267 research outputs found

    Towards operational sea ice type retrieval using L-band Synthetic aperture radar

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    Source at https://doi.org/10.1109/IGARSS.2019.8900458.Operational ice services around the world have recognized the economic and environmental benefits that come from the increased capabilities and uses of space-borne Synthetic Aperture Radar (SAR) observation system. The two major objectives in SAR based remote sensing of sea ice is on the one hand to have a large areal coverage, and on the other hand to obtain a radar response that carries as much information as possible. Although until now, L-Band SAR sensors are rarely used in an operational context, it offers greater capabilities for sea ice type retrieval and is more robust during the melt season compared to higher frequency bands. With the help of JAXA’s ALOS-2 PALSAR-2 sensor, we are able to explore the potential of polarimetric L-band acquisitions for sea ice analysis and classification in an operational environment. In this study we investigated the incidence angle related variation on the L-band backscatter and recommended optimal scenarios for Artificial Neural Network based sea ice type retrieval schemes

    Detecting Methane Ebullition In Winter From Alaskan Lakes Using Synthetic Aperture Radar Remote Sensing

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    Thesis (Ph.D.) University of Alaska Fairbanks, 2012Methane (CH4) is a greenhouse gas with a high radiative forcing attribute, yet large uncertainties remain in constraining atmospheric CH4 sources and sinks. While freshwater lakes are known atmospheric CH4 sources, flux through ebullition (bubbling) is difficult to quantify in situ due to uneven spatial distribution and temporally irregular gas eruptions. This heterogeneous distribution of CH4 ebullition also creates error when scaling up field measurements for flux estimations. This thesis reviews estimates of CH4 contribution to the atmosphere by freshwater lakes presented in current literature and identifies knowledge gaps and the logistical difficulties in sampling CH 4 flux via ebullition (bubbling). My research investigates various imaging parameters of space-borne synthetic aperture radar (SAR) to constrain current CH4 emissions from northern lakes. In a GIS spatial analysis of lakes on the northern Seward Peninsula, Alaska, comparing field data of ebullition to SAR, I found that SAR L-band backscatter from lake ice was high from lakes with CH4 bubbles trapped by lake ice and low from lakes with low ebullition activity. The 'roughness' component of a Pauli polarimetric decomposition of quad-pol SAR showed a significant correlation with the percentage of lake ice area containing CH4 bubbles and with CH4 ebullition flux. This indicates that the mechanism of SAR scattering from ebullition bubbles trapped by lake ice is single bounce. I conclude that SAR remote sensing could improve our ability to quantify lake ebullition at larger spatial scales than field measurements alone, could offer between-lake comparison of CH 4 ebullition activity, and is a potential tool for developing regional estimations of lake-source CH4

    Remote Sensing of Natural Hazards

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    Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human population, largescale development activities, and changes to the natural environment, the frequency and intensity of extreme natural events and consequent impacts are expected to increase in the future.Technological interventions provide essential provisions for the prevention and mitigation of natural hazards. The data obtained through remote sensing systems with varied spatial, spectral, and temporal resolutions particularly provide prospects for furthering knowledge on spatiotemporal patterns and forecasting of natural hazards. The collection of data using earth observation systems has been valuable for alleviating the adverse effects of natural hazards, especially with their near real-time capabilities for tracking extreme natural events. Remote sensing systems from different platforms also serve as an important decision-support tool for devising response strategies, coordinating rescue operations, and making damage and loss estimations.With these in mind, this book seeks original contributions to the advanced applications of remote sensing and geographic information systems (GIS) techniques in understanding various dimensions of natural hazards through new theory, data products, and robust approaches

