7,091 research outputs found

    Advanced InSAR atmospheric correction: MERIS/MODIS combination and stacked water vapour models

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    A major source of error for repeat-pass Interferometric Synthetic Aperture Radar (InSAR) is the phase delay in radio signal propagation through the atmosphere (especially the part due to tropospheric water vapour). Based on experience with the Global Positioning System (GPS)/Moderate Resolution Imaging Spectroradiometer (MODIS) integrated model and the Medium Resolution Imaging Spectrometer (MERIS) correction model, two new advanced InSAR water vapour correction models are demonstrated using both MERIS and MODIS data: (1) the MERIS/MODIS combination correction model (MMCC); and (2) the MERIS/MODIS stacked correction model (MMSC). The applications of both the MMCC and MMSC models to ENVISAT Advanced Synthetic Aperture Radar (ASAR) data over the Southern California Integrated GPS Network (SCIGN) region showed a significant reduction in water vapour effects on ASAR interferograms, with the root mean square (RMS) differences between GPS- and InSAR-derived range changes in the line-of-sight (LOS) direction decreasing from ,10mm before correction to ,5mm after correction, which is similar to the GPS/MODIS integrated and MERIS correction models. It is expected that these two advanced water vapour correction models can expand the application of MERIS and MODIS data for InSAR atmospheric correction. A simple but effective approach has been developed to destripe Terra MODIS images contaminated by radiometric calibration errors. Another two limiting factors on the MMCC and MMSC models have also been investigated in this paper: (1) the impact of the time difference between MODIS and SAR data; and (2) the frequency of cloud-free conditions at the global scale

    Imaging ionospheric inhomogeneities using spaceborne synthetic aperture radar

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    We present a technique and results of 2-D imaging of Faraday rotation and total electron content using spaceborne L band polarimetric synthetic aperture radar (PolSAR). The results are obtained by processing PolSAR data collected using the Phased Array type L-band Synthetic Aperture Radar (PALSAR) on board the Advanced Land Observation Satellite. Distinguished ionospheric inhomogeneities are captured in 2-D images from space with relatively high resolutions of hundreds of meters to a couple of kilometers in auroral-, middle-, and low-latitude regions. The observed phenomena include aurora-associated ionospheric enhancement arcs, the middle-latitude trough, traveling ionospheric disturbances, and plasma bubbles, as well as ionospheric irregularities. These demonstrate a new capability of spaceborne synthetic aperture radar that will not only provide measurements to correction of ionospheric effects in Earth science imagery but also significantly benefit ionospheric studies

    A systematic study of earthquake detectability using Sentinel-1 Interferometric Wide-Swath data

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    The Sentinel-1 mission comprises two synthetic aperture radar satellites, each with a 12 day orbital repeat, orbiting 6 days apart within a narrow tube. The mission design promises the ability to respond quickly to earthquakes with InSAR, and to facilitate production of interferograms with good interferometric correlation globally. We report on our efforts to study global seismicity using Sentinel-1 Interferometric Wide-Swath data between April 2015 and December 2016. We select 35 potentially detectable terrestrial earthquakes in the range 5.5 ≤ Mw ≤ 7.8 on the basis of their locations, depths and magnitudes, and process the first post-event interferogram with the shortest possible time-span for each using the ISCE software. We evaluate each interferogram for earthquake deformation signals by visual inspection. We can identify deformation signals attributable to earthquakes in 18 of these interferograms (51%); a further six interferograms (17%) have ambiguous interferometric phase affected by tropospheric noise. 11 events (31%) could not be identified from their interferograms. The majority of these failed detections were due to interferogram decorrelation, particularly apparent for earthquakes that occurred between 15°N and 15°S, where climate conditions promote dense vegetation. The majority of the ambiguous interferograms are affected by tropospheric noise, suggesting that techniques to mitigate such noise could improve detection performance. The largest event we do not detect with Sentinel-1 data is a Mw7.0 earthquake that occurred in Vanuatu in April 2016; we also fail to detect the 2016 Mw6.2 Kurayoshi earthquake in one out of two possible 24-day interferograms. We propose these as upper and lower estimates on the magnitude of completeness for earthquakes studied with Sentinel-1 data; to lower the magnitude of completeness we suggest that more frequent (e.g. six day) recurrence may be necessary in low latitude areas

