The Changbaishan Tianchi volcano is a massive stratovolcano, located in the northeast of China, at the boundary between China and North Korea (Fig. 1). Based on the previous study, Changbaishan Tianchi volcano has experienced several stages of explosive eruption in history especially during the latest 1000 years, in which the 946 AD eruption, the so-called millennium eruption, is considered as one of the largest eruptions in the world in the past 2000 years.1,2 At least three eruptive activities occurred in AD 1668, 1702, and 1903 after the millennium eruption.3 Due to these large explosive eruption events, Changbaishan Tianchi volcano is considered the most dangerous volcano in China. From 2002 to 2006, volcanic seismicity, ground deformation, volcanic thermal anomaly, and volcanic gas geochemistry increased, indicating the volcano has begun to wake after more than 100 years of inactivity.2,4,5 The 2002 to 2006 volcanic unrest events attracted much attention from the Chinese government and volcanologists.
Many researchers have used geophysical approaches to detect the magma system beneath the Changbaishan Tianchi volcano (e.g., see Refs. 6 and 7). Magnetotelluric soundings show that lower resistivity anomalies exist beneath the Changbaishan Tianchi volcano at a depth of 12 km.6 Seismic explosion experiments reveal that low-velocity anomalies in the crust and upper mantle are divided into three layers under the Changbaishan Tianchi volcano,7 which is speculated to be the magma chamber. Thus, geophysical measurements indicate that the Changbaishan Tianchi volcano does have a magma chamber. However, the location and depth of the magma chamber from different approaches are different due to different spatial resolutions and other unknown reasons.
Geodetic measurements, including leveling and global positioning system (GPS) have also been carried out at the Changbaishan Tianchi volcano.5,8,9 Hu et al.8 modeled the leveling and GPS displacements based on a Mogi point source10 in an elastic half space, and the result indicates that the magma chamber is located at a depth between 2 and 6 km beneath the caldera. Based on an ellipsoid point source model, Zhu et al.11 made a jointly inversion using the leveling and GPS displacements, showing that the magma chamber is located in about 10 km depth. Obviously, different researchers got different magma chamber depths. These distinct results are probably related to those pointwise techniques, which cannot provide an adequately dense mapping of the deformation affecting the Changbaishan Tianchi volcano area.
Conventional interferometric synthetic aperture radar (InSAR) has proven to be an effective tool to study crustal deformation due to volcanic activities (e.g., see Refs. 12, 13, and 14). In contrast to leveling, GPS or other ground-based measurements, InSAR has the potential to dramatically improve the spatial density and continuity of surface displacement measurements. However, in Changbaishan Tianchi volcano area, heavy temporal decorrelation on the interferometric signal due to high vegetation coverage seriously limits the efficiency of the conventional InSAR approach (e.g., see Refs. 15 and 16). Besides, at Changbaishan Tianchi volcanic area, the accuracy of conventional InSAR measurements is also reduced by atmospheric artifacts that are difficult to remove from interferograms.15 To overcome these limitations, we implement the Persistent scatterer interferometric synthetic aperture radar (PSInSAR) approach17 to detect the crustal deformation around Changbaishan Tianchi volcano area. The PSInSAR technique considers those pixels that exhibit phase stability over a time series of interferograms, i.e., permanent or persistent scatterers. Hence, the PS pixels behave like point scatterers and interferometric decorrelation is greatly reduced. The PSInSAR technique has shown its potential for volcanic deformation monitoring worldwide (e.g., see Refs. 17, 18, 19, 20, and 21). In this article, we present deformation time series during 2004 to 2010 around Changbaishan Tianchi volcano of the PSInSAR analysis based on a set of ENVISAT radar archives. To verify the accuracy of the PSInSAR-derived deformation, the precise leveling results are shown. Based on modeling, an interpretation of the displacement field observed at Changbaishan Tianchi volcano is proposed.
Dataset and PSInSAR Method
To map the surface displacement associated with the volcanic activities, we use data from the ENVISAT SAR archive provided by the European Space Agency (ESA). Among all possible tracks covering the Changbaishan Tianchi volcano area, we focus on the descending track 146, which provides the largest number of suitable images for our analysis. We only choose SAR images acquired during the summer and early fall (from mid-May to mid-October) to avoid coherence loss due to snow and ice. Eighteen images (Table 1) acquired between May 2004 and June 2010 are selected at last.
