In Finger et al. (2022), we created consistent three-dimensional models in terms of temperature, density and composition of the upper mantle of the cratonic part of the African continent by combining seismic [Celli et al., 2020] and gravity [Förste et al., 2014] data with mineral physics constraints in an iterative integrated inversion approach [Kaban et al., 2014; Tesauro et al., 2014]. Further, we calculated a new model of depth to the Moho to correct the gravity field for crustal effects and calculate the residual topography, and provide an update for the average crystalline crust density from Litho1.0 [Pasyanos et al., 2014]. To calculate depth to the Moho, data from the GSC [Global Seismic Catalog, Mooney, 2015 with updates up to 2019] were combined with those published by Globig et al. [2016]. Here, we share data used from the GSC, final models of the upper mantle and crust that are discussed in the article, as well as the test cases set up in the uncertainty assessment. The upper mantle models are given in six layers centered at 50, 100, 150, 200, 250 and 300 km. In addition, density variations determined for the crust are given in an additional layer at 15 km depth. All fields range from -40.5°N to 40.5°N and -20.5°E to 55.5°E with a 1° by 1° lateral resolution. The data is provided in binary format as three netCDF4 files, containing the final results discussed in the paper ("Results_AF"), and the two uncertainty assessment cases for an upwards/downwards shifted Moho ("Results_AF_Moho_up" / "Results_AF_Moho_down"), respectively. In addition, data extracted from "Results_AF" to create the six profiles shown in the main article, and measurements of depth to Moho from the GSC are provided as ASCII formatted .dat files.
Here we present a photogrammetric dataset on the 2018-2019 eruption episode at Shiveluch Volcano, one of the most active volcanoes in Kamchatka Peninsula. The data were acquired by optical sensors and complemented by thermal sensors. The optical satellite images were tri-stereo panchromatic 1-m resolution imagery acquired on 18 July 2018 with Pléiades satellite PHR1B sensor. We processed the data in Erdas Imagine 2015 v15.1. For the relative orientation of the images, 37 tie points were calculated automatically with further manual correction, and for the interior and exterior orientation, Rational Polynomial Coefficients block adjustment, which is a transformation between pixels to latitude, longitude, and height information, was automatically employed. After the image orientation, we obtained a photogrammetric model with a total root mean square error (RMSE) of 0.2 m. By using the Enhanced Automatic Terrain Extraction module (eATE) with normalized cross correlation algorithm as implemented in the Erdas Imagine software, we were able to extract a 2 m resolution point cloud (PC) referenced to the WGS84 coordinate system UTM57 zone. This PC was filtered with the CloudCompare v2.9.1 noise filter and then manually cleaned with the CloudCompare segmentation tool. As strong volcanic steam emissions caused a large gap in the PC at the NE part of the dome, we used a 5 m resolution DEM constructed from TanDEM-X data to fill the gap and obtain the missing topography.
TanDEM-X is a bistatic SAR mission, formed by adding a second, almost identical spacecraft, to TerraSAR-X. Therefore, it allows the acquisition of two simultaneous SAR imageries over the same area, eliminating possible temporal decorrelations between them and maintaining a normal baseline between 250 and 500 m, which is suitable for SAR interferometry for DEM generation. We used the interferometric module in ENVI SARscape to build the interferogram, perform the unwrapping step and finally convert it into height information using forward transformation from radar to geographic coordinates. The RMSE of the generated DEM is evaluated based on the coherence value, i.e. quality of the interferogram, and is estimated to be approximately 5 m.
In Finger et al. (2021), we created consistent three dimensional models in terms of temperature, density and composition of the upper mantle of the cratonic South American Platform ("Upper MAntle Model") by combining seismic (Celli et al., 2020, Schaeffer & Lebedev, 2013) and gravity (Förste et al., 2014) data with mineral physics constraints in an iterative integrated inversion approach (Kaban et al., 2014; Tesauro et al., 2014). We further compiled a new crustal model ("Crustal Model"), including sediment and average crustal density and depth to the Moho to correct the gravity field for crustal effects and calculate the residual topography. To obtain these models we used data from the GSC (Global Seismic Catalog, Mooney, 2015 with updates up to 2019). To calculate depth to the Moho, the GSC data were combined with those published by Rivadeneyra-Vera et al. (2019). Here, we share the initial and final models of the upper mantle, sediment density and crust that are discussed in the article as well as the test cases set up in the uncertainty assessment. The upper mantle models are given in six layers centered at 50, 100, 150, 200, 250 and 300 km. All models range from -60.5°N to 15.5°N and -90.5°E to -29.5°E, except for the sediment density model (-59.5°N to 24.5°N and -99.5°E to -25.5°E) with a 1° by 1° lateral resolution. A detailed description of the respective files is given in each subfolder. All data are in ASCII format.