2022年汤加火山喷发的综合遥感快速解译分析

2022年1月14日—15日南太平洋汤加Hunga Tonga-Hunga Ha'apai(HTHH)海底火山发生剧烈喷发并造成海啸,引起了国际广泛关注.对此次"千年一遇"的汤加HTHH火山喷发事件进行应急响应,首先综合利用国内外多时相卫星光学影像、雷达影像、全球导航卫星系统(global navigation sat...     

Determination of chlorophyll content of small water bodies (kettle holes) using hyperspectral airborne data

This study presents an approach for chlorophyll content determination of small shallow water bodies (kettle holes) from hyperspectral airborne ROSIS and HyMap data (acquired on 15 May and 29 July 2008 respectively). Investigated field and airborne spectra for almost all kettle holes do not correspond to each other due to differences in ground sampling distance. Field spectra were collected from the height of 30–35 cm (i.e. area of 0.01–0.015 m²). Airborne pixels of ROSIS and HyMap imageries cover an area of 4 m² and 16 m² respectively and their spectra are highly influenced by algae or bottom properties of the kettle holes. Analysis of airborne spectra revealed that chlorophyll absorption near 677 nm is the same for both datasets. In order to enhance absorption properties, both airborne hyperspectral datasets were normalized by the continuum removal approach. Linear regression algorithms for ROSIS and HyMap datasets were derived using normalized average chlorophyll absorption spectra for each kettle hole. Overall accuracy of biomass mapping for ROSIS data was 71%, and for HyMap 64%. Biomass mapping results showed that, depending on the type of kettle hole, algae distribution, the ‘packaging effect’ and bottom reflection lead to miscalculations of the chlorophyll content using hyperspectral airborne data.     

Surface deformation associated with the 2008 Ms8.0 Wenchuan earthquake from ALOS L-band SAR interferometry

The Ms8.0 Wenchuan earthquake (in China) occurred on 12 May 2008 as a result of slip on the northeastern-striking Longmen Shan (LMS) faults beneath the rugged margin between the Qinghai-Tibet Plateau and Sichuan Basin. The catastrophic event caused significant surface ruptures and permanent ground displacement in a wide area. This paper concentrates on mapping surface deformation caused by the main shock with the interferometric synthetic aperture radar (InSAR) technology. The coseismic interferogram covering an area of over 83,000 km² is computed with use of 46 SAR images that were collected along 6 adjacent ascending orbits by the L-band SAR sensor onboard the Japanese Advanced Land Observing Satellite (ALOS). The displacements measured at 16 GPS sites are used to check the accuracy of the InSAR deformation measurements. The radar coherence is computed and analyzed in relation to the topography and the normalized difference vegetation index (NDVI) estimated from the Landsat-7 imagery. The results show that the coseismic surface deformation can be mapped up to a centimeter-accuracy level even over the highly mountainous and heavily vegetated area with the L-band interferometer. It is also demonstrated that the L-band interferograms with time interval of months to years can still maintain acceptable radar coherence for deformation extraction over the area under the extreme conditions. The extracted InSAR deformation measurements show that the lands in the Sichuan Basin had moved 0.1–1.3 m toward the satellite along the radar line of sight (LOS) direction with an azimuth of 349.8° and an elevation angle of 51.3°, while the lands in the LMS area had moved 1.4 m at most away from the satellite.     

Large-area rice yield forecasting using satellite imageries

Ability to make large-area yield prediction before harvest is important in many aspects of agricultural decision-making. In this study, canopy reflectance band ratios (NIR/RED, NIR/GRN) of paddy rice (Oryza sativa L.) at booting stage, from field measurements conducted from 1999 to 2005, were correlated with the corresponding yield data to derive regression-type yield prediction models for the first and second season crop, respectively. These yield models were then validated with ground truth measurements conducted in 2007 and 2008 at eight sites, of different soil properties, climatic conditions, and various treatments in cultivars planted and N application rates, using surface reflectance retrieved from atmospherically corrected SPOT imageries. These validation tests indicated that root mean square error of predicting grain yields per unit area by the proposed models were less than 0.7 T ha⁻¹ for both cropping seasons. Since village is the basic unit for national rice yield census statistics in Taiwan, the yield models were further used to forecast average regional yields for 14 selected villages and compared with officially reported data. Results indicate that the average yield per unit area at village scale can be forecasted with a root mean square error of 1.1 T ha⁻¹ provided no damaging weather occurred during the final month before actual harvest. The methodology can be applied to other optical sensors with similar spectral bands in the visible/near-infrared and to different geographical regions provided that the relation between yield and spectral index is established.     

