Other language confidence: 0.8950787820322097
This dataset provides Near Realtime Orbits (NRT) from the Low Earth Orbiter (LEO) satellite TerraSAR-X. It is part of the compilation of GFZ NRT products for various LEO missions and the appropriate GNSS constellation in sp3 format. The individual solutions for each satellite mission are published with individual DOI as part of the compilation (Schreiner et al., 2022). The TerraSAR-X NRT cover the period - from 2007 264 to up-to-date The LEO NRTs in version 2 are generated based on the 30-hour GPS NRTs in two pieces for the actual day with arc lengths of 14 hours and overlaps of 2 hours. One starting at 22:00 and ending at 12:00, one starting at 10:00 and ending at 24:00. Due to the extended length of the constellation, there is no need to concatenate several constellations for day-overlapping arcs. The accuracy of the LEO NRTs is at the level of 1-2 cm in terms of SLR validation. Each solution in version 2 is given in the Conventional Terrestrial Reference System (CTS) based on the IERS 2010 conventions and related to the ITRF-2014 reference frame. The exact time covered by an arc is defined in the header of the files and indicated as well as in the filename.
Orbital products describe positions and velocities of satellites, be it the Global Navigation Satellite System (GNSS) satellites or Low Earth Orbiter (LEO) satellites. These orbital products can be divided into the fastest available ones, the Near Realtime Orbits (NRT, Zitat), which are mostly available within 15 to 60 minutes delay, followed by Rapid Science Orbit (RSO, Zitat) products with a latency of two days and finally the Precise Science Orbit (PSO) which, with a latency of up to a few weeks or longer in the case of reprocessing campaigns, are the most delayed. The absolute positional accuracy increases from NRT to PSO. This dataset compiles the PSO products for various LEO missions and GNSS constellation in sp3 format. GNSS Constellation: - GPS LEO Satellites: - ENVISAT - Jason-1 - Jason-2 - Jason-3 - Sentinel-3A - Sentinel-3B - Sentinel-6A - TOPEX Each solution follows specific requirements and parametrizations which are named in the respective processing metric table.
This dataset provides Rapid Science Orbits (RSO) from GNSS satellites. It is part of the compilation of GFZ RSO products for various LEO missions and the appropriate GNSS constellation in sp3 format. The individual solutions for each satellite mission are published with individual DOI as part of the compilation (Schreiner et al., 2022- Dach DOI). GNSS Constellation: GPS 30h The GPS RSOs of version 2 are 30-hour long arcs starting at 21:00 the day before and ending at 03:00 the day after. The accuracy of the GPS RSO sizes at the 3-cm level in terms of RMS values of residuals after Helmert transformation onto IGS combined orbit solutions. The GPS RSOs of version 2 cover the following period : - start date: June 2019 - end date: 30 June 2023
Multi-temporal landslide inventories are important information for the understanding of landslide dynamics and related predisposing and triggering factors, and thus a crucial prerequisite for probabilistic hazard and risk assessment. Despite the great importance of these inventories, they do not exist for many landslide prone regions in the world. In this context, the recently evolving global-scale availability of high temporal and spatial resolution optical satellite imagery (RapidEye, Sentinel-2A/B, planet) has opened up new opportunities for the creation of these multi-temporal inventories.To derive such multi-temporal landslide inventories, a semi-automated spatiotemporal landslide mapper was developed at the Remote Sensing Section of the GFZ Potsdam being capable of deriving post-failure landslide objects (polygons) from multi-sensor optical satellite time series data (Behling et al., 2016). The developed approach represents an extension of the original methodology (Behling et al., 2014, Behling and Roessner, 2020) and facilitates the integration of optical time series data acquired by different satellite systems. The goal of combining satellite data originating from variable sensor systems has been the establishment of longest possible time series for retrospective systematic assessment of multi-temporal landslide activity at highest possible temporal and spatial resolution. We applied the developed approach to a 2500 km² study area in Southern Kyrgyzstan using an optical satellite database acquired by the Landsat TM/ETM+, SPOT 1/5, IRS1-C LISSIII, ASTER, and RapidEye sensor systems covering a time period between 1986 and 2013. A multi-temporal landslide inventory