Bas Altena

Altimetry with GNSS-R interferometry: first proof of concept experiment

The Global Navigation Satellite System Reflectometry (GNSS-R) concept was conceived as a means to densify radar altimeter measurements of the sea surface. Until now, the GNSS-R concept relied on open access to GNSS transmitted codes. Recently, it has been proposed that the ranging capability of the technique for ocean altimetric applications can be improved by using all the signals transmitted in the bandwidth allocated to GNSS, which includes open access as well as encrypted signals. The main objective of this study is to provide experimental proof of this enhancement through a 2-day experiment on the Zeeland Bridge (The Netherlands). In the experiment, we used a custom built GNSS-R system, composed of high gain GPS antennas, calibration subsystem, and an FPGA-based signal processor which implemented the new concepts, an X-band radar altimeter and a local geodetic network. The results obtained indicate that the new approach produces a significant improvement in GNSS-R altimetric performance.

Glacier Remote Sensing Using Sentinel-2. Part I: Radiometric and Geometric Performance, and Application to Ice Velocity

With its temporal resolution of 10 days (five days with two satellites, and significantly more at high latitudes), its swath width of 290 km, and its 10 m and 20 m spatial resolution bands from the visible to the shortwave infrared, the European Sentinel-2 satellites have significant potential for glacier remote sensing, in particular mapping of glacier outlines and facies, and velocity measurements. Testing Level 1C commissioning and ramp-up phase data for initial sensor quality experiences, we find a high radiometric performance, but with slight striping effects under certain conditions. Through co-registration of repeat Sentinal-2 data we also find lateral offset patterns and noise on the order of a few metres. Neither of these issues will complicate most typical glaciological applications. Absolute geo-location of the data investigated was on the order of one pixel at the time of writing. The most severe geometric problem stems from vertical errors of the DEM used for ortho-rectifying Sentinel-2 data. These errors propagate into locally varying lateral offsets in the images, up to several pixels with respect to other georeferenced data, or between Sentinel-2 data from different orbits. Finally, we characterize the potential and limitations of tracking glacier flow from repeat Sentinel-2 data using a set of typical glaciers in different environments: Aletsch Glacier, Swiss Alps; Fox Glacier, New Zealand; Jakobshavn Isbree, Greenland; Antarctic Peninsula at the Larsen C ice shelf.

Elevation Change and Improved Velocity Retrieval Using Orthorectified Optical Satellite Data from Different Orbits

Optical satellite products are available at different processing levels. Of these products, terrain corrected (i.e., orthorectified) products are the ones mostly used for glacier displacement estimation. For terrain correction, a digital elevation model (DEM) is used that typically stems from various data sources with variable qualities, from dispersed time instances, or with different spatial resolutions. Consequently, terrain representation used for orthorectifying satellite images is often in disagreement with reality at image acquisition. Normally, the lateral orthoprojection offsets resulting from vertical DEM errors are taken into account in the geolocation error budget of the corrected images, or may even be neglected. The largest offsets of this type are often found over glaciers, as these may show strong elevation changes over time and thus large elevation errors in the reference DEM with respect to image acquisition. The detection and correction of such orthorectification offsets is further complicated by ice flow which adds a second offset component to the displacement vectors between orthorectified data. Vice versa, measurement of glacier flow is complicated by the inherent superposition of ice movement vectors and orthorectification offset vectors. In this study, we try to estimate these orthorectification offsets in the presence of terrain movement and translate them to elevation biases in the reference surface. We demonstrate our method using three different sites which include very dynamic glaciers. For the Oriental Glacier, an outlet of the Southern Patagonian icefield, Landsat 7 and 8 data from different orbits enabled the identification of trends related to elevation change. For the Aletsch Glacier, Swiss Alps, we assess the terrain offsets of both Landsat 8 and Sentinel-2A: a superior DEM appears to be used for Landsat in comparison to Sentinel-2, however a systematic bias is observed in the snow covered areas. Lastly, we demonstrate our methodology in a pipeline structure; displacement estimates for the Helheim-glacier, in Greenland, are mapped and corrected for orthorectification offsets between data from different orbits, which enables a twice as dense a temporal resolution of velocity data, as compared to the standard method of measuring velocities from repeat-orbit data only. In addition, we introduce and implement a novel matching method which uses image triplets. By formulating the three image displacements as a convolution, a geometric constraint can be exploited. Such a constraint enhances the reliability of the displacement estimations. Furthermore the implementation is simple and computationally swift.