20 years of active deformation on volcano caldera: Joint analysis of InSAR and AInSAR techniques

InSAR (interferometric synthetic aperture radar) techniques are applied to investigate last two decades of surface deformation of the Cerro Blanco/Robledo Caldera (CBRC). The objective is the identification of deforming patterns that alter the shape of these complex structures when they show low or null activity. The joint analysis between results by using different methods over a long time span, represents a unique opportunity to improve knowledge of volcanic structures located in remote area and, for this, poorly or not monitored.In this work we identify displacement patterns over the volcanic area, by using both classical differential InSAR analysis, and A-InSAR (advanced InSAR) analysis based on SAR data acquired by ERS-1/2 and ENVISAT sensors during the 1996–2010 time interval. The satellite-derived information allows us to characterize the deformation pattern that affected the CBRC and shows that the actively deforming CBRC is subsiding in the observed period. In order to figure out the deformation history of CBRC, we analyzed the four sub-periods 1992–1996, 1996–2000, and 2005–2010 by using standard differential InSAR technique, and the interval 2003–2007 by adopting an A-InSAR technique.Subsidence velocities of the CBRC caldera are about 2.6 cm/yr in the time interval 1992–1996 (measured with ERS descending data), 1.8 cm/yr in 1996–2000 (ERS descending data), 1.2 cm/yr in 2003–2007 (ENVISAT descending data), and finally, 0.87 cm/yr in 2005–2010 (ENVISAT ascending data). Moreover, outside the caldera and in particular in the NW area, we observe the presence of positive velocity values. Results show that: (a) a decreasing subsidence rate might be related to the reduction of volcanic activity in correspondence of the CBRC; (b) positive velocity signal, decreasing with time, might be interpreted as follows: – evidence of volcano structure lateral spreading, according to the velocity pattern distribution in this area and to the relative local flanks topographic convexity of the volcano structure; – uplift signal of this sector of mountain chain; – combination of the two mechanisms above.     

Monitoring agricultural cropping patterns across the Laurentian Great Lakes Basin using MODIS-NDVI data

The Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16-day composite data product (MOD12Q) was used to develop annual cropland and crop-specific map products (corn, soybeans, and wheat) for the Laurentian Great Lakes Basin (GLB). The crop area distributions and changes in crop rotations were characterized by comparing annual crop map products for 2005, 2006, and 2007. The total acreages for corn and soybeans were relatively balanced for calendar years 2005 (31,462 km² and 31,283 km², respectively) and 2006 (30,766 km² and 30,972 km², respectively). Conversely, corn acreage increased approximately 21% from 2006 to 2007, while soybean and wheat acreage decreased approximately 9% and 21%, respectively. Two-year crop rotational change analyses were conducted for the 2005–2006 and 2006–2007 time periods. The large increase in corn acreages for 2007 introduced crop rotation changes across the GLB. Compared to 2005–2006, crop rotation patterns for 2006–2007 resulted in increased corn–corn, soybean–corn, and wheat–corn rotations. The increased corn acreages could have potential negative impacts on nutrient loadings, pesticide exposures, and sediment-mediated habitat degradation. Increased in US corn acreages in 2007 were related to new biofuel mandates, while Canadian increases were attributed to higher world-wide corn prices. Additional study is needed to determine the potential impacts of increases in corn-based ethanol agricultural production on watershed ecosystems and receiving waters.     

Volcanic ash detection by GPS signal

We investigate the ability of GPS to detect volcanic plumes at Mt. Etna, Italy. We use a robust statistical approach to highlight whether the presence of a volcanic plume in the atmosphere may really affect the GPS undifferenced post-fit phase residuals. The proposed method has been tested for the September 4–5, 2007 activity of Mt. Etna. This eruption produced powerful lava fountains forming a weak, a few kilometers high plume for several hours, representing typical activity at Etna over the last 5 years. We analyzed data from nineteen Etna permanent GPS stations located on the volcano flanks at different heights and applied a statistical test based on four main steps: (a) realization of a simplified model representing the volcanic plume in atmosphere; (b) evaluation of the GPS satellite and station couples intersecting the plume; (c) calculation of the volcanic plume region crossed by the GPS signal; (d) application of a robust statistical test in order to see whether the volcanic plume affected the GPS signals. Results show that during the September 4–5, 2007 explosive activity, the GPS residuals definitely include the contribution of the volcanic plume. Our analysis shows that values of the GPS residuals are ten times smaller than those found for the Miyakejima eruption (Japan), highlighting a likely relationship between residuals and eruption intensity. In the future, data derived from the GPS stations located on Etna’s flanks could be used to improve the alerting system of volcanic ash, already operating at the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo.     

