L-band Advanced Land Observing Satellite Research Articles

InSAR-DEM Block Adjustment Model for Upcoming BIOMASS Mission: Considering Atmospheric Effects

The unique P-band synthetic aperture radar (SAR) instrument, BIOMASS, is scheduled for launch in 2024. This satellite will enhance the estimation of subcanopy topography, owing to its strong penetration and fully polarimetric observation capability. In order to conduct global-scale mapping of the subcanopy topography, it is crucial to calibrate systematic errors of different strips through interferometric SAR (InSAR) DEM (digital elevation model) block adjustment. Furthermore, the BIOMASS mission will operate in repeat-pass interferometric mode, facing the atmospheric delay errors introduced by changes in atmospheric conditions. However, the existing block adjustment methods aim to calibrate systematic errors in bistatic mode, which can avoid possible errors from atmospheric effects through interferometry. Therefore, there is still a lack of systematic error calibration methods under the interference of atmospheric effects. To address this issue, we propose a block adjustment model considering atmospheric effects. Our model begins by employing the sub-aperture decomposition technique to form forward-looking and backward-looking interferograms, then multi-resolution weighted correlation analysis based on sub-aperture interferograms (SA-MRWCA) is utilized to detect atmospheric delay errors. Subsequently, the block adjustment model considering atmospheric effects can be established based on the SA-MRWCA. Finally, we use robust Helmert variance component estimation (RHVCE) to build the posterior stochastic model to improve parameter estimation accuracy. Due to the lack of spaceborne P-band data, this paper utilized L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR data, which is also long-wavelength, to emulate systematic error calibration of the BIOMASS mission. We chose climatically diverse inland regions of Asia and the coastal regions of South America to assess the model’s effectiveness. The results show that the proposed block adjustment model considering atmospheric effects improved accuracy by 72.2% in the inland test site, with root mean square error (RMSE) decreasing from 10.85 m to 3.02 m. Moreover, the accuracy in the coastal test site improved by 80.2%, with RMSE decreasing from 16.19 m to 3.22 m.

Channel Imbalance Calibration Based on the Zero Helix of Bragg-like Targets

The calibration of channel imbalances is currently the main concern in polarimetric calibration (POLCAL) since the crosstalk of recent polarimetric synthetic aperture radar (Pol-SAR) systems is lower than −20 dB. The existing channel imbalance calibration method without corner reflectors utilizes both volume-dominated and Bragg-like targets. However, there are two limitations to using volume-dominated targets. One is that the inaccurate selection of volume-dominated areas in the uncalibrated Pol-SAR images has a negative influence on the estimation of cross-polarization (x-pol) channel imbalance, which subsequently impacts the estimation of copolarization (copol) channel imbalance. The other is that there are minimal volume-dominated areas in some special applications of Pol-SAR, such as planetary exploration. Thus, only selecting Bragg-like targets to estimate the values of both transmitting and receiving channel imbalances, which is proposed in this paper, can avoid the uncertainty brought about by selecting other distributed targets in an uncalibrated imaginary. In addition, the reciprocity assumption and characteristics corresponding to H/α¯ decomposition are introduced to eliminate the phase ambiguity for the first time. Compared with previous methods, our method had an obvious advantage in terms of universality, since Bragg-like targets are common in the most illuminating areas. The novel method was applied to both the simulated data from the L-band Advanced Land Observing Satellite (ALOS) and C-band GaoFen-3 (GF-3), and to real data with corner reflectors on site. The results from the simulated data showed that the errors of the amplitude and phase estimation were less than 0.5 dB and 5.0° in most topographical features. Meanwhile, the VV/HH terms from all trihedral corner reflectors were less than 0.3 dB for amplitude, and 5.5° for phase after calibration by using the estimated channel imbalances.

