Abstract In 2014, the Geological Survey of Austria (GBA) published – in cooperation with further national institutions – an overview map on radionuclides in groundwater, rocks and stream sediments at a scale of 1:500 000 with explanatory notes. In the frame of this activity, the uranium, 228 Ra, 226 Ra, 222 Rn, 210 Pb and 210 Po analyses in groundwater studies made by the Austrian Agency for Health and Food Safety (AGES) and Environment Agency of Austria (Umweltbundesamt), as well as the uranium and thorium analyses of stream sediments of the GBA and whole-rock analyses from different sources, were evaluated statistically. Furthermore, the GBA’s comprehensive airborne radiometric data were exploited. The aim of this study was to work out typical spectra of the radionuclide content in the groundwater and aquifers of different geological settings. It appeared that the concentration of 222 Rn in groundwater depends significantly on the uranium content of the aquifer. In contrast to this, the other radionuclides in groundwater did not show a clear correlation with uranium and thorium in the subsurface geology. Concerning 228 Ra, 226 Ra, 210 Pb and 210 Po, the lack of relationship to the subsurface composition seems to be a result of the low concentrations in groundwater. With respect to uranium in groundwater, there is a mixed situation: on the one hand, high uranium concentrations in groundwater can be observed in the Alps in regions with uranium bearing orthogneisses. On the other hand, in sediment basins of NE Austria where the underlying geology contains little uranium. Whether this is caused by special geological features combined with the given low precipitation or by the extensive agriculture (uranium from phosphate fertilizer) is under examination. Concerning the threshold values of the radionuclides in groundwater (radiation), no exceedance could be observed. In spite of this, the concentration of the heavy metal uranium sometimes exceeded the threshold value of 15 µg l −1 : this is especially true for the regions mentioned above. In addition, an attempt was made to compare the Austrian values with data from neighbouring countries. It became clear that only a few published datasets exist that are comparable. Radon analyses of soil gas in the Czech Republic and Bavaria show the same geological patterns as the Austrian radon analyses of the groundwater. In addition, to enable the reader to compare the Austrian data with datasets from other countries, additional tables are included here for all types of data. They show the statistic distributions of different geological classes in a coordinated way. Supplementary material: An Austrian map and explanation notes showing the uranium content of the underground and radionuclides in ground water are available at https://doi.org/10.6084/m9.figshare.c.3780170

Abstract Thermal observations of volcanic activity when the volcano is partially covered by clouds or observed under a wide-scan angle are often removed from further analyses. In the event of a volcanic crisis, such a reduced set of data is not adequate. Even when the observation conditions are favourable, the full observation set is still required to provide decision-makers with quality information about the data. Automatic quality estimation and outlier detection was not estimated in the past. We propose to analytically define the uncertainty for individual observations based on the measurement circumstances. To additionally reduce the temporal noise of the radiant power ( RP ) time series we apply a Kalman Filter (KF). The KF is able to recursively analyse an unevenly sampled time series. Based on some proposed rules, it can also detect outliers. We apply the proposed methodology to the 2008–09 Etna eruption monitored by MODIS (Moderate Resolution Imaging Spectroradiometer). The analysis of the results shows that the topography has a greater influence on RP than previously considered.

Abstract Many volcanoes around the world are poorly monitored and new eruptions increase the need for rapid ground-based monitoring, which is not always available in a timely manner. Initial observations therefore are commonly provided by orbital remote sensing instruments at different temporal, spatial and wavelength scales. Even at well-monitored volcanoes, satellite data still play an important role. The ASTER (Advanced Spaceborne Thermal Emission Radiometer) orbital sensor provides moderately high spatial resolution images in multiple wavelength regions; however, because ASTER is a scheduled instrument, the data are not acquired over specific targets every orbit. Therefore, in an attempt to improve the temporal frequency of ASTER specifically for volcano observations and to have the images integrate synergistically with high temporal resolution data, the Urgent Request Protocol (URP) system was developed in 2004. Now integrated with both the AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) hotspot monitoring programmes, the URP acquires an average of 24 volcanic datasets every month and planned improvements will allow this number to increase in the future. New URP data are sent directly to investigators responding to the ongoing eruption, and the large archive is also being used for retrospective science and operational studies for future instruments. The URP Program has been very successful over the past decade and will continue until at least 2017 or as long as the ASTER sensor is operational. Several volcanic science examples are given here that highlight the various stages of the URP development. However, not all are strictly focused on effusive eruptions. Rather, these examples were chosen to demonstrate the wide range of applications, as well as the general usefulness of the higher resolution, multispectral data of ASTER.