Parameters of ENVISAT ASAR images covered Changbaishan Tianchi volcanic area.
|1||May 28, 2004||11723||163.65|
|2||July 2, 2004||12224||167.14|
|3||October 15, 2004||13727||159.78|
|4||June 17, 2005||17234||157.51|
|5||July 22, 2005||17735||159.06|
|6||August 26, 2005||18236||166.50|
|7||September 30, 2005||18737||185.55|
|8||June 2, 2006||22244||186.94|
|9||July 7, 2006||22745||183.43|
|10||August 11, 2006||23246||191.26|
|11||May 18, 2007||27254||177.27|
|12||July 17, 2007||28256||185.97|
|13||August 31, 2007||28757||190.98|
|14||August 15, 2008||33767||195.10|
|15||June 26, 2009||38276||189.49|
|16||July 31, 2009||38777||187.02|
|17||September 4, 2009||39278||186.87|
|18||June 11, 2010||43286||180.02|
PSInSAR Method: StaMPS Processing
We use the Stanford method for persistent scatterers (StaMPS) approach19 to achieve the deformation time series. This approach has proven to be reliable even in natural terrains, especially in dense vegetated area. It does not rely on a prior assumption about the temporal nature of ground deformation. Instead, it assumes that the deformation and, consequently, the interferometric phase are spatially correlated.
The main processing parameters are given in Table 2. A single reference (master) image acquired on June 17, 2005 is selected for the generation of interferogram stack. The resulting perpendicular baselines range between and 710 m, whereas temporal baselines range between and 1820 days (Fig. 2). Seventeen differential interferograms are generated with respect to the common master image using the conventional two-pass DInSAR approach (e.g., see Ref. 22). A digital elevation model from the Shuttle Radar Topography Mission (SRTM)23 with 90-m pixel spacing is used to remove the topography phase from the interferograms. It is worth noting that we chose a strict threshold when selecting PS pixels, resulting in less false PS pixels that are included in the SAR interferograms. Also, this strict selection leads to sparse PS distribution (Fig. 3). The zero deformation area (i.e., reference area) is selected as the benchmark N0 of the Beipo leveling route (see Fig. 1 for location). Therefore, the two techniques, i.e., PSInSAR and leveling, have the same reference area. At the end of the StaMPS processing chain, the PS displacement time series at each acquisition date is reconstructed.
Parameters used in the StaMPS processing.
|DEM||SRTM 3 arc sec|
|Maximum DEM error||10 m|
|Band-pass phase filter grid cell size||20 m|
|Band-pass phase filter grid size||64×64|
|Band-pass phase filter low-pass cutoff||200 m|
|Band-pass phase filter α||1|
|Band-pass phase filter β||0.3|
|Spatially correlated filtering time window||730 days|
|Spatially correlated filtering minimum wavelength||200 m|
|Unwrapping grid cell size||200 m|
|Unwrapping time window||365 days|
|Weed standard deviation||1.0|
|Reference range (longitude)||128.167–128.187|
|Reference range (latitude)||42.215–42.235|
PSInSAR Results and Analysis
The StaMPS processing identified a total of 7825 PS pixels in the study area (), with a mean point density of [Fig. 3(a)]. There are 13 PS pixels falling in the reference area [Fig. 3(b)]. Obviously, dense PS pixels are identified around the crater rim and the bare rock area at North Korea, whereas sparse PS pixels are identified around the volcano flank due to high vegetation coverage.
Figure 4 shows deformation time series of four certain PS pixels at Changbaishan Tianchi volcano. Time series are rescaled to the first acquisition (i.e., May 28, 2004), being understood that the PSInSAR master image (temporal reference) of the processing is the June 17, 2005, acquisition. Among the four PS pixels, one of them (i.e., N12) is located near the crater, and the other three are located at different parts of the volcano flank (Fig. 3). From the displacement time series map of the four PS pixels, we make the following observations (Fig. 4):
1. Between May 2004 and August 2006, no significant deformation is observed in Changbaishan Tianchi volcano. In other words, deformation was generally lower than during this period.