    Arctic sea ice trafficability: new strategies for a changing icescape

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    Thesis (Ph.D.) University of Alaska Fairbanks, 2017Sea ice is an important part of the Arctic social-environmental system, in part because it provides a platform for human transportation and for marine flora and fauna that use the ice as a habitat. Sea ice loss projected for coming decades is expected to change ice conditions throughout the Arctic, but little is known about the nature and extent of anticipated changes and in particular potential implications for over-ice travel and ice use as a platform. This question has been addressed here through an extensive effort to link sea ice use and key geophysical properties of sea ice, drawing upon extensive field surveys around on-ice operations and local and Indigenous knowledge for the widely different ice uses and ice regimes of Utqiaġvik, Kotzebue, and Nome, Alaska. A set of nine parameters that constrain landfast sea ice use has been derived, including spatial extent, stability, and timing and persistence of landfast ice. This work lays the foundation for a framework to assess and monitor key ice-parameters relevant in the context of ice-use feasibility, safety, and efficiency, drawing on different remote-sensing techniques. The framework outlines the steps necessary to further evaluate relevant parameters in the context of user objectives and key stakeholder needs for a given ice regime and ice use scenario. I have utilized this framework in case studies for three different ice regimes, where I find uses to be constrained by ice thickness, roughness, and fracture potential and develop assessment strategies with accuracy at the relevant spatial scales. In response to the widely reported importance of high-confidence ice thickness measurements, I have developed a new strategy to estimate appropriate thickness compensation factors. Compensation factors have the potential to reduce risk of misrepresenting areas of thin ice when using point-based in-situ assessment methods along a particular route. This approach was tested on an ice road near Kotzebue, Alaska, where substantial thickness variability results in the need to raise thickness thresholds by 50%. If sea ice is thick enough for safe travel, then the efficiency of travel is relevant and is influenced by the roughness of the ice surface. Here, I develop a technique to derive trafficability measures from ice roughness using polarimetric and interferometric synthetic aperture radar (SAR). Validated using Structure-from-Motion analysis of imagery obtained from an unmanned aerial system near Utqiaġvik, Alaska, I demonstrate the ability of these SAR techniques to map both topography and roughness with potential to guide trail construction efforts towards more trafficable ice. Even when the ice is sufficiently thick to ensure safe travel, potential for fracturing can be a serious hazard through the ability of cracks to compromise load-bearing capacity. Therefore, I have created a state-of-the-art technique using interferometric SAR to assess ice stability with capability of assessing internal ice stress and potential for failure. In an analysis of ice deformation and potential hazards for the Northstar Island ice road near Prudhoe Bay on Alaska's North Slope I have identified a zone of high relative fracture intensity potential that conformed with road inspections and hazard assessments by the operator. Through this work I have investigated the intersection between ice use and geophysics, demonstrating that quantitative evaluation of a given region in the ice use assessment framework developed here can aid in tactical routing of ice trails and roads as well as help inform long-term strategic decision-making regarding the future of Arctic operations on or near sea ice

    Comparing synthetic aperture radar and LiDAR for above-ground biomass estimation in Glen Affric, Scotland

