The JUpiter ICy moons Explorer (JUICE) of ESA was launched on 14 April 2023 and will arrive at Jupiter and its moons in July 2031. In this review article, we describe how JUICE will investigate the interior of the three icy Galilean moons, Ganymede, Callisto and Europa, during its Jupiter orbital tour and the final orbital phase around Ganymede. Detailed geophysical observations about the interior of the moons can only be performed from close distances to the moons, and best estimates of signatures of the interior, such as an induced magnetic field, tides and rotation variations, and radar reflections, will be obtained during flybys of the moons with altitudes of about 1000 km or less and during the Ganymede orbital phase at an average altitude of 490 km. The 9-month long orbital phase around Ganymede, the first of its kind around another moon than our Moon, will allow an unprecedented and detailed insight into the moon’s interior, from the central regions where a magnetic field is generated to the internal ocean and outer ice shell. Multiple flybys of Callisto will clarify the differences in evolution compared to Ganymede and will provide key constraints on the origin and evolution of the Jupiter system. JUICE will visit Europa only during two close flybys and the geophysical investigations will focus on selected areas of the ice shell. A prime goal of JUICE is the characterisation of the ice shell and ocean of the Galilean moons, and we here specifically emphasise the synergistic aspects of the different geophysical investigations, showing how different instruments will work together to probe the hydrosphere. We also describe how synergies between JUICE instruments will contribute to the assessment of the deep interior of the moons, their internal differentiation, dynamics and evolution. In situ measurements and remote sensing observations will support the geophysical instruments to achieve these goals, but will also, together with subsurface radar sounding, provide information about tectonics, potential plumes, and the composition of the surface, which will help understanding the composition of the interior, the structure of the ice shell, and exchange processes between ocean, ice and surface. Accurate tracking of the JUICE spacecraft all along the mission will strongly improve our knowledge of the changing orbital motions of the moons and will provide additional insight into the dissipative processes in the Jupiter system. Finally, we present an overview of how the geophysical investigations will be performed and describe the operational synergies and challenges.

Many research and industrial communities are betting on LoRa to provide reliable, long-range communication for the Internet of Things. This new radio technology, however, provides widely heterogeneous coverage; a LoRa link may span hundreds of meters or tens of kilometers, depending on the surrounding environment. This high variability is not captured by popular channel models for LoRa, and on-site measurementsÐa common alternativeÐare impractical due to the large geographical areas involved. We propose a novel, automated approach to estimate the coverage of LoRa gateways prior to deployment and without on-site measurements. We achieve this goal by combining free, readily-available multispectral images from remote sensing with the right channel model. Our processing toolchain automatically classifies the type of environment (e.g., buildings, trees, or open fields) traversed by a link, with high accuracy (>90%) and spatial resolution (10×10m²). We use this information to explain the attenuation observed in experiments. As signal attenuation is not well captured by popular channel models, we focus on the Okumura-Hata empirical model, hitherto largely unexplored for LoRa, and show that i) it yields estimates very close to our observations, and ii) we can use our toolchain to automatically select and configure its parameters. A validation on 8,000+ samples from a real dataset shows that our automated approach predicts the expected signal power within a ∼10dBm error, against the 20ś40dBm of popular channel models.