A Phase-Decomposition-Based PSInSAR Processing Method Cao, Ning; Lee, Hyongki; Jung, Hahn Chul
IEEE transactions on geoscience and remote sensing,
2016-Feb., 2016-2-00, 20160201, Letnik:
54, Številka:
2
Journal Article
Recenzirano
A phase-decomposition-based persistent scatterer (PS) InSAR (PD-PSInSAR) method is developed in this paper to improve coherence and spatial density of measurement points (MPs). In order to improve PS ...network density, a distributed scatterer (DS) has been utilized in some advanced PSInSAR process, such as SqueeSAR. In addition to the conventional DS that consists of independent small scatterers with a uniform scattering mechanism, processing the DSs dominated by two or more scattering mechanisms is a promising way to improve MP density. Estimating phases from DS with multiple scattering mechanisms is difficult for many DS algorithms because of the interference between different scattering mechanisms. Recently, a covariance-matrix-decomposition-based method, which is named Component extrAction and sElection SAR (CAESAR), is proposed to extract different scattering components from the analysis of the covariance matrix. Instead of using a covariance matrix, the PD-PSInSAR in this study is developed to perform eigendecomposition on a coherence matrix, in order to estimate the phases corresponding to the different scattering mechanisms, and then to implement these estimated phases in a conventional PSInSAR process. The major benefit of using a coherence matrix rather than a covariance matrix is to compensate the amplitude unbalances among SAR images. A detailed study of comparison among SqueeSAR, CAESAR, and PD-PSInSAR is also performed in this study. It has been found that these three methods share very similar mathematic forms with different weight values. The PD-PSInSAR method is implemented to estimate land deformation over the greater Houston area using Envisat ASAR images, which verifies that the proposed method can detect more MPs and provide better coherences.
To improve the spatial density of measurement points of persistent-scatterer interferometry, distributed scatterer (DS) should be considered and processed. An important procedure in DS interferometry ...is the phase triangulation (PT). This letter introduces two modified PT algorithms (i.e., equal-weighted PT and coherence-weighted PT) and analyzes the mathematical relations between different published PT methods (i.e., the maximum-likelihood phase estimator, least squares estimator, and eigendecomposition-based phase estimators). The analysis shows that the above five PT methods share very similar mathematical forms with different weight values in the estimation procedure.
Water level dynamics in continental‐scale rivers is an important factor for surface water studies and flood hazard management. However, most continental‐scale river models have not focused on the ...reproduction of water level because the storage and movement of surface waters are regulated by smaller‐scale topography than their grid resolutions. Here we analyzed the water level dynamics simulated by a state‐of‐the‐art global river model, CaMa‐Flood, with subgrid representation of floodplain topography. As a case study, hydrodynamics simulation in the Amazon River was accomplished, and the simulated water surface elevations along the main stem were compared against Envisat altimetry. The seasonal cycles of the simulated water surface elevations are in agreement with the altimetry (correlation coefficient >0.69, annual amplitude error <1.6 m). The accuracy of absolute water surface elevations was also good (averaged RMSE of 1.83 m), and the associated errors were within the range of the model uncertainty due to channel cross‐section parameters. Then the ocean tide variation at river mouth was incorporated for simulating the tidal effect in the inland Amazon basin, which requires realistic representation of absolute water surface elevations. By applying power spectra analysis to the simulated water level variations, the 15 day cycle due to spring and neap tides was detected at Obidos, located 800 km upstream from the river mouth. The reproduction of the ocean tide propagation to the inland region suggests that CaMa‐Flood includes the main physical processes needed to accurately simulate the water level dynamics in continental‐scale rivers.
