Surface displacement of the Mw 7 Machaze earthquake (Mozambique): Complementary use of multiband InSAR and radar amplitude image correlation with elastic modelling

In this paper we investigate the surface displacement related to the 2006 Machaze earthquake using Synthetic Aperture Radar Interferometry (InSAR) and sub-pixel correlation (SPC) of radar amplitude images. We focus on surface displacement measurement during three stages of the seismic cycle. First, we examined the co-seismic stage, using an Advanced SAR (ASAR) sensor onboard the Envisat satellite. Then we investigated the post-seismic stage using the Phase Array L-band SAR sensor (PALSAR) onboard the ALOS satellite. Lastly, we focussed on the inter-seismic stage, prior to the earthquake by analysing the L-band JERS-1 SAR data. The high degree of signal decorrelation in the C-band co-seismic interferogram hinders a correct positioning of the surface rupture and correct phase unwrapping. The post-seismic L-band interferograms reveal a time-constant surface displacement, causing subsidence of the surface at a ∼ 5 cm/yr rate. This phenomenon continued to affect the close rupture field for at least two years following the earthquake and intrinsically reveals a candidate seismogenic fault trace that we use as a proxy for an inversion against an elastic dislocation model. Prior to the earthquake, the JERS interferograms do not indicate any traces of pre-seismic slip on the seismogenic fault. Therefore, slip after the earthquake is post-seismic, and it was triggered by the Machaze earthquake. This feature represents a prominent post-seismic slip event rarely observed in such a geodynamic context.     

Mapping land cover types in the Amazon Basin using 1 km JERS-1 mosaic

During the Global Rain Forest Mapping (GRFM) project, the JERS-1 SAR (Synthetic Aperture Radar) satellite acquired wall-to-wall image coverage of the humid tropical forests of the world. The rationale for the project was to demonstrate the application of spaceborne L-band radar in tropical forest studies. In particular, the use of orbital radar data for mapping land cover types, estimating the area of floodplains, and monitoring deforestation and forest regeneration were of primary importance. In this paper we examine the information content of the JERS-1 SAR data for mapping land cover types in the Amazon basin. More than 1500 high-resolution (12.5 m pixel spacing) images acquired during the low flood period of the Amazon river were resampled to 100 m resolution and mosaicked into a seamless image of about 8 million km², including the entire Amazon basin. This image was used in a classifier to generate a 1 km resolution land cover map. The inputs to the classifier were 1 km resolution mean backscatter and seven first-order texture measures derived from the 100 m data by using a 10 x 10 independent sampling window. The classification approach included two interdependent stages. First, a supervised maximum a posteriori Baysian approach classified the mean backscatter image into five general cover categories: terra firme forest (including secondary forest), savanna, inundated vegetation, open deforested areas and open water. A hierarchical decision rule based on texture measures was then applied to attempt further discrimination of known subcategories of vegetation types based on taxonomic information and woody biomass levels. True distributions of the general categories were identified from the RADAMBRASIL project vegetation maps and several field studies. Training and validation test sites were chosen from the JERS-1 image by consulting the RADAM vegetation maps. After several iterations and combining land cover types, 14 vegetation classes were successfully separated at the 1 km scale. The accuracy of the classification methodology was estimated to be 78% when using the validation sites. The results were also verified by comparison with the RADAM- and AVHRR-based 1 km resolution land cover maps.     

Motion patterns of Nabesna Glacier (Alaska) revealed by interferometric SAR techniques

