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

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

Re-evaluating Scattering Mechanisms in Snow-Covered Freshwater Lake Ice Containing Bubbles Using Polarimetric Ground-based and Spaceborne Radar Data

Lakes are a prominent feature of the sub-Arctic and Arctic regions of North America, covering up to 40% of the landscape. Seasonal ice cover on northern lakes afford habitat for several flora and fauna species, and provide drinking water and overwintering fishing areas for local communities. The presence of lake ice influences lake-atmosphere exchanges by modifying the radiative properties of the lake surface and moderating the transfer of heat to the atmosphere. The thermodynamic aspects of lakes exhibit a pronounced effect on weather and regional climate, but are also sensitive to variability in climate forcings such as air temperature and snow fall, acting as proxy indicators of climate variability and change. To refine the understanding of lake-climate interactions, improved methods of monitoring lake ice properties are needed. Manual lake ice monitoring stations have dropped significantly since the 1990s and existing stations are restricted to populated and coastal regions. Recently, studies have indicated the use of radar remote sensing as a viable option for the monitoring of small lakes in remote regions due to its high spatial resolution and imaging capability independent of solar radiation or cloud cover. Active microwave radar in the frequency range of 5 – 10 GHz have successfully retrieved lake ice information pertaining to the physical status of the ice cover and areas that are frozen to bed, but have not been demonstrated as effective for the derivation of on-ice snow depth. In the 10 – 20 GHz range, radar has been shown to be sensitive to terrestrial snow cover, but has not been investigated over lakes. Utilizing a combination of spaceborne and ground-based radar systems spanning a range of 5 – 17 GHz, simulations from the Canadian Lake Ice Model (CLIMo), and ice thickness information from a shallow water ice profiler (SWIP), this research aimed to further our understanding of lake ice scattering sources and mechanisms for small freshwater lakes in the sub-Arctic. Increased comprehension of scattering mechanisms in ice advances the potential for the derivation of lake ice properties, including on-ice snow depth, lake ice thickness and identification of surface ice types. Field observations of snow-covered lake ice were undertaken during the winter seasons of 2009-2010 and 2010-2011 on Malcolm Ramsay Lake, near Churchill Manitoba. In-situ snow and ice observations were coincident with ground-based scatterometer (UW-Scat) and spaceborne synthetic aperture radar (SAR) acquisitions. UW-Scat was comprised of two fully polarimetric frequency modulated continuous wave (FMCW) radars with centre frequencies of 9.6 and 17.2 GHz (X- and Ku-bands, respectively). SAR observations included fine-beam fully polarimetric RADARSAT-2 acquisitions, obtained coincident to UW-Scat observations during 2009-2010. Three experiments were conducted to characterize and evaluate the backscatter signatures from snow-covered freshwater ice coincident to in-situ snow and ice observations. To better understand the winter backscatter (σ°) evolution of snow covered ice, three unique ice cover scenarios were observed and simulated using a bubbled ice σ° model. The range resolution of UW-SCAT provided separation of microwave interaction at the snow/ice interface (P1), and within the ice volume (P2). Ice cores extracted at the end of the observation period indicated that a considerable σ° increase at P2 of approximately 10 – 12 decibels (dB) HH/VV at X- and Ku-band occurred coincident to the timing of tubular bubble development in the ice. Similarly, complexity of the ice surface (high density micro-bubbles and snow ice) resulted in increased P1 σ° at X- and Ku-band at a magnitude of approximately 7 dB. P1 observations also indicated that Ku-band was sensitive to snowpack overlying lake ice, with σ° exhibiting a 5 (6) dB drop for VV (HH) when ~ 60 mm SWE is removed from the scatterometer field of view. Observations indicate that X-band was insensitive to changes in overlying snowpack within the field of view. A bubbled ice σ° model was developed using the dense medium radiative transfer theory under the Quasi-Crystalline Approximation (DMRT-QCA), which treated bubbles as spherical inclusions within the ice volume. Results obtained from the simulations demonstrated the capability of the DMRT model to simulate the overall magnitude of observed σ° using in-situ snow and ice measurements as input. This study improved understanding of microwave interaction with bubble inclusions incorporated at the ice surface or within the volume. The UW-Scat winter time series was then used to derive ice thickness under the assumption of interactions in range occurring at the ice-snow and ice-water interface. Once adjusted for the refractive index of ice and slant range, the distance between peak returns agreed with in-situ ice thickness observations. Ice thicknesses were derived from the distance of peak returns in range acquired in off-nadir incidence angle range 21 - 60°. Derived ice thicknesses were compared to in-situ measurements provided by the SWIP and CLIMo. Median ice thicknesses derived using UW-Scat X- and Ku-band observations agreed well with in-situ measurements (RMSE = 0.053 and 0.045 m), SWIP (RMSE = 0.082 and 0.088 m) and Canadian Lake Ice Model (CLIMo) simulations using 25% of terrestrial snowpack scenario (RMSE = 0.082 and 0.079), respectively. With the launch of fully polarimetric active microwave satellites and upcoming RADARSAT Constellation Mission (RCM), the utility of polarimetric measurements was observed for freshwater bubbled ice to further investigate scattering mechanisms identified by UW-Scat. The 2009-2010 time series of UW-Scat and RADARSAT-2 (C-band) fully polarimetric observations coincident to in-situ snow and ice measurements were acquired to identify the dominant scattering mechanism in bubbled freshwater lake ice. Backscatter time series at all frequencies show increases from the ice-water interface prior to the inclusion of tubular bubbles in the ice column based on in-situ observations, indicating scattering mechanisms independent of double-bounce scatter, contrary to the longstanding hypothesis of double-bounce scatter off tubular bubbles and the ice-water interface. The co-polarized phase difference of interactions at the ice-water interface from both UW-Scat and SAR observations were centred at 0°, indicating a scattering regime other than double bounce. A Yamaguchi three-component decomposition of the time series suggested the dominant scattering mechanism to be single-bounce off the ice-water interface with appreciable surface roughness or preferentially oriented facets. Overall, this work provided new insight into the scattering sources and mechanisms within snow-covered freshwater lake ice containing spherical and tubular bubbles

