TanDEM-X Ground Segment – DEM Products Specification Document

The purpose of this document is to describe the TanDEM-X DEM products, their specifications and formats.The chapter 4 introduces the main DEM product, and its variants. The target accuracies are presented (Section 4.1.) and the DEM generation process is shortly summarized in Section 4.2.. The DEM product specifications are given in Section 4.3. Therein, the accuracy and grid definitions (Section 4.3.1) all information layers are described (Section 4.3.2). Information about the structure of the DEM product is provided in Section 4.3.3. Section 4.4. gives a short summary about the characteristics of the Intermediate DEM Product and future FDEM and HDEM products. In the Appendices an introduction to the XML schema, product parameters and change log information are described. Please note that the current XSDs are appended to this document

Forest attributes mapping with SAR data in the romanian South-Eastern Carpathians requirements and outcomes

Esta tesis doctoral se centra en la estimación de variables forestales en la zona Sureste de los Cárpatos Rumanos a partir de imágenes de radar de apertura sintética. La investigación abarca parte del preprocesado de las imágenes, métodos de generación de mosaicos y la extracción de la cobertura de bosque, sus subtipos o su biomasa. La tesis se desarrolló en el Instituto Nacional de Investigación y Desarrollo Forestal Marín Dracea (INCDS) y la Universidad de Alcalá (UAH) gracias a varios proyectos: el proyecto EO-ROFORMON del INCDS (Prototyping an Earth-Observation based monitoring and forecasting system for the Romanian forests), y el proyecto EMAFOR de la UAH (Synthetic Aperture Radar (SAR) enabled Analysis Ready Data (ARD) cubes for efficient monitoring of agricultural and forested landscapes). El proyecto EO-ROFORMON fue financiado por la Autoridad Nacional para la Investigación Científica de Rumania y el Fondo Europeo de Desarrollo Regional. El proyecto EMAFOR fue financiado por la Comunidad Autónoma de Madrid (España). El objetivo de esta tesis es el desarrollo de algoritmos para la extracción de variables forestales de uso general como la cobertura, el tipo o la biomasa del bosque a partir de imagen de radar de apertura sintética. Para alcanzar dicho propósito se analizaron posibles fuentes de sesgo sistemático que podrían aparecer en zonas de montaña (ej., normalización topográfica, generación de mosaicos), y se aplicaron técnicas de aprendizaje de máquina para tareas de clasificación y regresión. La tesis contiene ocho secciones: una introducción, cinco publicaciones en revistas o actas de congresos indexados, una pendiente de publicación (quinto capítulo) y las conclusiones. La introducción contextualiza la importancia del bosque, cómo se recoge la información sobre su estado (ej., inventario forestal) y las iniciativas o marcos legislativos que requieren dicha información. A continuación, se describe cómo la teledetección puede complementar la información de inventario forestal, detallando el contexto histórico de las distintas tecnologías, su funcionamiento, y cómo pueden ser aplicadas para la extracción de información forestal. Por último, se describe la problemática y el monitoreo del bosque en Rumanía, detallando el objetivo de la tesis y su estructura. El primer capítulo analiza la influencia del modelo digital de elevaciones (MDE) en la calidad de la normalización topográfica, analizando tres MDE globales (SRTM, AW3D y TanDEM-X DEM) y uno nacional (PNOA-LiDAR). Los experimentos se basan en la comparación entre órbitas, con un MDE de referencia, y la variación del acierto en la clasificación dependiendo del MDE empleado para la normalización. Los resultados muestran una menor diferencia ente órbitas al utilizar un MDE con una mejor resolución (ej. TanDEM-X, PNOA-LIDAR), especialmente en el caso de zonas con fuertes pendientes o formas del terreno complejas, como pueden ser los valles. En zonas de alta montaña las imágenes de radar de apertura sintética (SAR) sufren frecuentes distorsiones. Estas distorsiones dependen de la geometría de adquisición, por lo que es posible combinar imágenes adquiridas desde varias órbitas para que la cobertura sea lo más completa posible. El segundo capítulo evalúa dos metodologías para la clasificación de usos del suelo utilizando datos de Sentinel-1 adquiridos desde varias órbitas. El primer método crea clasificaciones por órbita y las combina, mientras que el segundo genera un mosaico con datos de múltiples órbitas y lo clasifica. El acierto obtenido mediante combinación de clasificaciones es ligeramente mayor, mientras que la clasificación de mosaicos tiene importantes