-2 (multispectral) data, as well as Sentinel-1 (SAR) and Night-time lights data.