Spatio-temporal influence of tundra snow properties on Ku-band (17.2 GHz) backscatter

During the 2010/11 boreal winter, a distributed set of backscatter measurements was collected using a ground-based Ku-band (17.2 GHz) scatterometer system at 26 open tundra sites. A standard snow-sampling procedure was completed after each scan to evaluate local variability in snow layering, depth, density and water equivalent (SWE) within the scatterometer field of view. The shallow depths and large basal depth hoar encountered presented an opportunity to evaluate backscatter under a set of previously untested conditions. Strong Ku-band response was found with increasing snow depth and snow water equivalent (SWE). In particular, co-polarized vertical backscatter increased by 0.82 dB for every 1 cm increase in SWE (R2 = 0.62). While the result indicated strong potential for Ku-band retrieval of shallow snow properties, it did not characterize the influence of sub-scan variability. An enhanced snow-sampling procedure was introduced to generate detailed characterizations of stratigraphy within the scatterometer field of view using near-infrared photography along the length of a 5m trench. Changes in snow properties along the trench were used to discuss variations in the collocated backscatter response. A pair of contrasting observation sites was used to highlight uncertainties in backscatter response related to short length scale spatial variability in the observed tundra environment

Observing Scattering Mechanisms of Bubbled Freshwater Lake Ice Using Polarimetric RADARSAT-2 (C-Band) and UW-Scat (X- and Ku-Bands)

A winter time series of ground-based (X- and Ku-bands) scatterometer and spaceborne synthetic aperture radar (SAR) (C-band) fully polarimetric observations coincident with in situ snow and ice measurements are used to identify the dominant scattering mechanism in bubbled freshwater lake ice in the Hudson Bay Lowlands near Churchill, Manitoba. Scatterometer observations identify two physical sources of backscatter from the ice cover: the snow-ice and ice-water interfaces. Backscatter time series at all frequencies show increases from the ice-water interface prior to the inclusion of tubular bubbles in the ice column based on in situ observations, indicating scattering mechanisms independent of double-bounce scatter. The co-polarized phase difference of interactions at the ice-water interface from both scatterometer and SAR observations is centered at 0° during the time series, also indicating a scattering regime other than double bounce. A Yamaguchi three-component decomposition of the RADARSAT-2 C-band time series is presented, which suggests the dominant scattering mechanism to be single-bounce off the ice-water interface with appreciable surface roughness or preferentially oriented facets, regardless of the presence, absence, or density of tubular bubble inclusions. This paper builds on newly established evidence of single-bounce scattering mechanism for freshwater lake ice and is the first to present a winter time series of ground-based and spaceborne fully polarimetric active microwave observations with polarimetric decompositions for bubbled freshwater lake ice.European Space Agency (ESTEC): 10.13039/501100000844 Natural Sciences and Engineering Research Council of Canada: 10.13039/50110000003

Monitoring Snow Cover and Snowmelt Dynamics and Assessing their Influences on Inland Water Resources

Snow is one of the most vital cryospheric components owing to its wide coverage as well as its unique physical characteristics. It not only affects the balance of numerous natural systems but also influences various socio-economic activities of human beings. Notably, the importance of snowmelt water to global water resources is outstanding, as millions of populations rely on snowmelt water for daily consumption and agricultural use. Nevertheless, due to the unprecedented temperature rise resulting from the deterioration of climate change, global snow cover extent (SCE) has been shrinking significantly, which endangers the sustainability and availability of inland water resources. Therefore, in order to understand cryo-hydrosphere interactions under a warming climate, (1) monitoring SCE dynamics and snowmelt conditions, (2) tracking the dynamics of snowmelt-influenced waterbodies, and (3) assessing the causal effect of snowmelt conditions on inland water resources are indispensable. However, for each point, there exist many research questions that need to be answered. Consequently, in this thesis, five objectives are proposed accordingly. Objective 1: Reviewing the characteristics of SAR and its interactions with snow, and exploring the trends, difficulties, and opportunities of existing SAR-based SCE mapping studies; Objective 2: Proposing a novel total and wet SCE mapping strategy based on freely accessible SAR imagery with all land cover classes applicability and global transferability; Objective 3: Enhancing total SCE mapping accuracy by fusing SAR- and multi-spectral sensor-based information, and providing total SCE mapping reliability map information; Objective 4: Proposing a cloud-free and illumination-independent inland waterbody dynamics tracking strategy using freely accessible datasets and services; Objective 5: Assessing the influence of snowmelt conditions on inland water resources

