Extraction of digital elevation model from Chinese GF-3 C-band synthetic aperture radar data with a step-wise method focusing on facilitating phase unwrapping

2018 ◽  
Vol 12 (03) ◽  
pp. 1
Author(s):  
Haoyang Yu ◽  
Wenjian Ni
Polar Record ◽  
2011 ◽  
Vol 48 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Nora Jennifer Schneevoigt ◽  
Monica Sund ◽  
Wiley Bogren ◽  
Andreas Kääb ◽  
Dan Johan Weydahl

ABSTRACTDifferential synthetic aperture radar interferometry (DInSAR) exploits the coherence between the phases of two or more satellite synthetic aperture radar (SAR) scenes taken from the same orbit to separate the phase contributions from topography and movement by subtracting either phase. Hence pure terrain displacement can be derived without residual height information in it, but only the component of movement in line-of-sight direction is represented in a differential interferogram. Comfortlessbreen, a recently surging glacier, flows predominantly in this direction with respect to the European Remote Sensing satellites ERS-1 and ERS-2. Four C-band SAR scenes from spring 1996 were selected because of the high coherence between the respective pairs of the 1-day repeat-pass tandem mission of the ERS sensors. 2-pass DInSAR is performed in combination with a SPOT5 (Satéllite pour l'Observation de la Terre 5) SPIRIT (SPOT5 stereoscopic survey of Polar Ice: Reference Images and Topography) digital elevation model (DEM) from 2007. The different processing steps and intermediate image products, including unwrapping and generation of displacement maps, are detailed in order to convey the DInSAR processing chain to the beginner in the field of interferometry. Maximum horizontal displacements of 18 to 20 cm d−1 in ground range direction can be detected at the glacier terminus, while a few centimetres per day characterised most of the middle and upper portions of Comfortlessbreen in spring 1996.


2017 ◽  
Author(s):  
Αρλίντα Σακελλάρη

Η διατριβή έχει ως στόχο να καθορίσει τίς βέλτιστες μεθόδους επεξεργασίας των απεικονίσεων Ραντάρ Συνθετικού Ανοίγματος (Synthetic Aperture Radar) (SAR) με σκοπό να παράγονται κατά το δυνατόν αξιόπιστα συμβολομετρικά προϊόντα. Η βέλτιστη επεξεργασία περιλαμβάνει τόσο βελτίωση της ποιότητας των απεικονίσεων SAR καθώς και των ενδιάμεσων προϊόντων τα οποία παράγονται κατά την συμβολομετρική διαδιακασία, όσο και την ανάπτυξη μεθοδολογιών για την ακριβή εκτίμηση όλων των συνιστωσών της συμβολομετρικής φάσης, θεωρώντας και την καθυστέρηση λόγω ατμόσφαιρας ως μια συνιστώσα της συμβολομετρικής φάσης. Ιδιαίτερη έμφαση έχει δοθεί στην εκτίμηση αυτής της συνιστώσας και ιδιαίτερα των επιδράσεων της τροπόσφαιρας, θεωρώντας ότι η συνιστώσα της μετατόπισης παρουσιάζεται σε περιορισμένο αριθμό εφαρμογών σε σχέση με αυτήν της ατμόσφαιρας η οποία είναι μία από τις κύριες αιτίες σφάλματος κατά την εκτίμηση του υψομέτρου με συμβολομετρία και διαφορική συμβολομετρία. Γι αυτό το λόγο, καθώς και για το γεγονός ότι οι μέθοδοι που έχουν αναπτυχθεί δεν βασίζονται στην αφαίρεση γνωστού Ψηφιακού Μοντέλου Εδάφους (Digital Elevation model) (DEM), οι μέθοδοι αυτές περιγράφονται καλύτερα από τον όρο «μέθοδοι Συμβολομετρίας πολλαπλών απεικονίσεων SAR» σε σχέση με τον ήδη υπάρχοντα όρο της διαφορικής Συμβολομετρίας.


2016 ◽  
Vol 173 ◽  
pp. 15-28 ◽  
Author(s):  
David C. Mason ◽  
Mark Trigg ◽  
Javier Garcia-Pintado ◽  
Hannah L. Cloke ◽  
Jeffrey C. Neal ◽  
...  

Author(s):  
M. Esmaeilzade ◽  
J. Amini ◽  
S. Zakeri

Due to the SAR<sup>1</sup> geometry imaging, SAR images include geometric distortions that would be erroneous image information and the images should be geometrically calibrated. As the radar systems are side looking, geometric distortion such as shadow, foreshortening and layover are occurred. To compensate these geometric distortions, information about sensor position, imaging geometry and target altitude from ellipsoid should be available. In this paper, a method for geometric calibration of SAR images is proposed. The method uses Range-Doppler equations. In this method, for the image georeferencing, the DEM<sup>2</sup> of SRTM with 30m pixel size is used and also exact ephemeris data of the sensor is required. In the algorithm proposed in this paper, first digital elevation model transmit to range and azimuth direction. By applying this process, errors caused by topography such as foreshortening and layover are removed in the transferred DEM. Then, the position of the corners on original image is found base on the transferred DEM. Next, original image registered to transfer DEM by 8 parameters projective transformation. The output is the georeferenced image that its geometric distortions are removed. The advantage of the method described in this article is that it does not require any control point as well as the need to attitude and rotational parameters of the sensor. Since the ground range resolution of used images are about 30m, the geocoded images using the method described in this paper have an accuracy about 20m (subpixel) in planimetry and about 30m in altimetry. <br><br> <sup>1</sup> Synthetic Aperture Radar <br> <sup>2</sup> Digital Elevation Model


2020 ◽  
Vol 12 (8) ◽  
pp. 1353 ◽  
Author(s):  
Edward Park ◽  
Eder Merino ◽  
Quinn W. Lewis ◽  
Eric O. Lindsey ◽  
Xiankun Yang

Global measurements of reservoir water levels are crucial for understanding Earth’s hydrological dynamics, especially in the context of global industrialization and climate change. Although radar altimetry has been used to measure the water level of some reservoirs with high accuracy, it is not yet feasible unless the water body is sufficiently large or directly located at the satellite’s nadir. This study proposes a gauging method applicable to a wide range of reservoirs using Sentinel–1 Synthetic Aperture Radar data and a digital elevation model (DEM). The method is straightforward to implement and involves estimating the mean slope–corrected elevation of points along the reservoir shoreline. We test the model on six case studies and show that the estimated water levels are accurate to around 10% error on average of independently verified values. This study represents a substantial step toward the global gauging of lakes and reservoirs of all sizes and in any location where a DEM is available.


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