Remote detection of bare soil moisture using a surface-temperature-based soil evaporation transfer coefficient

An approach for estimating soil moisture is presented and tested by using surface-temperature-based soil evaporation transfer coefficient (h_a), a coefficient recently proposed through the equation h_a = (T_s − T_a)/(T_sd − T_a), where T_s, T_sd, and T_a are land surface temperature (LST), reference soil (dry soil without evaporation) surface temperature, and air temperature respectively. Our analysis and controllable experiment indicated that h_a closely related to soil moisture, and therefore, a relationship between field soil moisture and h_a could be developed for soil moisture estimation. Field experiments were carried out to test the relationship between h_a and soil moisture. Time series Aqua-MODIS images were acquired between 11 Sep. 2006 and 1 Nov. 2007. Then, MODIS derived h_a and simultaneous measured soil moisture for different soil depths were used to establish the relations between the two variables. Results showed that there was a logarithmic relationship between soil moisture and h_a (P < 0.01). These logarithmic models were further validated by introducing another ground-truth data gathered from 46 meteorological stations in Hebei Province. Good agreement was observed between the measured and estimated soil moisture with RMSE of 0.0374 cm³/cm³ and 0.0503 cm³/cm³ for surface energy balance method at two soil depths (10 cm and 20 cm), with RMSE of 0.0467 cm³/cm³ and 0.0581 cm³/cm³ for maximum temperature method at two soil depths. For vegetated surfaces, the ratio of h_a and NDVI suggested to be considered. The proposed approach has a great potential for soil moisture and drought evaluation by remote sensing.     

Estimating vegetation parameter for soil erosion assessment in an alpine catchment by means of QuickBird imagery

Soil erosion rates in alpine regions are related to high spatial variability complicating assessment of risk and damages. A crucial parameter triggering soil erosion that can be derived from satellite imagery is fractional vegetation cover (FVC). The objective of this study is to assess the applicability of normalized differenced vegetation index (NDVI), linear spectral unmixing (LSU) and mixture tuned matched filtering (MTMF) in estimating abundance of vegetation cover in alpine terrain. To account for the small scale heterogeneity of the alpine landscape we used high resolved multispectral QuickBird imagery (pixel resolution = 2.4 m) of a site in the Urseren Valley, Central Swiss Alps (67 km²). A supervised land-cover classification was applied (total accuracy 93.3%) prior to the analysis in order to stratify the image. The regression between ground truth FVC assessment and NDVI as well as MTMF-derived vegetation abundance was significant (r² = 0.64, r² = 0.71, respectively). Best results were achieved for LSU (r² = 0.85). For both spectral unmixing approaches failed to estimate bare soil abundance (r² = 0.39 for LSU, r² = 0.28 for MTMF) due to the high spectral variability of bare soil at the study site and the low spectral resolution of the QuickBird imagery. The LSU-derived FVC map successfully identified erosion features (e.g. landslides) and areas prone to soil erosion. FVC represents an important but often neglected parameter for soil erosion risk assessment in alpine grasslands.     

Using multi-temporal remote sensor imagery to detect earthquake-triggered landslides