Monitoring permafrost environments with Synthetic Aperture Radar (SAR) sensors

Permafrost occupies approximately 24% of the exposed land area in the Northern Hemisphere. It is an important element of the cryosphere and has strong impacts on hydrology, biological processes, land surface energy budget, and infrastructure. For several decades, surface air temperatures in the high northern latitudes have warmed at approximately twice the global rate. Permafrost temperatures have increased in most regions since the early 1980s, the averaged warming north of 60°N has been 1-2°C. In-situ measurements are essential to understanding physical processes in permafrost terrain, but they have several limitations, ranging from difficulties in drilling to the representativeness of limited single point measurements. Remote sensing is urgently needed to supplement ground-based measurements and extend the point observations to a broader spatial domain. This thesis concentrates on the sub-arctic permafrost environment monitoring with SAR datasets. The study site is selected in a typical discontinuous permafrost region in the eastern Canadian sub-Arctic. Inuit communities in Nunavik and Nunatsiavut in the Canadian eastern sub-arctic are amongst the groups most affected by the impacts of climate change and permafrost degradation. Synthetic Aperture Radar (SAR) datasets have advantages for permafrost monitoring in the Arctic and sub-arctic regions because of its high resolution and independence of cloud cover and solar illumination. To date, permafrost environment monitoring methods and strategies with SAR datasets are still under development. The variability of active layer thickness is a direct indication of permafrost thermal state changes. The Differential SAR Interferometry (D-InSAR) technique is applied in the study site to derive ground deformation, which is introduced by the thawing/freezing depth of active layer and underlying permafrost. The D-InSAR technique has been used for the mapping of ground surface deformation over large areas by interpreting the phase difference between two signals acquired at different times as ground motion information. It shows the ability to detect freeze/thaw-related ground motion over permafrost regions. However, to date, accuracy and value assessments of D-InSAR applications have focused mostly on the continuous permafrost region where the vegetation is less developed and causes fewer complicating factors for the D-InSAR application, less attention is laid on the discontinuous permafrost terrain. In this thesis, the influencing factors and application conditions for D-InSAR in the discontinuous permafrost environment are evaluated by using X- band and L-band data. Then, benefit from by the high-temporal resolution of C-band Sentinel-1 time series, the seasonal displacement is derived from small baseline subsets (SBAS)-InSAR. Landforms are indicative of permafrost presence, with their changes inferring modifications to permafrost conditions. A permafrost landscape mapping method was developed which uses multi-temporal TerraSAR-X backscatter intensity and interferometric coherence information. The land cover map is generated through the combined use of object-based image analysis (OBIA) and classification and regression tree analysis (CART). An overall accuracy of 98% is achieved when classifying rock and water bodies, and an accuracy of 79% is achieved when discriminating between different vegetation types with one year of single-polarized acquisitions. This classification strategy can be transferred to other time-series SAR datasets, e.g., Sentinel-1, and other heterogeneous environments. One predominant change in the landscape tied to the thaw of permafrost is the dynamics of thermokarst lakes. Dynamics of thermokarst lakes are developed through their lateral extent and vertical depth changes. Due to different water depth, ice cover over shallow thermokarst ponds/lakes can freeze completely to the lake bed in winter, resulting in grounded ice; while ice cover over deep thermokarst ponds/lakes cannot, which have liquid water persisting under the ice cover all winter, resulting in floating ice. Winter ice cover regimes are related to water depths and ice thickness. In the lakes having floating ice, the liquid water induces additional heat in the remaining permafrost underneath and surroundings, which contributes to further intensified permafrost thawing. SAR datasets are utilized to detect winter ice cover regimes based on the character that liquid water has a remarkably high dielectric constant, whereas pure ice has a low value. Patterns in the spatial distribution of ice-cover regimes of thermokarst ponds in a typical discontinuous permafrost region are first revealed. Then, the correlations of these ice-cover regimes with the permafrost degradation states and thermokarst pond development in two historical phases (Sheldrake catchment in the year 1957 and 2009, Tasiapik Valley 1994 and 2010) were explored. The results indicate that the ice-cover regimes of thermokarst ponds are affected by soil texture, permafrost degradation stage and permafrost depth. Permafrost degradation is difficult to directly assess from the coverage area of floating-ice ponds and the percentage of all thermokarst ponds consisting of such floating-ice ponds in a single year. Continuous monitoring of ice-cover regimes and surface areas is recommended to elucidate the hydrological trajectory of the thermokarst process. Several operational monitoring methods have been developed in this thesis work. In the meanwhile, the spatial distribution of seasonal ground thaw subsidence, permafrost landscape, thermokarst ponds and their winter ice cover regimes are first revealed in the study area. The outcomes help understand the state and dynamics of permafrost environment.Der Permafrostboden bedeckt etwa 24% der exponierten Landfläche in der nördlichen Hemisphäre. Es ist ein wichtiges Element der Kryosphäre und hat starke Auswirkungen auf die Hydrologie, die biologischen Prozesse, das Energie-Budget der Landoberfläche und die Infrastruktur. Seit mehreren Jahrzehnten erhöhen sich die Oberflächenlufttemperaturen in den nördlichen hohen Breitengraden etwa