2. From August 2006 to August 2008, an inflation occurred at Changbaishan Tianchi volcano, with maximum displacement of 20 mm.
3. The deformation pattern changed to deflation from August 2008 to June 2010, with a nearly constant deformation rate. In other words, the subsidence that occurred in Changbaishan Tianchi volcano was linear with time during 2008 to 2010 with a total subsidence of 10 mm.
Comparison with Leveling Results
In order to evaluate the reliability of the PSInSAR measurements, the results should be compared with the deformation obtained from other techniques. From the GPS results shown in Ref. 5, the horizontal displacements of Changbaishan Tianchi volcano were not significant at the 95% confidence level during 2004 and 2010, i.e., the PSInSAR-working period. Therefore, we assume that the ground displacement in Changbaishan Tianchi volcano occurs only in the vertical direction.
Thus, we compare the PSInSAR results against precise leveling results to quantitatively validate the results obtained. For the leveling results, the standard deviation of accidental is 0.13 mm.9 Based on the nearly vertical deformation assumption, the InSAR line of sight (LOS) measurements () can be converted to vertical displacements () following the relation , where is incidence angle from the vertical. Eight benchmarks of precise leveling are chosen (see Fig. 1 for location). As the PS density is higher than the density of benchmarks, we estimate an average PS LOS displacement around each benchmark by selecting all PS pixels within a certain radius centered on each benchmark. The minimum radius is set to 400 m. We increase it until at least 10 PS pixels are found. The maximum radius is set to 3 km. Uncertainty of the average LOS displacement is estimated by the standard deviation of the individual PS LOS displacements inside this area.
The time series of vertical displacements show a good agreement between PSInSAR and leveling results (Fig. 5). Therefore, we conclude that PSInSAR can extract deformation with a high precision, even though the area is covered by dense vegetation. On the other hand, the agreement is consistent with our assumption of mainly vertical motion for the Changbaishan Tianchi volcano during 2004 to 2010.
We assume that the surface deformation was caused by a volume change beneath the Changbaishan Tianchi volcano due to an injection or withdrawal of magmatic or hydrothermal fluids. In order to explain the PSInSAR-detected deformation field, we test a point source of dilation in an elastic half-space10 that includes a correction to account for topographic variation.24 In the model, we introduce linear terms to account for any possible phase ramp due to uncertainties in satellite positions.22 We use the downhill simplex method and Monte Carlo simulations25 to estimate optimal parameters and their uncertainties, and the root mean square errors between the observed and modeled interferograms as the prediction-fit criterion. We choose the time series map obtained in August 2008 for modeling because this deformation map shows the largest inflationary displacement (Fig. 5). Figure 6(a) shows observed interferograms, Fig. 6(b) shows modeled interferograms, and Fig. 6(c) shows residual interferograms for the Mogi model. The cross shown in Fig. 6(b) represents the horizontal position of the Mogi source. The Mogi source emplaced directly beneath the volcanic edifice of the Changbaishan Tianchi volcano, with a depth of 9-km below sea level. Then, we forward modeled the vertical deformation at the selected leveling benchmarks, based on the PSInSAR-inversed Mogi source. The observed and forward modeled displacements agree with each other reasonably well (Fig. 7), which indicates that the Mogi source can account for the magma chamber reasonably. However, in Fig. 6, the model cannot fit the observed interferogram very well according to the residual interferogram. All the model parameters are loosely constrained according to the uncertainties shown in Table 3. We will propose some possible explanations in Sec. 4.
Parameters from Mogi source. Errors are in 95% confidence.
|Volume change (m3)||2.8×106±1.1×106|
Note: The reference for the horizontal coordinates (X,Y) is at (128.0559 deg, 42.0075 deg).