Landslides are a major type of geohazards claiming thousands of casualties and billions of dollars in property damages every year. Catastrophic landslide activities are often triggered by some extreme events such as earthquakes, excessive precipitations, or volcanic eruptions. Quickly identifying the spatial distribution of landslides induced by these extreme events is crucial for coordinating rescue efforts and planning in situ investigations. In this study, we propose an automated method for detecting the spatial distribution of earthquake-triggered landslides by examining after-event vegetation changes. Central to this method is the use of pre- and post-event remote sensor images covering the same area. Geometric correction and radiometric normalization are performed before deriving a vegetation index from each image. Then, an image differencing procedure is applied to the two derived indices. With the resultant difference image, an initial landslide distribution map is generated by highlighting the pixels with a threshold percentage decrease in the brightness values as a direct result of the image subtraction. The threshold percentage value is interactively determined by using a visual interpretation method. The final landslide distribution map is produced after using a modal filter to suppress boundary errors in the initial map. This method has been implemented in a test site, approximately 30 km from the epicenter of the Sichuan earthquake (7.9 Ms) that struck on 12 May 2008. A pre-event Thematic Mapper image and a post-event Advanced Spaceborne Thermal Emission and Reflection Radiometer scene are used. The thematic accuracy assessment indicates that 90% of the landslides have correctly been mapped. Given the relatively simple procedures and the good mapping accuracy, the image processing and change detection method identified in this study seems to be promising from an operational perspective.     

Earth surface deformation analysis of 2005 Qeshm earthquake based on three-dimensional displacement field derived from radar imagery measurements

We derived the 3D vector displacement field due to the 5.9 Mw Qeshm island (Iran) earthquake using ascending and descending interferograms and azimuth offsets obtained from ENVISAT ASAR data. The pick-to-pick estimated displacement was 10 cm in west, 69 cm in south and 22 cm in vertical directions. We then used strain analysis to study coseismic surface deformation of the earthquake. Finite differences and finite element as two numerical solutions were applied in order to compute the strain tensors. Furthermore, dilation and shear parameters were derived using the strain tensors. Finite differences results showed the maximum expansion of 0.002 and maximum contraction of 0.003. The amounts of maximum shear in xy, xz and yz planes were estimated using finite differences method as 0.05, 0.1 and 0.049, respectively. The maximum expansion and contraction were computed as 0.006 and 0.005, respectively, using finite element approach. Moreover, the maximum shear in xy, xz and yz planes obtained by finite element method was 0.2, 0.4 and 0.19, respectively.     

Performance analysis of the spaceborne laser ranging system

The Spaceborne Laser Ranging System is a proposed short pulse laser on board an orbiting spacecraft.^1,2,3,4 It measures the distance between the spacecraft and many laser retroreflectors (targets) deployed on the Earth’s surface. The precision of these range measurements is assumed to be about ±2 cm (M. W. Fitzmaurice, private communication). These measurements are then used together with the orbital dynamics of the spacecraft, to derive the relative position of the laser ground targets. Assuming a six day observing period with 50% cloud cover, uncertainties in the baseline for target separations of 50 km to 1200 km were estimated to be on the order of 1 to 3 cm and the corresponding values in the vertical direction, ranged from 1 cm to 12 cm. By redetermining the measurements of the relative target positions, the estimated precision in the baseline for a target separation of 50 km is less than 0.3 cm and for a separation of 1200 km is less than 1 cm. In the vertical direction, the estimated precision ranged from 0.4 cm to 4.0 cm respectively. As a result of the repeated estimation of the relative laser target positions, most of the non-temporal effects of error sources as exemplified by the errors in geopotential are reduced. The Spaceborne Laser Ranging System’s capability of determining baselines to a high degree of precision provides a measure of strain and strain rate as shown byCohen, 1979. These quantities are essential for crustal dynamic studies which include determination and monitoring of strain near seismic zones, land subsidence, and edifice building preceding volcanic eruptions. It is evident that such a system can also be used for geodetic surveys where such precisions are more than adquate.     

Role of Fracturing in the Organization of the Karst Features of Azrou Plateau (Middle Atlas,Morroco) Studied by Remote Sensing Imagery

Karst formation geometry can be controlled by fractures and faults, and by other lithologies. Here we show the organization of kastic collapse features related to structures and to extensive basaltic lava flows in the Middle Atlas of Morocco. A lineament map of major faults and fractures has been created for the Middle Atlas using Landsat 7 ETM⁺ satellite images. This shows a dominant NE–SW regional direction and less prominent NNW–SSE and ENE–WSE directions. All these directions coincide with the alignments of karstic depressions that have formed in the Liassic limestones. The basaltic flows covering these formations on the Middle Atlas limestone plateau, have allowed the generation of cryptokarst, geometrically organized a long these major lineament directions. Karst landforms probabaly existed before the eruption of the lavas, but there were partly invaded by intrusions and volcanism. The extensive basaltic flows allowed for increased infiltration, and subsurface water flow, increasing the rate of kast formation after eruptions. Some basins show evidence of increased subsidence after lava emplacement (Aguelmam Sidi Ali Lake) and some maar-like craters also have subsided after eruption, by karts formation. We lay out the structural and lithological controls on Karstic formation in an intraplate volcanic field based on limestones and evaporites.     