doppelt so stark wie die globale Rate. Die Temperaturen der Permafrostböden sind in den meisten Regionen seit den frühen 1980er Jahren gestiegen. Die durchschnittliche Erwärmung nördlich von 60° N beträgt 1-2°C. In-situ-Messungen sind essentiell für das Verständnis der physischen Prozesse im Permafrostgelände. Es gibt jedoch mehrere Einschränkungen, die von Schwierigkeiten beim Bohren bis hin zur Repräsentativität begrenzter Einzelpunktmessungen reichen. Fernerkundung ist dringend benötigt, um bodenbasierte Messungen zu ergänzen und punktuelle Beobachtungen auf einen breiteren räumlichen Bereich auszudehnen. Diese Dissertation konzentriert sich auf die Umweltbeobachtung der subarktischen Permafrostböden mit SAR-Datensätzen. Das Untersuchungsgebiet wurde in einer typischen diskontinuierlichen Permafrostzone in der kanadischen östlichen Sub-Arktis ausgewählt. Die Inuit-Gemeinschaften in den Regionen Nunavik und Nunatsiavut in der kanadischen östlichen Sub-Arktis gehören zu den Gruppen, die am stärksten von den Auswirkungen des Klimawandels und Permafrostdegradation betroffen sind. Synthetische Apertur Radar (SAR) Datensätze haben Vorteile für das Permafrostmonitoring in den arktischen und subarktischen Regionen aufgrund der hohen Auflösung und der Unabhängigkeit von Wolkendeckung und Sonnenstrahlung. Bis heute sind die Methoden und Strategien mit SAR-Datensätzen für Umweltbeobachtung der Permafrostböden noch in der Entwicklung. Die Variabilität der Auftautiefe der aktiven Schicht ist eine direkte Indikation der Veränderung des thermischen Zustands der Permafrostböden. Die Differential-SAR-Interferometrie(D-Insar)-Technik wird im Untersuchungsgebiet zur Ableitung der Bodendeformation, die durch Auftau- / und Gefriertiefe der aktiven Schicht und des unterliegenden Permafrostbodens eingeführt wird, eingesetzt. Die D-InSAR-Technik wurde für Kartierung der Landoberflächendeformation über große Flächen verwendet, indem der Phasenunterschied zwischen zwei zu verschiedenen Zeitpunkten als Bodenbewegungsinformation erfassten Signalen interpretiert wurde. Es zeigt die Fähigkeit, tau- und gefrierprozessbedingte Bodenbewegungen über Permafrostregionen zu detektieren. Jedoch fokussiert sich die Genauigkeit und Wertschätzung der D-InSAR-Anwendung bis heute hauptsächlich auf kontinuierliche Permafrostregion, wo die Vegetation wenig entwickelt ist und weniger komplizierte Faktoren für D-InSAR-Anwendung verursacht. Das diskontinuierliche Permafrostgelände wurde nur weniger berücksichtigt. In dieser Dissertation wurden die Einflussfaktoren und Anwendungsbedingungen für D-InSAR im diskontinuierlichen Permafrostgebiet mittels X-Band und L-Band Daten ausgewertet. Dann wurde die saisonale Verschiebung dank der hohen Auflösung der C-Band Sentinel-1 Zeitreihe von „Small Baseline Subsets (SBAS)-InSAR“ abgeleitet. Landformen weisen auf die Präsenz des Permafrosts hin, wobei deren Veränderungen auf die Modifikation der Permafrostbedingungen schließen. Eine Kartierungsmethode der Permafrostlandschaft wurde entwickelt, dabei wurde Multi-temporal TerraSAR-X Rückstreuungsintensität und interferometrische Kohärenzinformationen verwendet. Die Landbedeckungskarte wurde durch kombinierte Anwendung objektbasierter Bildanalyse (OBIA) und Klassifikations- und Regressionsbaum Analyse (CART) generiert. Eine Gesamtgenauigkeit in Höhe von 98% wurde bei Klassifikation der Gesteine und Wasserkörper erreicht. Bei Unterscheidung zwischen verschiedenen Vegetationstypen mit einem Jahr einzelpolarisierte Akquisitionen wurde eine Genauigkeit von 79% erreicht. Diese Klassifikationsstrategie kann auf andere Zeitreihen der SAR-Datensätzen, z.B. Sentinel-1, und auch anderen heterogenen Umwelten übertragen werden. Eine vorherrschende Veränderung in der Landschaft, die mit dem Auftauen des Permafrosts verbunden ist, ist die Dynamik der Thermokarstseen. Die Dynamik der Thermokarstseen ist durch Veränderungen der seitlichen Ausdehnung und der vertikalen Tiefe entwickelt. Aufgrund der unterschiedlichen Wassertiefen kann die Eisdecke über den flachen Thermokarstteichen/-seen im Winter bis auf den Wasserboden vollständig gefroren sein, was zum geerdeten Eis führt, während die Eisdecke über den tiefen Thermokarstteichen/-seen es nicht kann. In den tiefen Thermokarstteichen/-seen bleibt den ganzen Winter flüssiges Wasser unter der Eisdecke bestehen, was zum Treibeis führt. Das Wintereisdeckenregime bezieht sich auf die Wassertiefe und die Eisdicke. In den Seen mit Treibeis leitet das flüssige Wasser zusätzliche Wärme in den restlichen Permafrost darunter oder in der Umgebung, was zur weiteren Verstärkung des Permafrostauftauen beiträgt. Basiert auf den Charakter, dass das flüssige Wasser eine bemerkenswert hohe Dielektrizitätskonstante besitzt, während reines Eis einen niedrigen Wert hat, wurden die SAR Datensätzen zur Erkennung des Wintereisdeckenregimes verwendet. Zunächst wurden Schemen in der räumlichen Verteilung der Eisdeckenregimes der Thermokarstteiche in einer typischen diskontinuierlichen Permafrostregion abgeleitet. Dann wurden die Zusammenhänge dieser Eisdeckenregimes mit dem Degradationszustand des Permafrosts und der Entwicklung der Thermokarstteiche in zwei historischen Phasen (Sheldrake Einzugsgebiet in 1957 und 2009, Tasiapik Tal in 1994 und 2010) erforscht. Die Ergebnisse deuten darauf, dass die Eisdeckenregimes der Thermokarstteiche von der Bodenart, dem Degradationszustand des Permafrosts und der Permafrosttiefe beeinflusst werden. Es ist schwer, die Permafrostdegradation in einem einzelnen Jahr direkt durch den Abdeckungsbereich der Treibeis-Teiche und die Prozentzahl aller aus solchen Treibeis-Teichen bestehenden Thermokarstteiche abzuschätzen. Ein kontinuierliches Monitoring der Eisdeckenregimes und -oberflächen ist empfehlenswert, um den hydrologischen Verlauf des Thermokarstprozesses zu erläutern. In dieser Dissertation wurden mehrere operativen Monitoringsmethoden entwickelt. In der Zwischenzeit wurden die räumliche Verteilung der saisonalen Bodentauabsenkung, die Permafrostlandschaft, die Thermokarstteiche und ihre Wintereisdeckenregimes erstmals in diesem Untersuchungsgebiet aufgedeckt. Die Ergebnisse tragen dazu bei, den Zustand und die Dynamik der Permafrostumwelt zu verstehen