Abstract Developments in spaceborne Earth Observation (EO) sensor technology over the last decade, combined with well-tested physical models and multispectral data-processing techniques developed from the early 1980s, have paved the way to the global monitoring of volcanoes by sensors of metric, decametric, kilometric and multi-kilometric spatial resolution. Such variable geometries provide for revisit intervals ranging from about monthly – at high-spatial resolution in Low-Earth Orbit – to less than 5 min – at low-spatial resolution, from geostationary platforms. There are currently about 20 spacecrafts available for carrying out 24/7 quantitative observations of volcanic unrest, at all resolutions and as close as possible to real-time. We show some successful examples of synergetic EO on volcanoes on three continents from 10 different payloads, automatically processed with three, end-to-end unsupervised procedures, on eight major eruptions and a lava lake between 2006 and 2014.

Abstract We present a novel method for interpreting time series of multispectral observations of volcanic eruptions. We show how existing models relating to radiance and area emplacement can be generalized into an integration-convolution of a Net Area Emplacement (NAE) function and a cooling function, assuming all surfaces follow the same cooling curve. The NAE describes the variation in the rate of emplacement of hot material with time and temperature, while the cooling function describes the cooling of a hot surface with time. Discretizing the integration-convolution equation yields an underdetermined matrix equation that we solve using second-order Tikhonov regularization to stabilize the solution. We test the inversion by modelling plausible NAE surfaces, calculating the radiances, adding noise and inverting for the original surface. Three or more spectral bands are required to capture the overall shape of the NAE, and recovering specific quantities is difficult. Single wavebands that yield flat kernels recover the total area emplacement curve (rate of increase of hot area – the integral of the NAE with respect to temperature) surprisingly well due to their property of conserving NAE, suggesting novel methods for calculating area emplacement rates (and effusion rates) from time series of satellite images and radiometer measurements.

Abstract Accurate and fast delivery of information about recent lava flows is important for near-real-time monitoring of eruptions. Here, we have characterized the October 2010 lava flow at Piton de la Fournaise using various InSAR datasets. We first produced a map of the area covered by the lava flow (i.e. Area lava =0.71–0.75 km 2 ) using the coherence of two syn-eruptive interferograms. Then we analysed two post-eruptive InSAR datasets (i.e. monostatic and bistatic data). The monostatic database provided us simultaneously with the displacement rates, lava thickness, volume and volume flux. We found that the lava flow was subsiding and moving eastward at maximum rates of 13±0.3 and 4±0.2 cm a −1 , respectively. Also, it had a mean thickness of Z mean =5.85 m, Vol DRE =1.77±0.75×10 6 m 3 (1σ) and MOR=1.25±0.53 m 3 s −1 . The bistatic database provided us only with the thickness and volume information (i.e. Z mean =6.00 m, Vol DRE =1.83±0.65×10 6 m 3 and MOR=1.29±0.46 m 3 s −1 ). Finally, we used a thermal remote sensing technique to verify the InSAR-derived measurements. Results show that the monostatic and bistatic datasets were both well within the range for the DRE volume obtained from MODIS data (2.44–4.40×10 6 m 3 ). Supplementary material: Tables A1 and A2 give satellite images used in this study. Table A3 gives the parameters used for the calculation of the effusion rates. The figures give the data processing of the post-eruptive radar images. These are available at https://doi.org/10.6084/m9.figshare.c.2213563

Abstract Subsurface coal-mine fires occur in many mining regions, especially where coal has been previously excavated by “room-and-pillar” mining methods. The surface above these fires heats up to produce a thermal anomaly. The shape of the temperature profile over the fire zone holds clues to the depth of the underground fire. We simulated an underground coal-mine fire in the laboratory by burying a hot glass tube in a sandbox. The thermal anomaly over the tube was recorded using a forward looking infrared radiometer (FLIR TM ) camera. Numerical modeling using finite-element techniques for various combinations of tube depth and tube temperature helped to empirically derive a depth-estimation function, called the linear anomaly surface transect (LAST) function. Comparisons of the results from the LAST function with the half-anomaly-width function for depth estimation developed by Panigrahi et al. ( 1995 ) showed that the LAST function gave more accurate results for shallow subsurface coal fires ranging in depth from a few centimeters to ∼10 m. for moderate-depth coal fires, ranging in depth from 10 m to 40 m, the depths estimated by the two functions were comparable.