omisiones de las zonas boscosas debido a problemas en la normalización topográfica y a los efectos direccionales. El tercer capítulo se enfoca en separar la cobertura forestal de otras coberturas del suelo (urbano, vegetación baja, agua) analizando la utilidad de las variables basadas en la coherencia interferométrica. En él se realizan tres clasificaciones de máquina vector-soporte basadas en un conjunto concreto de variables. El primer conjunto contiene las estadísticas anuales de la retrodispersión (media y desviación típica anual), el segundo añade la coherencia a largo plazo (separación temporal mayor a un año), el tercero incluye las estadísticas de la coherencia a corto plazo (mínima separación temporal). Utilizar variables basadas en la coherencia aumenta el acierto de la clasificación hasta un 5% y reduce los errores de omisión de la cobertura forestal. El cuarto capítulo evalúa la posibilidad de detectar talas selectivas utilizando datos de Sentinel-1 y Sentinel-2. Sus resultados muestran que la detección resulta muy difícil debido a la saturación de los sensores y la confusión introducida por el efecto de la fenología. El quinto capítulo se centra en la clasificación de tipos de bosque basado en una serie temporal de datos Sentinel-1. Se basa en la creación de un conjunto de modelos que describen la relación entre la retrodispersión y el ángulo local de incidencia para un determinado tipo de bosque y fecha concreta. Para cada píxel se calcula el residuo respecto al modelo de cada uno de los tipos de bosque, acumulando dichos residuos a lo largo de la serie temporal. Hecho esto, cada píxel es asignado al tipo de bosque que acumula un menor residuo. Los resultados son prometedores, mostrando que frondosas y coníferas tienen un comportamiento distintivo, y que es posible separar ambos tipos de bosque con un alto grado de acierto. El sexto capítulo está dedicado a la estimación de biomasa utilizando datos Sentinel-1, ALOS PALSAR y regresión Random Forest. Se obtiene un error similar para ambos sensores a pesar de utilizar una banda diferente (band-C vs. -L), con poca reducción en el error cuando ambas bandas se utilizan conjuntamente. Sin embargo, el ajuste de un estimador adaptado a las condiciones locales de Rumanía sí ofreció una reducción de del error al ser comparado con las estimaciones globales de biomasa

Quantification and Change Assessment Benjamin Aubrey Robson 2016 Dissertation date: 31st October 2016 of Debris-Covered Glaciers using Remote Sensing

This thesis investigates how remote sensing data can be used to assess the changing state of debris-covered ice. The principal study areas are the Manaslu Region in Nepal (papers I and III) and the Hohe Tauern National Park, Austria (paper II). Clean glacier ice is straightforward to semi-automatically classify using multi-spectral satellite imagery owing to the strong spectral signature of clean ice in the visible and near-infrared sections of the electromagnetic spectrum. Since the ablation zones of clean ice glaciers are at the pressure melting point, a change in terminus position or glacier area can be directly linked to a change in climate. Debris-covered ice is however more complicated to map and to interpret temporal change. Supraglacial debris is spectrally indistinguishable from the surrounding paraglacial terrain, and requires auxiliary data such as a Digital Elevation Model (DEM), thermal band data, or flow data. Object-Based Image Analysis (OBIA) provides a framework for combining multiple datasets in one analysis, while additionally allowing shape, contextual, hierarchical and textural criteria to be used to classify imagery. Paper I combines optical (Landsat-8), topographic (void-filled SRTM) and SAR coherence (ALOS PALSAR) data within an OBIA workflow to semi-automatically classify both clean ice and debris-covered ice in the challenging area surrounding Mount Manaslu in Nepal. When compared with manually delineated outlines, the classification achieved an accuracy of 91% (93% for clean ice and 83% for debriscovered ice). The classification was affected by seasonal snow and shadows while the debris-covered ice mapping was influenced by the datasets being temporally inconsistent, and the mountainous topography causing inconsistencies in the SAR coherence data. The method compares well with other automated techniques for classifying debris-covered ice, but has two additional advantages: firstly, that SAR coherence data can distinguish active ice from stagnant ice based on whether motion or significant downwasting has occured, and secondly, that the method is applicable over a large study area using just space-borne data. Paper II explores the