Application of L-band SAR for mapping tundra shrub biomass, leaf area index, and rainfall interception

Rapid shrub expansion has been observed across the Arctic, driving a need for regional-scale estimates of shrub biomass and shrub-mediated ecosystem processes such as rainfall interception. Synthetic-Aperture Radar (SAR) data have been shown sensitive to vegetation canopy characteristics across many ecosystems, thereby potentially providing an accurate and cost-effective tool to quantify shrub canopy cover. This study evaluated the sensitivity of L-band Advanced Land Observing Satellite 2 (ALOS-2) data to the aboveground biomass and Leaf Area Index (LAI) of dwarf birch and alder in the Trail Valley Creek watershed, Northwest Territories, Canada. The σ°VH /σ°VV ratio showed strong sensitivity to both LAI (R2 = 0.72 with respect to in-situ measurements) and wet aboveground biomass (R2 = 0.63) of dwarf birch. Our ALOS-2-derived maps revealed high variability of birch shrub LAI and biomass across spatial scales. The LAI map was fed into the sparse Gash model to estimate shrub rainfall interception, an important but under-studied component of the Arctic water balance. Results suggest that on average across the watershed, 17 ± 3% of incoming rainfall was intercepted by dwarf birch (during summer 2018), highlighting the importance of shrub rainfall interception for the regional water balance. These findings demonstrate the unexploited potential of L-band SAR observations from satellites for quantifying the impact of shrub expansion on Arctic ecosystem processes.

Mapping potential signs of gas emissions in ice of Lake Neyto, Yamal, Russia, using synthetic aperture radar and multispectral remote sensing data

Abstract. Regions of anomalously low backscatter in C-band synthetic aperture radar (SAR) imagery of lake ice of Lake Neyto in northwestern Siberia have been suggested to be caused by emissions of gas (methane from hydrocarbon reservoirs) through the lake’s sediments. However, to assess this connection, only analyses of data from boreholes in the vicinity of Lake Neyto and visual comparisons to medium-resolution optical imagery have been provided due to a lack of in situ observations of the lake ice itself. These observations are impeded due to accessibility and safety issues. Geospatial analyses and innovative combinations of satellite data sources are therefore proposed to advance our understanding of this phenomenon. In this study, we assess the nature of the backscatter anomalies in Sentinel-1 C-band SAR images in combination with very high resolution (VHR) WorldView-2 optical imagery. We present methods to automatically map backscatter anomaly regions from the C-band SAR data (40 m pixel spacing) and holes in lake ice from the VHR data (0.5 m pixel spacing) and examine their spatial relationships. The reliability of the SAR method is evaluated through comparison between different acquisition modes. The results show that the majority of mapped holes (71 %) in the VHR data are clearly related to anomalies in SAR imagery acquired a few days earlier, and similarities to SAR imagery acquired more than a month before are evident, supporting the hypothesis that anomalies may be related to gas emissions. Further, a significant expansion of backscatter anomaly regions in spring is documented and quantified in all analysed years 2015 to 2019. Our study suggests that the backscatter anomalies might be caused by lake ice subsidence and consequent flooding through the holes over the ice top leading to wetting and/or slushing of the snow around the holes, which might also explain outcomes of polarimetric analyses of auxiliary L-band Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) data. C-band SAR data are considered to be valuable for the identification of lakes showing similar phenomena across larger areas in the Arctic in future studies.

Mapping of High-Spatial-Resolution Three-Dimensional Electron Density by Combing of Full-Polarimetric SAR and IRI Model

Retrieval of ionospheric parameters from spaceborne synthetic aperture radar (SAR) and SAR interferometry (InSAR) observations has been developed in recent years due to its high spatial resolution. However, current studies are centered on the one-dimensional or two-dimensional ionospheric parameters, and there is a lack of retrieving three-dimensional ionospheric electron density. Based on this background, this study proposes an efficient method to map high-spatial-resolution three-dimensional electron density by combing of the full-polarimetric SAR images and international reference ionosphere (IRI) model. For a performance test of the proposed method, two L-band Advanced Land Observation Satellite (ALOS) Phase Array L-band SAR (PALSAR) full-polarimetric SAR images over Alaska regions are processed. The high-spatial-resolution ionospheric parameters, including vertical total electronic content (VTEC) and three-dimensional ionospheric electron density, are reconstructed over the study area. When comparing with the electron density derived from Poker Flat Incoherent Scatter Radar (PFISR) system, it is found that the IRI-derived electron density is obviously improved, where the standard deviations of differences between PFISR and IRI decrease respectively by about 2 times and 1.5 times compared to those before the correction, demonstrating the reliability of the proposed method. This study can help us better understand the characteristics of ionospheric variation in space.