    An accurate method to correct atmospheric phase delay for InSAR with the ERA5 global atmospheric model

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    Differential SAR Interferometry (DInSAR) has proven its unprecedented ability and merits of monitoring ground deformation on a large scale with centimeter to millimeter accuracy. However, atmospheric artifacts due to spatial and temporal variations of the atmospheric state often affect the reliability and accuracy of its results. The commonly-known Atmospheric Phase Screen (APS) appears in the interferograms as ghost fringes not related to either topography or deformation. Atmospheric artifact mitigation remains one of the biggest challenges to be addressed within the DInSAR community. State-of-the-art research works have revealed that atmospheric artifacts can be partially compensated with empirical models, point-wise GPS zenith path delay, and numerical weather prediction models. In this study, we implement an accurate and realistic computing strategy using atmospheric reanalysis ERA5 data to estimate atmospheric artifacts. With this approach, the Line-of-Sight (LOS) path along the satellite trajectory and the monitored points is considered, rather than estimating it from the zenith path delay. Compared with the zenith delay-based method, the key advantage is that it can avoid errors caused by any anisotropic atmospheric phenomena. The accurate method is validated with Sentinel-1 data in three different test sites: Tenerife island (Spain), AlmerĂ­a (Spain), and Crete island (Greece). The effectiveness and performance of the method to remove APS from interferograms is evaluated in the three test sites showing a great improvement with respect to the zenith-based approach.Peer ReviewedPostprint (published version

    The planning of a South African airborne synthetic aperture radar measuring campaign

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    Bibliography: leaves 153-163.This thesis sets out the results of work done in preparation for a South African Airborne Synthetic Aperture Radar (SAR) measuring campaign envisaged for 1994/5. At present both airborne and spaceborne SARs have found a niche in remote sensing with applications in subsurface mapping, surface moisture mapping, vegetation mapping, rock type discrimination and Digital Elevation Modelling. Since these applications have considerable scientific and economic benefits, the Radar Remote Sensing Group at the University of Cape Town committed themselves to an airborne SAR campaign. The prime objective of the campaign is to provide the South African users with airborne SAR data and enable the Radar Remote Sensing Group to evaluate the usefulness of SAR as a remote sensing tool in South Africa

    Monitoring of Incomati River Basin with Remote Sensing

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    Incomati river basin is located in the continent of South Africa and is shared between three countries of Republic of Mozambique, Republic of South Africa, and the Kingdom of Swaziland. Located in a water-stressed region and shared between three countries it has importance in both sociopolitical and water scarcity aspect. The three countries recently (in 2002) signed an agreement for letting certain amount of water pass through the borders. Accordingly all 3 countries need to implement a monitoring method to evaluate the agreement. This thesis deals with different remote sensing methods for monitoring of water resources in the basin. To do this, after explaining site conditions, different literature has been reviewed and three main remote sensing methods (Optical method, Synthetic Aperture Radar imagery (SAR), Radar Altimetry) are explained briefly. Their advantages and disadvantages and their limitations are discussed. By creating an inventory of available satellites and considering the site specific conditions the use and applicability of those methods to the region are discussed. This paper shows that among the three major Remote Sensing methods, optical method and Synthetic Aperture Radar (SAR) can be used for monitoring of the Incomati basin. Furthermore, the optical method was applied to assess water storage in the region. Some free Landsat images of the region obtained from Global Land Cover Facility (GLCF), www.landcover.org have been analyzed and water storage has been estimated and the results compared with ground truth information. The results obtained from 6 Landsat images showed high accuracy of water storage estimation with an average accuracy of 3.5%

    Temporal stability of soil moisture and radar backscatter observed by the advanced Synthetic Aperture Radar (ASAR)

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    The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R-2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments
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