potential of using high-resolution (10 m) topographic data and an edge detection algorithm to morphologically map the extent of debris-covered ice. The method was applied in the Hohe Tauern National Park, Austria, using a 10 m DEM derived from airborne Light Detection and Radar (LiDAR) acquisitions. Additionally, the end-of-summer transient snowline (TSL) was also mapped, which approximates the annual Equilibrium Line Altitude (ELA). Our classification was applied on three Landsat satellite images from 1985, 2003 and 2013 and compared the results to the Austrian Glacier Inventories from 1969 and 1998 to derive decadal-scale glacial changes. A mean rate of glacier area reduction of 1.4 km2a-1 was calculated between 1969 and 2013 with a total reduction in area of 33%. The TSL rose by 92 m between 1985 and 2013 to an altitude of 3005 m. By comparing our results with manually delineated outlines an accuracy of 97.5% was determined. When a confusion matrix was calculated it could be seen that the results contained few false positives but some false negatives which were attributed to seasonal snow, shadows and misclassified debris. Our results correspond broadly with those found in other areas of the European Alps although a heterogeneity in glacier change is observable. We recommend that future glacier mapping investigations should utilise a combination of both SAR coherence data and high-resolution topographic data in order to delineate the extent of both active and stagnant glacier ice. Paper III investigates decadal scale changes in glacier area, velocity and volume in the previously undocumented Manaslu Region, Nepal. Between 2001 and 2013 the glacier area reduced by 8.2% (-0.68% a-1). Simultaneously, the glaciers lowered by -0.21 ± 0.08 m a-1 and had a slightly negative specific mass balance of -0.05 ± 016 m w.e a-1 although mass balances ranged -2.49 ± 2.24 to +0.27 ± 0.30 m w.e a-1 throughout the region. The geodetic mass balance for select glaciers covered by a Corona DEM between 1970 and 2013 was -0.24 ± 0.12 m w.e a-1 which became more negative (-0.51 ± 0.12 m w.e. a-1) between 2005 and 2013. Rates of surface lowering over debriscovered ice increasing by 168% between 1970 – 2000 (0.40 ± 0.18 m a-1) and 2005 – 2013 (1.07 ±0.48 m a-1). The rate of glacier melt varies due to presumed increases in debris thickness at the upper and lower boundaries of the ablation zone, while an area of enhanced glacier downwasting corresponds to the presence of supraglacial lakes and exposed ice. The glacier velocity varies across the region. Many glaciers have stagnant sections towards the glacier termini, and a trend of ongoing stagnation is observable. No relationship exists between trends in glacier area and glacier volume or velocity, although a weak relationship exists between trends in the changes of volume and velocity. The rates of glacier area and velocity change appear to be similar, although the number of glaciers that had records of area, velocity, and volume was few. Our results are comparable to studies looking at mean surface lowerings and geodetic mass balances in other areas of the Himalayas, and point towards heterogeneous yet pronounced mass losses across the Himalaya region

Radar Backscatter Modeling Based on Global TanDEM-X Mission Data

Radarrückstreuung bezeichnet den Teil eines ausgesendeten elektromagnetischen Signals, der von einem Ziel am Boden wieder zurück zur Antenne gerichtet ist. Die Eigenschaften des zurückgestreuten Signals ändern sich in Abhängigkeit von Frequenz und Polarisation des Radarsignals, der Aufnahmegeometrie, sowie vom Zustand des Erdbodens und der Art der Bodenbedeckung. Informationen über das Radarrückstreuverhalten sind von höchster Wichtigkeit für die Auslegung von SAR-Missionen und werden verbreitet zur Entwicklung wissenschaftlicher Modelle genutzt, beispielsweise bei der Erforschung der Biosphäre und Kryosphäre. Hauptziel dieser Arbeit ist die Auswertung und Nutzung des globalen TanDEM-X-Datensatzes zur Modellierung der Radarrückstreuung im X-Band unter Berücksichtigung unterschiedlicher Aufnahmeparameter und Landnutzungsarten, sowie die Bereitstellung einer Reihe von globalen Rückstreumodellen, die auf aktuellen Daten basieren, für die wissenschaftliche Gemeinschaft. Es wurde ein neuer Ansatz zur statistischen Modellierung der Rückstreuinformation entwickelt, der die Qualität der zugrunde liegenden Messungen berücksichtigt. Daraus ergeben sich gewichtete polynomiale Modelle für die verschiedenen Landnutzungsarten, wie sie in der GlobCover-Karte der ESA definiert sind. Darüber hinaus wird ein eigener Validierungsansatz vorgestellt, mit zusätzlicher Betrachtung der saisonalen Variation der