Monitoring and Detecting Archaeological Features with Multi-Frequency Polarimetric Analysis

In remote sensing for archaeology, an unequivocal method capable of automatic detection of archaeological features still does not exists. Applications of Synthetic Aperture Radar (SAR) remote sensing for archaeology mainly focus on high spatial resolution SAR sensors, which allow the recognition of structures of small dimension and give information of the surface topography of sites. In this study we investigated the potential of combined dual and fully polarized SAR data and performed polarimetric multi-frequency and multi-incidence angle analysis of C-band Sentinel-1, L-band Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) and of C-band Radar Satellite-2 (RADARSAT-2) datasets for the detection of surface and subsurface archaeological structures over the United Nations Educational, Scientific and Cultural Organization (UNESCO) site of Gebel Barkal (Sudan). While PALSAR offers a good historical reference, Sentinel-1 time series provide recent and systematic monitoring opportunities. RADARSAT-2 polarimetric data have been specifically acquired in 2012/2013, and have been scheduled to achieve a multi-temporal observation of the archaeological area under study. This work demonstrated how to exploit a complex but significant dataset composed of SAR full polarimetric and dual polarimetric acquisitions, with the purpose of identifying the most suitable earth observation technique for the preservation and identification of archaeological features. The scientific potential of the illustrated analysis fits perfectly with the current delicate needs of cultural heritage; such analysis demonstrates how multi-temporal and multi-data cultural heritage monitoring can be applied not only for documentation purposes, but can be addressed especially to those areas exposed to threats of different nature that require a constant and prompt intervention plans.

A Decade of Ground Deformation in Kunming (China) Revealed by Multi-Temporal Synthetic Aperture Radar Interferometry (InSAR) Technique.

Large-scale urbanization has brought about severe ground subsidence in Kunming (China), threatening the stability of urban infrastructure. Mapping of the spatiotemporal variations of ground deformation is urgently needed, along with summarization of the causes of the subsidence over Kunming with the purpose of disaster prevention and mitigation. In this study, for the first time, a multi-temporal interferometric synthetic aperture radar (InSAR) technique with L-band Advanced Land Observation Satellite (ALOS-1) and X-band Constellation of Small Satellites for Mediterranean basin Observation (COSMO-SkyMed) data was applied to Kunming to derive the time series deformation from 2007 to 2016. The annual deformation velocity revealed two severe subsiding regions in Kunming, with a maximum subsidence of 35 mm/y. The comparison of the deformation between InSAR and leveling showed root-mean-square error (RMSE) values of about 4.5 mm for the L-band and 3.7 mm for the X-band, indicating that our results were reliable. We also found that the L-band illustrated a larger amount of subsidence than the X-band in the tested regions. This difference was mainly caused by the different synthetic aperture radar (SAR)-acquired times and imaging geometries between the L- and X-band SAR images. The vertical time series deformation over two severe subsiding regions presented an approximate linear variation with time, where the cumulative subsidence reached 209 mm during the period of 2007–2016. In view of relevant analyses, we found that the subsidence in Kunming was the result of soft soil consolidation, building load, and groundwater extraction. Our results may provide scientific evidence regarding the sound management of urban construction to mitigate potential damage to infrastructure and the environment.

Synthetic Aperture Radar Interferometry (InSAR) Ionospheric Correction Based on Faraday Rotation: Two Case Studies

Spaceborne synthetic aperture radar (SAR) imagery is affected by the ionosphere, resulting in distortions of the SAR intensity, phase, and polarization. Although several methods have been proposed to mitigate the ionospheric phase delay of SAR interferometry, the application of them with full-polarimetric SAR interferometry is limited. Based on this background, Faraday rotation (FR)-based methods are used in this study to mitigate the ionospheric phase errors on full-polarimetric SAR interferometry. For a performance test of the selected method, L-band Advanced Land Observation Satellite (ALOS) Phase Array L-band SAR (PALSAR) full-polarimetric SAR images over high-latitude and low-latitude regions are processed. The result shows that most long-wavelength ionospheric phase errors are removed from the original phase after using the FR-based method, where standard deviations of the corrected result have decreased by almost a factor of eight times for the high-latitude region and 28 times for low-latitude region, compared to those of the original phase, demonstrating the efficiency of the method. This result proves that the FR-based method not only can mitigate the ionospheric effect on SAR interferometry, but also can map the high-spatial-resolution vertical total electronic content (VTEC) distribution.