Polarimetric differential SAR interferometry in an arid natural environment

Ground deformation measurements have contributed to a better understanding of the processes and mechanisms involved in natural hazards. Those include landslides, subsidence, earthquakes and volcanic eruptions. Spaceborne Differential Interferometric Synthetic Aperture RADAR (DInSAR) is a well studied technique for measuring ground deformation. Quality of deformation measurements, however, is often degraded by decorrelation. With the advent of fully polarimetric SAR satellite sensors, polarimetric optimization techniques exploiting polarimetric diversity improve the phase quality of interferograms. In this paper, we analyzed three polarimetric optimization methods to determine the optimal one for application in an arid natural environment. We considered coherence decomposition in single and double phase center scenarios. Coherence estimation bias associated with each optimization method has been analyzed. We compared the derived displacement values with terrestrial GPS measurements. The study shows that polarimetric optimization increases the number of coherent pixels by upto 6.89% as compared with a single polarization channel. The study concludes that polarimetric optimization coupled with DInSAR analysis yields more reliable deformation results in a low coherence region.     

基于D-InSAR技术的金沙江地区滑坡形变监测与分析

滑坡是发生在我国山区的主要地质灾害类型,金沙江地区由于地势较高、地形复杂、多云多雨的特点,给传统的滑坡监测增加了难度。合成孔径雷达差分干涉测量技术(Differential interferometry synthetic aperture radar,D-InSAR)已在滑坡地面沉降监测中得到了广泛应用。本文选取金沙江上游沿岸作为研究区域,基于2018年8月11日与9月28日的Sentinel-1A影像及SRTM1数据,利用GAMMA软件及D-InSAR技术监测到金沙江地区的地表形变,成功识别出金沙江右岸的一处滑坡灾害。研究结果显示,在此滑坡的坡顶部分出现了约2.5 cm的沉降,而在坡底部分由于崩塌物的累积,地面出现了约3 cm的抬升。从实验结果可以得出,InSAR技术是一种有效的滑坡变形监测手段,利用Sentinel-1A卫星的SAR数据对滑坡区域进行形变监测,可以得到较好的干涉结果。     

Terrestrial laser scanning to estimate plot-level forest canopy fuel properties

This paper evaluates the potential of a terrestrial laser scanner (TLS) to characterize forest canopy fuel characteristics at plot level. Several canopy properties, namely canopy height, canopy cover, canopy base height and fuel strata gap were estimated. Different approaches were tested to avoid the effect of canopy shadowing on canopy height estimation caused by deployment of the TLS below the canopy. Estimation of canopy height using a grid approach provided a coefficient of determination of R² = 0.81 and an RMSE of 2.47 m. A similar RMSE was obtained using the 99th percentile of the height distribution of the highest points, representing the 1% of the data, although the coefficient of determination was lower (R² = 0.70). Canopy cover (CC) was estimated as a function of the occupied cells of a grid superimposed upon the TLS point clouds. It was found that CC estimates were dependent on the cell size selected, with 3 cm being the optimum resolution for this study. The effect of the zenith view angle on CC estimates was also analyzed. A simple method was developed to estimate canopy base height from the vegetation vertical profiles derived from an occupied/non-occupied voxels approach. Canopy base height was estimated with an RMSE of 3.09 m and an R² = 0.86. Terrestrial laser scanning also provides a unique opportunity to estimate the fuel strata gap (FSG), which has not been previously derived from remotely sensed data. The FSG was also derived from the vegetation vertical profile with an RMSE of 1.53 m and an R² = 0.87.     