Rückstreuung und einer separaten Analyse des Rückstreuverhaltens des Tropischen Regenwaldes. Der nächste Schwerpunkt ist die Betrachtung des Grönländischen Eisschildes, das gekennzeichnet ist durch das Vorhandensein verschiedener Arten von Schneebedeckung, die von trockenem bis hin zu sehr feuchtem Schnee variiert. Der begrenzte Detailgrad, den die GlobCover Karte in Grönland aufweist (nur eine Klasse für das gesamte Eisschild), erlaubt dort keine verlässliche Modellierung der Rückstreuung. Diese Schwierigkeit lieferte die Motivation für die Entwicklung eines neuen Ansatzes zur Analyse des Informationsgehalts der interferometrischen TanDEM-X-Daten mit dem Ziel, unterschiedliche Schnee-Fazien mit Hilfe des sog. C-Means Fuzzy Clustering Algorithmus zu lokalisieren. Aus dieser Untersuchung konnte die Existenz von vier unterschiedlichen Klassen von Schnee-Fazien abgeleitet werden, deren Eigenschaften anschließend mit Hilfe externer Referenzdaten interpretiert wurden. Die daraus entstandene Karte wurde zur Erstellung eines einfallswinkelabhängigen Rückstreumodells genutzt, separat für jede der vier Klassen, wobei eine modifizierte Version des entwickelten Algorithmus zur Generierung globaler Rückstreumodelle eingesetzt wurde. Darüber hinaus wurde als Nebenprodukt zusätzlich die Eindringtiefe von TanDEM-X in die Eisschicht geschätzt, durch Inversion des von Weber Hoen und Zebker vorgeschlagenen "Ein-chicht Volumendekorrelationsmodells". Die Ergebnisse wurden mit dem Höhenunterschied zwischen dem globalen TanDEM-X-DEM und ICESat-Messungen verglichen. Abschließend wird ein neu entwickelter Algorithmus zur Generierung von Rückstreukarten großer Gebiete vorgestellt. Dieser erlaubt unter Verwendung von Rückstreumodellen das Angleichen der erstellten Karten anhand eines Referenzeinfallswinkels, was dann das Füllen verbleibender Lücken ermöglicht, die aufgrund fehlender Eingangsdaten vorhanden sind

Analysis and visualisation of digital elevation data for catchment management

River catchments are an obvious scale for soil and water resources management, since their shape and characteristics control the pathways and fluxes of water and sediment. Digital Elevation Models (DEMs) are widely used to simulate overland water paths in hydrological models. However, all DEMs are approximations to some degree and it is widely recognised that their characteristics can vary according to attributes such as spatial resolution and data sources (e.g. contours, optical or radar imagery). As a consequence, it is important to assess the ‘fitness for purpose’ of different DEMs and evaluate how uncertainty in the terrain representation may propagate into hydrological derivatives. The overall aim of this research was to assess accuracies and uncertainties associated with seven different DEMs (ASTER GDEM1, SRTM, Landform Panorama (OS 50), Landform Profile (OS 10), LandMap, NEXTMap and Bluesky DTMs) and to explore the implications of their use in hydrological analysis and catchment management applications. The research focused on the Wensum catchment in Norfolk, UK. The research initially examined the accuracy of the seven DEMs and, subsequently, a subset of these (SRTM, OS 50, OS10, NEXTMap and Bluesky) were used to evaluate different techniques for determining an appropriate flow accumulation threshold to delineate channel networks in the study catchment. These results were then used to quantitatively compare the positional accuracy of drainage networks derived from different DEMs. The final part of the thesis conducted an assessment of soil erosion and diffuse pollution risk in the study catchment using NEXTMap and OS 50 data with SCIMAP and RUSLE modelling techniques. Findings from the research demonstrate that a number of nationally available DEMs in the UK are simply not ‘fit for purpose’ as far as local catchment management is concerned. Results indicate that DEM source and resolution have considerable influence on modelling of hydrological processes, suggesting that for a lowland catchment the availability of a high resolution DEM (5m or better) is a prerequisite for any reliable assessment of the consequences of implementing particular land management measures. Several conclusions can be made from the research. (1) From the collection of DEMs used in this study the NEXTMap 5m DTM was found to be the best for representing catchment topography and is likely to prove a superior product for similar applications in other lowland catchments across the UK. (2) It is important that error modelling techniques are more routinely employed by GIS users, particularly where the fitness for purpose of a data source is not well-established. (3) GIS modelling tools that can be used to test and trial alternative management options (e.g. for reducing soil erosion) are particularly helpful in simulating the effect of possible environmental improvement measures

