Thermal monitoring of Lascar Volcano, Chile, using infrared data from the along-track scanning radiometer: a 1992-1995 time series

1997 ◽  
Vol 58 (7) ◽  
pp. 566-579 ◽  
Author(s):  
M. J. Wooster ◽  
D. A. Rothery
Keyword(s):  
Time Series ◽  
Thermal Monitoring ◽  
Along Track ◽  
Lascar Volcano ◽  
Infrared Data

Large-scale, high-resolution maps of interseismic strain accumulation from Sentinel-1, and incorporation of along-track measurements

2021 ◽  
Author(s):  
Andy Hooper ◽  
Pawan Piromthong ◽  
Tim Wright ◽  
Jonathan Weiss ◽  
Milan Milan Lazecky ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Velocity Field ◽  
Reference Frame ◽  
Line Of Sight ◽  
Tectonic Deformation ◽  
Low Resolution ◽  
Gnss Measurements ◽  
Along Track ◽  
East West

<p>High-resolution geodetic measurements of crustal deformation from InSAR have the potential to provide crucial constraints on a region’s tectonics, geodynamics and seismic hazard. Here, we present a high-resolution crustal velocity field for the Alpine-Himalayan Seismic Belt (AHSB) derived from Sentinel-1 InSAR and GNSS. We create time series and average velocities from ~220,000 interferograms covering an area of 15 million km<sup>2</sup>, with an average of 170 acquisitions per measurement point. We tie the velocities to a Eurasian reference frame by jointly inverting the InSAR data with GNSS data to produce a low-resolution model of 3D surface velocities. We then use the referenced InSAR velocities to invert for high-resolution east-west and sub-vertical velocity fields for the entire region. The sub-vertical velocities, which also include a small component of north-south motion, are dominated by non-tectonic deformation, such as subsidence due to water extraction. The east-west velocity field, however, reveals the tectonics of the AHSB with an unprecedented level of detail.</p><p>The approach described above only provides good constraints on horizontal displacement in the east-west direction, with the north-south component provided by low-resolution GNSS measurements. Sentinel-1 does also have the potential to provide measurements that are sensitive to north-south motion, through exploitation of the burst overlap areas produced by the TOPS acquisition mode. These along-track measurements have lower precision than line-of-sight InSAR and are more effected by ionospheric noise, but have the advantage of being almost insensitive to tropospheric noise. We present a time series approach to tease out the subtle along-track signals associated with interseismic strain. Our approach includes improvements to the mitigation of ionospheric noise and we also investigate different filtering approaches to optimize the reduction of decorrelation noise. In contrast to the relative measurements of line-of-sight InSAR, these along-track measurements are automatically provided in a global reference frame. We present results from five years of data for the West-Lut Fault in eastern Iran and the Chaman Fault in Pakistan and Afghanistan. Our results agree well with independent GNSS measurements; however, the denser coverage of the technique allows us to also detect the variation in slip rate along the faults.</p><p>Finally, we demonstrate the improvement in the resolution of horizontal strain rates when including these along-track measurements, in addition to the conventional line-of-sight InSAR measurements.</p>

scholarly journals Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

2018 ◽  
Vol 18 (3) ◽  
pp. 1573-1592 ◽  
Author(s):  
Gerrit de Leeuw ◽  
Larisa Sogacheva ◽  
Edith Rodriguez ◽  
Konstantinos Kourtidis ◽  
Aristeidis K. Georgoulias ◽  
...  
Keyword(s):  
Time Series ◽  
European Space Agency ◽  
Mainland China ◽  
Satellite Observations ◽  
Data Sets ◽  
Data Set ◽  
Modis Aod ◽  
The Difference ◽  
Along Track ◽  
Aerosol Properties

Abstract. The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth – AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995–2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the Envisat period in 2012, showing decreasing AOD.

scholarly journals GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS

2016 ◽  
Vol XLI-B8 ◽  
pp. 489-494 ◽  
Author(s):  
Luc Girod ◽  
Christopher Nuth ◽  
Andreas Kääb
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Volume Change ◽  
Thermal Emission ◽  
Aster Data ◽  
Rational Polynomial ◽  
The Cross ◽  
Cross Track ◽  
Along Track

Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic stereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo sensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long consistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here, we developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and software suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection and correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of approximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor modeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes. <br><br> As a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time series of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and accounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track component of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus contaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the latter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the DEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner and spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s AST14DMO DEM standard products. <br><br> The quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume change time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate change and their influence on runoff and sea level.