Cryosphere Applications

Synthetic aperture radar (SAR) provides large coverage and high resolution, and it has been proven to be sensitive to both surface and near-surface features related to accumulation, ablation, and metamorphism of snow and firn. Exploiting this sensitivity, SAR polarimetry and polarimetric interferometry found application to land ice for instance for the estimation of wave extinction (which relates to sub surface ice volume structure) and for the estimation of snow water equivalent (which relates to snow density and depth). After presenting these applications, the Chapter proceeds by reviewing applications of SAR polarimetry to sea ice for the classification of different ice types, the estimation of thickness, and the characterisation of its surface. Finally, an application to the characterisation of permafrost regions is considered. For each application, the used (model-based) decomposition and polarimetric parameters are critically described, and real data results from relevant airborne campaigns and space borne acquisitions are reported

Monitoring permafrost environments with Synthetic Aperture Radar (SAR) sensors

Permafrost occupies approximately 24% of the exposed land area in the Northern Hemisphere. It is an important element of the cryosphere and has strong impacts on hydrology, biological processes, land surface energy budget, and infrastructure. For several decades, surface air temperatures in the high northern latitudes have warmed at approximately twice the global rate. Permafrost temperatures have increased in most regions since the early 1980s, the averaged warming north of 60°N has been 1-2°C. In-situ measurements are essential to understanding physical processes in permafrost terrain, but they have several limitations, ranging from difficulties in drilling to the representativeness of limited single point measurements. Remote sensing is urgently needed to supplement ground-based measurements and extend the point observations to a broader spatial domain. This thesis concentrates on the sub-arctic permafrost environment monitoring with SAR datasets. The study site is selected in a typical discontinuous permafrost region in the eastern Canadian sub-Arctic. Inuit communities in Nunavik and Nunatsiavut in the Canadian eastern sub-arctic are amongst the groups most affected by the impacts of climate change and permafrost degradation. Synthetic Aperture Radar (SAR) datasets have advantages for permafrost monitoring in the Arctic and sub-arctic regions because of its high resolution and independence of cloud cover and solar illumination. To date, permafrost environment monitoring methods and strategies with SAR datasets are still under development. The variability of active layer thickness is a direct indication of permafrost thermal state changes. The Differential SAR Interferometry (D-InSAR) technique is applied in the study site to derive ground deformation, which is introduced by the thawing/freezing depth of active layer and underlying permafrost. The D-InSAR technique has been used for the mapping of ground surface deformation over large areas by interpreting the phase difference between two signals acquired at different times as ground motion information. It shows the ability to detect freeze/thaw-related ground motion over permafrost regions. However, to date, accuracy and value assessments of D-InSAR applications have focused mostly on the continuous permafrost region where the vegetation is less developed and causes fewer complicating factors for the D-InSAR application, less attention is laid on the discontinuous permafrost terrain. In this thesis, the influencing factors and application conditions for D-InSAR in the discontinuous permafrost environment are evaluated by using X- band and L-band data. Then, benefit from by the high-temporal resolution of C-band Sentinel-1 time series, the seasonal displacement is derived from small baseline subsets (SBAS)-InSAR. Landforms are indicative of permafrost presence, with their changes inferring modifications to permafrost conditions. A permafrost landscape mapping method was developed which uses multi-temporal TerraSAR-X backscatter intensity and interferometric coherence information. The land cover map is generated through the combined use of object-based image analysis (OBIA) and classification and regression tree analysis (CART). An overall accuracy of 98% is achieved when classifying rock and water bodies, and an accuracy of 79% is achieved when discriminating