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    Quantifying above-ground biomass (AGB) and carbon sequestration has been a significant focus of attention within the UNFCCC and Kyoto Protocol for improvement of national carbon accounting systems (IPCC, 2007; UNFCCC, 2011). A multitude of research has been carried out in relatively flat and homogeneous forests (Ranson & Sun, 1994; Beaudoin et al.,1994; Kurvonen et al., 1999; Austin et al., 2003; Dimitris et al., 2005), yet forests in the highlands, which generally form heterogeneous forest cover and sparse woodlands with mountainous terrain have been largely neglected in AGB studies (Cloude et al., 2001; 2008; Lumsdon et al., 2005; 2008; Erxue et al., 2009, Tan et al., 2010; 2011a; 2011b; 2011c; 2011d). Since mountain forests constitute approximately 28% of the total global forest area (Price and Butt, 2000), a better understanding of the slope effects is of primary importance in AGB estimation. The main objective of this research is to estimate AGB in the aforementioned forest in Glen Affric, Scotland using both SAR and LiDAR data. Two types of Synthetic Aperture Radar (SAR) data were used in this research: TerraSAR-X, operating at X-band and ALOS PALSAR, operating at L-band, both are fully polarimetric. The former data was acquired on 13 April 2010 and of the latter, two scenes were acquired on 17 April 2007 and 08 June 2009. Airborne LiDAR data were acquired on 09 June 2007. Two field measurement campaigns were carried out, one of which was done from winter 2006 to spring 2007 where physical parameters of trees in 170 circular plots were measured by the Forestry Commission team. Another intensive fieldwork was organised by myself with the help of my fellow colleagues and it comprised of tree measurement in two transects of 200m x 50m at a relatively flat and dense plantation forest and 400m x 50m at hilly and sparse semi-natural forest. AGB is estimated for both the transects to investigate the effectiveness of the proposed method at plot-level. This thesis evaluates the capability of polarimetric Synthetic Aperture Radar data for AGB estimation by investigating the relationship between the SAR backscattering coefficient and AGB and also the relationship between the decomposed scattering mechanisms and AGB. Due to the terrain and heterogeneous nature of the forests, the result from the backscatter-AGB analysis show that these forests present a challenge for simple AGB estimation. As an alternative, polarimetric techniques were applied to the problem by decomposing the backscattering information into scattering mechanisms based on the approach by Yamaguchi (2005; 2006), which are then regressed to the field measured AGB. Of the two data sets, ALOS PALSAR demonstrates a better estimation capacity for AGB estimation than TerraSAR-X. The AGB estimated results from SAR data are compared with AGB derived from LiDAR data. Since tree height is often correlated with AGB (Onge et al., 2008; Gang et al., 2010), the effectiveness of the tree height retrieval from LiDAR is evaluated as an indicator of AGB. Tree delineation was performed before AGB of individual trees were calculated allometrically. Results were validated by comparison to the fieldwork data. The amount of overestimation varies across the different canopy conditions. These results give some indication of when to use LiDAR or SAR to retrieve forest AGB. LiDAR is able to estimate AGB with good accuracy and the R2 value obtained is 0.97 with RMSE of 14.81 ton/ha. The R2 and RMSE obtained for TerraSAR-X are 0.41 and 28.5 ton/ha, respectively while for ALOS PALSAR data are 0.70 and 23.6 ton/ha, respectively. While airborne LiDAR data with very accurate height measurement and consequent three-dimensional (3D) stand profiles which allows investigation into the relationship between height, number density and AGB, it's limited to small coverage area, or large areas but at large cost. ALOS PALSAR, on the other hand, can cover big coverage area but it provide a lower resolution, hence, lower estimation accuracy

    ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications

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    Twelve edited original papers on the latest and state-of-art results of topics ranging from calibration, validation, and science to a wide range of applications using ALOS-2/PALSAR-2. We hope you will find them useful for your future research

    Polarimetric Synthetic Aperture Radar

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    This open access book focuses on the practical application of electromagnetic polarimetry principles in Earth remote sensing with an educational purpose. In the last decade, the operations from fully polarimetric synthetic aperture radar such as the Japanese ALOS/PalSAR, the Canadian Radarsat-2 and the German TerraSAR-X and their easy data access for scientific use have developed further the research and data applications at L,C and X band. As a consequence, the wider distribution of polarimetric data sets across the remote sensing community boosted activity and development in polarimetric SAR applications, also in view of future missions. Numerous experiments with real data from spaceborne platforms are shown, with the aim of giving an up-to-date and complete treatment of the unique benefits of fully polarimetric synthetic aperture radar data in five different domains: forest, agriculture, cryosphere, urban and oceans

    Quad polarimetric synthetic aperture radar analysis of icebergs in Greenland and Svalbard