Nabesna Glacier is one of the longest land-terminus mountain glaciers in North America. However, its flow has never been studied. We derived detailed motion patterns of Nabesna Glacier in winter and spring 1994–1996 from the synthetic aperture radar (SAR) images acquired by the European Remote Sensing satellites (ERS-1 and ERS-2) using interferometric SAR (InSAR) techniques. Special effort was made to assess the accuracy of the motion estimates, and remove data points with high uncertainty from the motion profiles, enabling us to obtain reliable glacier flow patterns along the highly curved main course of Nabesna Glacier. The results, covering 80 km of the 87 km main course of the glacier, were used to delineate four distinctive sections in terms of spatial and temporal variability of the glacier speed: (1) the upper section where glacier flow was apparently random both temporally and spatially presumably due to development of crevasses; (2) the upper-middle section with relatively steady flow around 0.27 to 0.4 m/day; (3) the middle section with a stable pattern of acceleration from 0.27–0.3 m/day to the maximum about 0.67–0.73 m/day, followed by a general deceleration to 0.17–0.33 m/day before reaching (4) the lower section where the glacier motion was generally slow yet highly variable although uncertainty in the estimation is high. Occurrence of the flow maximum, as well as many local maxima and minima at consistent locations over different periods suggests that the valley geometry affect the overall flow pattern. On top of this general trend, many small-scale temporal/spatial variations in the glacier flow patterns were observed along the glacier, especially in the lower sections. On average, the flow speeds were in the range of 0.3 to 0.7 m/day; however this lacks any measurements of summer flow speeds which are expected to be significantly higher.     

Estimation of tree growth in a conifer plantation over 19 years from multi-satellite L-band SAR

The general capability of synthetic aperture radar (SAR) for monitoring forest ecosystems is well documented. However, the majority of SAR studies of forest dynamics use only imagery acquired by one SAR system and are thus limited to the lifecycle of a particular satellite. The synergistic analysis of SAR data from one of the earliest spaceborne SAR missions, the SEASAT mission, with the Japanese JERS-1 satellite-borne SAR is presented. Biophysical parameters frequently retrieved from SAR are tree biomass using backscatter and tree height from the interferometric phase. One potential application that has not been thoroughly examined is mapping of incremental tree growth from SAR backscatter changes. Tree growth measures biomass changes over time, and is correlated to the amount of carbon sequestered by the trees. This paper examines the retrieval of tree growth from multitemporal spaceborne L-band SAR. A SEASAT SAR image from 1978 and a JERS-1 SAR image from 1997 over Thetford forest, UK are used to retrieve tree growth of Corsican Pine stands. Incremental growth was estimated from the changes in backscatter coefficient, and compared to the expected tree growth from general yield class models used by the UK Forestry Commission. The accuracy of the retrieval algorithm depends on the minimum forest stand size included in the analysis. For managed forest plantations, multitemporal L-band SAR has some potential for detecting incremental biomass to support sustainable forest management.     

Movement estimate of the Dongkemadi Glacier on the Qinghai–Tibetan Plateau using L-band and C-band spaceborne SAR data

We measured the complex motion of the Dongkemadi Glacier on Tanggula Mountain, Qinghai–Tibetan Plateau, using two-pass differential synthetic aperture radar interferometry (InSAR) with satellite L-band and C-band SAR data. We derived detailed motion patterns of the Dongkemadi Glacier for the winter seasons of 1996, 2007 and 2008 using a European Remote sensing Satellite-1/2 (ERS-1/2) tandem InSAR pair acquired from descending orbit and a 46-day-separation Advanced Land Observing Satellite (ALOS) InSAR pair acquired from ascending orbit. In this article, we focus on an analysis of the glacier's surface motion features and a validation of the results from the InSAR using Global Positioning System (GPS) survey data. The experimental results show that the glacier flow distribution displays strong spatial variations depending on elevation. The glacier is divided into four clearly defined fast-flowing units in terms of spatial variability of the glacier speed, with evidence from both ERS and ALOS/PALSAR InSAR pairs (palsar – Phased Array type L-band Synthetic Aperture Radar). Among the four fast-flowing units, three are on the Dadongkemadi Glacier (DDG) and one on the Xiaodongkemadi Glacier (XDG). The flow patterns are generally characterized by terrain complexity for both glacier branches. The upper central area of the DDG shows slow movement, maybe due to the convergent and uptaking effect of ice from steep slope areas with opposite flow directions.     