between different vegetation types with one year of single-polarized acquisitions. This classification strategy can be transferred to other time-series SAR datasets, e.g., Sentinel-1, and other heterogeneous environments. One predominant change in the landscape tied to the thaw of permafrost is the dynamics of thermokarst lakes. Dynamics of thermokarst lakes are developed through their lateral extent and vertical depth changes. Due to different water depth, ice cover over shallow thermokarst ponds/lakes can freeze completely to the lake bed in winter, resulting in grounded ice; while ice cover over deep thermokarst ponds/lakes cannot, which have liquid water persisting under the ice cover all winter, resulting in floating ice. Winter ice cover regimes are related to water depths and ice thickness. In the lakes having floating ice, the liquid water induces additional heat in the remaining permafrost underneath and surroundings, which contributes to further intensified permafrost thawing. SAR datasets are utilized to detect winter ice cover regimes based on the character that liquid water has a remarkably high dielectric constant, whereas pure ice has a low value. Patterns in the spatial distribution of ice-cover regimes of thermokarst ponds in a typical discontinuous permafrost region are first revealed. Then, the correlations of these ice-cover regimes with the permafrost degradation states and thermokarst pond development in two historical phases (Sheldrake catchment in the year 1957 and 2009, Tasiapik Valley 1994 and 2010) were explored. The results indicate that the ice-cover regimes of thermokarst ponds are affected by soil texture, permafrost degradation stage and permafrost depth. Permafrost degradation is difficult to directly assess from the coverage area of floating-ice ponds and the percentage of all thermokarst ponds consisting of such floating-ice ponds in a single year. Continuous monitoring of ice-cover regimes and surface areas is recommended to elucidate the hydrological trajectory of the thermokarst process. Several operational monitoring methods have been developed in this thesis work. In the meanwhile, the spatial distribution of seasonal ground thaw subsidence, permafrost landscape, thermokarst ponds and their winter ice cover regimes are first revealed in the study area. The outcomes help understand the state and dynamics of permafrost environment.Der Permafrostboden bedeckt etwa 24% der exponierten Landfläche in der nördlichen Hemisphäre. Es ist ein wichtiges Element der Kryosphäre und hat starke Auswirkungen auf die Hydrologie, die biologischen Prozesse, das Energie-Budget der Landoberfläche und die Infrastruktur. Seit mehreren Jahrzehnten erhöhen sich die Oberflächenlufttemperaturen in den nördlichen hohen Breitengraden etwa doppelt so stark wie die globale Rate. Die Temperaturen der Permafrostböden sind in den meisten Regionen seit den frühen 1980er Jahren gestiegen. Die durchschnittliche Erwärmung nördlich von 60° N beträgt 1-2°C. In-situ-Messungen sind essentiell für das Verständnis der physischen Prozesse im Permafrostgelände. Es gibt jedoch mehrere Einschränkungen, die von Schwierigkeiten beim Bohren bis hin zur Repräsentativität begrenzter Einzelpunktmessungen reichen. Fernerkundung ist dringend benötigt, um bodenbasierte Messungen zu ergänzen und punktuelle Beobachtungen auf einen breiteren räumlichen Bereich auszudehnen. Diese Dissertation konzentriert sich auf die Umweltbeobachtung der subarktischen Permafrostböden mit SAR-Datensätzen. Das Untersuchungsgebiet wurde in einer typischen diskontinuierlichen Permafrostzone in der kanadischen östlichen Sub-Arktis ausgewählt. Die Inuit-Gemeinschaften in den Regionen Nunavik und Nunatsiavut in der kanadischen östlichen Sub-Arktis gehören zu den Gruppen, die am stärksten von den Auswirkungen des Klimawandels und Permafrostdegradation betroffen sind. Synthetische Apertur Radar (SAR) Datensätze haben Vorteile für das Permafrostmonitoring in den arktischen und subarktischen Regionen aufgrund der hohen Auflösung und der Unabhängigkeit von Wolkendeckung und Sonnenstrahlung. Bis heute sind die Methoden und Strategien mit SAR-Datensätzen für Umweltbeobachtung der Permafrostböden noch in der Entwicklung. Die Variabilität der Auftautiefe der aktiven Schicht ist eine direkte Indikation der Veränderung des thermischen Zustands der Permafrostböden. Die Differential-SAR-Interferometrie(D-Insar)-Technik wird im Untersuchungsgebiet zur Ableitung der Bodendeformation, die durch Auftau- / und