from 2009-2013 derived from RapidEye satellite time series data is available as separate publications (Behling et al., 2014; Behling and Roessner, 2020).The resulting systematic multi-temporal landslide inventory being subject of this data publication is supplementary to the article of Behling et al. (2016), which describes the extended spatiotemporal landslide mapper in detail. This multi-sensor approach prioritizes most suitable images within the available multi-sensor satellite time series using parameters, such as spatial resolution, cloud coverage, similarity of sensor characteristics and seasonality related to vegetation characteristics with the goal of establishing a robust back-bone time series for initial detection of possible landslide objects. In a second step, this initial analysis gets more refined in order to achieve the best possible approximation of the date of landslide occurrence. For a more detailed description of the methodology of the extended spatiotemporal landslide mapper, please see Behling et al. (2016).In general, this landslide mapper detects landslide objects by analyzing temporal NDVI-based vegetation cover changes and relief-oriented parameters in a rule-based approach combining pixel- and object-based analysis. Typical landslide-related vegetation changes comprise abrupt disturbances of vegetation cover in the result of the actual failure as well as post-failure revegetation which usually happens at a slower pace compared to vegetation growth in the surrounding undisturbed areas, since the displaced landslide masses are susceptible to subsequent erosion and reactivation processes. The resulting landslide-specific temporal surface cover dynamics in form of temporal trajectories is used as input information to identify freshly occurred landslides and to separate them from other temporal variations in the surrounding vegetation cover (e.g., seasonal vegetation changes or changes due to agricultural activities) and from permanently non-vegetated areas (e.g., urban non-vegetated areas, water bodies, rock outcrops).The data are provided in vector format (polygons) in form of a standard shapefile contained in the zip-file 2020-002_Behling_et-al_2016_landslide_inventory_SouthernKyrgyzstan_1986_2013.zip and are described in more detail in the associated data description.
This dataset provides Rapid Science Orbits (RSO) from the Low Earth Orbiter (LEO) satellite GRACE-A. It is part of the compilation of GFZ RSO products for various LEO missions and the appropriate GNSS constellation in sp3 format. The individual solutions for each satellite mission are published with individual DOI as part of the compilation (Schreiner et al., 2022). • The GRACE RSO cover the period: - GRACE-A from 2004 200 to 2017 334 - GRACE-B from 2004 200 to 2017 245 (this DOI) The LEO RSOs in version 1 are generated based on the 24-hour GPS RSOs in two pieces for the actual day with arc lengths of 14 hours and overlaps of 2 hours. One starting at 22:00 and ending at 12:00, one starting at 10:00 and ending at 24:00. For day overlapping arcs two 24h GNSS constellations are concatenated. The accuracy of the LEO RSOs is at the level of 1-2 cm in terms of SLR validation. Each solution in version 1 is given in the Conventional Terrestrial Reference System (CTS) based on the IERS 2003 conventions and related to the ITRF-2008 reference frame. The exact time covered by an arc is defined in the header of the files and indicated as well as in the filename.
This dataset provides Rapid Science Orbits (RSO) from the Low Earth Orbiter (LEO) satellite GRACE-A. It is part of the compilation of GFZ RSO products for various LEO missions and the appropriate GNSS constellation in sp3 format. The individual solutions for each satellite mission are published with individual DOI as part of the compilation (Schreiner et al., 2022). • The GRACE RSO cover the period: - GRACE-A from 2004 200 to 2017 334 (this DOI) - GRACE-B from 2004 200 to 2017 245 The LEO RSOs in version 1 are generated based on the 24-hour GPS RSOs in two pieces for the actual day with arc lengths of 14 hours and overlaps of 2 hours. One starting at 22:00 and ending at 12:00, one starting at 10:00 and ending at 24:00. For day overlapping arcs two 24h GNSS constellations are concatenated. The accuracy of the LEO RSOs is at the level of 1-2 cm in terms of SLR validation. Each solution in version 1 is given in the Conventional Terrestrial Reference System (CTS) based on the IERS 2003 conventions and related to the ITRF-2008 reference frame. The exact time covered by an arc is defined in the header of the files and indicated as well as in the filename.