Mass balance of Icelandic glaciers in variable climate

The mass balance of a glacier is strongly connected to climate. At high latitudes, mass balance is typically controlled by snow accumulation during the winter and the glacier ablation during the summer. In Iceland, direct mass balance observations have been mostly focused on the three largest ice caps (~600 to ~8000 km2), measured in situ for the last 25 years. There are, however, glaciers and ice caps distributed over all quarters of the country that lack mass balance observations. Remote sensing data with the capability to retrieve the glacier surface geometry through Digital Elevation Models (DEMs) are valuable tools to measure mass balance using the geodetic method. For a typical Icelandic glacier (with an area between 1 km2 and hundreds of km2), this can be optimally achieved from optical stereoscopic imagery, emplaced in airborne or spaceborne sensors, and from airborne lidar. This thesis focuses on remote sensing techniques to accurately measure geodetic mass balance from seasonal to decadal time spans and the relationship of mass balance to climate. As an example of seasonal mass balance, the winter mass balance of Drangajökull was measured from satellite sub-meter stereo images at the beginning, middle and end of the 2014–2015 winter using data from the Pléiades and WorldView-2 satellites. The results were complemented with in situ snow density measurements and validated with snow thickness measurements. The study concludes that images from the sensors mentioned above may often be used to monitor seasonal mass balance without tedious field logistics. A vast archive of aerial photographs exists for Iceland extending back to 1945. Since then, most glaciers were surveyed every 5 to 20 years. In addition, a wealth of modern satellite stereo images is available since the early 2000s as well as airborne lidar data in 2008–2013. This creates a unique dataset to construct a 70-year time series of geodetic mass balances. Eyjafjallajökull (~70 km2) was used to develop semi-automated processing chains based on open-source software. The result is a detailed record of glacier changes resulting from climatic and volcanic forcing. Simple linear regression of the annual mass balance of Eyjafjallajökull indicates that most mass balance variations can be related to changes in summer temperature and winter precipitation. It also allows to infer the sensitivities of mass balance to these two climatic variables. The processing chain was then applied to 14 glaciers and ice caps spatially distributed in all quarters of Iceland, resulting in a dense mass-balance record for the last 70 years. The mean and standard deviation (±SD) of mass balances of the target glaciers were –0.44±0.16 m w.e. a–1 in 1945–1960, 0.00±0.21 m w.e. a–1 in 1960–1980, 0.11±0.25 m w.e. a–1 in 1980–1994, –1.01±0.50 m w.e. a–1 in 1994–2004, –1.27±0.56 m w.e. a–1 in 2004–2010 and –0.14±0.51 m w.e. a–1 in 2010–2015. The glaciers located at the south and west coasts revealed the highest decadal variability, in contrast to glaciers located in the north. This study improves the knowledge of Icelandic glaciers prior to the warm 1990s. The obtained glacier DEMs reveals in some cases elevation changes caused by irregularities in ice motion and opens for opportunities of modelling the ice dynamics of some of these glaciers coupled with their mass balance.Afkoma jökla ræðst af veðurfari. Augljós eru tengslin við snjósöfnun vetrar, en einnig hitastig sumars sem vísbending um orku til leysingar. Hefðbundnar reglulegar afkomumælingar með mælingu þykktar vetrarsjós að hausti og sumarleysingu að hausti, á völdum mælistöðvum, hófust á þremur stærstu jöklum Íslands á níunda og tíunda áratug síðustu aldar og hefur verið haldið úti síðan. Á öðrum jöklum Íslands eru beinar afkomumælingar takmarkaðar; á langflestum hafa engar slíkar mælingar verið gerðar. Upplýsingar um afkomu jökla má einnig meta með því að bera saman hæðarkort af yfirborði þeirra á mismunandi tímum. Í þessu skyni eru fjarkönnunargögn eins og loftmyndir, gervihnattaljósmyndir og leysihæðarskönnun (lidar) sem nýtast við gerð hæðarkorta einkar gagnleg. Viðfangsefni ritgerðarinnar er úrvinnsla slíkra gagna og hvernig má nýta þau til að fá sem nákvæmasta mælinga á afkomu jökla á tímabilum sem spanna allt frá árstíð til áratuga, auk þess sem vensl afkomu og veðurfars eru greind. Til að kanna notagildi fjarkönnunargagna við rannsóknir á árstíðabundinni afkomu jökla voru