MONITORING OF IONOSPHERIC SCINTILLATION PHENOMENA USING SYNTHETIC APERTURE RADAR (SAR)

Abstract. The applications of synthetic aperture radars (SAR) have increased manifold in the past decade, which includes numerous Earth observation applications such as agriculture, forestry, disaster monitoring cryospheric- and atmospheric- studies. Among them, the potential of SAR for ionospheric studies is gaining importance. The susceptibility of SAR to space weather dynamics, and ionosphere in particular, comes at low frequencies of L- and P-bands. This paper discusses one such scintillation event that was observed by L-band Advanced Land Observation Satellite (ALOS)-2 Phased Array L-type SAR (PALSAR) over southern India on March 23, 2015. The sensors also acquired data sets on four other days on which the ionosphere was quiet. Ionospheric parameter measurements of total electron content (TEC) and amplitude scintillation (S4) index from ground-based Global Navigation Satellite System (GNSS) receiver at Tirunelveli was used to establish the ionospheric conditions on the days of SAR acquisition as well as to corroborate the S4 estimated from SAR. Multi-temporal ALOS-2 data sets were utilized to calculate S4 from two separate methods and the results have a good agreement with GNSS receiver measurements. This highlights the potential of SAR as an alternate technique of monitoring ionospheric scintillations that can be utilized as complementary to the highly accurate and dedicated measurements from the GNSS networks.

Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data

The estimation of above-ground biomass (AGB) in boreal forests is of special concern as it constitutes the highest carbon pool in the northern hemisphere. In particularly, monitoring of the forests in the Russian Federation is important as some regions have not been inventoried for many years. This study explores the combination of multi-frequency, multi-polarization, and multi-temporal radar data as one key approach to provide an accurate estimate of forest biomass. The data from L-band Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-Band Synthetic Aperture Radar 2 (PALSAR-2), together with C-band RADARSAT-2 data, were applied for AGB estimation. Backscatter coefficients from L- and C-band radar were used independently and in combination with a non-parametric model to retrieve AGB data for a boreal forest in Siberia (Krasnoyarskiy Kray). AGB estimation was performed using the random forests machine learning algorithm. The results demonstrated that high estimation accuracies can be achieved at a spatial resolution of 0.25 ha. When the L-band data alone were used for the retrieval, a corrected root-mean-square error (RMSEcor) of 29.4 t ha−1 was calculated. A marginal decrease in RMSEcor was observed when only the filtered L-band backscatter data, without ratio and texture, were used (29.1 t ha−1). The inclusion of the C-band data reduced the over and underestimation; the bias was reduced from 5.5 t ha−1 to 4.7 t ha−1; and a RMSEcor of 30.2 t ha−1 was calculated.

Using Dual-Polarization Interferograms to Correct Atmospheric Effects for InSAR Topographic Mapping

Atmospheric effect represents one of the major error sources for interferometric synthetic aperture radar (InSAR), particularly for the repeat-pass InSAR data. In order to further improve the practicability of InSAR technology, it is essential to study how to estimate and eliminate the undesired impact of atmospheric effects. In this paper, we propose the multi-resolution weighted correlation analysis (MRWCA) method between the dual-polarization InSAR data to estimate and correct atmospheric effects for InSAR topographic mapping. The study is based on the a priori knowledge that atmospheric effects is independent of the polarization. To find the identical atmospheric phase (ATP) signals of interferograms in different polarizations, we need to remove the other same or similar phase components. Using two different topographic data, differential interferometry was firstly performed so that the obtained differential interferograms (D-Infs) have different topographic error phases. A polynomial fitting method is then used to remove the orbit error phases. Thus, the ATP signals are the only identical components in the final obtained D-Infs. By using a forward wavelet transform, we break down the obtained D-Infs into building blocks based on their frequency properties. We then applied weighted correlation analysis to estimate the wavelet coefficients attributed to the atmospheric effects. Thus, the ATP signals can be obtained by the refined wavelet coefficients during inverse wavelet transform (IWT). Lastly, we tested the proposed method by the L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR dual-polarization SAR data pairs covering the San Francisco (USA) and Moron (Mongolia) regions. By using Ice, Cloud, and land Elevation Satellite (ICESat) data as the reference data, we evaluated the vertical accuracy of the InSAR digital elevation models (DEMs) with and without atmospheric effects correction, which shows that, for the San Francisco test site, the corrected interferogram could provide a DEM with a root-mean-square error (RMSE) of 7.79 m, which is an improvement of 40.5% with respect to the DEM without atmospheric effects correction. For the Moron test site, the corrected interferogram could provide a DEM with an RMSE of 10.74 m, which is an improvement of 30.2% with respect to the DEM without atmospheric effects correction.