Estimation and validation of glacier surface motion in the northwestern Himalayas using high-resolution SAR intensity tracking

We estimate two-dimensional (2D) glacier surface motion using synthetic aperture radar (SAR) X-band intensity tracking. It has been observed that the viability of SAR interferometry (InSAR) is often limited by coherence loss over glaciers in landlocked regions using SAR data pairs of more than 1 day temporal baseline. An alternative to InSAR is the intensity-tracking approach, which relies on intensity cross-correlation for the estimation of subpixel surface motion in range and azimuth direction. In this work, we apply this approach for 2D glacier surface motion estimation in the north-western (NW) Himalayas, using TerraSAR-X (TS-X) spotlight mode high-resolution data pairs of 11, 22, and 33 day temporal separation. The results are in good agreement with total station surveying measurements synchronous with the satellite data acquisition period. The technique is found to be highly appropriate for monitoring the flow rate of glaciers in the Himalayas on a multitemporal basis.     

Bara Shigri and Chhota Shigri glacier velocity estimation in western Himalaya using Sentinel-1 SAR data

In this article, we have presented surface velocity estimation of Chhota Shigri (CS) and Bara Shigri (BS) glaciers in the Himalaya using C-band synthetic aperture radar (SAR) data from Sentinel-1 (S-1). Repeat-pass SAR image subpixel offset tracking has been used to generate velocity vectors from yearly and seasonal S-1 data sets. SAR offset tracking on the basis of maximum intensity correlation provided the two-dimensional (2-D) movement of the both CS and BS glaciers of Chandra valley in western Himalaya. Movement of the glacier has been observed in the terminus to ablation zone during 2014–2018. S-1-derived movement is compared with in-situ measurement over CS glacier, and it has shown approximately 25% deviation during 2015–2016 with respect to field measurements from 2009 to 2010. Similar to previous decade observations, S-1 offset tracking movement results of recent three years have shown a decreasing trend.     

Estimation of rice-planted area in the tropical zone using a combination of optical and microwave satellite sensor data

The area planted with rice in Indramayu Province, Indonesia was estimated using satellite sensor data. We determined the arable land area using Landsat Thematic Mapper (TM) data acquired in the dry season and identified newly rice-planted fields using JERS-1 Synthetic Aperture Radar (SAR) data acquired in the rainy season (planting season). Two rice crops per year are common and rice is not planted simultaneously in this region. Since the planted area changes monthly, some asumptions were necessary for estimating the planted area. Our estimates suggested that the actual rice-planted area in Indonesia was 12-14% smaller than that reported by the Indonesian government.     

Comparison of annual changes in winter ERS-1 SAR images and glacier mass balance of Slakbreen,Svalbard

The Arctic glaciers are sensitive to climate change, and glacier mass balance is used as an indicator of climate change. However, few mass balance observations are available from the Arctic region. Winter ERS-1 SAR images of the Arctic glacier Slakbreen (78degreesN, 16degrees 30'E) on Svalbard were analysed to investigate a possible relation between SAR backscatter and temporal variations in glacier mass balance. A winter ERS-1 SAR image acquired in 1993 after a summer with large ablation was compared with a winter ERS-1 SAR image acquired after the following summer with low ablation. Changes in mass balance from one year to another were difficult to detect using SAR backscatter data only. Comparison of ground-penetrating radar and SAR data showed that the SAR data contain a signal of the near-surface glacier properties. SAR data were interpreted to reflect variations in accumulation and ablation integrated over several years.     

Deformation mapping in three dimensions for underground mining using InSAR – Southern highland coalfield in New South Wales,Australia

This article presents 3D surface deformation mapping results derived from satellite synthetic aperture radar (SAR) data acquired over underground coal mines. Both ENVISAT Advanced Synthetic Aperture Radar (ASAR) and Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data were used in this study. The quality of the 3D deformation mapping results due to underground mining is mainly limited by two factors. (1) Differential interferometric synthetic aperture radar (DInSAR) is less sensitive to displacement along the north–south direction in the case of the current SAR satellite configurations. (2) The mining-induced displacement is continuous and nonlinear; and the accuracy of the 3D DInSAR measurement is severely affected by the similar but non-identical temporal overlaps of the InSAR pairs. The simulation and real data analyzes have shown that it would be more practical to use DInSAR pairs with the assumption of negligible northing displacement to derive the displacements in the easting and vertical directions. The northing displacement could then be estimated from the residuals. This limitation could be overcome in the future with the launch of more radar satellites, which would provide better viewing geometry.     