Key Points
Accuracy of water surface elevation simulated by a continental‐scale river
Simulation accuracy adequate for direct comparison against satellite altimeter
Representation of ocean tide variation propagating to the inland Amazon basin
Radar satellite altimeters are widely used in offshore areas, whereas they are underutilized in coastal areas due to a number of interference factors. Altimeter satellite data can be used to ...summarize elevation information at 1 Hz for offshore areas, but for areas close to land, it is more effective to utilize imagery with a resolution of 20 Hz to provide a more detailed representation. The use of highresolution satellite altimeter data is expected to increase the amount of data available for hydrological data such as complex coastlines and small lakes. Therefore, in this study, we investigated the applicability of 20 Hz altimeter data in the Korean Peninsula. First, the accuracy was analyzed by comparing the 20 Hz altimeter data from the Jason-3 satellite with the Ulleungdo tide data. Second, we compared the 20 Hz altimeter data from the Sentinel-3A satellite with the water level data of Soyang Lake to see if it can be applied to land areas. In the case of inland lakes, the water level is estimated to be affected by the discharge volume due to heavy rainfall in summer, and it was determined that the satellite altimeter data can be utilized. Therefore, utilizing the data from this study is expected to improve the accuracy of hydrological analysis in coastal and lake environments.
Synthetic Aperture Radar (SAR) has been successfully used to map wetland's inundation extents and types of vegetation based on the fact that the SAR backscatter signal from the wetland is mainly ...controlled by the wetland vegetation type and water level changes. This study describes the relation between L-band PALSAR and seasonal water level changes obtained from Envisat altimetry over the island of Ile Mbamou in the Congo Basin where two distinctly different vegetation types are found. We found positive correlations between and water level changes over the forested southern Ile Mbamou whereas both positive and negative correlations were observed over the non-forested northern Ile Mbamou depending on the amount of water level increase. Based on the analysis of sensitivity, we found that denser vegetation canopy leads to less sensitive variation with respect to the water level changes regardless of forested or non-forested canopy. Furthermore, we attempted to estimate water level changes which were then compared with the Envisat altimetry and InSAR results. Our results demonstrated a potential to generate two-dimensional maps of water level changes over the wetlands, and thus may have substantial synergy with the planned Surface Water and Ocean Topography (SWOT) mission.
The Congo Basin is the world's third largest in size (~
3.7
million
km
2), and second only to the Amazon River in discharge (~
40,200
m
3
s
−
1
annual average). However, the hydrological dynamics of ...seasonally flooded wetlands and floodplains remains poorly quantified. Here, we separate the Congo wetland into four 3°
×
3° regions, and use remote sensing measurements (i.e., GRACE, satellite radar altimeter, GPCP, JERS-1, SRTM, and MODIS) to estimate the amounts of water filling and draining from the Congo wetland, and to determine the source of the water. We find that the amount of water annually filling and draining the Congo wetlands is 111
km
3, which is about one-third the size of the water volumes found on the mainstem Amazon floodplain. Based on amplitude comparisons among the water volume changes and timing comparisons among their fluxes, we conclude that the local upland runoff is the main source of the Congo wetland water, not the fluvial process of river-floodplain water exchange as in the Amazon. Our hydraulic analysis using altimeter measurements also supports our conclusion by demonstrating that water surface elevations in the wetlands are consistently higher than the adjacent river water levels. Our research highlights differences in the hydrology and hydrodynamics between the Congo wetland and the mainstem Amazon floodplain.
► We provide the first-ever measurements of the Congo wetlands water volume change. ► Wetland water is dominated by local upland runoff and much less from mainstem. ► Differences between the Congo wetland and the Amazon floodplain are highlighted.
Differential synthetic aperture radar (SAR) interferometry (DInSAR) has been successfully used to estimate water level changes (∂h/∂t) over wetlands and floodplains. Specifically, amongst ALOS PALSAR ...datasets, the fine-beam stripmap mode has been mostly implemented to estimate ∂h/∂t due to its availability of multitemporal images. However, the fine-beam observation mode provides limited swath coverage to study large floodplains and wetlands, such as the Amazon floodplains. Therefore, for the first time, this paper demonstrates that ALOS2 ScanSAR data can be used to estimate the large-scale ∂h/∂t in Amazon floodplains. The basic procedures and challenges of DInSAR processing with ALOS2 ScanSAR data are addressed and final ∂h/∂t maps are generated based on the Satellite with ARgos and ALtiKa (SARAL) altimetry’s reference data. This study reveals that the local ∂h/∂t patterns of Amazon floodplains are spatially complex with highly interconnected floodplain channels, but the large-scale (with 350 km swath) ∂h/∂t patterns are simply characterized by river water flow directions.