Our Mogi modeling test at Changbaishan Tianchi volcano indicates that the PSInSAR-derived deformation was caused by a Mogi point source centered about 9 km beneath the edifice. However, only the deformation around the caldera part can fit the observed one very well (Fig. 6). The large modeling residual may be caused by the following reasons, or combination of factors. First, the deformation is not large enough for modeling, even though we choose the largest accumulative deformation map. Second, the observed deformation might consist of several parts, for example, the deformation caused by magma recharge, local deformation, or noise. In other words, we speculate that only magma intrusion cannot account for the observed deformation. Next, we investigate the possible activities that occurred across the regional fault, i.e., Maanshan–Sandaobaihe fault [Fig. 6(c), fault trace is based on Ref. 26]. Figure 8 shows two profiles of LOS displacement across the Maanshan–Sandaobaihe fault. The two profiles reveal a slight change across the two sides of the fault, which may indicate that the fault was active during the study period. In addition, even though we chose a strict threshold when selecting PS pixels, there were some false PS pixels left, which may cause the large modeling residual.
According to the seismic record, a number of small volcano-tectonic earthquake swarms occurred at Changbaishan Tianchi volcano area.27,28 Figure 9 shows the cumulative earthquake numbers during May 2004 to September 2010. Earthquake number increased gradually before 2008 and sporadic earthquakes occurred after 2008. These earthquake records and PSInSAR-derived deformation time series are particularly similar (Figs. 4 and 5). Generally, if there is no clear main shock for a volcano-tectonic swarm, the swarm may be triggered by a magmatic intrusion beneath the volcano.29 Therefore, an episodic magma intrusion event may have occurred during August 2006 to August 2008. The intrusive magma went up along cracks in the shallow crust, which may perturb the stresses on overlaying faults, resulting earthquake swarms. The magma intrusion event ceased sometimes after August 2008, followed by a subsidence at the volcano, which may due to solidification of cooling magma or draining of magma.
Deformation accompanying seismicity has also been detected with InSAR at other volcanoes that have not erupted for more than a century, including Akutan volcano in Alaska and Campi Flegrei caldera in Italy. At Akutan, an intense seismic swarm occurred in March 1996, accompanying by as much as 60 cm of uplift on the western part of the island. However, no eruptive events issued during the seismicity active period.30 The situation is similar at Campi Flegrei, where episodes of subsidence and uplift occurred during 1992 to 2006, accompanied by seismic activity, without producing eruptions.31
Using PSInSAR approach, we are able to extract the deformation time series at Changbaishan Tianchi volcano, even though it is covered by thick vegetation. Our modeling results show a Mogi point source at a depth of 9 km just beneath the caldera is responsible for the observed deformation. The modeling results indicate the deformation was not solely caused by magmatic activity. Active fault may produce a part of the observed deformation.
Changbaishan Tianchi volcano has produced multiple eruptions and pyroclastic flows in the past, and it is located close to densely populated areas, for example, Erdaobaihe county is located only 20 km from the Changbaishan Tianchi volcano. More than 60,000 inhabitants are directly at risk from the Changbaishan Tianchi volcano. We have presented results of PSInSAR time series survey of the Changbaishan Tianchi volcano from ENVISAT interferograms spanning 2004 to 2010. Such surveys are important for identifying deformation trends and deformed range, which can inform future hazard assessments.
We would like to thank two anonymous reviewers for comments that helped improve this manuscript. This research was supported by the special earthquake research project granted by the China Earthquake Administration (201208009), and Natural Science Foundation of Shanxi, China (2011021024-1). ENVISAT SAR data are copyrighted by ESA and were provided by ESA under CAT1-7864.
Lingyun Ji received his master degree in geodesy from Chang’an University in 2007 and the PhD degree in structural geology from Institute of Geology, China Earthquake Administration (CEA) in 2013. In July 2007, he joined the Second Crust Monitoring and Application Center, CEA, working on volcanic/seismic deformation using InSAR. He visited Cascades Volcano Observatory/USGS, as a visiting scientist from October 2011 to October 2012. His research interests concern InSAR applications, such as detecting volcanic/seismic deformation and modeling.
Jiandong Xu received his PhD degree from the University at Buffalo, the State University of New York in 1998. He is currently professor of Institute of Geology, CEA. His main research interests concern volcano geology, chronology, and volcanic activities monitoring.
Qingliang Wang received his PhD degree on geophysics from the Institute of Geophysics, CEA in 2003. He is currently the deputy director of the Second Crust Monitoring and Application Center, CEA, where he is professor of geophysics.