Gefriertiefe der aktiven Schicht und des unterliegenden Permafrostbodens eingeführt wird, eingesetzt. Die D-InSAR-Technik wurde für Kartierung der Landoberflächendeformation über große Flächen verwendet, indem der Phasenunterschied zwischen zwei zu verschiedenen Zeitpunkten als Bodenbewegungsinformation erfassten Signalen interpretiert wurde. Es zeigt die Fähigkeit, tau- und gefrierprozessbedingte Bodenbewegungen über Permafrostregionen zu detektieren. Jedoch fokussiert sich die Genauigkeit und Wertschätzung der D-InSAR-Anwendung bis heute hauptsächlich auf kontinuierliche Permafrostregion, wo die Vegetation wenig entwickelt ist und weniger komplizierte Faktoren für D-InSAR-Anwendung verursacht. Das diskontinuierliche Permafrostgelände wurde nur weniger berücksichtigt. In dieser Dissertation wurden die Einflussfaktoren und Anwendungsbedingungen für D-InSAR im diskontinuierlichen Permafrostgebiet mittels X-Band und L-Band Daten ausgewertet. Dann wurde die saisonale Verschiebung dank der hohen Auflösung der C-Band Sentinel-1 Zeitreihe von „Small Baseline Subsets (SBAS)-InSAR“ abgeleitet. Landformen weisen auf die Präsenz des Permafrosts hin, wobei deren Veränderungen auf die Modifikation der Permafrostbedingungen schließen. Eine Kartierungsmethode der Permafrostlandschaft wurde entwickelt, dabei wurde Multi-temporal TerraSAR-X Rückstreuungsintensität und interferometrische Kohärenzinformationen verwendet. Die Landbedeckungskarte wurde durch kombinierte Anwendung objektbasierter Bildanalyse (OBIA) und Klassifikations- und Regressionsbaum Analyse (CART) generiert. Eine Gesamtgenauigkeit in Höhe von 98% wurde bei Klassifikation der Gesteine und Wasserkörper erreicht. Bei Unterscheidung zwischen verschiedenen Vegetationstypen mit einem Jahr einzelpolarisierte Akquisitionen wurde eine Genauigkeit von 79% erreicht. Diese Klassifikationsstrategie kann auf andere Zeitreihen der SAR-Datensätzen, z.B. Sentinel-1, und auch anderen heterogenen Umwelten übertragen werden. Eine vorherrschende Veränderung in der Landschaft, die mit dem Auftauen des Permafrosts verbunden ist, ist die Dynamik der Thermokarstseen. Die Dynamik der Thermokarstseen ist durch Veränderungen der seitlichen Ausdehnung und der vertikalen Tiefe entwickelt. Aufgrund der unterschiedlichen Wassertiefen kann die Eisdecke über den flachen Thermokarstteichen/-seen im Winter bis auf den Wasserboden vollständig gefroren sein, was zum geerdeten Eis führt, während die Eisdecke über den tiefen Thermokarstteichen/-seen es nicht kann. In den tiefen Thermokarstteichen/-seen bleibt den ganzen Winter flüssiges Wasser unter der Eisdecke bestehen, was zum Treibeis führt. Das Wintereisdeckenregime bezieht sich auf die Wassertiefe und die Eisdicke. In den Seen mit Treibeis leitet das flüssige Wasser zusätzliche Wärme in den restlichen Permafrost darunter oder in der Umgebung, was zur weiteren Verstärkung des Permafrostauftauen beiträgt. Basiert auf den Charakter, dass das flüssige Wasser eine bemerkenswert hohe Dielektrizitätskonstante besitzt, während reines Eis einen niedrigen Wert hat, wurden die SAR Datensätzen zur Erkennung des Wintereisdeckenregimes verwendet. Zunächst wurden Schemen in der räumlichen Verteilung der Eisdeckenregimes der Thermokarstteiche in einer typischen diskontinuierlichen Permafrostregion abgeleitet. Dann wurden die Zusammenhänge dieser Eisdeckenregimes mit dem Degradationszustand des Permafrosts und der Entwicklung der Thermokarstteiche in zwei historischen Phasen (Sheldrake Einzugsgebiet in 1957 und 2009, Tasiapik Tal in 1994 und 2010) erforscht. Die Ergebnisse deuten darauf, dass die Eisdeckenregimes der Thermokarstteiche von der Bodenart, dem Degradationszustand des Permafrosts und der Permafrosttiefe beeinflusst werden. Es ist schwer, die Permafrostdegradation in einem einzelnen Jahr direkt durch den Abdeckungsbereich der Treibeis-Teiche und die Prozentzahl aller aus solchen Treibeis-Teichen bestehenden Thermokarstteiche abzuschätzen. Ein kontinuierliches Monitoring der Eisdeckenregimes und -oberflächen ist empfehlenswert, um den hydrologischen Verlauf des Thermokarstprozesses zu erläutern. In dieser Dissertation wurden mehrere operativen Monitoringsmethoden entwickelt. In der Zwischenzeit wurden die räumliche Verteilung der saisonalen Bodentauabsenkung, die Permafrostlandschaft, die Thermokarstteiche und ihre Wintereisdeckenregimes erstmals in diesem Untersuchungsgebiet aufgedeckt. Die Ergebnisse tragen dazu bei, den Zustand und die Dynamik der Permafrostumwelt zu verstehen

