Development of a land deformation model from InSAR: combination with heterogeneous geodetic measurements in the Latrobe Valley (Australia) test site

2020 ◽  
Author(s):  
Mick Filmer ◽  
Paul Johnston ◽  
Thomas Fuhrmann ◽  
Matt Garthwaite ◽  
Alex Woods
Keyword(s):  
Time Series ◽  
Reference Frame ◽  
Test Site ◽  
Temporal Variations ◽  
Local Deformation ◽  
Radar Interferometry ◽  
Deformation Model ◽  
Time And Space ◽  
Alos Palsar ◽  
Geodetic Measurements

<p>Deformation of the Earth’s surface affects the maintenance of geodetic infrastructure and its reference frame to support e.g., construction, mineral exploration, telecommunications, and environmental monitoring. As the land deforms, the 3D coordinates of each position will change within the reference frame. Monitoring these changes is particularly challenging for local deformation occurring between GNSS continuously operating reference stations (CORS), as it is not directly measured. Hence, a deformation model to correct for this deformation is required, using radar interferometry (InSAR) to measure localised deformation occurring between the sparse GNSS CORS. The Australian Intergovernmental Committee for Surveying and Mapping’s (ICSM’s) Permanent Committee on Geodesy has recently identified the need for such a deformation model, leading to a project to develop a prototype deformation model combining radar interferometry with other geodetic measurements.</p><p>We present the first stage of this project where these data are analysed in the Latrobe Valley study area (south east Australia), where we have used 2.7 years (2015-2018) of Sentinel-1 and ~4 years (19 scenes; 2007-2011) of ALOS PALSAR SAR data to provide estimates of line of sight (LOS) velocity and uncertainties. Time series from five local GNSS CORS have been reprocessed in a consistent reference frame (ITRF2014) giving 3D velocities and uncertainties to which the InSAR time series are referenced. The InSAR rates are converted from LOS to vertical within the ITRF2014 reference frame so that the results are comparable to other geodetic measurements. Repeat levelling measurements from 1980 and 2015 and periodic (non-continuous) GNSS measurements were included for 2015.9 - 2018.5, which provided complementary information to constrain the rates in the study area in both time and space. We test methods to combine these data that relate to different time periods, spatial location, temporal and spatial frequency. We find that all of the data contribute to our understanding of deformation in the Latrobe Valley:  GNSS data shows temporal variations at specific sites, InSAR gives information about the spatial variation in deformation, periodic GNSS provides information at additional spatial locations but at limited points in time, and levelling extends the time series several decades into the past. Subsidence rates approaching 30 mm/yr are found near an open cut mining pit, but the deformation is non-linear in time and space across the study area, adding to the challenge of modelling the deformation where the geodetic observations are sparse. An important outcome of the project is to determine which types of observations best constrain the deformation model and how much new data is required.</p>

scholarly journals Landslides detection in Bat Xat district, Lao Cai province, Vietnam using the Alos PalSAR time-series imagery by the SBAS method

2020 ◽  
Vol 61 (4) ◽  
pp. 1-10
Author(s):  
Anh Van Tran ◽  
Binh An Nguyen ◽  
Tien Dinh ◽  
Yen Hai Thi Nguyen ◽  
Nghi Thanh Le ◽  
...  
Keyword(s):  
Time Series ◽  
Mineral Resources ◽  
Radar Interferometry ◽  
Alos Palsar ◽  
Aerial Photos ◽  
Radar Images ◽  
Multi Temporal ◽  
Lao Cai

Radar Interferometry (InSAR) has been known as a technology to monitor the change of elements on the earth's surface for many years. There are many InSAR methods, in which the permanent scattering InSAR Radar (PSInSAR) method uses a series of images to determine the terrain deformetions quite well. However, for areas with lots of vegetation, the number of permanent scattering points (PS points) will be limited. In this paper, we have chosen a method that also uses a set of multi-temporal Radar images but has the lowest spatial and temporal image baselines, this method is called the Small Baselines method (SBAS). With the ALOS PalSAR images series that was collected from August 2007 to November 2010, many landslide points in the area of Bat Xat district, Lao Cai province were discovered. The landslide locations detected from Radar images were compared with the landslide surveying points and landslide interpreted by aerial photos in 2013 provided by Vietnam Institute of Geosciences and Mineral Resources Vietnam. There have been many sliding sites coinsiding with the surveyed landslides, which proves that many landslides exist and develop continuously such as the location of Mong Sen bridge, Trung Chai Commune or at Sai Duan bridge, Phin Ngan commune.

