Characterization and verification of the Rita payload hyperspectral imager in Alainsat-1, as part of the 2nd IEEE GRSS student grand challenge

• Published in: IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
• Main Authors: Contreras Benito, Luis Juan, Gonga i Siles, Amadeu, Crisan, Ieremia, Pérez Portero, Adrián, Garcia Morilla, Alejandro, Gràcia i Solà, Guillem, Ramos Castro, Juan José, Jallad, Abdul-Halim, Camps Carmona, Adriano José
• Other Authors: Universitat Politècnica de Catalunya. Doctorat en Ciència i Tecnologia Aeroespacials, Universitat Politècnica de Catalunya. Doctorat en Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica, Universitat Politècnica de Catalunya. IEB - Instrumentació Electrònica i Biomèdica, Universitat Politècnica de Catalunya. CommSensLab-UPC - Centre Específic de Recerca en Comunicació i Detecció UPC
• Format: Conference Object
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE) 2023
• Subjects: Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços; Artificial satellites in earth sciences; CubeSat; Hyperspectral camera; Earth observation; Educational; Satèl·lits artificials en ciències de la terra; Sea ice
• Online Access: http://hdl.handle.net/2117/401764; https://doi.org/10.1109/IGARSS52108.2023.10282956

The Remote sensing and Interference detector with radiome-Try and vegetation Analysis (RITA Payload) [1] is a development of the UPC NanoSat Lab, aimed at Earth Observation (EO). It is one of the winners of the Second IEEE GRSS Student Grand Challenge, and will fly on-board AlainSat-1, a 3U CubeSat developed by the National Space Science and Technology Center (NSSTC) of the United Arab Emirates.RITA hosts three experiments. An L-band microwave radiometer (MWR) will gather data of soil moisture and sea ice thickness and concentration, aided with a Radio-frequency Interference (RFI) detection algorithm. A LoRa transceiver will perform on-demand execution of the EO experiments [2]. Finally, a Near-Infrared (NIR) Hyperspectral Camera will gather data for vegetation monitoring, agriculture applications, hydrology and coastal and inland waters mapping, among others [3].This work is focused on the calibration and validation of the Hyperspectral imager, at optical, electronic and spectral levels, as well as in the verification of its performance to measure Normalized Difference Vegetation Index (NDVI). This project is supported and funded by the IEEE Geoscience and Remote Sensing Society (GRSS), as one of the winners of the 2nd IEEE GRSS Student Grand Challenge. It is also part of the project ”GENESIS: GNSS Environmental and Societal Missions – Subproject UPC”, Grant PID2021-126436OB-C21 funded by the Ministerio de Ciencia e Investigación (MCIN) / Agencia Estatal de Investigación (AEI) / 10.13039/501100011033 and EU FEDER “Una manera de hacer Europa. Peer Reviewed Postprint (author's final draft)