Suitability of open-access elevation models for micro-scale watershed planning.

Watershed planning is a major issue in Turkey and other parts of the world. Surrounded by seawater on almost three-quarters of its international borders and by sheer mountains along the coastal regions and throughout the country, Turkey experiences a range of climatic changes, which constantly shape its topography. Recently, the occurrences of floods, landslides, and torrents have increased, forcing decision-makers to come up with solutions to manage and rehabilitate the upper watersheds in order to stop or limit the impact of disasters on downstream areas. Possible solutions should reduce flow coefficients, erosion, and sedimentation and increase reservoir capacities. It is expected that torrent volumes will decrease, drainage regimes on slopes will be better organized and adjusted, thawing snow will be better deposited and delayed, evapotranspiration will increase, surface runoffs will be delayed, and water regimes will be better managed, meaning that flood and torrent control will be achieved. For the reasons mentioned above, watershed parameters need to be firmly set. In the scope of this study, the elevation, slope acreage, and reservoir capacity of a small watershed, as extracted from open-access elevation models, were compared to a real-time kinematic (RTK) global positioning system (GPS)-generated point cloud and the resulting elevation model through various geospatial and analytical means. The Shuttle Radar Topography Mission (SRTM) C-band digital elevation model (DEM) (version 3) proved to be a satisfactory method in making residual, correlation, mean, and reservoir capacity comparisons. An L-band Advanced Land Observing Satellite (ALOS) phased-array-type synthetic aperture radar (PALSAR) and an X-band DLR_SRTM ASTER were slightly superior methods in terms of defining a greater number of slope categories than the other models. Finally, DLR_SRTM and SRTMv3 could match a greater number of slope façades than the other models. Seventeen years after its acquisition, SRTM and its derivatives have continued leading the topographic definition of the Earth.

L-Band Temporal Coherence Assessment and Modeling Using Amplitude and Snow Depth over Interior Alaska

Interferometric synthetic aperture radar (InSAR) provides the capability to detect surface deformation. Numerous processing approaches have been developed to improve InSAR results and overcome its limitations. Regardless of the processing methodology, however, temporal decorrelation is a major obstacle for all InSAR applications, especially over vegetated areas and dynamic environments, such as Interior Alaska. Temporal coherence is usually modeled as a univariate exponential function of temporal baseline. It has been, however, documented that temporal variations in surface backscattering due to the change in surface parameters, i.e., dielectric constant, roughness, and the geometry of scatterers, can result in gradual, seasonal, or sudden decorrelations and loss of InSAR coherence. The coherence models introduced so far have largely neglected the effect of the temporal change in backscattering on InSAR coherence. Here, we introduce a new temporal decorrelation model that considers changes in surface backscattering by utilizing the relative change in SAR intensity between two images as a proxy for the change in surface scattering parameters. The model also takes into account the decorrelation due to the change in snow depth between two images. Using the L-band Advanced Land Observation Satellite (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) data, the model has been assessed over forested and shrub landscapes in Delta Junction, Interior Alaska. The model decreases the RMS error of temporal coherence estimation from 0.18 to 0.09 on average. The improvements made by the model have been statistically proved to be significant at the 99% confidence level. Additionally, the model shows that the coherence of forested areas are more prone to changes in backscattering than shrub landscape. The model is based on L-band data and may not be expanded to C-band or X-band InSAR observations.

Investigating a reservoir bank slope displacement history with multi-frequency satellite SAR data

Slope instability arisen along with dam construction is a common problem of great concern in reservoir areas. Thus, displacement monitoring of active slopes is of great importance for the safety of dam operation. The unstable Guobu slope is located only about 1.5 km away from Laxiwa hydropower station in upstream Yellow River. In this study, Synthetic Aperture Radar (SAR) datasets acquired by C-band Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR), L-band Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar 2 (PALSAR-2), and X-band TerraSAR-X covering different evolution stages of Guobu slope were collected to investigate the displacement history so as to facilitate understanding of its deformation and failure mechanisms. The displacements occurred during the past decade were quantitatively identified for the first time by SAR pixel offset tracking analyses. The results show that before the reservoir impoundment, the maximum accumulative displacements on the slope were more than 7 m from 2003 to 2008, while the post-impoundment displacements also exceeded 7 m in just 1 year from September 2009 to September 2010. Furthermore, this slope is still in active deformation up to now. Nevertheless, the displacement rates seem decreased recently according to the interferometric results of TerraSAR-X data pairs from September 2015 to March 2016.