yfirborðshæðarkort af Drangajökli unnin eftir háupplausnarljósmyndum frá Pléiades og WorldView-2 gervitunglunum við upphaf, miðbik og lok vetursins 2014–2015. Mælingar á eðlismassa vetrarsnjós að vori voru nýttar til að skorða betur vetrarafkomu jökulsins auk þess sem niðurstöðurnar voru bornar saman við mælda snjóþykkt í afkomumælistöðum. Niðurstöður rannsóknarinnar sýna ótvírætt að oft er hægt að nýta myndir frá áðurnefndum gervitunglum við mælingu vetrarákomu jökla í stað þess að leggja í og erfiða mælileiðangra. Gríðarmikið safn loftmynda er til af íslenskum jöklum allt aftur til ársins 1945. Síðan þá hafa þeir flestir verið myndaðir á 5 til 20 ára fresti. Einnig hefur verulegu magni gervihnattaljósmynda sem nýtast til vinnslu hæðarkorta af jöklum verið aflað eftir 2000 auk hæðarkorta eftir leysimælingum úr flugvél af flestum jöklum landsins frá 2008 til 2013. Þessi yfirgripsmiklu gögn gera mögulega vinnslu 70 ára afkomusögu margra jökla. Með slíka vinnslu að markmiði var sett saman hálfsjálfvirk úrvinnslulína (flæðilína úrvinnsluþátta) sem byggist á opnum hugbúnaðarlausnum. Hún var þróuð fyrir og fyrst beitt á öll tiltæk gögn af Eyjafjallajökli (~70 km2 ). Úrvinnslan skilaði ítarlegri sögu um hæðarbreytingar, afkomu og umfang Eyjafjallajökuls sem bæði veðurfar og eldgos hafa stjórnað. Útfrá afkomuröðinni var bestað línulegt fall sem lýsir venslum ársafkomu við sumarhita og vetrarúrkomu auk leiðréttingarliðs vegna breytilegs umfangs jökulsins. Þetta fall sýnir að stór þáttur breytileika afkomu jökulsins má skýra með breytileika í þessum veðurfarsþáttum. Það gerir einnig kleift að meta hversu næm afkoma jökulsins er fyrir breytingum í þeim. Úrvinnslulínan var síðan notuð til að setja saman afkomusögu 14 íslenska jökla á um 70 ára tímabili. Jöklar í öllum landsfjórðungum sem og á miðhálendinu voru rannsakaðir. Meðaltal og staðalfrávik afkomu jöklanna á hverju tímabili fyrir sig var -0.44±0.16 m v.g. ár–1 (metrar vatnsígildis á ári) 1945–1960, 0.00±0.21 m v.g. ár–1 1960–1980, 0.11±0.25 m v.g. ár–1 1980–1994, -1.01±0.50 m v.g. ár–1 1994–2004, -1.27±0.56 m v.g. ár–1 2004–2010 og -0.14±0.51 m v.g. ár–-1 2010–2015. Jöklar við suður og vesturströndina sýna breytilegasta afkomu frá einu tímabili til annars, ólíkt jöklum í norðri þar sem þessi breytileiki er mun minni. Þessi rannsókn eykur mjög við þekkingu okkar á íslenskum jöklum áður en mikil hlýnun varð á tíunda áratug síðustu aldar sem og hvernig afkomu íslenskra jökla breyttist í kjölfarið. Jökla-kortin sem þessi vinna hefur skilað sýna víða hæðarbreytingar sem skýrast af tímabreyti-leika eða óreglu í ísflæði frá afkomu- til leysingasvæðis jöklanna. Þau nýtast einnig sem próf fyrir framtíðarrannsóknir með samtengdum líkönum ísflæðis og afkomu þessara jökla.Le bilan de masse des glaciers est fortement lié au climat. Aux hautes latitudes, l’accumulation de neige pendant l’hiver et la fonte de glace pendant l’été sont les principales composantes du bilan de masse. En Islande, le bilan de masse des trois plus larges calottes glaciaires (~600-~8000 km²) a été suivi régulièrement depuis 25 ans notamment grâce à des mesures in situ. Mais les bilans de masse des autres glaciers et calottes glaciaires islandaises ont été très peu étudiés. Aujourd’hui, les données de télédétection, notamment via la comparaison des modèles numériques du terrain (MNT), permettent de mesurer le bilan de masse par la méthode géodésique. Pour ces glaciers et calottes de plus petites tailles (de 1 km² et à quelques centaines de km²), les photographies aériennes, l’imagerie satellitaire stéréoscopique sub-métriques, et le lidar aérien sont parfaitement adaptées. Cette thèse se focalise donc sur l’estimation des bilans de masse des « petits » glaciers et calottes islandaises depuis le pas de temps saisonnier jusqu’à pluridécennal et leur relation avec les variations spatiales et temporelles du climat. Le bilan de masse hivernal de la calotte du Drangajökull (NO-Islande) a été mesuré par des images satellitaires stéréoscopiques sub-métriques (données Pléiades et WorldView-2) acquises au début, milieu et à la fin de l’hiver 2014-2015. Les changements de volume ont été convertis en bilan de masse grâce à des mesures in situ de densité de neige, et validés avec des mesures in situ de profondeur de neige. Ce travail permet d’envisager désormais un suivi du bilan de masse saisonnier sans un laborieux travail de terrain. Une importante archive de photographies aériennes est disponible en Islande depuis 1945. Ces données offrent une revisite de 5 à 20 ans pour la majorité des glaciers. De plus, depuis 2000, cette archive est complétée par les données des capteurs satellitaires stéréoscopiques et de lidar aérien acquis