scholarly journals Constructing Adaptive Deformation Models for Estimating DEM Error in SBAS-InSAR Based on Hypothesis Testing

2021 ◽  
Vol 13 (10) ◽  
pp. 2006
Author(s):  
Jun Hu ◽  
Qiaoqiao Ge ◽  
Jihong Liu ◽  
Wenyan Yang ◽  
Zhigui Du ◽  
...  
Keyword(s):  
Time Series ◽  
Hypothesis Testing ◽  
Surface Deformation ◽  
A Priori ◽  
Least Square ◽  
Deformation Model ◽  
Phase Time ◽  
Testing Theory ◽  
Sbas Insar ◽  
Deformation Models

The Interferometric Synthetic Aperture Radar (InSAR) technique has been widely used to obtain the ground surface deformation of geohazards (e.g., mining subsidence and landslides). As one of the inherent errors in the interferometric phase, the digital elevation model (DEM) error is usually estimated with the help of an a priori deformation model. However, it is difficult to determine an a priori deformation model that can fit the deformation time series well, leading to possible bias in the estimation of DEM error and the deformation time series. In this paper, we propose a method that can construct an adaptive deformation model, based on a set of predefined functions and the hypothesis testing theory in the framework of the small baseline subset InSAR (SBAS-InSAR) method. Since it is difficult to fit the deformation time series over a long time span by using only one function, the phase time series is first divided into several groups with overlapping regions. In each group, the hypothesis testing theory is employed to adaptively select the optimal deformation model from the predefined functions. The parameters of adaptive deformation models and the DEM error can be modeled with the phase time series and solved by a least square method. Simulations and real data experiments in the Pingchuan mining area, Gaunsu Province, China, demonstrate that, compared to the state-of-the-art deformation modeling strategy (e.g., the linear deformation model and the function group deformation model), the proposed method can significantly improve the accuracy of DEM error estimation and can benefit the estimation of deformation time series.

scholarly journals An Analysis of Vertical Crustal Movements along the European Coast from Satellite Altimetry, Tide Gauge, GNSS and Radar Interferometry

2021 ◽  
Vol 13 (11) ◽  
pp. 2173
Author(s):  
Kamil Kowalczyk ◽  
Katarzyna Pajak ◽  
Beata Wieczorek ◽  
Bartosz Naumowicz
Keyword(s):  
Time Series ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Measurement Techniques ◽  
Radar Interferometry ◽  
Vertical Movements ◽  
Persistent Scatterer ◽  
Gnss Time Series ◽  
Vertical Crustal Movements ◽  
European Coast

The main aim of the article was to analyse the actual accuracy of determining the vertical movements of the Earth’s crust (VMEC) based on time series made of four measurement techniques: satellite altimetry (SA), tide gauges (TG), fixed GNSS stations and radar interferometry. A relatively new issue is the use of the persistent scatterer InSAR (PSInSAR) time series to determine VMEC. To compare the PSInSAR results with GNSS, an innovative procedure was developed: the workflow of determining the value of VMEC velocities in GNSS stations based on InSAR data. In our article, we have compiled 110 interferograms for ascending satellites and 111 interferograms for descending satellites along the European coast for each of the selected 27 GNSS stations, which is over 5000 interferograms. This allowed us to create time series of unprecedented time, very similar to the time resolution of time series from GNSS stations. As a result, we found that the obtained accuracies of the VMEC determined from the PSInSAR are similar to those obtained from the GNSS time series. We have shown that the VMEC around GNSS stations determined by other techniques are not the same.

scholarly journals Countrywide Monitoring of Ground Deformation Using InSAR Time Series: A Case Study from Qatar

2021 ◽  
Vol 13 (4) ◽  
pp. 702
Author(s):  
Mustafa Kemal Emil ◽  
Mohamed Sultan ◽  
Khaled Alakhras ◽  
Guzalay Sataer ◽  
Sabreen Gozi ◽  
...  
Keyword(s):  
Time Series ◽  
Arabian Peninsula ◽  
Ground Deformation ◽  
Anthropogenic Activities ◽  
Urban Centers ◽  
Alos Palsar ◽  
Groundwater Levels ◽  
Temporal Correlations ◽  
Time Series Approach ◽  
Sbas Insar