Surface movements in Bologna (Po Plain — Italy) detected by multitemporal DInSAR

We studied the surface deformations affecting the southeastern sector of the Po Plain sedimentary basin, in particular the area of Bologna. To this aim an advanced DInSAR technique, referred to as DInSAR-SBAS (Small BAseline Subset), has been applied. This technique allows monitoring the temporal evolution of a deformation phenomenon, via the generation of mean deformation velocity maps and displacement time series from a data set of acquired SAR images. In particular, we have processed a set of SAR data acquired by the European Remote Sensing Satellite (ERS) sensors and compared the achieved results with optical levelling measurements, assumed as reference. The surface displacements detected by DInSAR SBAS from 1992 to 2000 are between 10 mm/year in the historical part of Bologna town, and up to 59 mm/year in the NE industrial and agricultural areas. Former measurements from optical levelling referred to 1897 show 2-3 mm/year vertical movements. This trend of displacement increased in the second half of the 20th century and the subsidence rate reached 60 mm/year. We compared the more recent levelling campaigns (in 1992 and late 1999) and DInSAR results from 1992 to 1999. The standard deviation of the difference between levelling data, projected onto the satellite Line Of Sight, and DInSAR results is 2 mm/year. This highlights a good agreement between the measurements provided by two different techniques. The explanation of soil movements based on interferometric results, ground data and geological observations, allowed confirming the anthropogenic cause (surface effect due to the overexploitation of the aquifers) and highlights a natural, tectonic, subsidence.     

A new algorithm for forest height estimation based on the varied extinction random volume over ground (VERVoG) model using PolInSAR data

ABSTRACT

This paper examines a simple geometrical method for forest height estimation using single-baseline single frequency polarimetric synthetic aperture radar interferometry (PolInSAR) data. The suggested method estimates the forest biophysical parameters based on the varied extinction random volume over ground (VERVoG) model with top layer extinction greater than zero. We approach the problem using a geometrical method without the need for any auxiliary data or prior information. The biophysical parameters, i.e. top layer extinction value, forest height and extinction gradient are estimated in two separate stages. In this framework, the offset value of the extinction is estimated in an independent procedure as a function of a geometrical index based on the signal penetration in the volume layer. As a result, two remaining biophysical parameters can be calculated in a geometrical way based on the observed volume coherence. The proposed algorithm was evaluated using the L-band PolInSAR data of the European Space Agency (ESA) BioSAR 2007 campaign. A pair of experimental SAR (ESAR) images was acquired over the Remningstorp test site in southern Sweden. The selected images were employed for the performance analysis of the proposed approach in the forest height estimation application based on the VERVoG model. The experimental result shows that the proposed inversion method based on the VERVoG model with top layer extinction greater than zero estimates the volume height with an average root mean square error (RMSE) of 2.08 m against light detection and ranging (LiDAR) heights. It presents a significant improvement of forest height accuracy, i.e. 4.1 m compared to the constant extinction RVoG model result, which ignores the forest heterogeneity in the vertical direction.     

Forest canopy height and carbon estimation at Monks Wood National Nature Reserve, UK, using dual-wavelength SAR interferometry

Forest canopy height is a critical parameter in better quantifying the terrestrial carbon cycle. It can be used to estimate aboveground biomass and carbon pools stored in the vegetation, and predict timber yield for forest management. Polarimetric SAR interferometry (PolInSAR) uses polarimetric separation of scattering phase centers derived from interferometry to estimate canopy height. A limitation of PolInSAR is that it relies on sufficient scattering phase center separation at each pixel to be able to derive accurate forest canopy height estimates. The effect of wavelength-dependent penetration depth into the canopy is known to be strong, and could potentially lead to a better height separation than relying on polarization combinations at one wavelength alone. Here we present a new method for canopy height mapping using dual-wavelength SAR interferometry (InSAR) at X- and L-band. The method is based on the scattering phase center separation at different wavelengths. It involves the generation of a smoothed interpolated terrain elevation model underneath the forest canopy from repeat-pass L-band InSAR data. The terrain model is then used to remove the terrain component from the single-pass X-band interferometric surface height to estimate forest canopy height. The ability of L-band to map terrain height under vegetation relies on sufficient spatial heterogeneity of the density of scattering elements that scatter L-band electromagnetic waves within each resolution cell. The method is demonstrated with airborne X-band VV polarized single-pass and L-band HH polarized repeat-pass SAR interferometry using data acquired by the E-SAR sensor over Monks Wood National Nature Reserve, UK. This is one of the first radar studies of a semi-natural deciduous woodland that exhibits considerable spatial heterogeneity of vegetation type and density. The canopy height model is validated using airborne imaging LIDAR data acquired by the Environment Agency. The rmse of the LIDAR canopy height estimates compared to theodolite data is 2.15 m (relative error 17.6%). The rmse of the dual-wavelength InSAR-derived canopy height model compared to LIDAR is 3.49 m (relative error 28.5%). From the canopy height maps carbon pools are estimated using allometric equations. The results are compared to a field survey of carbon pools and rmse values are presented. The dual-wavelength InSAR method could potentially be delivered from a spaceborne constellation similar to the TerraSAR system.     

