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Interferometric stacking is a useful technique to detect active slope deformation over vast mountainous area. Compared to the analysis of single interferograms, the stacking approach improves the signal to noise ratio and deformation signals become clearer. In this work, we used stacked interferograms to detect active slow-moving landslides during the years 2015 to 2019 over a 1200 km2 portion of the Northern Apennines of Italy. C-band Sentinel 1 SAR images were used to create short temporal baseline (6 to 24 days) interferograms which limit decorrelation and maximize the range of measurable displacement rates. Then we operated a further selection of interferograms based on coherence and visual inspection, before stacking over multiple time scales (1 month to years). The products of the analysis are ground displacement maps where the presence of residual noise is inversely proportional to the duration of the stack and the deformation signal is clearly recognized. Results show that only a small fraction of the mapped landslide deposits are experiencing deformation that can be detected by differential interferometry. In particular, we identified 118 InSAR deformation signals corresponding to ongoing gravitational slope deformations over the 9916 landslides mapped in the area. Active movements are mostly located on landslides that have undergone catastrophic reactivation in relatively recent times. Annual interferometric stacks proved better suited to detect active slope movements, while <15 % of our deformation signals can only be detected by inspecting monthly stacks. Active slow-moving landslides show variable displacement rates in monthly stacks. Periods of dormancy alternate to accelerations that may lead to actual catastrophic failures or, more often, determine finite periods of sustained slow movement before the displacement rates drop below the detection limit. We compared the evolutionary trends of the phenomena to the occurrence of rainfall events. For this purpose, we use the probability of landslide occurrence which is associated with a rainfall event based on a territorial alert threshold. Results show that, at increasing landslide occurrence probabilities, an increasing fraction of actively deforming landslides can be detected by InSAR. [ABSTRACT FROM AUTHOR]

Abstract: PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral instrument is an advanced hyperspectral sensor including a panchromatic camera at medium resolution. The instrument is the focus of the new Earth observation mission that a consortium of Italian companies has started developing under contract of Italian Space Agency. Key features of the instrument are the very high requirement for signal-to-noise and the high quality of data that have to be provided. To meet these demanding figures the optical system has been based on a high transmittance optical system, including a single mirror telescope and two prism spectrometers based on an innovative concept to minimize number of optical elements, while high performance detectors have been chosen for the photon detection. To provide the required data quality for the entire mission lifetime an accurate calibration unit (radiometric and spectral) will be included in the instrument optomechanical assembly. The thermo-mechanical design of the instrument is based on innovative concepts, considering that the use of prism spectrometers implies a tight control of temperature variations to guarantee the stability of all instrument features once in orbit. The presented paper describes the concepts and design principle of the optomechanical assembly of the instrument, at the present status of development. [Copyright &y& Elsevier]

The PRISMA satellite mission launched on March 22nd, 2019 is one of the latest spaceborne imaging spectroscopy mission for Earth Observation. The PRISMA satellite comprises a high-spectral resolution VNIR-SWIR imaging spectrometer and a panchromatic camera. In summer 2019, first operations during the commissioning phase were mainly devoted to acquisitions in specific areas for evaluating instrument functioning, in-flight performance, and mission data product accuracy. A field and airborne campaign was carried out over an agriculture area in Italy to collect in-situ multi-source spectroscopy measurements at different scales simultaneously with PRISMA. The spectral, radiometric and spatial performance of PRISMA Level 1 Top-Of-Atmosphere radiance (LTOA) product were analyzed. The in-situ surface reflectance measurements over different landcovers were propagated to LTOA using MODTRAN5 radiative transfer simulations and compared with satellite observations. Overall, this work offers a first quantitative evaluation about the PRISMA mission performance and imaging spectroscopy LTOA data product consistency. Our results show that the spectral smile is less than 5 nm, the average spectral resolution is 13 nm and 11 nm (VNIR and SWIR respectively) and it varies ±2 nm across track. The radiometric comparison between PRISMA and field/airborne spectroscopy shows a difference lower than 5% for NIR and SWIR, whereas it is included in the 2–7% range in the VIS. The estimated instrument signal to noise ratio (SNR) is ≈400–500 in the NIR and part of the SWIR (<1300 nm), lower SNR values were found at shorter (<700 nm) and longer wavelengths (>1600 nm). The VNIR-to-SWIR spatial co-registration error is below 8 m and the spatial resolution is 37.11 m and 38.38 m for VNIR and SWIR respectively. The results are in-line with the expectations and mission requirements and indicate that acquired images are suitable for further scientific applications. However, this first assessment is based on data from a rural area and this cannot be fully exhaustive. Further studies are needed to confirm the performance for other land cover types like snow, inland and coastal waters, deserts or urban areas. • The PRISMA mission is successfully operating and collecting data after the launch. • In-situ simultaneous field/airborne spectroscopy data were compared to PRISMA. • PRISMA spectral resolution is 13–11 nm (VNIR-SWIR), smile is lower of 5 nm. • A radiometric difference of 2–7% was observed between PRISMA and in-situ data. • VNIR-to-SWIR spatial co-registration error is lower of 8 m. [ABSTRACT FROM AUTHOR]