entre 2008 et 2013. Cet ensemble de données est exploité pour créer une série temporelle de 70 ans de bilan de masse en Islande. La calotte d’Eyjafjallajökull (~70 km²) sert de zone test pour la création et l’automatisation d’une chaîne de traitement, basée sur des logiciels libres. Le résultat est une série de 70 ans de bilan de masse et changements glaciaires liés au climat et au volcanisme. Les variations décennales du bilan de masse sont mises en relation avec les variations des températures estivales et les précipitations hivernales. Cette relation, quasi linéaire, sert pour le calcul de la sensibilité du bilan de masse au changement de température et précipitation. La chaîne de traitement est alors appliquée à 14 glaciers et calottes glaciaires distribuées aux quatre coins de l’Islande. La moyenne et déviation standard (±DS) du bilan de masse des glaciers sélectionnés est : –0.44±0.16 m w.e. a–1 en 1945–1960, 0.00±0.21 m w.e. a–1 en 1960–1980, 0.11±0.25 m w.e. a–1 en 1980–1994, –1.01±0.50 m w.e. a–1 en 1994–2004, –1.27±0.56 m w.e. a–1 en 2004–2010 et –0.14±0.51 m w.e. a–1 en 2010–2015. Les glaciers maritimes situés près des côtes sud et ouest montrent une plus forte variabilité décennale que les glaciers plus continentaux situés dans le nord et nord-ouest. Notre étude améliore la connaissance des évolutions des glaciers islandais et leur relation avec le climat, en particulier avant les années 1990s et l’augmentation de température. Nos travaux montrent aussi la complexité de la réponse géométrique des glaciers (en lien avec leur dynamique) et offre des données uniques pour la calibration/validation des modèles des glaciers.This work was financially supported by the University of Iceland Research Fund, the Jules Verne Fund and the Katla Kalda project. The lidar mapping of the glaciers in Iceland was funded by the Icelandic Research Fund, the Landsvirkjun research fund, the Icelandic Road Administration, the Reykjavík Energy Environmental and Energy Research Fund, the Klima- og Luftgruppen research fund of the Nordic Council of Ministers, the Vatnajökull National Park, the organization Friends of Vatnajökull, LMÍ, IMO and the UI research fund. Pléiades images were acquired at research price thanks to the CNES ISIS program. WorldView DEMs were obtained through the ArcticDEM project

Bilan de masse des glaciers islandais depuis 1945 : reconstruction et relation avec la variabilité climatique

Le bilan de masse des glaciers est fortement lié au climat. Aux hautes latitudes, l'accumulation de neige pendant l'hiver et la fonte de glace pendant l'été sont les principales composantes du bilan de masse. En Islande, le bilan de masse des trois plus larges calottes glaciaires (~600-~8000 km²) a été suivi régulièrement depuis 25 ans notamment grâce à des mesures in situ. Mais les bilans de masse des autres glaciers et calottes glaciaires islandaises ont été très peu étudiés. Aujourd'hui, les données de télédétection, notamment via la comparaison des modèles numériques du terrain (MNT), permettent de mesurer le bilan de masse par la méthode géodésique. Pour ces glaciers et calottes de plus petites tailles (de 1 km² et à quelques centaines de km²), les photographies aériennes, l'imagerie satellitaire stéréoscopique sub-métriques, et le lidar aérien sont parfaitement adaptées. Cette thèse se focalise donc sur l'estimation des bilans de masse des " petits " glaciers et calottes islandaises depuis le pas de temps saisonnier jusqu'à pluri-décennal et leur relation avec les variations spatiales et temporelles du climat. Le bilan de masse hivernal de la calotte du Drangajökull (NO-Islande) a été mesuré par des images satellitaires stéréoscopiques sub-métriques (données Pléiades et WorldView-2) acquises au début, milieu et à la fin de l'hiver 2014-2015. Les changements de volume ont été convertis en bilan de masse grâce à des mesures in situ de densité de neige, et validés avec des mesures in situ de profondeur de neige. Ce travail permet d'envisager désormais un suivi du bilan de masse saisonnier sans un laborieux travail de terrain. Une importante archive de photographies aériennes est disponible en Islande depuis 1945. Ces données offrent une revisite de 5 à 20 ans pour la majorité des glaciers. De plus, depuis 2000, cette archive est complétée par les données des capteurs satellitaires stéréoscopiques et de lidar aérien acquis entre 2008 et 2013. Cet ensemble de données est exploité pour créer une série temporelle de 70 ans de bilan de masse en Islande. La calotte d'Eyjafjallajökull (~70 km²) sert de zone test pour la création et l'automatisation d'une chaîne de traitement, basée sur des logiciels libres. Le résultat est une série de 