scholarly journals GLACIER VOLUME CHANGE ESTIMATION USING TIME SERIES OF IMPROVED ASTER DEMS

2016 ◽  
Vol XLI-B8 ◽  
pp. 489-494
Author(s):  
Luc Girod ◽  
Christopher Nuth ◽  
Andreas Kääb
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Volume Change ◽  
Thermal Emission ◽  
Aster Data ◽  
Rational Polynomial ◽  
The Cross ◽  
Cross Track ◽  
Along Track

Volume change data is critical to the understanding of glacier response to climate change. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system embarked on the Terra (EOS AM-1) satellite has been a unique source of systematic stereoscopic images covering the whole globe at 15m resolution and at a consistent quality for over 15 years. While satellite stereo sensors with significantly improved radiometric and spatial resolution are available to date, the potential of ASTER data lies in its long consistent time series that is unrivaled, though not fully exploited for change analysis due to lack of data accuracy and precision. Here, we developed an improved method for ASTER DEM generation and implemented it in the open source photogrammetric library and software suite MicMac. The method relies on the computation of a rational polynomial coefficients (RPC) model and the detection and correction of cross-track sensor jitter in order to compute DEMs. ASTER data are strongly affected by attitude jitter, mainly of approximately 4 km and 30 km wavelength, and improving the generation of ASTER DEMs requires removal of this effect. Our sensor modeling does not require ground control points and allows thus potentially for the automatic processing of large data volumes. <br><br> As a proof of concept, we chose a set of glaciers with reference DEMs available to assess the quality of our measurements. We use time series of ASTER scenes from which we extracted DEMs with a ground sampling distance of 15m. Our method directly measures and accounts for the cross-track component of jitter so that the resulting DEMs are not contaminated by this process. Since the along-track component of jitter has the same direction as the stereo parallaxes, the two cannot be separated and the elevations extracted are thus contaminated by along-track jitter. Initial tests reveal no clear relation between the cross-track and along-track components so that the latter seems not to be easily modeled analytically from the first one. We thus remove the remaining along-track jitter effects in the DEMs statistically through temporal DEM stacks to finally compute the glacier volume changes over time. Our method yields cleaner and spatially more complete elevation data, which also proved to be more in accordance to reference DEMs, compared to NASA’s AST14DMO DEM standard products. <br><br> The quality of the demonstrated measurements promises to further unlock the underused potential of ASTER DEMs for glacier volume change time series on a global scale. The data produced by our method will help to better understand the response of glaciers to climate change and their influence on runoff and sea level.

scholarly journals High frequency variations in Earth rotation

1988 ◽  
Vol 128 ◽  
pp. 181-186 ◽  
Author(s):  
W. E. Carter ◽  
D. S. Robertson ◽  
F. W. Fallon
Keyword(s):  
Time Series ◽  
Earth Orientation ◽  
Continuous Coverage ◽  
Standard Product ◽  
Orientation Time ◽  
Monitoring Service ◽  
Cross Track ◽  
Along Track ◽  
Frequency Variations ◽  
Nearly Continuous

The combined POLARIS-IRIS Earth orientation time series now span nearly a full cycle of the Chandler-annual beat period, beginning in late 1980. Since April 1985 there is also a nearly continuous coverage of UT1 at daily intervals. We have fit a simple model, consisting of circular 14-month and annual components and a linear drift to the polar motion series, then computed the “along-track” and “cross-track” residuals. Both sets of residuals display structure with amplitudes of tens of milliseconds of arc on time scales of months, but Fourier analysis reveals no significant peaks at shorter periods, including the 40-60 day period found in the UT1 time series.During September, 1986, we introduced a new “quick-look” UT1 time series. The values are typically available within 7 days. The accuracy, which depends strongly on the accuracy of the X and Y pole coordinates used in the computations, ranged from 0.3 to 0.7 milliseconds during the first two weeks, but improved to about 0.1 milliseconds during the latter two weeks of the month. We plan to continue the quick-look UT1 series as a standard product of the IRIS Earth orientation monitoring service.

scholarly journals A comparison of methods to estimate vertical land motion trends from GNSS and altimetry at tide gauge stations