Over the past few decades the country of Qatar has been one of the fastest growing economies in the Middle East; it has witnessed a rapid increase in its population, growth of its urban centers, and development of its natural resources. These anthropogenic activities compounded with natural forcings (e.g., climate change) will most likely introduce environmental effects that should be assessed. In this manuscript, we identify and assess one of these effects, namely, ground deformation over the entire country of Qatar. We use the Small Baseline Subset (SBAS) InSAR time series approach in conjunction with ALOS Palsar-1 (January 2007 to March 2011) and Sentinel-1 (March 2017 to December 2019) synthetic aperture radar (SAR) datasets to assess ground deformation and conduct spatial and temporal correlations between the observed deformation with relevant datasets to identify the controlling factors. The findings indicate: (1) the deformation products revealed areas of subsidence and uplift with high vertical velocities of up to 35 mm/yr; (2) the deformation rates were consistent with those extracted from the continuously operating reference GPS stations of Qatar; (3) many inland and coastal sabkhas (salt flats) showed evidence for uplift (up to 35 mm/yr) due to the continuous evaporation of the saline waters within the sabkhas and the deposition of the evaporites in the surficial and near-surficial sabkha sediments; (4) the increased precipitation during Sentinel-1 period compared to the ALOS Palsar-1 period led to a rise in groundwater levels and an increase in the areas occupied by surface water within the sabkhas, which in turn increased the rate of deposition of the evaporitic sediments; (5) high subsidence rates (up to 14 mm/yr) were detected over landfills and dumpsites, caused by mechanical compaction and biochemical processes; and (6) the deformation rates over areas surrounding known sinkhole locations were low (+/−2 mm/yr). We suggest that this study can pave the way to similar countrywide studies over the remaining Arabian Peninsula countries and to the development of a ground motion monitoring system for the entire Arabian Peninsula.

The Contribution of LARES to Global Climate Change Studies With Geodetic Satellites

2015 ◽  
Author(s):  
Giampiero Sindoni ◽  
Claudio Paris ◽  
Cristian Vendittozzi ◽  
Erricos C. Pavlis ◽  
Ignazio Ciufolini ◽  
...  
Keyword(s):  
Reference Frame ◽  
Earth Science ◽  
Global Climate ◽  
Temporal Variations ◽  
Terrestrial Reference Frame ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Long Baseline ◽  
Geophysical Processes ◽  
Global Navigation Satellite

Satellite Laser Ranging (SLR) makes an important contribution to Earth science providing the most accurate measurement of the long-wavelength components of Earth’s gravity field, including their temporal variations. Furthermore, SLR data along with those from the other three geometric space techniques, Very Long Baseline Interferometry (VLBI), Global Navigation Satellite Systems (GNSS) and DORIS, generate and maintain the International Terrestrial Reference Frame (ITRF) that is used as a reference by all Earth Observing systems and beyond. As a result we obtain accurate station positions and linear velocities, a manifestation of tectonic plate movements important in earthquake studies and in geophysics in general. The “geodetic” satellites used in SLR are passive spheres characterized by very high density, with little else than gravity perturbing their orbits. As a result they define a very stable reference frame, defining primarily and uniquely the origin of the ITRF, and in equal shares, its scale. The ITRF is indeed used as “the” standard to which we can compare regional, GNSS-derived and alternate frames. The melting of global icecaps, ocean and atmospheric circulation, sea-level change, hydrological and internal Earth-mass redistribution are nowadays monitored using satellites. The observations and products of these missions are geolocated and referenced using the ITRF. This allows scientists to splice together records from various missions sometimes several years apart, to generate useful records for monitoring geophysical processes over several decades. The exchange of angular momentum between the atmosphere and solid Earth for example is measured and can be exploited for monitoring global change. LARES, an Italian Space Agency (ASI) satellite, is the latest geodetic satellite placed in orbit. Its main contribution is in the area of geodesy and the definition of the ITRF in particular and this presentation will discuss the improvements it will make in the aforementioned areas.

scholarly journals Does EO NDVI seasonal metrics capture variations in species composition and biomass due to grazing in semi-arid grassland savannas?