70 ans de bilan de masse et changements glaciaires liés au climat et au volcanisme. Les variations décennales du bilan de masse sont mises en relation avec les variations des températures estivales et les précipitations hivernales. Cette relation, quasi linéaire, sert pour le calcul de la sensibilité du bilan de masse au changement de température et précipitation. La chaîne de traitement est alors appliquée à 14 glaciers et calottes glaciaires distribuées aux quatre coins de l'Islande. La moyenne et déviation standard (±DS) du bilan de masse des glaciers sélectionnés est : -0.44±0.16 m w.e. a-1 en 1945-1960, 0.00±0.21 m w.e. a-1 en 1960-1980, 0.11±0.25 m w.e. a-1 en 1980-1994, -1.01±0.50 m w.e. a-1 en 1994-2004, -1.27±0.56 m w.e. a-1 en 2004-2010 et -0.14±0.51 m w.e. a-1 en 2010-2015. Les glaciers maritimes situés près des côtes sud et ouest montrent une plus forte variabilité décennale que les glaciers plus continentaux situés dans le nord et nord-ouest. Notre étude améliore la connaissance des évolutions des glaciers islandais et leur relation avec le climat, en particulier avant les années 1990s et l'augmentation de température. Nos travaux montrent aussi la complexité de la réponse géométrique des glaciers (en lien avec leur dynamique) et offre des données uniques pour la calibration/validation des modèles des glaciers.The mass balance of a glacier is strongly connected to climate. At high latitudes, mass balance is typically controlled by snow accumulation during the winter and the glacier ablation during the summer. In Iceland, direct mass balance observations have been mostly focused on the three largest ice caps (~600 to ~8000 km2), measured in situ for the last 25 years. There are, however, glaciers and ice caps distributed over all quarters of the country that lack mass balance observations. Remote sensing data with the capability to retrieve the glacier surface geometry through Digital Elevation Models (DEMs) are valuable tools to measure mass balance using the geodetic method. For a typical Icelandic glacier (with an area between 1 km2 and hundreds of km2), this can be optimally achieved from optical stereoscopic imagery, emplaced in airborne or spaceborne sensors, and from airborne lidar. This thesis focuses on remote sensing techniques to accurately measure geodetic mass balance from seasonal to decadal time spans and the relationship of mass balance to climate. As an example of seasonal mass balance, the winter mass balance of Drangajökull was measured from satellite sub-meter stereo images at the beginning, middle and end of the 2014-2015 winter using data from the Pléiades and WorldView-2 satellites. The results were complemented with in situ snow density measurements and validated with snow thickness measurements. The study concludes that images from the sensors mentioned above may often be used to monitor seasonal mass balance without tedious field logistics. A vast archive of aerial photographs exists for Iceland extending back to 1945. Since then, most glaciers were surveyed every 5 to 20 years. In addition, a wealth of modern satellite stereo images is available since the early 2000s as well as airborne lidar data in 2008-2013. This creates a unique dataset to construct a 70-year time series of geodetic mass balances. Eyjafjallajökull (~70 km2) was used to develop semi-automated processing chains based on open-source software. The result is a detailed record of glacier changes resulting from climatic and volcanic forcing. Simple linear regression of the annual mass balance of Eyjafjallajökull indicates that most mass balance variations can be related to changes in summer temperature and winter precipitation. It also allows to infer the sensitivities of mass balance to these two climatic variables. The processing chain was then applied to 14 glaciers and ice caps spatially distributed in all quarters of Iceland, resulting in a dense mass-balance record for the last 70 years. The mean and standard deviation (±SD) of mass balances of the target glaciers were -0.44±0.16 m w.e. a-1 in 1945-1960, 0.00±0.21 m w.e. a-1 in 1960-1980, 0.11±0.25 m w.e. a-1 in 1980-1994, -1.01±0.50 m w.e. a-1 in 1994-2004, -1.27±0.56 m w.e. a-1 in 2004-2010 and -0.14±0.51 m w.e. a-1 in 2010-2015. The glaciers located at the south and west coasts revealed the highest decadal variability, in contrast to glaciers located in the north. This study improves the knowledge of Icelandic glaciers prior to the warm 1990s. The obtained glacier DEMs reveals in some cases elevation changes caused by irregularities in ice motion and opens for opportunities of modelling the ice dynamics of some of these glaciers coupled with their mass balance