Ground deformation associated with exploitation of deep groundwater in Cangzhou City measured by multi-sensor synthetic aperture radar images

The magnitude and severity of ground deformation over time were investigated in Cangzhou City, Hebei Province, China. A total of 17 descending orbit C-band Envisat and 22 ascending orbit L-band Advanced Land Observing Satellite synthetic aperture radar (SAR) images covering the study area between the beginning of 2007 and the end of 2010 were integrated using an enhanced small baseline subset algorithm. The annual rates of ground deformation were retrieved from combined ASAR and PALSAR interferograms in our study area where the average subsidence reached 19 mm/a and subsidence rates up to 51 mm/a were observed. Subsidence in Cangzhou is mainly caused by the excessive abstraction of groundwater from a confined aquifer and consequently the ground subsides evenly over time. A multi-sensor SAR imaging technique was used to survey the extent and severity of ground deformation associated with the exploitation of deep groundwater in Cangzhou City. With abundant observations from different wavebands, the highly accurate ground subsidence result is not only sensitive to minor ground displacement but maintains fine coherence. Additionally, the temporal resolution is improved, and the sampling period is decreased to 5 days.

Mapping Annual Forest Cover in Sub-Humid and Semi-Arid Regions through Analysis of Landsat and PALSAR Imagery

Accurately mapping the spatial distribution of forests in sub-humid to semi-arid regions over time is important for forest management but a challenging task. Relatively large uncertainties still exist in the spatial distribution of forests and forest changes in the sub-humid and semi-arid regions. Numerous publications have used either optical or synthetic aperture radar (SAR) remote sensing imagery, but the resultant forest cover maps often have large errors. In this study, we propose a pixel- and rule-based algorithm to identify and map annual forests from 2007 to 2010 in Oklahoma, USA, a transitional region with various climates and landscapes, using the integration of the L-band Advanced Land Observation Satellite (ALOS) PALSAR Fine Beam Dual Polarization (FBD) mosaic dataset and Landsat images. The overall accuracy and Kappa coefficient of the PALSAR/Landsat forest map were about 88.2% and 0.75 in 2010, with the user and producer accuracy about 93.4% and 75.7%, based on the 3270 random ground plots collected in 2012 and 2013. Compared with the forest products from Japan Aerospace Exploration Agency (JAXA), National Land Cover Database (NLCD), Oklahoma Ecological Systems Map (OKESM) and Oklahoma Forest Resource Assessment (OKFRA), the PALSAR/Landsat forest map showed great improvement. The area of the PALSAR/Landsat forest was about 40,149 km2 in 2010, which was close to the area from OKFRA (40,468 km2), but much larger than those from JAXA (32,403 km2) and NLCD (37,628 km2). We analyzed annual forest cover dynamics, and the results show extensive forest cover loss (2761 km2, 6.9% of the total forest area in 2010) and gain (3630 km2, 9.0%) in southeast and central Oklahoma, and the total area of forests increased by 684 km2 from 2007 to 2010. This study clearly demonstrates the potential of data fusion between PALSAR and Landsat images for mapping annual forest cover dynamics in sub-humid to semi-arid regions, and the resultant forest maps would be helpful to forest management.

Coherent Change Detection Using InSAR Temporal Decorrelation Model: A Case Study for Volcanic Ash Detection

Detection of changes caused by major events-such as earthquakes, volcanic eruptions, and floods-from interferometric synthetic aperture radar (SAR) data is challenging because of the coupled effects with temporal decorrelation caused by natural phenomena, including rain, snow, wind, and seasonal changes. The coupled effect of major events and natural phenomena sometimes leads to misinterpretation of interferometric coherence maps and often degrades the performance of change detection algorithms. To differentiate decorrelation sources caused by natural changes from those caused by an event of interest, we formulated a temporal decorrelation model that accounts for the random motion of canopy elements, temporally correlated dielectric changes, and temporally uncorrelated dielectric changes of canopy and ground. The model parameters are extracted from the interferometric pairs associated with natural changes in canopy and ground using the proposed temporal decorrelation model. In addition, the cumulative distribution functions of the temporally uncorrelated model parameters, which are associated with natural changes in canopy and ground, are estimated from interferometric pairs acquired before the event. Model parameters are also extracted from interferometric SAR data acquired across the event and compared with the cumulative probabilities of natural changes in order to calculate the probability of a major event. Subsequently, pixels with cumulative probabilities greater than 75% are marked as changed due to the event. A case study for detecting volcanic ash during the eruption of the Shinmoedake volcano in January 2011 was carried out using L-band Advanced Land Observation Satellite PALSAR data.