Forward Modelling of Multifrequency SAR Backscatter of Snow-Covered Lake Ice: Investigating Varying Snow and Ice Properties Within a Radiative Transfer Framework

Lakes are a key feature in the Northern Hemisphere landscape. The coverage of lakes by ice cover has important implications for local weather conditions and can influence energy balance. The presence of lake ice is also crucial for local economies, providing transportation routes, and acting as a source of recreation/tourism and local customs. Both lake ice cover, from which ice dates and duration can be derived (i.e., ice phenology), and ice thickness are considered as thematic variables of lakes as an essential climate variable by the Global Climate Observing System (GCOS) for understanding how climate is changing. However, the number of lake ice phenology ground observations has declined over the past three decades. Remote sensing provides a method of addressing this paucity in observations. Active microwave remote sensing, in particular synthetic aperture radar (SAR), is popular for monitoring ice cover as it does not rely on sunlight and the resolution allows for the monitoring of small and medium-sized lakes. In recent years, our understanding of the interaction between active microwave signals and lake ice has changed, shifting from a double bounce mechanism to single bounce at the ice-water interface. The single bounce, or surface scattering, at the ice-water interface is due to a rough surface and high dielectric contrast between ice and water. However, further work is needed to fully understand how changes in different lake ice properties impact active microwave signals. Radiative transfer modelling has been used to explore these interactions, but there are a variety of limitations associated with past experiments. This thesis aimed to faithfully represent lake ice using a radiative transfer framework and investigate how changes in lake ice properties impact active microwave backscatter. This knowledge was used to model backscatter throughout ice seasons under both dry and wet conditions. The radiative transfer framework used in this thesis was the Snow Microwave Radiative Transfer (SMRT) model. To investigate how broad changes in ice properties impact microwave backscatter, SMRT was used to conduct experiments on ice columns representing a shallow lake with tubular bubbles and a deep lake without tubular bubbles at L/C/X-band frequencies. The Canadian Lake Ice Model (CLIMo) was used to parameterize SMRT. Ice properties investigated included ice thickness, snow ice bubble radius and porosity, root mean square (RMS) height of the ice-water interface, correlation length of the ice-water interface, and tubular bubble radius and porosity. Modelled backscatter indicated that changes in ice thickness, snow ice porosity, and tubular bubble radius and porosity had little impact on microwave backscatter. The property that had the largest impact on backscatter was RMS height at the ice-water interface, confirming the results of other recent studies. L and C-band frequencies were found to be most sensitive to changes in RMS height. Bubble radius had a smaller impact on backscatter, but X-band was found to be most sensitive to changes in this property and would be a valuable frequency for studying surface ice conditions. From the results of these initial experiments, SMRT was then used to simulate the backscatter from lake ice for two lakes during different winter seasons. Malcolm Ramsay Lake near Churchill, Manitoba, represented a shallow lake with dense tubular bubbles and Noell lake near Inuvik, Northwest Territories, represented a deep lake with no tubular bubbles. Both field data and CLIMo simulations for the two lakes were used to parameterize SMRT. Because RMS height was determined to be the ice property that had the largest impact on backscatter, simulations focused on optimizing this value for both lakes. Modelled backscatter was validated using C-band satellite imagery for Noell Lake and L/C/X-band imagery for Malcolm Ramsay Lake. The root mean square error values for both lakes ranged from 0.38 to 2.33 dB and Spearman’s correlation coefficient (ρ) values >0.86. Modelled backscatter for Noell Lake was closer to observed values compared to Malcolm Ramsay Lake. Optimized values of RMS height provided a better fit compared to a stationary value and indicated that roughness likely increases rapidly at the start of the ice season but plateaus as ice growth slows. SMRT was found to model backscatter from ice cover well under dry conditions, however, modelling backscatter under wet conditions is equally important. Detailed field observations for Lake Oulujärvi in Finland were used to parameterize SMRT during three different conditions. The first was lake ice with a dry snow cover, the second with an overlying layer of wet snow, and the third was when a slush layer was present on the ice surface. Experiments conducted under dry conditions continued to support the dominance of scattering from the ice-water interface. However, when a layer of wet snow or slush layer was introduced the dominant scattering interface shifted to the new wet layer. Increased roughness at the boundary of these wet layers resulted in an increase in backscatter. The increase in backscatter is attributed to the higher dielectric constant value of these layers. The modelled backscatter was found to be representative of observed backscatter from Sentinel-1. The body of work of this thesis indicated that the SMRT framework can be used to faithfully represent lake ice and model backscatter from ice covers and improved understanding of the interaction between microwave backscatter and ice properties. With this improved understanding inversion models can be developed to retrieve roughness of the ice-water interface, this could be used to build other models to estimate ice thickness based on other remote sensing data. Additionally, insights into the impact of wet conditions on radar backscatter could prove useful in identifying unsafe ice locations

Sea Ice Extraction via Remote Sensed Imagery: Algorithms, Datasets, Applications and Challenges

The deep learning, which is a dominating technique in artificial intelligence, has completely changed the image understanding over the past decade. As a consequence, the sea ice extraction (SIE) problem has reached a new era. We present a comprehensive review of four important aspects of SIE, including algorithms, datasets, applications, and the future trends. Our review focuses on researches published from 2016 to the present, with a specific focus on deep learning-based approaches in the last five years. We divided all relegated algorithms into 3 categories, including classical image segmentation approach, machine learning-based approach and deep learning-based methods. We reviewed the accessible ice datasets including SAR-based datasets, the optical-based datasets and others. The applications are presented in 4 aspects including climate research, navigation, geographic information systems (GIS) production and others. It also provides insightful observations and inspiring future research directions.Comment: 24 pages, 6 figure