Ocean Science ◽  
2018 ◽  
Vol 14 (2) ◽  
pp. 187-204 ◽  
Author(s):  
Marcel Kleinherenbrink ◽  
Riccardo Riva ◽  
Thomas Frederikse
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Tide Gauge ◽  
Satellite System ◽  
Vertical Land Motion ◽  
Correlation Threshold ◽  
The Mean ◽  
Highly Correlated ◽  
Global Navigation Satellite ◽  
Along Track

Abstract. Tide gauge (TG) records are affected by vertical land motion (VLM), causing them to observe relative instead of geocentric sea level. VLM can be estimated from global navigation satellite system (GNSS) time series, but only a few TGs are equipped with a GNSS receiver. Hence, (multiple) neighboring GNSS stations can be used to estimate VLM at the TG. This study compares eight approaches to estimate VLM trends at 570 TG stations using GNSS by taking into account all GNSS trends with an uncertainty smaller than 1 mm yr−1 within 50 km. The range between the methods is comparable with the formal uncertainties of the GNSS trends. Taking the median of the surrounding GNSS trends shows the best agreement with differenced altimetry–tide gauge (ALT–TG) trends. An attempt is also made to improve VLM trends from ALT–TG time series. Only using highly correlated along-track altimetry and TG time series reduces the SD of ALT–TG time series by up to 10 %. As a result, there are spatially coherent changes in the trends, but the reduction in the root mean square (RMS) of differences between ALT–TG and GNSS trends is insignificant. However, setting correlation thresholds also acts like a filter to remove problematic TG time series. This results in sets of ALT–TG VLM trends at 344–663 TG locations, depending on the correlation threshold. Compared to other studies, we decrease the RMS of differences between GNSS and ALT–TG trends (from 1.47 to 1.22 mm yr−1), while we increase the number of locations (from 109 to 155), Depending on the methods the mean of differences between ALT–TG and GNSS trends vary between 0.1 and 0.2 mm yr−1. We reduce the mean of the differences by taking into account the effect of elastic deformation due to present-day mass redistribution. At varying ALT–TG correlation thresholds, we provide new sets of trends for 759 to 939 different TG stations. If both GNSS and ALT–TG trend estimates are available, we recommend using the GNSS trend estimates because residual ocean signals might correlate over long distances. However, if large discrepancies ( > 3 mm yr−1) between the two methods are present, local VLM differences between the TG and the GNSS station are likely the culprit and therefore it is better to take the ALT–TG trend estimate. GNSS estimates for which only a single GNSS station and no ALT–TG estimate are available might still require some inspection before they are used in sea level studies.

scholarly journals A comparison of data weighting methods to derive vertical land motion trends from GNSS and altimetry at tide gauge stations

2017 ◽  
Author(s):  
Marcel Kleinherenbrink ◽  
Riccardo Riva ◽  
Thomas Frederikse
Keyword(s):  
Time Series ◽  
Tide Gauge ◽  
Satellite System ◽  
Vertical Land Motion ◽  
Correlation Threshold ◽  
The Mean ◽  
Highly Correlated ◽  
Global Navigation Satellite ◽  
Along Track ◽  
Weighting Methods

Abstract. This study compares eight weighting techniques for Global Navigation Satellite System (GNSS)-derived Vertical Land Motion (VLM) trends at 570 tide gauge (TG) stations. The spread between the methods has a comparable size as the formal uncertainties of the GNSS trends. Taking the median of the surrounding GNSS trends shows the best agreement with differenced altimetry – tide gauge (ALT-TG) trends. An attempt is also made to improve VLM trends from ALT-TG time series. Only using highly correlated along-track altimetry and TG time series, reduces the standard deviation of ALT-TG time series up to 10 %. As a result, there are spatially coherent changes in the trends, but the reduction in the RMS of differences between ALT-TG and GNSS trends is insignificant. However, setting correlation thresholds also acts like a filter to remove problematic TG stations. This results in sets of ALT-TG VLM trends at 344–663 TG locations, depending on the correlation threshold. Compared to other studies, we decrease the RMS of differences between GNSS and ALT-TG trends (from 1.47 to 1.22 mm/yr), while we increase the number of locations (from 109 to 155), Depending on the weighting methods the mean of differences between ALT-TG and GNSS trends varies between 0.1–0.2 mm/yr. We reduce the mean of differences by taking into account the effect of elastic deformation due to present-day mass redistribution into account.

Sign in / Sign up

Export Citation Format

Share Document