Enhanced target characterization and improved scattering power decompositions using the optimized coherency matrix from full-polarimetric SAR data

ABSTRACTIn this article, a methodology is proposed for enhanced target characterization and improvement in scattering powers from model-based decomposition using full Polarimetric Synthetic Aperture Radar (PolSAR) data. The novelty of this approach is established by utilizing the degree of polarization (DOP) from full PolSAR data. The optimum degree of polarization (DOPopt) is obtained by maximizing the DOP estimated from each of the four Mueller matrices corresponding to the original 3 × 3 coherency matrix and the three unitary transformed (one real and two complex) coherency matrices, respectively. The optimized coherency matrix which corresponds to the is then used for the enhanced target detection using a polarimetric similarity measure. It is observed that the optimized coherency matrix corresponding to a target is much closer to an elementary target (i.e., either dihedral, trihedral or helix) with a canonical scattering mechanism than the original coherency matrix. Furthermore, it can be seen that the scattering powers obtained from the Freeman–Durden-model-based polarimetric decomposition technique using this optimized coherency matrix shows good improvement than using the original coherency matrix. The double-bounce power over the urban areas has increased for the L-band Airborne Synthetic Aperture Radar (AIRSAR) San Francisco data and for the L-band Advanced Land Observing Satellite 2 (ALOS2) Kyoto, Japan data compared to the original PolSAR data. Negative powers have also decreased by the use of this novel technique.

Anatomy of Subsidence in Tianjin from Time Series InSAR

Groundwater is a major source of fresh water in Tianjin Municipality, China. The average rate of groundwater extraction in this area for the last 20 years fluctuates between 0.6 and 0.8 billion cubic meters per year. As a result, significant subsidence has been observed in Tianjin. In this study, C-band Envisat (Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) images and L-band ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) data were employed to recover the Earth’s surface evolution during the period between 2007 and 2009 using InSAR time series techniques. Similar subsidence patterns can be observed in the overlapping area of the ASAR and PALSAR mean velocity maps with a maximum radar line of sight rate of ~170 mm·year−1. The west subsidence is modeled for ground water volume change using Mogi source array. Geological control by major faults on the east subsidence is analyzed. Storage coefficient of the east subsidence is estimated by InSAR displacements and temporal pattern of water level changes. InSAR has proven a useful tool for subsidence monitoring and displacement interpretation associated with underground water usage.

The Influence of Equatorial Scintillation on L-Band SAR Image Quality and Phase

It is well known that many of the nighttime acquisitions of the L-band Advanced Land Observing Satellite (ALOS) Phased Array-type L-band Synthetic Aperture Radar (PALSAR) instrument over equatorial regions show significant distortions of the image amplitude information. These distortions have the form of amplitude stripes that are roughly aligned with the local geomagnetic field. While ionospheric scintillation has been identified as the source of these distortions, the exact nature of the induced artifacts on synthetic aperture radar (SAR) image quality and SAR signal phase has not yet been studied in sufficient detail. Hence, this paper provides a quantitative analysis of equatorial scintillation effects on SAR image quality and SAR phase. We have performed a statistical analysis of ALOS PALSAR images over equatorial regions to describe the observed distortions and relate them to ionospheric parameters. An ionospheric simulator was developed and validated that is capable of simulating ionospheric distortions based on ionospheric scintillation parameters. Using this simulator, we found that ionospheric scintillation in the equatorial zone can cause significant distortions of SAR image amplitudes, image focus, and SAR signal phase. We determined threshold ionospheric environmental conditions that lead to the formation of these image distortions. Based on these thresholds, we quantified the likelihood of occurrence of ionospheric distortions for the global equatorial belt and for L-band sensors ALOS PALSAR, ALOS-2 PALSAR-2, and NASA-ISRO SAR (NISAR).