A method to estimate forest biomass and its application to monitor Mongolian Taiga using JERS-1 SAR data

This study presents a technique and potential utilization of JERS-1 Synthetic Aperture Radar (SAR) data for the estimation of Taiga species biomass in the Huvsgul Lake basin, Mongolia. In order to develop algorithms for estimating total stand biomass, shapes of the tree trunks were considered. A least-squares method was used to define tree trunk shape coefficients, which were then used to estimate total stand biomass using ground data. L-band data confirmed the backscattering coefficient to be dependent upon not only the quantity of biomass, but also tree parameters. The relationship between backscattering coefficient and forest stand biomass in slope areas of the study area was obtained.     

JERS-1/SAR backscatter and its relationship with biomass of regenerating forests

It has been hypothesized that regenerating tropical forests are large atmospheric carbon sinks. Accurate estimates of the location, extent and biomass of regenerating tropical forests are needed in order to quantify their contribution to global carbon budgets. Synthetic Aperture Radar (SAR) data are independent of near-constant tropical cloud cover and have proved useful for locating and mapping the extent of regenerating tropical forests. To estimate the biomass of regenerating tropical forests we need to determine the nature and strength of the relationship between radar backscatter and biomass for different types of regenerating forest. To further investigate this, two extreme forms of regenerating forest were considered; they were block-logged (clear-cut) forest in the Tapajós area of Pará State, Brazil and selectively-logged forest in Southern Cameroon. Biomass was estimated alometrically for 15 plots in Tapajós and 34 plots in Cameroon and was related to L-band backscatter derived from the JERS-1 SAR. The relationship between backscatter and biomass was strong for the Tapajós study area and weak for the Cameroonian study area. It was concluded that there is potential for the use of JERS-1/SAR to locate, map and estimate biomass for young regenerating forests following block-logging rather than selective-logging.     

Perito Moreno Glacier (Argentina) flow estimation by COSMO SkyMed sequence of high-resolution SAR-X imagery

The Perito Moreno Glacier (Los Glaciares National Park, Patagonia, Argentina) ice stream has been investigated using X-band SAR amplitude images collected from February to December 2009 (excluding June) at time intervals of 8 and 16 days by the COSMO SkyMed satellites. The high spatial resolution dataset (10 × 10 km swath, 1 m per pixel) reveals many details of the glacier surface and the ice velocity fields extracted from sequential image pairs by the maximum cross-correlation method cover most of the glacier area. The efficiency of the cross-correlation method improves with high spatial resolution imagery and the co-registration error of the image pair also reduces. The glacier motion detected in the period shows variability on the time scale considered, evidencing the areas of higher dynamics under different speed regimes.     