Tropical reservoirs are critical infrastructure for managing drinking and irrigation water and generating hydroelectric power. However, long-term spaceborne monitoring of reservoir storage is ...challenged by data scarcity from near-persistent cloud cover and drought, which may reduce volumes below those in the observational record. In evaluating our ability to accurately monitor long-term reservoir volume dynamics using spaceborne data and overcome such observational challenges, we integrated optical, lidar, and radar time series to estimate reservoir volume dynamics across 13 reservoirs in eastern Brazil over a 12-year (2003–2014) period affected by historic drought. We (i) used 1560 Landsat images to measure reservoir surface area; (ii) built reservoir-specific regression models relating surface area and elevation from ICESat GLAS and Envisat RA-2 data; (iii) modeled volume changes for each reservoir; and (iv) compared modeled and in situ reservoir volume changes. Regression models had high goodness-of-fit (median RMSE = 0.89 m and r = 0.88) across reservoirs. Even though 88% of an average reservoir’s volume time series was based on modeled area–elevation relationships, we found exceptional agreement (RMSE = 0.31 km3 and r = 0.95) with in situ volume time series, and accurately captured seasonal recharge/depletion dynamics and the drought’s prolonged drawdown. Disagreements in volume dynamics were neither driven by wet/dry season conditions nor reservoir capacity, indicating analytical efficacy across a range of monitoring scenarios.
The Florida Everglades plays a significant role in controlling floods, improving water quality, supporting ecosystems, and maintaining biodiversity in south Florida. Adaptive restoration and ...management of the Everglades requires the best information possible regarding wetland hydrology. We developed a new and innovative approach to quantify spatial and temporal variations in wetland water levels within the Everglades, Florida. We observed high correlations between water level measured at in situ gages and L-band SAR backscatter coefficients in the freshwater marsh, though C-band SAR backscatter has no close relationship with water level. Here we illustrate the complementarity of SAR backscatter coefficient differencing and interferometry (InSAR) for improved estimation of high spatial resolution water level variations in the Everglades. This technique has a certain limitation in applying to swamp forests with dense vegetation cover, but we conclude that this new method is promising in future applications to wetland hydrology research.
•We analyzed SAR backscatter coefficients in the Everglades freshwater marsh.•We found a close relationship between radar backscatter and water level change.•Increased water level in the freshwater marsh will reduce L-band SAR backscatter.•Both modes of FB/ScanSAR are similarly affected by hydrologic change in the marsh.•Integration of backscatter/InSAR enables to estimate absolute water level change.
Surface water is a vital component of the Earth’s water cycle and characterizing its dynamics is essential for understanding and managing our water resources. Satellite-based remote sensing has been ...used to monitor surface water dynamics, but cloud cover can obscure surface observations, particularly during flood events, hindering water identification. The fusion of optical and synthetic aperture radar (SAR) data leverages the advantages of both sensors to provide accurate surface water maps while increasing the temporal density of unobstructed observations for monitoring surface water spatial dynamics. This paper presents a method for generating dense time series of surface water observations using optical–SAR sensor fusion and gap filling. We applied this method to data from the Copernicus Sentinel-1 and Landsat 8 satellite data from 2019 over six regions spanning different ecological and climatological conditions. We validated the resulting surface water maps using an independent, hand-labeled dataset and found an overall accuracy of 0.9025, with an accuracy range of 0.8656–0.9212 between the different regions. The validation showed an overall false alarm ratio (FAR) of 0.0631, a probability of detection (POD) of 0.8394, and a critical success index (CSI) of 0.8073, indicating that the method generally performs well at identifying water areas. However, it slightly underpredicts water areas with more false negatives. We found that fusing optical and SAR data for surface water mapping increased, on average, the number of observations for the regions and months validated in 2019 from 11.46 for optical and 55.35 for SAR to 64.90 using both, a 466% and 17% increase, respectively. The results show that the method can effectively fill in gaps in optical data caused by cloud cover and produce a dense time series of surface water maps. The method has the potential to improve the monitoring of surface water dynamics and support sustainable water management.
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