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    Polarimetric synthetic aperture radar (PolSAR) has been widely used in ocean and cryospheric applications. This is because, PolSAR can be used in all-day operations and in areas of cloud cover, and therefore can provide valuable large-scale monitoring in polar regions, which is very helpful to shipping and offshore maritime operations. In the last decades, attention has turned to the potential of PolSAR to detect icebergs in the Arctic since they are a major hazard to vessels. However, there is a substantial lack of literature exploring the potentialities of PolSAR and the understanding of iceberg scattering mechanisms. Additionally, it is not known if high resolution PolSAR can be used to detect icebergs smaller than 120 metres. This thesis aims to improve the knowledge of the use of PolSAR scattering mechanisms of icebergs, and detection of small icebergs. First, an introduction to PolSAR is outlined in chapter two, and monitoring of icebergs is presented in chapter three. The first data chapter (Chapter 4) is focused on developing a multi-scale analysis of icebergs using parameters from the Cloude-Pottier and the Yamaguchi decompositions, the polarimetric span and the Pauli scattering vector. This method is carried out using ALOS-2 PALSAR quad polarimetric L-band SAR on icebergs in Greenland. This approach outlines the good potential for using PolSAR for future iceberg classification. One of the main important outcomes is that icebergs are composed by a combination of single targets, which therefore may require a more complex way of processing SAR data to properly extract physical information. In chapter five, the problem of detecting icebergs is addressed by introducing six state-of-the-art detectors previously applied to vessel monitoring. These detectors are the Dual Intensity Polarisation Ratio Anomaly Detector (iDPolRAD), Polarimetric Notch Filter (PNF), Polarimetric Matched Filter (PMF), reflection symmetry (sym), Optimal Polarimetric Detector (OPD) and the Polarimetric Whitening Filter (PWF). Cloude-Pottier entropy, and first and third eigenvalues (eig1 and eig3) of the coherency matrix are also utilised as parameters for comparison. This approach uses the same ALOS-2 dataset, but also evaluates detection performance in two scenarios: icebergs in open ocean, and in sea ice. Polarimetric modes (quad-pol, dual-pol, and single intensities) are also considered for comparison. Currently it is very difficult to detect icebergs less than 120 metres in length using this approach, due to the scattering mechanisms of icebergs and sea ice being very similar. However, it was possible to obtain detection performances of the OPD and PWF, which both showed a Probability of Detection (PF) of 0.99 when the Probability of False Alarms (PF) was set to 10-5 in open ocean. Similarly, in dual pol images, the PWF gave the best performance with a PD of 0.90. Results in sea ice found eig3 to be the best detector with a PD of 0.90 while in dual-pol mode, iDPolRAD gave a PD of 0.978. Single intensity detector performance found the HV channel gave the best detection with a PD of 0.99 in open ocean and 0.87 in sea ice. In the previous two approaches, only satellite data is used. However, in chapter six, data from a ground-based Ku-band Gamma Portable Radio Interferometer (GPRI) instrument is introduced, providing images that are synchronised with the satellite acquisitions. In this approach, the same six detectors are applied to three multitemporal RADARSAT-2 quad pol C-band SAR images on icebergs in Kongsfjorden, Svalbard to evaluate the detection performance within a changing fjord environment. As before, we also make use of Cloude-Pottier entropy, eig1 and eig3. Finally, we evaluate the target-to-clutter ratio (TCR) of the icebergs and check for correlation between the backscattering coefficients and the iceberg dimension. The results obtained from this thesis present original additions to the literature that contributes to the understanding of PolSAR in cryospheric applications. Although these methods are applied to PolSAR and ground-based radar on vessels, they have been applied for the first time on icebergs in this thesis. To summarise, the main findings are that icebergs cannot be represented as single or partial targets, but they do exhibit a collection of single targets clustered together. This result leads to the fact that entropy is not sufficient as a parameter to detect icebergs. Detection results show that the OPD and PWF detectors perform best in an open ocean setting and using quad-pol mode. These results are degraded in dual-pol mode, while single intensity detection is best in the HV cross polarisation channel. When these detectors are applied to the RADARSAT-2 in Svalbard, the OPD and PWF detectors also perform best with PD values ranging between 0.5-0.75 for a PF of 0.01-0.05. However, the sea ice present in the fjord degrades performance across all detectors. Correlation plots with iceberg size show that a regression is not straightforward and Computer Vision methodologies may work best for this
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