Monitoring migration rates of an active subarctic dune field using optical imagery

We developed a novel method to quantify subtle rates of landscape evolution using two satellite imaging systems with different viewing angles and spectral sensitivities. We selected the slowly migrating, high-latitude, subarctic Great Kobuk Sand Dunes (GKSD), Kobuk Valley National Park, Alaska (USA), for our study. The COSI-Corr technique was used for precise orthorectification, co-registration, and subpixel correlation of satellite data. ASTER Visible Near Infrared (VNIR) and SPOT Panchromatic images with a 5-year temporal separation were correlated to measure the horizontal velocity of the GKSD. To reduce correlation noise, ASTER VNIR bands were linearly mixed to match the SPOT Panchromatic band, and raw correlation measurements were projected onto a local robust migration direction to estimate unbiased velocity magnitudes. The results show that the most likely migration rate for the GKSD ranges from 0.5 to 1.5 m/year, with peak velocities up to 3.8 m/year, and uncertainty of approximately 0.16 m/year. The unprecedented ability to measure slow migration rates, including those that may occur over a relatively short time interval, illustrates the value of this method to reliably detect and monitor subtle ground movements including dune migration, glacier flow, mass movements, and other small-scale processes.     

A technique to estimate topsoil thickness in arid and semi-arid areas of north-eastern Jordan using synthetic aperture radar data

A Japanese Earth Resources Satellite (JERS)-1 L-band synthetic aperture radar (SAR) dataset was used for estimating topsoil thickness, of different types, in arid and semi-arid areas in north-eastern Jordan. In this research, the relationship between remotely sensed data, backscattering coefficient and the thickness of topsoil was investigated. Based on the dielectric constant properties of the topsoil samples, the relationship between the backscattering coefficient and the topsoil thickness was obtained by developing a multilayer modelling analysis. Using this model, the topsoil thickness had been estimated by means of the derived backscattering coefficients from JERS-1 SAR image. The estimated thickness values of the different topsoil types were found to be comparable with field ground data. The estimated minimum thickness for hardpan topsoil is 55?cm; Qaa topsoil, 74?cm; and topsoil of herbaceous area, 46?cm, while the estimated maximum thickness is more than 98?cm, more than 100?cm, and 82?cm, respectively. Ground data, on the other hand, revealed the minimum thickness for hardpan topsoil to be 50?cm; Qaa topsoil, 70?cm; and topsoil of herbaceous area, 40?cm, while the maximum thickness is more than 120?cm, more than 100?cm, and 80?cm, respectively.     

基于纹理的雷达与多光谱遥感数据小波融合研究

众所周知,多光谱与雷达影像融合具有重要的意义,但雷达影像小尺度的纹理特征在先前的融合方法中却没有被考虑。为了更好地对多光谱与雷达影像进行融合,基于双正交小波变换,提出了一种小尺度纹理影像参与融合的三影像小波融合方法。该方法借鉴多通道滤波及基于亮度调节的平滑滤波(SFIM)融合的原理,首先提取多时相雷达影像的小尺度纹理数据;然后再将该纹理数据、单时相JERS-1SAR数据及TM多光谱数据进行小波融合。分析表明,该方法的融合结果较雷达与多光谱影像小波融合的结果不仅具有更丰富的光谱特征,而且由于继承了雷达影像丰富的小尺度纹理特征,因而具有更高的清晰度。实验证明,该方法可获得较好的融合结果,是一种切实有效的融合法。     

Semi-automated feature-tracking of East Antarctic sea ice from Envisat ASAR imagery

While feature tracking of sea ice using cross-correlation methods on pairs of satellite Synthetic Aperture Radar (SAR) images has been extensively carried out in the Arctic, this is not the case in the Antarctic. This is due to the dynamic nature of Antarctic pack ice, its microwave signature, the tendency for SAR swath paths to be poorly aligned with the often narrow sea ice zone around the continent and inadequate satellite sampling. A semi-automated system, known as IPADS (IMCORR [IMageCORRelation] Processing, Analysis and Display System), has been developed to map fast ice and pack ice in Antarctica using multiple pairs of SAR images. The software processing pipeline uses overlapping image pairs which are geocoded and roughly registered using only data contained in the image headers. Next, fast ice maps are rapidly generated using zero motion features located within ocean regions. This also provides precise image registration. Finally, the same image pairs are re-examined for pack ice motion in a slower off-line batch process. The pack and fast ice are identified using a cluster-based search method which compares both location and motion information. Each image pair generates a NetCDF file which adds to a growing database of Antarctic sea ice motion and ice roughness. Five image-pair examples are presented to illustrate the methods used as well as their strengths and limitations. Substantial pack ice motion can often be detected in the marginal ice zone on SAR images only a few days apart.