2015 ◽  
Vol 12 (14) ◽  
pp. 4407-4419 ◽  
Author(s):  
J. L. Olsen ◽  
S. Miehe ◽  
P. Ceccato ◽  
R. Fensholt
Keyword(s):  
Time Series ◽  
Species Composition ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Grazing Intensity ◽  
Test Site ◽  
Grazing Pressure ◽  
Modis Ndvi ◽  
Coarse Resolution

Abstract. Most regional scale studies of vegetation in the Sahel have been based on Earth observation (EO) imagery due to the limited number of sites providing continuous and long term in situ meteorological and vegetation measurements. From a long time series of coarse resolution normalized difference vegetation index (NDVI) data a greening of the Sahel since the 1980s has been identified. However, it is poorly understood how commonly applied remote sensing techniques reflect the influence of extensive grazing (and changes in grazing pressure) on natural rangeland vegetation. This paper analyses the time series of Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI metrics by comparing it with data from the Widou Thiengoly test site in northern Senegal. Field data include grazing intensity, end of season standing biomass (ESSB) and species composition from sizeable areas suitable for comparison with moderate – coarse resolution satellite imagery. It is shown that sampling plots excluded from grazing have a different species composition characterized by a longer growth cycle as compared to plots under controlled grazing or communal grazing. Also substantially higher ESSB is observed for grazing exclosures as compared to grazed areas, substantially exceeding the amount of biomass expected to be ingested by livestock for this area. The seasonal integrated NDVI (NDVI small integral; capturing only the signal inherent to the growing season recurrent vegetation), derived using absolute thresholds to estimate start and end of growing seasons, is identified as the metric most strongly related to ESSB for all grazing regimes. However plot-pixel comparisons demonstrate how the NDVI/ESSB relationship changes due to grazing-induced variation in annual plant species composition and the NDVI values for grazed plots are only slightly lower than the values observed for the ungrazed plots. Hence, average ESSB in ungrazed plots since 2000 was 0.93 t ha−1, compared to 0.51 t ha−1 for plots subjected to controlled grazing and 0.49 t ha−1 for communally grazed plots, but the average integrated NDVI values for the same period were 1.56, 1.49, and 1.45 for ungrazed, controlled and communal, respectively, i.e. a much smaller difference. This indicates that a grazing-induced development towards less ESSB and shorter-cycled annual plants with reduced ability to turn additional water in wet years into biomass is not adequately captured by seasonal NDVI metrics.

scholarly journals Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China

2017 ◽  
Vol 21 (11) ◽  
pp. 5805-5821 ◽  
Author(s):  
Fan Yang ◽  
Hui Lu ◽  
Kun Yang ◽  
Jie He ◽  
Wei Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Variations ◽  
Spatiotemporal Variability ◽  
Shortwave Radiation ◽  
Data Sets ◽  
Precipitation Data ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Several global and regional forcing data sets currently provide historical estimates of these two variables over China, including the Global Land Data Assimilation System (GLDAS), the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the China Meteorological Forcing Dataset (CMFD). The CN05.1 precipitation data set, a gridded analysis based on CMA gauge observations, also provides high-resolution historical precipitation data for China. In this study, we present an intercomparison of precipitation and shortwave radiation data from CN05.1, CMFD, CLDAS and GLDAS during 2008–2014. We also validate all four data sets against independent ground station observations. All four forcing data sets capture the spatial distribution of precipitation over major land areas of China, although CLDAS indicates smaller annual-mean precipitation amounts than CN05.1, CMFD or GLDAS. Time series of precipitation anomalies are largely consistent among the data sets, except for a sudden decrease in CMFD after August 2014. All forcing data indicate greater temporal variations relative to the mean in dry regions than in wet regions. Validation against independent precipitation observations provided by the Ministry of Water Resources (MWR) in the middle and lower reaches of the Yangtze River indicates that CLDAS provides the most realistic estimates of spatiotemporal variability in precipitation in this region. CMFD also performs well with respect to annual mean precipitation, while GLDAS fails to accurately capture much of the spatiotemporal variability and CN05.1 contains significant high biases relative to the MWR observations. Estimates of shortwave radiation from CMFD are largely consistent with station observations, while CLDAS and GLDAS greatly overestimate shortwave radiation. All three forcing data sets capture the key features of the spatial distribution, but estimates from CLDAS and GLDAS are systematically higher than those from CMFD over most of mainland China. Based on our evaluation metrics, CLDAS slightly outperforms GLDAS. CLDAS is also closer than GLDAS to CMFD with respect to temporal variations in shortwave radiation anomalies, with substantial differences among the time series. Differences in temporal variations are especially pronounced south of 34° N. Our findings provide valuable guidance for a variety of stakeholders, including land-surface modelers and data providers.

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