Spectral properties of volcanic materials from hyperspectral field and satellite data compared with LiDAR data at Mt. Etna

Spectral properties of volcanic materials in the optical region (350–2500 nm) of the electromagnetic spectrum are analyzed. The goal is to characterize air-fall deposits, recent lava flows, and old lava flows based on their spectral reflectance properties and on the textural characteristics (grain size) of pyroclastic deposits at an active basaltic volcano. Data were acquired during a spectroradiometric field survey at Mt. Etna (Italy) in summer 2003 and combined with hyperspectral satellite (Hyperion) and airborne LiDAR (Light Detection and Ranging) data. In addition, air-fall deposits produced by the highly explosive 2002–2003 eruption have been sampled and spectrally characterized at different distances from the new vents. The spectral analysis shows that air-fall deposits are characterized by low reflectance values besides variations in grain size. This distinguishes them from other surface materials. Old lava flows show highest reflectance values due to weathering and vegetation cover. The spectral data set derived from the field survey has been compared to corrected satellite hyperspectral data in order to investigate the Hyperion capabilities to differentiate the surface cover using the reflectance properties. This has allowed us to identify the 2002–2003 air-fall deposits in a thematic image just few months after their emplacement. Moreover, the observed differences in the field spectra of volcanic surfaces have been compared with differences in the signal intensity detected by airborne LiDAR survey showing the possibility to include information on the texture of volcanic surfaces at Mt. Etna. The approach presented here may be particularly useful for remote and inaccessible volcanic areas and also represents a potentially powerful tool for the exploration of extraterrestrial volcanic surfaces.     

The airborne laser ranging system,its capabilities and applications

The Airborne Laser Ranging System is a proposed multibeam short pulse laser ranging system on board an aircraft. It simultaneously measures the distances between the aircraft and six laser retroreflectors (targets) deployed on the Earth's surface. Depending on the host aircraft and terrain characteristics, the system can interrogate hundreds of targets distributed over an area as large as 6×10⁴ sq. kilometers in a matter of hours. Potentially, a total of 1.3 million individual range measurements can be made in a six hour flight. The precision of these range measurements is approximately ±1 cm. These measurements are then used in a procedure which is basically an extension of trilateration techniques to derive the intersite vector between the laser ground targets. By repeating the estimation of the intersite vector, strain and strain rate errors can be estimated. These quantities are essential for crustal dynamic studies which include determination and monitoring of regional strain in the vicinity of active fault zones, land subsidence, and edifice building preceding volcanic eruptions.     

Estimating the parameters of forest inventory using machine learning and the reduction of remote sensing features

Locally computed statistics of image texture and a case-based reasoning (CBR) system were evaluated for mapping of forest attributes. Cluster analysis was preferred to regression models, as a pre-selection method of features. The best stand-based accuracy using satellite sensor images was 74.64 m⁻³ ha⁻¹ (36%) RMSE for stand volume, 1.98 m⁻³ ha⁻¹ a⁻¹ (49%) for annual increase in stand volume, where κ = 0.23 for stand growth classes and κ = 0.41 for dominant tree species in stands. The top pixel-based accuracy using orthophotos was 76.54 m⁻³ ha⁻¹ (41%) RMSE for stand volume, 1.87 m⁻³ ha⁻¹ a⁻¹ (44%) for annual increase in stand volume, where κ = 0.24 for stand growth classes and κ = 0.38 for dominant tree species in stands. Mean saturation in 30 m radius was the most useful feature when orthophotos were used, and standard deviation of Landsat ETM 6.2 values in 80 m radius was the best when satellite sensor images were used. The most valuable feature components (radii, channels and local statistics) for orthophotos were: 30 m kernel radius, lightness and the mean of pixel values; for satellite sensor images: 80 m kernel radius, near-infrared channel (ETM 4) and the mean of pixel values. Locally computed statistics.     

Ground deformation of Papandayan volcano before, during, and after the 2002 eruption as detected by GPS surveys

Papandayan is an A-type active volcano located in the southern part of Garut Regency, about 70 km southeast of Bandung, Indonesia. Its earliest recorded eruption, and the most violent and devastating outburst, occurred in 1772. The latest eruptions occurred in the period from 11 November–8 December 2002, and consisted of phreatic, freatomagmatic, and magmatic types of eruption. During the latest eruption period, GPS surveys were conducted at several points inside and around the crater in a radial mode, using the reference point located at the Papandayan observatory, about 10 km from the crater. At the points closest to the erupting craters, GPS displacements up to a few decimeters were detected, whereas at the points outside the crater, the displacements were at the centimeter level. The magnitude of displacements observed at each point also showed a temporal variation according to the eruption characteristics. The results show that deformation during eruption tends to be local, e.g. just around the crater. The pressure source is difficult to be properly modeled from GPS results, due to the limited GPS data available and differences in topography, geological structure, and/or rheology related to each GPS station.