This dataset provides Rapid Science Orbits (RSO) from the Low Earth Orbiter (LEO) satellite TanDEM-X. It is part of the compilation of GFZ RSO products for various LEO missions and the appropriate GNSS constellation in sp3 format. The individual solutions for each satellite mission are published with individual DOI as part of the compilation (Schreiner et al., 2022). • The TanDEM-X RSO cover the period: o from 2010 173 to up-to-date The LEO RSOs in version 1 are generated based on the 24-hour GPS RSOs in two pieces for the actual day with arc lengths of 14 hours and overlaps of 2 hours. One starting at 22:00 and ending at 12:00, one starting at 10:00 and ending at 24:00. For day overlapping arcs two 24h GNSS constellations are concatenated. The accuracy of the LEO RSOs is at the level of 1-2 cm in terms of SLR validation. Each solution in version 1 is given in the Conventional Terrestrial Reference System (CTS) based on the IERS 2003 conventions and related to the ITRF-2008 reference frame. The exact time covered by an arc is defined in the header of the files and indicated as well as in the filename.
This dataset provides Rapid Science Orbits (RSO) from the Low Earth Orbiter (LEO) satellite TerraSAR-X. It is part of the compilation of GFZ RSO products for various LEO missions and the appropriate GNSS constellation in sp3 format. The individual solutions for each satellite mission are published with individual DOI as part of the compilation (Schreiner et al., 2022). • The TerraSAR-X RSO cover the period - from 2007 264 to up-to-date The LEO RSOs in version 1 are generated based on the 24-hour GPS RSOs in two pieces for the actual day with arc lengths of 14 hours and overlaps of 2 hours. One starting at 22:00 and ending at 12:00, one starting at 10:00 and ending at 24:00. For day overlapping arcs two 24h GNSS constellations are concatenated. The accuracy of the LEO RSOs is at the level of 1-2 cm in terms of SLR validation. Each solution in version 1 is given in the Conventional Terrestrial Reference System (CTS) based on the IERS 2003 conventions and related to the ITRF-2008 reference frame. The exact time covered by an arc is defined in the header of the files and indicated as well as in the filename.
This dataset provides Rapid Science Orbits (RSO) from the Low Earth Orbiter (LEO) satellite TanDEM-X. It is part of the compilation of GFZ RSO products for various LEO missions and the appropriate GNSS constellation in sp3 format. The individual solutions for each satellite mission are published with individual DOI as part of the compilation (Schreiner et al., 2022). • The TanDEM-X RSO cover the period: from 2010 173 to up-to-date The LEO RSOs in version 2 are generated based on the 30-hour GPS RSOs in two pieces for the actual day with arc lengths of 14 hours and overlaps of 2 hours. One starting at 22:00 and ending at 12:00, one starting at 10:00 and ending at 24:00. Due to the extended length of the constellation, there is no need to concatenate several constellations for day-overlapping arcs. The accuracy of the LEO RSOs is at the level of 1-2 cm in terms of SLR validation. Each solution in version 2 is given in the Conventional Terrestrial Reference System (CTS) based on the IERS 2010 conventions and related to the ITRF-2014 reference frame. The exact time covered by an arc is defined in the header of the files and indicated as well as in the filename.
This dataset provides Rapid Science Orbits (RSO) from the Low Earth Orbiter (LEO) satellite CHAMP. It is part of the compilation of GFZ RSO products for various LEO missions and the appropriate GNSS constellation in sp3 format. The individual solutions for each satellite mission are published with individual DOI as part of the compilation (Schreiner et al., 2022). • The CHAMP RSO cover the period from 2000 202 to 2010 247 The LEO RSOs in version 1 are generated based on the 24-hour GPS RSOs in two pieces for the actual day with arc lengths of 14 hours and overlaps of 2 hours. One starting at 22:00 and ending at 12:00, one starting at 10:00 and ending at 24:00. For day overlapping arcs two 24h GNSS constellations are concatenated. The accuracy of the LEO RSOs is at the level of 1-2 cm in terms of SLR validation. Each solution in version 1 is given in the Conventional Terrestrial Reference System (CTS) based on the IERS 2003 conventions and related to the ITRF-2008 reference frame. The exact time covered by an arc is defined in the header of the files and indicated as well as in the filename.
| Organisation | Count |
|---|---|
| Wissenschaft | 15 |
| Type | Count |
|---|---|
| unbekannt | 15 |
| License | Count |
|---|---|
| Offen | 15 |
| Language | Count |
|---|---|
| Englisch | 15 |
| Resource type | Count |
|---|---|
| Keine | 15 |
| Topic | Count |
|---|---|
| Boden | 15 |
| Lebewesen und Lebensräume | 1 |
| Luft | 15 |
| Mensch und Umwelt | 15 |
| Wasser | 1 |
| Weitere | 15 |