Weekly Glacier Flow Estimation from Dense Satellite Time Series Using Adapted Optical Flow Technology

Contemporary optical remote sensing satellites or constellations of satellites can acquire imagery at sub-weekly or even daily timescales. Thus, these systems facilitate the potential for within-season velocity estimation of glacier surfaces. State-of-the-art techniques for displacement estimation are based on matching image pairs and are thus constrained by the need of significant displacement and/or preservation of the surface over time. Consequently, such approaches cannot benefit entirely from the increasing satellite revisit times. Here, we explore an approach that is fundamentally different from image correlation or similar techniques and exploits the concept of optical flow. Our goal is to assess if this concept could overcome above current limitations of image matching and thus give new insights in glacier flow dynamics. We implement two different methods of optical flow, and test these on the SPOT5 Take5 dataset over Kronebreen, Svalbard and over Kaskawulsh Glacier, Yukon. For Kaskawulsh Glacier we are able to extract seasonal velocity variation, that temporally coincide with events of increased air temperatures. Furthermore, even for the cloudy dataset of Kronebreen, we were able to extract spatio-temporal trajectories which correlate well with measured GPS flow paths. Because the underlying concept is simple and computationally efficient due to data-reduction, our methodology can easily be used for exploratory regional studies of several glaciers or estimation of small and slow flowing glaciers.

European Space agency (ESA) Landsat MSS/TM/ETM+/OLI archive: 42 years of our history

Whilst recent years have witnessed the development and exploitation of operational Earth Observation (EO) satellite constellation data, the valorisation of historical archives has been a challenge. The ESA Multi Spectral Scanner (MSS) products cover Greenland, Iceland, Continental Europe and North Africa representing an archive of over 600,000 Level 1 (L1) scenes that join the 1 million ESA Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) products already available. This paper presents the L1 MSS product functionality, and how the dataset will be fit for multi temporal purposes. For example, a quality assurance traceability concept is implemented through an innovative pixel based Quality Assurance Band (BQA) that includes land, cloud and anomaly flagging. Land cover application areas are showcased, including vegetation monitoring and snow cover monitoring on glaciers.

Observing Change in Glacier Flow from Space

A glacier is a large moving body of ice. Glaciers are natural phenomena that occur at the colder places of this Earth. When you travel to a glacier and look at it, you will see an enormous collection of ice, which lays in between mountains tops. At first sight, nothing seems to be moving, but this is not the case. Ice is actually a very thick liquid, and moves like honey, but very slowly. If you want to see a glacier move, you will need to wait a long time. But if you take a picture and come back some days or weeks later to take a second picture, the ice will have moved, and this can be measured if you compare both images. When we research glaciers we use the same technique, but we use pictures from satellites. The satellites fly over every part of the Earth and can see any glacier. This makes it possible for us to look at the flow of glaciers anywhere on Earth.

Glacier ice loss monitored through the Planet cubesat constellation

The Planet cubesat constellation is a developing earth observation constellation, that is and will continue to sense the whole earth surface on a daily scale at high resolution. In this contribution, we exploit this datastream to estimate the iceberg production of an outlet glacier of the Southern Patagonian icefield, called Perito Moreno. We demonstrate an automatic pipeline that takes into account the displacement due to glacier motion and the ad-hoc coverage of the glacier, due to different observation angles and orbits. With such a robust and adaptive pipeline, constructing a high resolution and temporal dense dataset is possible to be obtained. Which is of great value to understand the complex behavior of calving.

Robust glacier displacements using knowledge-based image matching

Matching of repeat optical satellite images is a powerful tool for the analysis of glacier movement. Due to the rapid growth of earth observation data archives there is an increasing potential for regional glacier flow studies on a decadal scale. However, exploitation of these image collections is hindered by the currently manual pre- and post-processing steps required. Automating these steps, and using content from all available imagery will help tap the wealth of information present within the data. In this study we explore this possibility with the aim to extract velocity fields that are both accurate and reliable. We propose a bottom-up approach in which simple image matching estimates from three images are pierced together, to give rise to the far more complex time-dependent glacier flow. Taking advantage of our knowledge of glacier behavior, rather then crude statistical inferences. We first loosen the threshold of the matching, estimating dispersions for every candidate match. Then by implementing the procedure for multiple time periods we constrain the solution making it possible to apply probabilistic testing. Our approach is alternative to common top-down implementations and instead derives from first principles. In summary, we introduce the concept of precision and reliability of image matching which enhances the analysis of velocity fields with hypothesis model testing to investigate its driving forces.